So anyway, they emailed us this month to say they’re permanently shuttering the program in December. 😥

They tell us it’s not about a lack of resources, as much as about how those resources get allocated. They run other programs that reach more children, and donors like to see that. The few dozen kids who do the intensive program (mine included) are a pretty privileged bunch. They offer subsidies to families who need them, but as ever with these intensive activities, the time and flexibility required to take kids to and fro is as much a barrier as the money. It’s a lot easier to sell the impact of their half-day school program that reaches hundreds of different kids every year.

I get it. It’s comparatively easy to create a field trip experience that will be fun and educational, if barely remembered a few months from now. You can count how many kids participated and put a big number in your annual report. In-depth programming is resource-intensive, the impact hard to convey.

Breadth and scale are important. We need our hospitals to treat a lot of patients, our marketing to reach lots of customers, a chicken in every pot. But in this quantified, gamified, AI-ified world of ours, I worry we’re losing our ability to recognize and value things like depth and quality.

It’s hard to shape the character of children by guiding them patiently for hundreds of hours, year after year. It doesn’t scale well. It’s an impact so profound it defies measurement. But it has meant the world to us.

Incentives and Generative AI in Healthcare

Even before generative AI took off in the mainstream, AI has been playing a significant role in healthcare. Medicine is a domain where our frail, human systems fall terribly short. Disease is an indefatigable foe that inflicts much suffering. The more progress we make against sickness and injury, the harder the healthcare system problem gets: the care gets more expensive, overstretched clinicians are asked to stretch further still, patients and families are required to navigate an even-more-bewildering landscape.

AI has had a bit of success in alleviating some bottlenecks, such as narrowing candidates for drug development, predicting which patients who are at risk of things like sepsis or ICU step-up, and identifying cancer from radiology scans. But so far, these solutions haven’t done much to alleviate an over-burdened system. The lengthy human process of clinical trials remains the limiting factor on bringing new treatments to market. Early warning systems lead to better outcomes for patients, but do little to lighten the load of overworked healthcare providers. The number of radiologists has actually increased since the advent of AI.

Generative AI in Healthcare: What could go right

There is potential that generative AI may finally change the calculus, and make healthcare work better as a system. It’s early days, but anecdotes from clinicians allow us to imagine a world where GenAI achieves improvement across multiple dimensions:

• better patient outcomes

• lessen physician burden

• ease patient access and navigation

• reduce cost

AI-enabled charting is one possible driver. Especially since the advent of electronic health records (EHRs), charting and notekeeping have become an enormous time-sink and a significant contributor to burnout. That calculus is changing as AI scribes become more prevalent. Dana Suskind describes how AI scribing has totally changed the atmosphere of her clinic. Exam rooms that used to be silent as physicians typed at a computer screen during patient visits have once again become a nexus of human interaction: clinicians and patients can have in-depth conversations while an AI takes care of the EHR input.

AI likewise has the potential to make an enormous difference in the realm of diagnosis. A lot of what doctors do is pattern-matching: given the symptoms a patient is presenting with, what is the most likely diagnosis and the treatment options most likely to succeed?

Diagnosis has become increasingly difficult with the pace of medical innovation. Over 1-million new articles are published each year in life sciences and medicine, with an overarching trend towards personalized treatments. No human can keep up. Generative AI is a first-rate pattern-matcher, and can really help here by surfacing considerations that might have been overlooked. There are many AI-enabled products focused on this task (here is a good recent summary), as well as individual physicians using Open Evidence to support their practice.

You can imagine a world where AI represents a real inflection point, allowing healthcare providers to focus on the human-side of care while AIs carry the administrative burden and support diagnosis and treatment, while making it more efficient and less error-prone.

Sadly, you can also imagine a world where none of this comes to pass. EHRs are something of a cautionary tale. In theory, they were going to reduce costs, improve patient care, and generate efficiencies for clinicians. In practice, EHRs have created no notable cost savings or patient benefits, while contributing significantly to physician burnout. EHRs have largely proven themselves to be a tool of bureaucracy, requiring clinicians to go through box-checking exercises at the cost of in-person clinical care.

All to say that a positive outcome for AI in healthcare is far from a foregone conclusion. The introduction of new technology often has unexpected results as people respond to incentives in surprising ways.

Rats, Cobras, and Incentives

In Hanoi around the turn of the century, the French colonial government wanted to reduce the rat population, so they offered a bounty on rat tails. Soon, officials noticed the sewers were filled with tail-less rats, as rat-catchers severed the tails but left the rats to run free and reproduce. The British Raj allegedly stumbled into a similar trap by offering a bounty on venomous cobras, which eventually led people to breed cobras as a source of income and increase the cobra population. It has come to be known as the cobra effect1 – given a solution to a problem, competing or unanticipated incentives within an ecosystem inadvertently make the problem worse.

In many ways, the implementation of EHRs is an example of the cobra law in action. Digitizing health records was supposed to make the system more efficient and reduce admin. But because of competing incentives within the healthcare system, EHRs actually make the problem worse. We should anticipate similar cobra effects as AI gets embedded into healthcare.

Introducing Goodhart’s Law

Goodhart’s Law is one way of formalizing cobra effects. In its original formulation, the law states:

“Any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes.”

That is, we can observe that a declining cobra population and dead cobras generally go together (i.e. the statistical regularity). But if we try to get a greater decline in population by producing or encouraging more dead cobras (i.e. the pressure being applied for control purposes), the relationship between the two collapses.

“Applying pressure for control purposes” sounds nefarious, but it’s actually standard practice in a healthcare context. If we know from data or experience that a particular set of symptoms generally resolves with a particular intervention, that is a statistical regularity. When a new patient presents with those symptoms and we apply the intervention, we are “applying pressure” hoping that the symptoms will subside.

In order to rely on a statistical regularity without falling prey to Goodhart’s Law, we need to know that the relationship is definitely causal (the symptoms abated because of treatment, rather than the two things simply co-occurring). We also need to know that no additional, unintended effects occurred to make the situation worse (treatment creating side effects worse than the original symptoms). Of course, this is exactly why we have randomized controlled trials in medicine. Because we have studied a new treatment in a controlled environment, we can be confident that the statistical regularity will hold and the treatment will be safe and effective.

Generative AI in healthcare is relying on (very sophisticated) statistical regularities to produce its output. When we use that output to inform clinical care, we are, inevitably, applying pressure on those regularities for control purposes. Of course, generative AI in healthcare is trained on published clinical trial results. But what makes AI such a powerful tool is its ability to identify many additional statistical regularities that have not been tested in a clinical trial, but that we nonetheless use to inform clinical care. Goodhart’s Law has entered the chat.

Goodhart’s Law applied to generative AI in healthcare

There are four different variants of Goodhart’s Law, which help us break down the risks and challenges of over-reliance on statistical regularities that AI has found2.

1. Stakeholders with competing goals

2. Misattribution of causation

3. Application in new domains

4. Omitting relevant variables

1. Stakeholders with Competing Goals

The challenge of stakeholders with competing goals is closest to the classic cobra effect. In healthcare, this is a constant challenge because there are so many stakeholders with somewhat different goals. At the highest level, clinicians, administrators, payors, caregivers, and patients all want high-quality, cost-efficient patient care. But when we define that goal in more detail, or make it specific to an individual with a particular health condition, we find that people make different trade-offs. Even for the same person, the trade-offs often shift over time. Thus, for any AI in healthcare, we need to be aware for whom its goals were defined, and how they might differ from the goals of other relevant stakeholders.

2. Misattribution of Causation

In medicine, misattribution of causation is surprisingly common, which is why bloodletting was central to medical practice for 2,000 years. More recently, radical mastectomies were a common treatment for breast cancer, until it was definitively shown they inflict serious side effects on patients without any clinical benefit. Many of today’s cutting edge cancer treatments work so well for some patients that they no longer have any evidence of disease. For other patients, the drugs don’t seem to have any effect on the cancer. Medical science does not know why some tumours respond and others do not, which is another way of saying we don’t yet understand the underlying human biology enough to identify the causal chain.

AI certainly has the potential to help us refine our causal understanding, but it also has the potential to rapidly propagate practices based on incorrect or incomplete causal understanding. History tells us that once a practice becomes the standard of care, it’s difficult to change. We should therefore be attuned to the risk of generative AI suggesting interventions based on statistical regularities rather than an established causal link.

3. Application in new domains

Domain shifting is particularly salient in healthcare, because health outcomes can be very different in different populations and healthcare practices vary across institutions and jurisdictions. And yet, applying knowledge to a new domain is in many ways fundamental to the practice of medicine. For example:

• Treating patients from populations that have been under-studied in clinical trials (racial minorities, pregnant people, the very young and the very old)

• Shifting a procedure from an academic hospital to the community, or from an inpatient procedure to an outpatient,

• Treating rare disease patients based on experience and data with more common conditions.

• Applying learnings from a treatment in a later line of therapy to first-line treatment, or vice versa.

Human clinicians are generally quite aware when they are shifting the domain, and proceed accordingly. When we are working with an AI model, domain shifts can be less obvious. A 2022 MIT study at Beth Israel Deaconess Hospital looked at an AI tool for predicting risk of sepsis in the ICU. Initially, prediction accuracy was quite good, but it degraded significantly over time. The culprit was two-fold:

1. A new version of the International Classification of Diseases (ICD) changed clinician input to the system, and

2. The model started to be used at affiliated suburban hospitals with different patient populations.

This example is from an older technology that wasn’t using generative AI, and we might expect more modern approaches to adapt better to changes in the data. But it does suggest we should be clear on the training domain for AI in healthcare, and be alert to the possible implications of domain shifts in order to interpret AI outputs appropriately.

4. Omitting relevant variables

A very simplistic example of this challenge is using low blood pressure as a proxy for good health, and ignoring other clinical indicators. This is the basic issue with older alert systems that often gave clinicians useless warnings based on a very small number of data points. In this simplest form, it’s not a very big challenge for modern AI systems, which are great at weighing enormous amounts of input and unlikely to over-index on a single variable.

However, AI cannot weigh information it doesn’t have. For instance, Dr. Robert Wachter outlines the risks of patients interacting directly with an AI for diagnosis: Patients are not expert at communicating the most important details of their case, which can lead the AI to provide bad advice based on missing information. Even when a clinician is using AI to support a case, they won’t necessarily have all the relevant clinical data. In healthcare, data collection is not free. Some diagnostics are expensive; others might require long waits. All of them require the patient to spend more time undergoing procedures they might rather avoid.

Further, healthcare decision-making is not just a matter of clinical data points — human values play a role too. Values encompasses weighty questions around end-of-life, but it equally includes how people experience the hassle and traffic of a treatment they can only get at a big hospital downtown. Because the universe of potentially relevant variables is so vast, it’s very likely that AI will be missing some of them, and any AI outputs should be interpreted through that lens.

The point is not that Goodhart’s Law exists, so AI in healthcare will never work. Nor is it that we can’t do anything about our metaphorical rats and cobras. Generative AI holds so much potential for the healthcare system, and ever-more-sophisticated generative AI models might be able to self-correct for Goodhart’s Law. But especially as AI becomes increasingly agentic and humans are in the loop less often, it behooves us to understand the different manifestations of Goodhart’s Law, and how they might cause problems in a healthcare context.

End Notes

At the behest of my ten-year old, we both signed up for the 5km race in this month’s Toronto Waterfront Marathon. The race was a special “Marathon Juniors” program that lets elementary school kids get a taste of participating in a big race with thousands of others. It was a big step up for him from 2km in school cross-country races, an even bigger step up for me from not-running-at-all-for-years. Anyway, we did a bit of training in the lead-up, and had a great race day together. These pre-teen years where our interests overlap more and he still likes to hang out with his parents are pretty great.

I have been reading a few different books about AI (in general and in healthcare), as you can tell from the subject of the main newsletter. I picked up interesting tidbits from all of them, but I think everything is moving a little too fast for something at book-length (and book publishing timelines) to really land. Elsewhere, I read Florence Knapp’s The Names, which was a wonderfully compelling book about a tough subject. I also finished Waubgeshig Rice’s Moon of the Turning Leaves, the sequel to Moon of the Crusted Snow. In an inversion of the usual order of things, I liked the sequel better — it’s a richly-detailed story about Indigenous people surviving in a dystopian future by living on the land. It also made me want to brush up on my wilderness skills. Finally, I read Ben Macintyre’s new release, Redwood: The Untold Story of the Cold War’s Most Extraordinary Spy. I absolutely adored Macintyre’s The Spy and the Traitor. This one was not quite as good: it was a little slower to get going and pretty gradual in its denouement. But it was completely riveting in the middle once the espionage really got going, and I learned a lot about the Iranian revolution.

Tomorrow, of course, is Halloween. It falls on a Saturday which has turned it into a weekend-long celebration. My boys are dressing as Harry Potter and Frankenstein’s monster this year, and we’re going to both a pre- and post- trick-or-treating party. I don’t think I’ve been to two parties in one night since university days… my costume will be a middle aged woman trying to stay awake.

Happy Halloween! In comradeship,

S.

As calamities go, ours was a very public one: a steady stream of people taking selfies, even a news crew at one point. It is a little bit annoying to sit on your front porch (because there is no AC) while people document your misfortune for their socials. However, the upside of a public calamity is that your neighbours know about your plight.

Ours were so quick to step up! People lent flashlights and tools and materials to help with the landscaping repairs Someone was headed out for the weekend and gave us her key so we could charge our devices and use her hot water to shower. Our food ended up scattered amongst the freezers of half-a-dozen people.

All small things. But in the string of annoying admin and upended plans it has been such a solace to have that support. Receiving help is a wonderful catalyst for community — you can’t house someone’s frozen vegetables for a weekend and not forge a deeper connection.

We picked up our new car earlier this week, and so the episode is now mostly behind us. Now our job is to nurture those new neighbourhood connections. The next misfortune to befall someone on the street won’t be as obvious as downed tree, and we are so conditioned to keep our troubles to ourselves. Sometimes, a little neighbourly assistance goes a long way, and it’s the ongoing work of connection that helps people feel comfortable sharing their troubles. Hopefully we can do that, and folks will reach out when they need a hand — we have a lot of kindness to reciprocate.

A Conversation with Asha Chaudhary

This installment in our Women’s Entrepreneur Series is an interview with Asha Chaudhary, CEO of Jaipur Living. Asha grew up in India, watching her dad be an entrepreneur. After an undergraduate degree in Atlanta, she returned to India to work at her father’s company, before returning to the US to lead operations there. Today, Jaipur sells hand-knotted artisan rugs to design firms and specialty retailers in the US. The core of their business is a supply chain of artisans in India.

In this interview, Asha talks about the company’s unique model, and their emphasis on empowering artisans. Along the way, we chat about maintaining authenticity in the age of AI, the pluses and minuses of a family business, and juggling motherhood with a busy CEO role.

Susan Bartlett: You talk about Jaipur Living as a supply chain, which is a bit unusual. In my experience, people talk about the supply chain as something that supports the business, but for you it is the business. Help me understand it.

Asha Chaudhary: The business was started by my dad fifty years ago with rugs and weaving. He started with two looms in his house, but he was always in love with people and craft. When he started working with artisans, he realized that they weren’t really treated well by the industry in general. My dad was always a rebel who questioned everything in society. He saw a huge opportunity to do something different and really take care of the artisans.

At the highest level, the business is a conduit between the artisan and the customer who really appreciates the product. What my dad built was a truly unique artisan supply chain doing everything from making rugs to processing yarn. Today, there are over 45,000 artisans across 900 villages in India.

Operationally, it’s a really strong ecosystem where we have “area commanders” on the ground, who each manage a set of 6–10 villages. We have branch offices that serve as hubs to manage many sets of villages through the area commanders. The head office works with the branch offices for raw materials or whatever else they might need. We give the artisans raw materials at their doorstep so they can work from home.

There is a lot of technology built in. Nowadays, we have apps so we can see how far along each rug is, and all that goes into head office. The automation helps it scale. But at its core, it’s a truly human supply chain. We know them by name. We know their families.

SB: You’re in the business of selling something real and authentic, that also has a deep integration with technology. How do you prove authenticity in the world of AI? How do you convince American customers there is a real difference in the quality of the work and the way the artisans are treated, and that the difference is worth paying for?

AC: I think that the more AI is ingrained in our lives, things like authenticity and human connection will become even more important. Our business is built on those principles, so it’s an advantage for us. But we have to do the work of telling the story.

Last year, for example, a bunch of our clients came to India and we made sure they could go to the villages and see the supply chain first-hand. Every time, they tell me it’s the best part of their trip. They may have seen the Taj Mahal, but having the direct experience of seeing the artisan and product being created is so meaningful.

I don’t think AI can match the empathy and creativity that we bring as humans. That’s what distinguishes us. As a brand we want to continue to lean into that human connection because AI can’t take that over.

SB: Tell me more about how empathy and human connection with the artisans is fostered through the business.

AC: My dad always believed in the power of human potential. He always said that these women — a lot of the artisans are women — are the most talented managers in the world, and he wanted them to feel proud of the work that they do.

By giving them a dignified wage and educating them, he really helped them see their own potential. Many of these women were not educated, and often their husbands would take their money. My dad focused on getting them to at least a second-grade education where they could open their own bank accounts and control their own money. Then he realized that health wasn’t necessarily a priority in the villages, so he partnered with doctors and hospitals to bring more health education and awareness and better healthcare.

I don’t think he was doing it because he would get amazing work from them. They already did amazing work. He wanted them to feel pride and self worth. That was what really transformed the villages. When one or two women in a village started participating in these initiatives, the other women would see it and want to be part of it.

The biggest transformation is that the artisans have consistent, sustainable income. The number one thing they do with that income is invest in their kids. We have hundreds of stories where the artisan didn’t even know how to read and write, and now their child is a leading doctor.

SB: How has the US organization grown from the business your dad started?

AC: In 2008, my dad recognized that an artisan supply chain can’t really thrive unless you have the end customer that appreciates the value. We discussed needing to get closer to the consumer in order to continue to evolve our supply chain and make products that are actually resonating with changing needs. That was the trigger for me to come back to the United States to start the US operations. At the beginning, it was me and two other people in a 200 square feet office. I had a little van to do customer deliveries, I took customer calls, I balanced the books. It was really hands-on, building the business ground up.

SB: How has getting closer to the customer changed your products?

AC: We try to really listen to the theme of what customers are saying, and then make those changes at the artisan level. A great example is CallaLuxe, our new performance rugs. Seventy percent of US households have kids or pets and they want rugs that are easy to clean and easy to live with. We found a special yarn that is made by one factory in the world, and we’ve spent the last four years experimenting with different rug constructions. It’s still 100% handmade, but the new product is really versatile. It can be used indoors or outdoors, cleaned with a little soap and water. It’s still beautiful and soft, but with more of the properties consumers are looking for.

SB: How do you involve the artisans? How do you get them on board with making a different kind of product after they’ve been doing it a different way for so long?

AC: We work alongside the artisans and we focus on the context: why we’re doing what we’re doing and how it’s important to the business. But also their context, and how it helps them, improves their income, helps to sustain the village.

We did a postcard campaign one time. We had our customers take a picture of their room with the rug in it, and then write a note to the artisan — whatever they wanted to say. When we gave a postcard to an artisan, that meant more than anything else we’ve ever done. Seeing a product they’ve made in a home and how a customer feels about that creates so much connection. Ultimately that’s what sustains the supply chain.

SB: Big picture, that’s a big trade-off between what’s functional and what sells, versus the art and tradition. I say this as someone who would buy the performance rug that I can wash more easily. How do you figure out which compromises are necessary, and which would dilute the core of what you do?

AC: To talk about the performance rug example, we knew the customers wanted performance. We could have made inexpensive polyester rugs, but we wanted to keep the craft.

You have to innovate and evolve, but you have to define the box you want to be in. Then you experiment within that box. When the customer need evolves, the supply chain has to evolve with it, or the business becomes obsolete. But our business model — the box we have made for ourselves — is to marry the needs of the artisans and the customers as much as possible. The two have to be connected. Teaching the artisans to weave with performance yarn took time. But by teaching them that skill, the artisans are evolving alongside the customer.

SB: Did you always know you were going to go into the family business? What are the pros and cons of following in your father’s footsteps?

AC: Even as young as seven or eight, my dad would take me into the villages. I remember spending my summers getting up at 5am and going into villages with him and seeing him work with the artisans. I saw what it means to really take care of people, and what my father had built. There was never a spoken expectation, but I developed a really deep passion for the work, so it was very natural for me to join the family business.

In total we are five siblings, and all of us are in the family business, three here in the US and two in India. You’re right that there are always pluses and minuses. Luckily we’re in a place where we have very clear roles and responsibilities. I’ve also learned a lot about how you solve conflicts and differences of opinion. In a family business a lot of things might be left unsaid — hard things aren’t addressed and problems allowed to fester. I’ve learned to make sure we have a good process and a good platform to resolve differences and make decisions.

SB: You also have to think about the other side of the family business. You remember being seven and visiting the artisan villages with your dad, and you have a seven-year old son yourself. How do you think about your son and the family business?

AC: I don’t have any expectation for him to join the family business per se. I want him to pursue his dreams. I feel that the most important thing my dad gave me was the right values: how I see the world and what I care about. I hope to translate similar values to him.

He’s growing up very differently from how I grew up, so I have to be very, very intentional about it. I share a lot of stories. He goes to India a couple of times a year. The last time I took him to one of the weaving villages and he saw how people live. We talked about how the kids don’t have too many toys. He’s still young, so I don’t think he has fully grasped everything, but I think my role as a mother is to make sure I’m exposing him to those aspects of the world.

SB: How do you balance your role as a mother with your role as a CEO?

AC: What I’ve found is that there are times when the business needs me and I have to be there, and I need to work hard. And then there are times when my family is a big priority and I have to be there for them. I’ve learnt to be present in whatever it is that I’m doing. If I have an hour with my son, I won’t want to be checking emails. I want to be present and give him my full self.

SB: I think that is excellent advice, but in my personal experience, it’s easier said than done. It’s hard to be fully present when your phone starts pinging because somebody’s got an issue at work. Do you have a secret decoder key?

AC: I wish I had one! I have built a very strong ecosystem of support in my life. My husband is incredible and we have a nanny. But I also have an incredible team here. I’ve learnt that I need to surround myself with people who are smarter and better than me. I’m the leader of the business, of course. And there are times when fires happen in the business, of course. But when you surround yourself with people who are smarter and better than you, they can take a lot of the load off. You have to learn to let go. You can’t do it all. You cannot.

SB: You cannot let yourself be indispensable.

AC: A hundred per cent. It’s not easy.

SB: What does success look like for you personally and for the business?

AC: For me, success is learning and growing, especially as a leader. If I’m not, then I wouldn’t be doing it.

For the business, success has always meant sustaining the craft and transforming the lives of the artisans. Are we helping to improve the incomes and quality of life for the artisans? That is the most critical thing that we measure.

Revenue and profits are all important. We’re north of a hundred million in US revenue, and our goal is to continue double-digit growth and take our products to more designers and more households. But the artisans are the DNA of the business. The end consumer needs to understand the beauty, the meaning, and the quality. We don’t want handmade rugs to become like a Birkin bag, only afforded by a few and everything else is made of machines. That means taking care of the ecosystem and the supply chain in India.

We have to sustain and elevate the craft and the artisan. That is the true measure of success for the business.

End Notes

There have been a few ups and downs this summer, but one especial highlight was our late summer canoe camping trip to Killarney Provincial Park. We were gifted with gloriously sunny, bug-free days, and very short portages to a campsite that offered almost perfect solitude. The swimming was particularly magical — a whole crystal-clear lake to ourselves. It was a perfect escape.

One highlight from my summer reading list was Eric Ries’s Incorruptible. He talks about how companies can preserve their pursuit of a substantive mission, rather than a Milton Friedman-esque focus on shareholder value. Up until about a hundred years ago, businesses used to have specific charter, approved by a legislative body, in service of specific goals (e.g., to build a transcontinental railroad). Nowadays, that has mostly fallen by the wayside, which means there is nothing there to counterbalance the pursuit of profits. I found it very thought-provoking.

My favourite novel of the summer was Flashlight by Susan Choi. It’s mysterious and atmospheric and I loved the way the plot unfolded alongside the characters. I also loved Rohinton Mistry’s A Fine Balance, which I read in anticipation of the new theatrical adaptation currently on stage in Toronto. The kids and I spent the summer reading aloud Arthur Ransome’s 1930 book Swallows and Amazons. It was the perfect summer choice — kids off having great adventures sailing and camping, enjoying the kind of freedom that’s rarely on offer in 2026.

Now, of course, we are settled into the fall routine —hockey rinks, Halloween costumes, and general hunkering down. I’m especially looking forward to Thanksgiving next week. September is always an all-out sprint of back-to-school activities, and the long weekend feels like a much-needed opportunity to catch our breaths and reset for the last few months of the year. Wishing you all a lovely October.

In Comradeship,

S.

Before I left, I had the chance to sit down for another interview in the women’s entrepreneur series. Ella Korets-Smith is a Toronto-based entrepreneur who focuses on commercialization in biotech. In that capacity, she has been a co-founder of two ventures, and been involved in others in a fractional leadership capacity. We talked about the ingredients for a successful biotech, but I think the theme running through our conversation is vulnerability: the vulnerability inherent in running a start-up, the vulnerability of open communication styles, the vulnerability of deciding to wind down a company. It was a wonderful chat that I thoroughly enjoyed, and I hope you will too. Many thanks to Ella for taking the time!

I will be back in your inboxes in late September. Until then, enjoy the back half of summer.

In Comradeship,

S.

A conversation with Ella Korets-Smith

This installment in our Women’s Entrepreneur Series is an interview with Ella Korets-Smith. To date, Ella has co-founded two different biotechs; she also owns and operates EKS Ventures, where she provides fractional leadership to biotechs on strategic business development and commercialization.

In this interview, Ella talks about starting two different biotechs based on the same technology, and the experience of winding one of them down. She also talks about her newest entrepreneurial ventures, and how she prioritizes relationship-building over the long-term.

Susan Bartlett: You have such a multi-faceted career arc, so why don’t we start with your story. What are some of the formative experiences that brought you to where you are today?

Ella Korets-Smith: I’m a scientist by training. I did a masters in medical genetics and then decided I didn’t want to do a PhD, even though that was the assumed track. I wanted to see what else was out there and took a course in entrepreneurship. It was an a-ha moment: “This is how the world works!” I had spent so many years studying the minute details of specific proteins and what they do in the body. It’s very cool, and I really loved it. But all of a sudden, I was learning about how the world functions. It opened my eyes.

At the same time, I was working as a scientist at a biotech in Halifax under a new CEO. He basically said to me, “You understand the science and you can talk to people. You should be in business development.”

My first reaction was, “What’s business development?”

That CEO became my mentor, helping me transition from a bench scientist to director of business development for an early-stage cancer vaccine company. That became the basis for how I spent the next twenty years of my career: business development, strategy, and commercialization for biotech.

Now fast forward to working 10 years on the business side of biotech, and I was wondering what I should do next in my career. The answer from many people I asked was to move to the US and get a job with pharma or a big biotech, because that’s where all the business development opportunities were. I had two young kids, and that was not going to work for me. Instead, I hung up a shingle for what would become EKS Ventures. The idea was to try to build a career in business development in Canada. I would become part of companies on a fractional basis and do that strategic business development and commercialization work, sometimes having an executive role in that company, but not being a full time employee.

Through that model, I worked with a number of companies doing deals and co-founded a couple of companies with other partners, building them from scratch. I’m continuing to do that. But for me, it’s always about being deeply involved — investing my time and operating the companies, as opposed to being a consultant.

SB: Having had that fractional leadership experience across a number of different ventures, what would you say you have learned about starting a company generally and starting a biotech specifically?

EKS: The very first thing is you need the right people around you. Yes, you need a technology that you believe in, but the team you are building is the number one most important thing. I think that’s true for any company, but for biotech specifically, the team has to be a three-legged stool:

1. the science person, who “owns” the science and can stand by it

2. the commercial person, who can translate the science and figure out how to make money from it

3. the finance person, who either has money or can get money, so that you can actually implement the science.

Those three things, you must have. If you’re missing any one of those three pieces, it makes things much harder — or even impossible — to get off the ground.

SB: How does the experience of building a company change over time?

EKS: I think of it as two distinct stages of a company: building mode vs. operating mode. For me, I love the first part, where you’re trying to create something, putting together the team and the structure. It’s more natural for me to imagine what needs to be done, to be consultative, to throw ideas around and then just do it. You can do that in the early building phase. Later, when you are operating and growing, you need more structure around decisions and communications. Especially if you are hiring people who are used to larger organizations, your internal decision processes and communications require so much more thought and planning. Until I realized that, there were instances of miscommunication in a growing organization that I didn’t even realize were happening. It was a huge learning for me.

SB: I can see how that happens. In large pharma, so much time and energy goes into every decision and communication, because building and maintaining alignment in large organizations is so hard. Whereas the start-up ethos is more throwing spaghetti at walls to see what sticks, and people who join small start-ups in the earliest days are usually more comfortable with freestyling.

EKS: That was my realization. In an early-stage biotech, you are putting your neck out for something all the time. You are completely exposed, because every step is yours to take; you’re always personally making decisions, promoting something you think is right or killing something you think is wrong. It’s a constant state of baseline vulnerability.

For me, being open and vulnerable in that kind of way matches my personality. I like to communicate my position openly, hear from others, get their input, and then make decisions quickly. At times, I’m not sure whether this open style of communication is most likely to lead to success. I sometimes wonder if it would be easier if I was better at keeping things to myself, instead of my natural tendency towards open communication.

SB: I don’t know about easier — and I say this as someone who has similar tendencies — but I wonder if that open communication style ultimately creates more fulfillment from your work.

EKS: I hope so, and I do think about it in those terms. What ends up happening for me most often is I lean toward getting involved in projects because I see someone struggle and think I can help with that. If it’s within the realm where I can support, I want to help the entrepreneur, I want to help the scientist, even if the project won’t necessarily fit the standard definition of commercial success.

SB: Can we talk a little bit about Virica Biotech and Virano Therapeutics, the two biotechs you co-founded?

EKS: We created Virica Biotech in 2018, licensing a set of technologies from the Ottawa Hospital Research Institute (OHRI). It was a set of patents with two different applications: one for manufacturing, and one for therapeutics. We had the three legs of the stool: Jean-Simon Diallo is the scientist, Ken Newport is the finance guy, and I was the commercial person. We started with an early fundraising round that was friends and family plus Canadian angel investors.

Although the underlying technology is the same, manufacturing and therapeutics are two different businesses. Manufacturing can deliver short-term revenue with a smaller investment, but carries operational and market risks, and potentially smaller multiples on exit. Therapeutics have very long timelines, require huge upfront investments, with the potential for even greater return on that investment. After the initial fundraising round, it was difficult to find investors who were interested in both sides of the company. We ended up creating Virano as a separate company with its own license from the OHRI to develop therapeutic applications.

We had a lead investor for Virica on the manufacturing side, so we doubled down and focused there for a few years. Eventually, we reached a point where it made sense for me to leave Virica and focus full-time on Virano, to try and get that going. It was good timing from the perspective of Virica and how well-positioned the manufacturing business was, but it was bad timing for Virano. Virano was developing an enhancement therapy to make other gene therapies more efficient. But the market for gene therapies was really struggling and there wasn’t appetite for a product that worked alongside when there was so little enthusiasm for the gene therapies themselves. It wasn’t the right time.

The other piece that was hard is the other two legs of the stool — our scientist and financial person— were still focused on Virica, as they should be. I didn’t want to take them away from the work they were doing, but to make Virano a success, I needed more support on the finance and science side.

In the end, we gave ourselves a date to make meaningful progress with Virano, and when it passed, we decided to wind down the company. The therapeutic asset went back to OHRI, where they can apply for grants and continue to work on it.

The thing that you learn in this business is that you don’t want a company that doesn’t grow and doesn’t die, but just subsists. We would rather make a call and go through the pain of wind-down rather than avoid the pain and stay in that subsistence state.

SB: It is hard, and it is painful, right?

EKS: It takes time to run something, so making the decision to stop is the right call if you believe you’re not going to reach your goals in the foreseeable future. Even as we were implementing this decision, we had to remind ourselves that winding down Virano should not be defined as “failing.” This was not about giving up; it was about us being thoughtful and making choices about where to focus. We made a decision, and a decision is not failure.

But you could also imagine that now we have a company on our record that didn’t get funded, didn’t go anywhere. To the extent that Virica is doing well and other things are going ahead, that’s good, but I feel that in Canada we are not so great at placing value on the lessons that come from even a perceived failure. Unfortunately, we don’t give people very many chances.

The people who have been successful, they get the chance to play again and again and again. But if you haven’t been successful in the traditional sense, the second and third chances are hard to come by. Realistically, that means it’s easier to give more money to someone who has sold a company and made lots of money; it’s potentially harder to give money to somebody he has had the experience of winding something down, even though there are all kinds of reasons why something doesn’t work out. The people who have had those “failure” experiences have learned so much. You want them to try again.

SB: You are trying again. You have a couple of ventures you’re currently working to get off the ground. Can you tell me about them?

EKS: One is a very unique gene therapy approach and the other is more of a commercial consumer product opportunity.

With the gene therapy, we have exciting scientific data and smart, engaged people who have been working at the science for years. We see the unmet need and how it can help the world. But we also know it’s going to be a very long, slow build, with a lot of pre-clinical and clinical development for which we’ll need to raise a lot of money. I’ve been in gene therapy for a long time, so I fully realize how hard this is going to be. For me, I really like the idea of coming in to galvanize all these pieces and act as the translator between science and business.

On the consumer product side, I’m excited to do something that’s a little closer to the customer. I would love to try to sell something you can touch and feel.

With gene therapy, I’m selling you “blue sky” — something that will be wonderful in the future. With the consumer product, I’m selling you something concrete right now.

It was like that with Virica and Virano too. Virica was selling a manufacturing process that exists; Virano was a therapy we were going to develop. I like having both sides of that coin. It’s nice to be solving different problems and working with different people.

SB: I’d love to dig a little bit more into the relationship side of things because the reason we’re having this conversation is that you’re a person who is very good at cultivating relationships — not just for yourself, but for other people. What is your philosophy, and how do you make time for that relationship work when you’re also busy operating companies?

EKS: With EKS Ventures, it all comes down to the relationships I’ve built over time. I’m not a person with a big pharma name on my CV, so people don’t call me to get a “pharma brand” that looks good for a start-up. I’ve just slowly, slowly, slowly built a network of people who trust me because they’ve worked with me, or I’ve helped them. I’ve taken a lot of time to cultivate that, and I really put a lot of emphasis on it. I keep having those conversations and building that network because who knows where it might go?

Pharma and biotech is a surprisingly small world and that helps with making time for it. There’s a standard set of meetings and events that you go to, and you end up building a network around those events. You see the same people every six months, and you stay open to it.

When I’m asked for advice about networking and connection, I always tell people not to just network “up”. It’s great to talk to the CEO, but get to know your peers — the people who are going to grow up with you. Eventually, they will be the senior decision-makers, and you’ll have known them for twenty years.

I also advise people to always ask “How can I help you?” No matter who you’re talking to, just ask that question. It’s memorable, and sometimes there is something tangible that you can do, which really cements that relationship. It goes back to my earlier comment about how I operate. I want to be involved in things where I feel I can help people. Let’s be clear: I want to run successful businesses and do well for myself, my partners, and my investors. But when I wake up in the morning, what I think about is how do I help, how do I make things work.

I was there a couple of weeks ago, sitting in the sunroom and reading about constraints, when the owner and her husband sat down for a meeting. I couldn’t help but overhear the conversation. It’s poor form to report your eavesdropping in your newsletter, but the details have since been published: they are being threatened with eviction in a dispute with the landlord over taxes, maintenance and insurance (TMI) charges. The landlord says they owe fees; when they asked for documentation to support the charges, the totals changed (a few times) and he subsequently served them with a notice of default.

The crux of the issue is a lack of clear norms on what constitutes valid TMI fees or appropriate documentation for commercial tenants. In their absence, the party with the least power is at the mercy of the party with the most power (in this case, the landlord with the power to summarily evict). Balanced negotiation is impossible.

As I sat overhearing the Rayah owners describe their situation, my reading put their plight into a broader context. As David Epstein outlines in his book Inside the Box, when entrepreneurs in Lusaka, Zambia are able to operate in a context with strong institutional norms, it facilitates partnerships and collaborations that allow their businesses to thrive. But many businesses in Lusaka are forced to operate without those norms, and it causes them to limit their collaboration and (by extension) their potential for growth. Much of what we think of as the modern economy rests on institutions that foster cooperation amongst strangers with competing interests. Their presence or absence matters most to the smaller, less powerful players in the ecosystem.

This isn’t just a story about markets in Zambia or a small local restaurant in Toronto. Lately, all of us feel like we’re operating with increasingly unreliable norms. From international affairs to AI slop in your inbox, it seems foolish to extend a presumption of good faith to anyone outside your inner circle. There is a new feeling of instability and uncertainty underlying so many of our interactions. In turn, those interactions are becoming increasingly impersonal and isolated.

For the owners of Rayah, that uncertainty is centred on fees for taxes, maintenance, and insurance. They are fighting for more transparency. But importantly, they are not just fighting this one set of fees from one landlord. They are working with their local representative to advocate for changes that will create predictability for all commercial tenants. Strong norms that protect the disadvantaged create the conditions for everyone to thrive. I admire the Rayah owners’ advocacy for systems change.

If you’re in Toronto, Rayah is open Wednesday through Sunday for dinner, weekday lunch, and weekend brunch. I recommend you save room for dessert. If you live in Ontario, you can sign the petition to reform commercial tenancy rules at the restaurant or online. Wherever you are, support the local businesses in your community and fight for institutions that keep the playing field level. Together, they are a bulwark of good faith in uncertain times.

Calibrating Constraints

There’s a trick we do at workshops sometimes, when we want to make a point about constraints and creativity.

First, ask the group to name as many fruits as they can in 30 seconds. The participants think 30 seconds is the constraint, so we get a rapidly scrawled list of apples, oranges, bananas. Maybe some intrepid soul ventures into berries.

Then, we repeat the exercise, but this time with an additional constraint: fruits that you think no one else will list. Suddenly, we have guava and yuzu, obscure Nordic berries, specific varietals of apples. Usually someone goes full botanist and advocates stridently for cucumbers, tomatoes, and bell peppers. The point is made: constraints can make us more creative.

That is the thesis of new book, Inside the Box: How constraints make us better. As well as providing examples of power imbalances such as those faced by my neighbourhood restaurant, Epstein weaves together compelling stories and scientific research, outlining different kinds of constraints and how they help:

• Constraints of time and place that push us to create something (anything), rather than wallow in analysis paralysis

• Constraints of norms and institutions that guide our interactions with other people and enable more productive collaboration

• Constraints of problem space, where limits we place on our solutions foreclose some possibilities and force more focused iteration and refinement.

Readers with a human-centred design background will recognize many familiar concepts cast in a new light. Problem framing, prototyping and iteration, systems thinking, universal design are all presented through the lens of constraints.

For the most part, Epstein’s book focuses on the dichotomy between constrained and unconstrained. We get lots of examples of people using constraints to achieve breakthroughs, set against cautionary tales where a lack of constraints contributed to stasis and stagnation. It builds a compelling case for the practical value of constraints.

But for those of us working inside organizations, it’s only half of the story. “My boss gives me too much freedom and resources,” is not a common complaint. We’re more likely to be saddled with a litany of counterproductive constraints — asked to list fifty fruits in five seconds, using an Etch-a-Sketch.

A taxonomy of constraints

Many constraints are helpful, and embracing them can stimulate “creativity, innovation, and collaboration,” just as the dust jacket of Inside the Box promises. But there are also unhelpful constraints, or constraints that might be helpful in isolation but become burdensome when layered with too many others.

Constraints live along a continuum. On one end, we have problems that are too open-ended. On the other end, we have problems that are overconstrained. Both can be equally problematic — the main risk is that you will produce nothing useful. With too few constraints, that might mean producing nothing at all; with too many, you are likely to produce something, but it may not actually solve a problem or deliver value.

When you are optimally constrained, you retain meaningful optionality. The constraints are providing helpful boundaries, but not foreclosing too many possibilities. There is a Goldilocks principle at work, where constraints are balanced with flexibility across a number of dimensions:

Admittedly, this is not a secret decoder key that automatically differentiates good constraints from bad ones. Crafting good, productive constraints is an art that requires judgement and practice. The task is all the harder because some of the most useful constraints are entirely arbitrary, and even self-imposed.

Navigating arbitrary constraints

There is no particular reason why a newsletter must be sent once a month (ahem), but creating that self-imposed, artificial constraint can generate motivation and focus where it might otherwise wane (ahem). In an organizational context, “because I promised the boss/the client” is often doing the same job.

However, the constraint in such cases is really just a proxy for one or more important goals. This kind of arbitrary constraint helps to crystallize the goal and make it more actionable. To judge the value of such a constraint, you have to be crystal clear on what it is helping you achieve, and the trade-offs required to meet it.

In one case, we delivered a project with a very aggressive timeline constraint that was seemingly arbitrary — our client had promised a certain date to senior leadership. There was nothing driving that particular date, but it was a stand-in for meaningful goals like speed-to-market and establishing the value of a new approach. We certainly had to make compromises to meet the deadline, but the time constraints enabled ruthless prioritization. We got to market sooner with the most important elements and gathered the data to build a case for subsequent investment. If we had been slower, we might not have launched anything at all.

But it could equally be the case that an aggressive timeline isn’t in service of a worthwhile goal, or results in unacceptable trade-offs. It is only by weighing the value of the goals implied by a constraint against the costs to satisfy the constraint, that you can begin to assess whether the constraint is a help or a hindrance.

The balance between goals and trade-offs is not fixed over time. Within an organization, stakeholders come and go. Priorities shift. New implications and trade-offs are uncovered. You should be beholden to constraints — that’s what makes them effective. However, when they are the kind of arbitrary constraint you could relax, you must also constantly interrogate them: What goals are they serving? For whom? What specifically are we giving up to satisfy them? Is that trade-off still worth it? When that balance shifts such that the constraint stops serving a goal, you are probably over-constrained.

Constraint anti-patterns

When constraints are more externally imposed, the question of goals and trade-offs becomes less relevant. However, there are a couple of traps, or anti-patterns that it’s easy to fall into when constraints are more fixed.

Constraints qua Barriers

It’s rare to encounter a constraint that is utterly fixed, in a defy-the-rules-of-physics way. But many constraints feel like they can’t be shifted without breaking the law of gravity: things like lack of money, inadequate technology, or legal and regulatory hurdles. Often, it makes sense to embrace these constraints and use them as creative fuel.

But sometimes, the constraint is actually a barrier — a counterproductive obstacle that makes meaningful progress impossible. In those cases, it might make sense to change course and focus on removing the constraint-barrier. It’s not necessarily easy, but it’s usually possible to find more funding, switch focus to the underlying technological limitation, lobby for a change to the rules. If removing the barrier is not realistic (for you, for now), then it’s often better to cut your losses and apply the organization’s resources to a different problem that is more optimally constrained.

Constraints qua Precedents

Precedents are the sneakiest kind of constraint. You don’t even realize you are limiting your options, but here you are nevertheless tacitly constrained to “how we’ve always done it,” or how “everyone else” does it. Sometimes that’s fine — no need to re-invent the wheel. Other times you find yourself following a well-worn path that isn’t taking you where you need to go.

If you find yourself stuck in this trap, the solve is to turn the constraint on its head: only allow solutions that avoid the precedent. Even as a thought experiment, it can help you see new possibilities when a constraint-precedent is keeping you stuck in old patterns.

Constraints — good ones — are a positive force. The trouble is that within a corporate context, you’re just as likely to run into bad constraints, or excessive ones, or barriers and precedents marauding as constraints. Identifying constraints, the goals they are serving, and the trade-offs they are forcing will go a long way to making constraints a helpful, productive contributor to your work.

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End Notes

Earlier this month I was in Boston for the World Orphan Drug Congress. It was my first time attending the conference, and I learned a lot. One thing that really stood out is how blurred the lines are between parents of children with rare disease, patient advocacy groups, and biotechs. Sometimes, it’s the exact same person wearing all three hats: a parent caring for a child with a rare disease, who has started a patient advocacy group to support fundraising and research, and then created a biotech to develop a treatment. Nothing is easy in this space — the treatments have incredible scientific complexity, matched only by the difficulty of making the economics work for something with so few potential patients. The commitment of individual families was truly inspiring.

We are eagerly following the World Cup. Toronto is hosting six games, but you’d never know it from our corner of the city. The timezones are more convenient, and there were a lot of German jerseys at the St. Lawrence Market a few weeks ago. Otherwise, the tournament may as well be happening overseas. I really don’t know how we justify the $1B price tag for hosting.

Obviously, I read Inside The Box this month. I also read Super Nintendo: The Game-Changing Company That Unlocked the Power of Play. I’m not a video game person. I read the book hoping to learn about the corporate culture of Nintendo. There were some really good nuggets, but also lots of detail about different games in Nintendo’s history, most of which I have never played. For me, that balance was wrong, but I am not the target audience. I expect all those game details would land a lot better with someone who has played more video games than I have.

Fiction this month:

• What We Can Know is a dystopian future of the world wrecked by climate change and world wars, and then it is something else entirely. I was initially mad at the sudden change — I wasn’t quite ready to leave Ian McEwan’s depiction of 22nd-century Britain. I ended up enjoying the second half enormously, but it would be an unfair spoiler to say any more.

• Hamnet by Maggie O’Farrell time travels in the other direction, and takes us back to Elizabethan England and a story about Shakespeare’s wife and family. Probably most people have seen the movie by now; I have not, but I enjoyed the novel very much; the way O’Farrell depicts the transmission of the plague was particularly vivid.

• The Women by Kristin Hannah and Atmosphere by Taylor Jenkins Reid are both set in the 1970s (ish), depicting the personal journeys of women in the very male arenas of the Vietnam War (Hannah) and the NASA space shuttle program (Reid). For me, they were both enjoyable summer reads, and that’s exactly what I was expecting from Reid. Perhaps it was just the pluralization of the title, but I was definitely hoping The Women would have given us a more wide-ranging perspective of the role of combat nurses in Vietnam. Like, how did that nurse-major get where she is? What was the story of Frankie’s other bunkmates? It was a good read, but narrower than it might have been.

Otherwise, we are enjoying summer! The kids are off school for ten weeks this year, so there’s a few extra rounds of summer camp logistics. In between, we are off to New Brunswick for three weeks of family time and outdoor adventures, which I’m really looking forward to. To that end, this newsletter will be taking its annual summer hiatus. I’ll be back in your inbox in mid-August with a new interview in the women’s entrepreneur series. Wishing everyone a lovely summer!

In comradeship,

S.

There is an old Wait But Why post about familial relationships and human lifespans. Tim Urban estimates that by the time he turned 18 and graduated high school, he had spent 93% of all the in-person time he would ever have with his parents. If pre-age-18 time is evenly distributed1, that would mean my 10-year old and I are over halfway through our in-person time together.

I’m not ready to be halfway through. It is going too quickly. They are growing too quickly. I would go back to the start and do it all over again; alas, I am growing old too quickly.

Since being maudlin never helped anyone, let me instead tell you about how ten is a truly excellent age. When my sister was that age, she declared her intention to stay ten forever, and she was quite correct. Ten is little enough to clamber into bed for a morning cuddle with an armful of stuffies, to play with toy trains, to actively seek out time with Mom and Dad. But it’s also big enough to do adventurous, ambitious things, to ask big questions, to order up beef Wellington and chocolate stout cake for a birthday meal. It’s a wonderful interstitial age, between little kid and surly teenager. I’m only about a week into it, but so far, it’s 10/10, no notes. If kiddo and I really are launching into the back half of our in-person time together, this is a wonderful place to launch from.

Meanwhile. Earlier this spring (back when I still had a nine-year old), I had the chance to sit down with Melissa Williams, Founder of Simply Patient. Melissa and I both spend our days working at the intersection of patients and biopharma, so we have a lot of common ground. We also both like to geek out over systems thinking and the architecture of decision-making, and I’m pretty sure we both had the same pirate lego set growing up. The legos turn out to be surprisingly central to her entrepreneurial story.

I hope you’ll enjoy reading it. Many thanks to Melissa for taking the time to chat.

A conversation with Melissa Williams

This installment in the Women’s Entrepreneur Series is an interview with Melissa Williams, the founder of Simply Patient. With Simply Patient, Melissa applies her expertise from 20 years in biopharma to help biotechs incorporate patient voices earlier in the development of new drugs. They focus on working with teams at two different stages: (1) very early on, when decisions are being made about clinical trial design or portfolio investment, and (2) in the 2–3 years leading up to a drug being approved and launched, when there is an opportunity to engage with patients on a larger scale.

In this interview, Melissa talks about the mission of Simply Patient, why patient-centricity can be challenging in pharmaceutical companies, and how she stays laser-focused on bringing patient voices earlier in drug development.

Susan Bartlett: Prior to starting Simply Patient, you worked for 9 years at Genentech. How has the experience of working at a large biotech shaped the choices you’ve made in setting up Simply Patient?

Melissa Williams: I recently stumbled across my college admissions essay to MIT, and I was shocked how much it still rang true. In that essay, I described my approach to Legos: first follow the “standard” approach according to the instruction book and then throw out the instructions and build what feels right, feels unique, feels interesting.

Genentech was an extraordinary place to learn a “standard” approach in the company that literally formed the biotechnology industry. I got to work across a broad swath of groups: insights and analytics, marketing, and patient services. Between my experience at Genentech, Ultragenyx, and management consulting, I started to see how the Lego pieces of patient engagement could be put together differently.

I’m a systems-thinking nerd, so it was fascinating to see how the various parts come together (or didn’t). All too often, Lego pieces placed years earlier limited what was possible for patients. I formed Simply Patient to change that. To go back to my admission essay, I took all the things I learned from the “traditional” approach, and I formed a company to put the pieces together in new ways and help teams take a better approach into the future.

Often, that starts with doing less, better.

SB: Can you unpack that for me? What does it mean for a biotech to “do less, better,” in the realm of patient centricity?

MW: Now more than ever, teams are stretched: stretched for time, stretched for budget, stretched for focus. I love helping teams focus and see which patient inputs are worth prioritizing sooner than later.

That really matters in biotech because of the timescales. In tech, you can swap in a software feature and A/B test. In developing medicines, you’re making choices and you won’t have the data on how it worked for five or ten years. When you’re making that kind of one-way door decision, how do you bring in patient voices to make the best decisions as early as possible?

So many of these decisions are made by scientists and clinical researchers. They are often extraordinarily good at thinking about the disease and its mechanisms. They can make assumptions about what patients care about, but they don’t have the lived experience of a 3am wake-up, worrying over an agitated child, or the logistical headache of managing a complex disease alongside two other school-aged children.

One of the most powerful ways for drug companies to tap into the patient reality is through partnerships with patient organizations. Patient organizations represent the collective voice of larger groups of patients.

It’s not just stories though. The trick is bringing in the right patient inputs at the right time to meaningfully shape the trade-offs that inevitably arise in drug development. That can be anything from drug candidate design to clinical trial design. All too often, teams discover that their assumptions were wrong when trials fail to enroll enough participants. Involving patients earlier helps get ahead of costly delays.

In the spirit of helping teams focus, we’ve been working on a book that will be published next year. The book is a guide for patient organization leaders on how to partner with biopharma in mutually beneficial ways. Drug development needs patient voices, and this guide will make it easier to focus on what matters earlier.

SB: People working in pharma and biotech are overwhelmingly motivated by wanting to help patients. So why is it so hard for organizations to translate that into practice? Why does it break down?

MW: It’s a system-level challenge. Individuals advocate to bring patient voices into their programs, but imagine that individual in a high-pressure environment where budgets are constrained and teams are shrinking. Relying on individual advocacy in that moment is hard. The industry is evolving. Thirty years ago, patients were “subjects,’ while today, patient-focused drug design is the regulatory expectation. However, even with that expectation, large, complex systems are slow to evolve.

When large, complex systems are slow to evolve, how do you change? One approach is intentional milestones. For example: in order to submit your phase two protocol for ethics review, you are required to have patient input on the endpoints [the data you are collecting to determine if the medicine is effective]. When we have that kind of specific milestone, patient centricity becomes the way business is done.

The small companies are doing cool stuff in patient centricity. They have the flexibility and the courage. One company that I really admire is Argenx. They made a choice that I think should be industry-standard: they combined patient advocacy, patient marketing, and patient services under one executive. In doing so, they intentionally brought together the silos that are patient-related into one decision maker. Cohesive patient experience is all the easier with cohesive decision-making. I think it’s fabulous.

SB: How does human‑centred design show up in biotechs, and how can it be more useful as a discipline within that context?

MW: If the “what” we focus on with Simply Patient is bringing patient voices earlier, the “how” is by getting disparate people moving in a common direction. For that, human-centred design becomes an inherently practical tool to achieve those outcomes. It provides a framework for diverging and capturing all the different perspectives in the room. Then it provides the framework for converging, so that collectively we can agree on the needs and the priorities to make better decisions and move together in one direction.

The other element I find so powerful is the separation of problem definition and problem solving. It is so easy, when you’re moving quickly, to jump into problem-solving, and that is when the patient tends to get left out. By treating problem-definition as a separate step, you stay focused on who you are designing your solution for. That keeps your work grounded in patient needs and realities. People who have been through a process and really believe are better able to articulate the “why.”

SB: How do you keep your focus on patients and rare disease? How do you handle it when you get requests that are from outside your focus area?

MW: In the first year of Simply Patient, I was approached by a former colleague who wanted my help, but it was focused on prescribers, not patients. I could help, but it was outside of where I wanted to focus the company. That was the first tangible point where I had to put my money where my mouth is and walk away. It meant continuing to burn through the runway of what I was investing in the business, and I’m so glad that I did.

It really embodied the bigger mission: I formed Simply Patient to help biopharma get patient voices earlier in drug development. As it became the reality of how we spend our time, which made it easier in future conversations to continue to say, “This is what we focus on.”

We are more flexible when it comes to rare vs. specialty diseases. Our approaches and tools transfer well across specialized, complex conditions and competitive markets. That said, despite having years of experience in diabetes, I probably wouldn’t work in that disease state. The need for patient voices in drug development is the same, but the tools to reach millions of people are very different.

SB: What has been surprising or unexpected about how these first four years with Simply Patient?

MW: I think the biggest joy, challenge, surprise, delight, has been who I have become as a result of creating Simply Patient. I am still myself (like that early MIT admissions essay), but it’s like I’m meeting different parts of myself. It’s such a fun experience to get to do my life’s work on something that is so deeply meaningful and do it in a way that is so deeply personal. I look forward to the future where I get to look back and see how the decisions we shaped play out better for patients thanks to our work.

End Notes

This month, we took the kids to Montreal for the long weekend. The highlight was Pointe-À-Callière. Although I’ve visited Montreal many times, somehow I have never been to them museum, and it’s wonderful. The museum is a sprawling set of buildings that integrate the archaeological remnants of the original settlement of Montreal into the exhibits. The history of both First Nations and settlers is presented in a super compelling way, and the pirates exhibit and Alley-oop interactive were a huge hit with the kiddos.

It was a great month, book-wise — I loved everything I read:

• Crossing to Safety is a beautiful meditation on a decades-long friendship between two couples. I feel like we rarely see adult friendships depicted at all, let alone with this kind of depth and poignancy. It’s well worth your time.

• Liz Moore’s God of the Woods is a more recent thriller/mystery. It’s a perfect summer beach/cottage/vacation read.

• Over in non-fiction, Everything is Tuberculosis, is more entertaining than a book about TB has any business being. It toggles between a real-life TB clinic in Sierra Leone and the role of TB in history, literature, science, and public health policy. It’s a surprisingly easy read, and you’ll come out much smarter about the world.

• In the bedtime story division, the kids and I are finishing up The Outsiders, and it was a HORRIBLE MISTAKE. It is far too violent to read to your eight-year old and you should not do it. But, also, while they found some parts scary, both boys completely loved it, and maybe we shelter kids too much. After all, S.E. Hinton was only 15 when she wrote it.

Finally, I would be remiss not to share the recipe for the chocolate stout cake requested by my birthday boy. It’s an absolute first-team all star of a cake — easy to whip up, not too sweet, and holds up well for multiple days (supposing it lasts that long). I make it with the best cocoa I can afford, and top it with about half of the ganache recommended in the recipe.

See you back here next month! In comradeship,

S.

Last year was rough for my dad. He started the year with six months of chemotherapy, which he tolerated stoically. On the very day he got the happy news that he was in complete remission, he was thrust into another, more dire medical crisis. Four surgeries in three months. ICU stays. Organ failure. Family rushing to the bedside, in case it was goodbye (twice). Then, a tenuous recovery — the kind where you visit this month, in case you can’t visit next month.

He was so physically diminished. He joked that the only thing he hadn’t lost was his broadcasting voice. It was true that you could talk to him on the phone and trick yourself into believing he was fine. But there was no tricking yourself when you saw him in person: frail, emaciated, housebound. It was really hard for him and there were dark moments, despair. No one was sure what kind of recovery might be possible — the surgeons had never seen a case like his.

My dad is not what you would call happy-go-lucky. If anything, he has a tendency to catastrophize, to react to small setbacks as if they were major disasters. But equally, he can be a person who greets real problems with pragmatism and determination. I still remember the flat tire during one of my first driving lessons. His reaction was nothing but sanguine — what an excellent opportunity to learn how to change a tire!

If not exactly sanguine about his health ordeal, Dad brought plenty of pragmatism and determination. He worked hard on his physical recovery. He had great gratitude for the care he received1. He nurtured hopes for the future, and then turned them into things to look forward to and work towards.

And, so, this past weekend, less than six months removed from his most recent ICU stay, he hosted his children and grandchildren for a birthday weekend. He tired more easily and was not quite as spry as he was at, oh, 78. But mostly, he was his old self, and we were our old selves with him. He played trains with his grandsons. We went out to brunch. We joined him for 2km (!) walks in the spring sunshine. And as he drove us to the airport (!!), we made plans to see him in a few months’ time.

It was a special occasion, but really it was a celebration of normalcy, and being able to do the little things you enjoy with the people you love.

The rest of this month’s newsletter is about creating caregiver-friendly workplaces. Obviously, that has been more on my mind on account of my dad’s situation, and I have helped out where I can. But it is my mother who has been shouldering the caregiving burden, allowing my siblings and I to continue with our parenting, our work, our lives.

As hard as the last year has been for my dad, it has been equally hard for my mom. I see what she has taken on, and I don’t know how someone manages that while also trying to perform at work. The daily demands, the uncertainty, the emotional turmoil — it’s a lot. Too much. And even with this wondrous recovery Dad has had, there are still hard days and struggles, and she is there for him still.

All weekend, you could see how proud she was of him and how far he has come. Rightly so. But I hope she is proud of herself too, because without her caregiving, it couldn’t have happened. His recovery is a triumph for both of them.

Happy birthday, Dad. And thank you, Mom. Love you both. ♥️

Caregiver-Friendly Workplaces

An employee steps out to take a call. Her dad has Alzheimer’s and she is working on finding him a new nursing home facility, closer to her home.

An employee asks about a workaround for the team’s weekly meeting. She drives her mother-in-law to stroke rehab that happens at that time.

An employee needs time off to go stay with his mother overseas, who lives alone and will need help in the first few weeks after knee replacement surgery.

An employee works an 80% work schedule. She spends her day off caring for her mom and preparing for the week ahead, so that she can better balance work and caregiving the other six days of the week.

Real people, working mid-career knowledge jobs while balancing caregiving responsibilities2. These are just the ones that emerged in our team’s orbit over the last week.

If supporting working caregivers isn’t currently on your organization’s radar, it will be soon. The population is aging. Modern medicine helps people live longer, but often in ways that require more intensive, hands-on care. Unpaid family caregivers play a critical role: the Canadian Centre for Caregiving Excellence estimates that replacing caregivers with paid care providers like personal support workers would cost nearly $100-billion dollars every year.

Meanwhile, households are getting smaller, people are retiring later, and more people (specifically, more women) are in the workforce. The math is inevitable: employees with caregiving responsibilities will increasingly be the norm.

Balancing caregiving and paid work

Balancing paid work with caregiving is difficult. Eighty percent of employees with caregiving responsibilities said it negatively affected their productivity. How could it be otherwise? Caregiving is physically, emotionally, and mentally draining. For caregivers who work full-time, the average daily time spent on caregiving tasks is 4.5 hours. Add that on top of an 8-hour workday and it’s no surprise caregivers struggle to consistently perform their best at the office. Indeed, the burden of the two roles proves too much for many caregivers, with nearly one-third of workers reporting they chose to leave a job because of the difficulty in balancing competing demands from work and caregiving.

Employers, for their part, often profess a desire to be supportive of employees with caregiving responsibilities. Many employers offer a mix of benefits3, ranging from “accommodative” (benefits that don’t incur additional costs like flexible work schedules, working remotely, reduced schedules), to “appropriative” (offerings that require additional spending like elder care subsidies, care provider referral services, counselling services). However, other than flexible work hours, most benefits are only offered by a minority of employers. When benefits are offered, uptake is low. Often, awareness of the benefits are low, but employees also worry that taking advantage of accommodative benefits might negatively impact how they are perceived and rewarded at work.

Those fears are well-founded. When researchers drill down to the level of individual behaviours, employers say the behaviours that impede career progression include arriving late and leaving early, unplanned absences, shortened hours, leaves of absence, turning down work travel, and rearranging work schedules. In other words, the very things that caregivers require in order to balance work and caregiving responsibilities.

In fairness to employers, when employees are actively managing caregiving responsibilities, lower job performance is likely. Over the long run, research shows that caregivers bring advanced skills in areas like empathy, time management, and teamwork. But during moments of intensive caregiving, employers aren’t seeing the benefits of those skills. Meanwhile, to the extent that employers offer appropriative support, the business will incur additional costs. That might create a temptation to gravitate towards employees without caregiving responsibilities who require less in the way of either accommodative or cost-incurring benefits.

Except, where will you find these employees? With all the structural trends, at least half of the workforce will be in a caregiving role at some point in their working life. If your organization does not support caregivers, you will be shrinking your talent pool, to your detriment. Research suggests that senior staff — the ones who are hardest to replace and have the largest organizational impact — are disproportionately more likely to leave a job because of care commitments.

The maternity leave analogue

An obvious analogue for caregiving is maternity leave. Fifty years ago, maternity leave in Canada was 15 weeks of benefits funded through what was then called Unemployment Insurance. As workers lobbied and negotiated for more robust paid leave policies, organizations worried that it would be too expensive, or that it would lead to women having more pregnancies because the benefits were in place.

That is not dissimilar to the status quo for caregiving benefits. Since 2017, Canadian employees can access caregiver benefits through the government’s Employment Insurance program. Like the initial 15 weeks of maternity leave benefits, the caregiving benefits are better than nothing, but the duration is still relatively short and doesn’t cover every situation. The employee is left to navigate it alone, while juggling caregiving responsibilities, as most employers are reluctant to provide information, citing a lack of familiarity with the details.

Today, Canadian maternity and parental leave benefits are far more robust than when they first rolled out. Benefits are available for 50+ weeks, and eligibility has expanded. Many companies offer “top-up” payments on top of the EI-funded benefit, as a way of attracting and retaining talent. HR departments are experienced at administering the programs, while the government has developed streamlined online applications. Old fears about the cost of the program or “excessive” uptake turned out to be unfounded.

Parental leave is not a perfect analogue for caregiving leave. When it comes to babies, the averages are not a guarantee, but they are a helpful guide. Mostly, parental leaves can be planned for, and infant development follows a predictable (if imprecise) set of milestones. A new baby is generally a happy event, widely announced and celebrated, and the relationships are clear-cut. Many people may help welcome a new child, but only the parents take leave from work.

Caregivers, by contrast, are sometimes thrust into their roles without warning. There is very little predictability to caregiving demands over time. Care needs might be stable, progressive, or episodic, and each of those might require different accommodations or support. The time horizon for caregiving is open-ended, with an average of 4.5 years. Caregivers tend to keep details private, and while it can be a rewarding role, it is often one tinged with sadness, grief, frustration.

Caregiving relationships are also more varied. An individual might provide care for a parent, sibling, spouse, adult child, or friend. Equally, they might share caregiving with multiple people, or not.

These differences notwithstanding, the evolution of parental leave provides a template for what might be possible in the realm of caregiving leave — a foundation of well-known, publicly-funded benefits with near-universal uptake amongst eligible employees, with many employers voluntarily providing varying additional supports as a way of competing for talent and supporting employee well-being.

If that is the destination, maternity leave equally helps us understand a possible path to get there. It was 30 years after the first maternity leave provisions before parental leave was extended to a full year, and further adjustments have been ongoing. Collective bargaining in unionized workplaces was critical to making maternity leave top-up payments a standard. Even today, parental leave policies vary wildly across organizations, with some offering no top-up whatsoever while some offer a full year at full pay.

What can organization do now

For now, there is a wide gap between the way EI-funded leave addresses the needs of new parents compared to the needs of caregivers. Meanwhile, you certainly have caregivers working in your organization right now, who would benefit from support. What does a caregiver-friendly workplace look like today?

Deepen everyone’s understanding of caregivers and their needs

One of the most striking things in the caregiving literature is how poorly employers understand the needs of their employees. Organizations consistently underestimate the proportion of their workforce with caregiving responsibilities, and the extent and range of those responsibilities. There is also a tendency for people to see “caregiving” and jump to “childcare.” Parents of young children are quick to share the demands they juggle, while caregivers to adults tend to be more private about their situation. That can contribute to caregiving being underrepresented. A clear definition that delineates them as two separate spheres can help the organization get a clearer picture of the caregiving responsibilities of their workforce.

At the individual level caregiving is so varied, so it’s important to understand the specifics of each situation. Many caregivers are reluctant to share details, however, because it’s the health information of another adult, whose privacy ought to be respected. A question that can help: “what would you like the organization to know about your caregiving responsibilities?” The answers to that question can help the organization develop solutions. Sometimes, something as simple as rescheduling a key meeting can make a big difference. By understanding the extent of an individual’s specific caregiving responsibilities (and how they evolve over time), managers and HR teams can tailor their support to a caregiving employee’s specific needs.

Normalize caregiving responsibilities

Employees are reluctant to speak up about caregiving responsibilities because they fear the consequences. That can create a negative reinforcement loop where uptake is low, the need is underestimated, organizations under-invest, and caregivers are undersupported. When under-supported, caregivers struggle at work. Those struggles can further entrench stigma around caregiving and make caregivers even more reluctant to share their caregiving situation or ask for support.

To break that cycle, leadership needs to be proactive in creating an open culture around caregiving. Very likely, there are senior leaders in your organization currently dealing with some aspect of caregiving. If they speak openly about their responsibilities and how they are balancing their workloads and accessing benefits, it makes it easier for others to speak up and get the support they need.

Formalize organizational support for caregivers

Many of the accommodative benefits that caregivers most value may already be in place at your organization — flexible hours, reduced schedules, remote work, unpaid leave. Framing these explicitly as part of your organization’s caregiver benefits can make it easier for individuals to ask for them.

Canadian employers can also proactively communicate about the EI program’s caregiver benefits. HR administrators are not as familiar with the program as they are with parental leave benefits, but employees juggling work and caregiving duties will find it especially difficult to navigate a new and unfamiliar program, so any organizational support is helpful. Over time, awareness and familiarity with these programs will grow, making them easier for everyone to access.

Think too about the broader cultural signals your organization is sending. When an organization insists that everyone must be in the office five days every week (or else), it sends a strong negative signal to caregivers who rely on working remotely to balance work and care. Workloads really matter too. If you assign people to work with the goal of resiliency in mind, then accommodations for caregivers are easier to manage. If, instead, you staff as few people as possible and assume AI will get you to maximum output, accommodating caregivers will be much harder. Supporting caregivers is antithetical to the current tenor in a lot of organizations, so if you are currently insisting on face-time or shrinking the workforce, it will take a lot of conscious and deliberate counter-programming for that to not translate into a hostile environment for caregivers.

Finally, based on what you know about employee needs, think hard about the appropriative benefits that might make sense for your organization. Your organization is almost certainly incurring costs due to caregiving—presenteeism, employee burnout, turnover. They just don’t show up as caregiving-related on the bottom line. If you can get a clear picture of the true organizational costs of caregiving, it’s easier to build a business case for benefits that cost real money, but help caregivers better balance their care responsibilities and perform well at work. For many caregivers, paid work is a welcome reprieve from care work, and programs like provider referrals, respite care, or cost subsidies can help them be more productive in the office and provide better care to their loved ones.

End Notes

This month I did succeed in getting my children settled in separate bedrooms. I’m still sorting through all the things that came out of the erstwhile office, but it feels great to have the project completed. I especially appreciate that I no longer have to referee post bedtime arguments over who is being the loudest and keeping the other up. (Don’t worry — they have found other things to argue about.)

Speaking of projects, I have spent the whole of April tackling David Copperfield. I was inspired to do so after reading Demon Copperhead last year, and it has been very interesting to see all the ways Barbara Kingsolver adapted the original Dickens story for her more modern setting. When I started on the Dickens, I didn’t fully appreciate that it is one of his longest novels, clocking in at nearly 360,000 words. Anyway, it has been mostly enjoyable, sometimes a bit of a slog, and when I finish these last 50 pages I’ll be glad to dive into something new.

April has felt like a very busy month for me— lots of travel, lots going on at work. One of those work things is some new articles about patient marketing for pharmaceuticals. At most, I get an editing credit on these, as others have been doing the heavy lifting. But pharmaceutical marketing can be a fraught topic. Recently, the topic has been in the news, as the FDA has cracked down on pharma companies and sent a lot of warning letters. We try to take a different approach to these kinds of patient materials, and we outlined some of our philosophy in these posts. If you’re interested, you can check them out here:

• Thinking holistically about patient experience

• Redesigning important safety information

• Clarifying clinical trial results

• Elevating visual strategy

In comradeship,

S.

Gifts at a kids birthday party can feel a little fraught. In the circles my children run in, the done thing is to request ‘no gifts,’ or ‘a five-dollar bill.’ It makes so much sense. The modern post-capitalist kid is over-burdened with “stuff,” and truly doesn’t need any more. Everyone is so busy, and finding and wrapping a birthday gift is another weight on a too-heavy to-do list. All gift-giving results in economic deadweight loss, but presents for a kid you don’t really know are especially likely to miss the mark. By the time you add up a year’s worth of birthday parties for every kid in the house, the cost can be a stretch.

I co-sign all of that, and yet putting ‘no gifts’ on an invitation always gives me pause, because I simultaneously have other thoughts in direct opposition. It’s lovely to think about what your friends might like as a gift. It’s helpful for kids to practice graciously receiving presents (even and especially when the gift misses the mark). Exchanging gifts is a way for little people to learn about generosity, gratitude, and reciprocity, which is another way of saying it’s a way for them to learn how to be in a community.

Torn in both directions, I ended up telling the parents that presents were not necessary (and meant it). Some kids brought presents anyway, and we thanked them graciously (and meant that too). And one little boy told his parents that he really wanted to give my kid a particular toy1, knowing my kid really wanted one. And when my kid opened that present, he was —no other word for it — overjoyed. Yes, for the toy. But also, because his friend knew just what he wanted.

On Journey Maps

The customer journey map is nearly ubiquitous in the modern enterprise. Historically, companies were organized around functions (customer service, supply chain, billing), or individual products and services. The result was that when customers would deal with large companies, the experience would be disjointed. The person helping you with your mobile phone couldn’t do anything about your Internet, even though it was the same company.

The journey map was intended to help with that problem by creating a single, unified model of the customers’ experience. By aligning to the customer journey, all the disparate teams working in different functional areas on different products or services could be contributing to a unified, consistent experience. The goal was to make things better for customers, while also creating efficiencies for the organization by reducing duplication of effort across big organizations.

So far, so good. The customer journey is a useful construct. Within organizations, there’s an unfortunate tendency to narrow our attention to our own scope and be a bit oblivious to interdependencies elsewhere in the organization. Journey maps are a tool that helps us look left and right, connecting dots across silos, making sure our work is aligned with work elsewhere. Today, it’s much more common that you can call your bank and the same person will help you sort out your credit card and your savings account. Journey maps were a tool that helped that happen.

But somewhere along the way, the journey map morphed into something else. Journey maps became evidence of customer centricity, rather than a tool to enable it. They became bludgeons to enforce organizationally-driven standards via overzealous maintenance of existing maps, without regard for variation in customer needs. It didn’t happen in every organization, but often enough that any journey map now deserves some skepticism. Is this a journey map that is truly in service of the customer? Or is it customer-centricity theatre?

A typology of journey maps

There are actually two different kinds of journey maps that serve two different purposes.

• The Journey-Map-As-Alignment-Tool is primarily a communication tool for translating across functions.

• The Journey-Map-As-Problem-Solving Tool is primarily a tool to visualize information, clarify a problem space, and find solutions.

Maps as alignment tools

If you’re building a map as an alignment tool, the objective is to help everyone in the organization put their work in a customer-centric context. These maps have a broad audience, and it should be relatively consistent over time. An organization doesn’t need to have one map to rule them all, but there should be relatively few, and they should be simple and memorable.

The analogy here is the map the cruise ship company uses to sell you on an upcoming voyage. They are glossy. They help you understand why these destinations are important and what makes them desirable. However, they leave out a lot of complexity in order to do the job of communicating.

If you are a biotech, you might build a map like this for the patient journey, highlighting the various hurdles and milestones patients and caregivers must navigate in order to receive your therapy. If you are embarking on an AI-driven transformation, you might create one so that the many different functions involved can remain focused on the customer value opportunities, rather than technology capabilities.

You would be right to insist that everyone align to the big picture of the map, and that it not be changed on a whim. Whenever many stakeholders need to be on (and stay on) the same page and have a common language to bridge different groups, a Journey-Map-As-Alignment-Tool is a valuable construct.

But having one journey map to outline the big picture and bridge different groups does not mean your Journey-Maps-As-Alignment-Tool is the be-all and end-all. Certainly, some of the cruise ship stakeholders will never need a map more detailed than the one in the brochure. But up on the bridge, we want the captain and crew to be using proper navigational charts.

Maps as problem-solving tools

What the captain and crew need is a map that helps them solve their very specific problem in their very specific role. They need a map-as-problem-solving tool. Like navigational charts, the audience for such maps is typically very narrow, and might require specialized knowledge to interpret. Unlike their alignment-map cousins, simple and memorable is not a helpful goal. These maps should be fit-for-purpose, in the sense that they get you where you’re going.

The London Tube map is iconic. It’s incredibly effective for navigating the London underground. It’s also next to useless for getting around above-ground on foot or in a car. That isn’t a shortcoming of the Tube map but rather a metaphor for what a problem-solving map should be.

To create a useful map, you must make choices to simplify real-world complexity and emphasize important relationships. In the case of the London Tube map, the designer chose to abstract the relationship between tube stops and cardinal directions, in order to better represent things like transfer points and fare zones. The same thing happens when you make a journey map as a problem-solving tool. You will abstract certain things and emphasize certain relationships, in service of the problem you are trying to solve.

The trouble begins when the map is complete. It almost certainly took a lot of effort and represents a lot of excellent thinking and new insight. Understandably, you want to show it off. But maps carry a certain organizational cachet, so as soon as you start sharing it more broadly, it becomes a quagmire. Other stakeholders experience your map as wrong and possibly dangerous. Imagine the Parks Department looking at the Tube map. You’ve removed all the parks! Does that mean you don’t think parks are important? That the parks department doesn’t do valuable work? Of course, it just means that the parks aren’t very relevant for the job of planning a subway journey, but that’s not how people experience it when they see their core contributions unrepresented.

Let a hundred journey maps bloom

The answer to this problem is to be clear on the distinction between alignment maps and problem-solving maps. For the latter, eschew standards and let them propagate at will. The value of a problem-solving map is largely in the mapping process — figuring out and visualizing what is salient for the problem space. The outputs should be as different as the problems themselves. Only one or two alignment maps have value as ongoing artifacts, helping keep teams on the same page, as they go about their more detailed work.

Within the realm of problem-solving maps, there is no “right way” to build one, or a “correct” set of attributes to capture. If we’re making a map for the experience of cancer patients, it’s very important to document patients’ emotional and physical well-being. If it’s the journey for renewing your cellphone, probably not so much. If the problem you’re trying to solve is how patients’ safety questions get addressed through the call centre, and you’ve only got a map of the full disease journey, the map is not going to help you. You may as well try to navigate the streets of London with a globe. Eventually, organizations will end up with all kinds of different maps, and for the most part they won’t fit together to form a coherent whole. That is okay.

Organizations put entirely too much effort into creating, maintaining, and organizing, rather than treating journey maps as tools to get a job done. You spent a lot of time making the map, but the valuable output is the problem that you solved, not the map itself. Their audience is limited to the team of people directly working on the project and their usefulness expires once the project is done. It follows that most maps should be much less beautiful. The truth is that most of the time, we should be making, ugly, low-fidelity maps, with sticky notes and markers, or on a Google spreadsheet. That helps clarify that their role is as problem-solving tools rather than the loftier, big picture alignment maps.

Although historically a tool for big organizations with silos to bridge, organizations of every size can benefit from journey mapping as a problem-solving tool. Whenever you have complex, multi-faceted, multi-stakeholder problems to solve, mapping can make it easier to find creative solutions. Just be clear on the kind of map you’re building, and avoid over-engineering every map into a permanent entity that needs care and feeding.

End Notes

In March of 2020 (was it really six whole years ago?), we hastily created a shared bedroom for our two boys, so that the third bedroom could be a home office while we weathered the pandemic. Fast forward to 2026, with growing boys and back-to-work mandates, we’re doing that in reverse. Operation Office-to-Boy-Bedroom is an enormous undertaking, as we’re really paying off 6+ years of decluttering debt. I would love to report that the project was completed in March, but that would be a lie. However, I did spend a good chunk of the kids’ school March break sorting and organizing, and it was very cathartic to get rid of manuals for appliances we no longer own and decades-old tax paperwork.

In between my bouts of sorting and organizing, we also had some school break adventures with the kiddos. Some highlights:

• We saw Hoppers in the cinema, which really hit my boys’ sweet spot of animals + politics + 1980s rock classics. “Everybody’s working for the weekend” is now officially in the rotation.

• I can recommend an early evening trip to the aquarium. It’s a good time to go with older kids, as it’s a bit less crowded and $5 cheaper after 5pm.

• At home, we marked the end of the minor hockey season by sitting down to watch the original Mighty Ducks movie. The flying V still slays.

In March I read Creation Lake, James, and Wild Dark Shore. I loved James. It’s a retelling of Huck Finn from the perspective of Jim, the slave, and it has inspired me to reread Mark Twain. Creation Lake was a disappointment. Perhaps the book is Good, Actually. But I went in expecting a thriller about a beautiful secret agent infiltrating an anarchist collective to foment unrest. What I got felt like a slow-moving slog, and it was just too big an expectation gap for me to cross. But I got all the redress I needed from Wild Dark Shore, which was the page-turning story about a beautiful woman infiltrating a remote group that I was looking for.

In April, we’ll tackle the next phase of Operation Office-to-Boy-Bedroom, which will feature a lot of furniture disassembly and reassembly. More daunting: a cull of the picture books that were once read endlessly to little boys in footie pyjamas, but have now been supplanted by piles of novels and non-fiction they read by themselves. I’ll need all my reserves of both physical and emotional strength, I think. Wishing you plenty of both in the month ahead.

In comradeship,

S.

Of course, these are not real toy stores. They are AI-generated images superimposed on Google streetview. If you go to these addresses, you’ll find they’re all just regular houses.

I don’t know the specific grift here. Presumably, no one is trying to lure bricks-and-mortar shoppers to non-existent retail stores… these fake toy store listings must be meant to buttress a scam on some social media platform. They are obvious fakes if you know the neighbourhood, but if you were looking up just one store to verify what you saw elsewhere, it might be good enough.

That was December. Since then, I have seen a steady stream of stories about all the ways AI fakes are costing us time and money.

• Made-up sob stories tugging our heart strings so we will overpay for generic, mass-produced goods.

• Fake AI-generated reviews drowning out real human perspectives.

• Real estate listings increasingly using AI photos to make houses and apartments seem larger and more desirable than the real thing.

• Fake recipes with fake recipe photos overwhelming recipes featuring actual food eaten by actual people

• Even death offers no reprieve, with AI-generated obituaries targeting the bereaved to generate revenue from memorial flowers and candles.

The Internet has always been a place where nobody knows you’re a dog, with a fair share of unreliable information. But also, most of what you found on the Internet was authentic. Perhaps not always accurate, but mostly real people sharing what they really believe. Through sheer volume, LLMs are changing that. In more and more domains, the preponderance of information is AI-generated fakes. It’s increasingly hard to find the real human signal amidst all the AI noise.

If this was just about the Internet as a channel, I could be sanguine about it. But online information is so completely integrated into our lives, I worry we are losing the very ideas of reliability and trust.

We navigate the world (online and physical) with a strong default assumption of truthfulness and accuracy. Most people are mostly honest. Historically, publishing information required a fair amount of effort from multiple people. If you saw something written somewhere, it was probably reliable.

The AIs are changing the priors. When a small number of individuals with nefarious motives can effortlessly publish infinite fakes, it becomes foolish to default to trust. Instead, we start to default to doubt — a constant state of high-alert, skeptical about everything, forever asking, “Is this real? Is it trying to trick me?” Norms around honesty and truthfulness break down. Cynicism is the only rational response. And in our hyperconnected world, that won’t be an online-only phenomenon. Cynicism will be just as pervasive as the technology that demands it.

We’re not there quite yet. But I think we are underestimating the risk inherent in all the AI-generated fakery. It’s not just the time and the money, the added search costs and the petty grift. It’s the erosion of trust in society at large.

“Dishonest dealings tend to drive honest dealings out of the market,” wrote economist George Akerlof back in 1970. His model predicts that misrepresentation leads to total market collapse. When people can’t discern reliable from unreliable, they stop consuming. If there are no more consumers, it becomes pointless to produce. Soon, the only thing left is AI-generated chimera.

You don’t know what you’ve got ‘til it’s gone. Our economy and our society run on trust and reliability. By letting AI run amok, we are in the process of undermining those things. If we’re not careful, we’ll destroy them altogether. And once they’re gone, I don’t know how we’ll get them back.

Co-creation and Construal Level Theory: Helping stakeholders think about the details

There’s a famous New Yorker cover called the View of the World from 9th Avenue. It shows a couple of blocks of Manhattan in exquisite detail, but as we look further into the distance, the world becomes increasingly fuzzy and abstract.

The illustration is a commentary on how New Yorkers view themselves as the centre of the universe, but it *also* captures a psychological phenomenon called Construal Level Theory, or CLT. In its most simple form, CLT says that our brains, as a sort of shortcut, remove most of the details from our mental images for anything that feels distant or remote.

Remoteness can be a function of geographic distance, but it can equally be something that is happening a long time from now (vs. imminently), to some unknown individual (vs. to you or someone you know personally), or hypothetically (vs. certainly). Typically, all these dimensions go together. So, if something is geographically distant, then it also feels somehow more hypothetical, more impersonal, further into the future. And we maintain an abstract, light-on-detail construal of that idea, until such a time as it feels closer, more immediate, more certain, or more personal. Only then does our mental model become much more concrete and detailed.

CLT explains why stakeholdering is so hard

CLT has important implications for stakeholdering and change management in organizations. Imagine you are trying to get buy-in for an initiative. Step one: gather your stakeholders and fire up PowerPoint. By its nature, a slide deck is an abstract representation of your initiative, so it will automatically make your initiative feel far away, impersonal, hypothetical.

No matter how many concrete details you share, CLT suggests that people will not keep those details in their mental model of your initiative. Instead, stakeholders will retain a few key features — whichever ones feel the most relevant to them personally. It’s not that they don’t care about those details. (Often they will have very! strong! views!) It’s that those details are just not currently in their understanding of what you just presented. It’s like a kind of detail blindness.

CLT further tells us that in this high-level state, people tend to be more optimistic — underestimating future difficulties1 — and more open to being swayed by others. CLT grimly predicts what will happen next: in the early meetings, everyone has a somewhat different, somewhat vague, overly-rosy picture of the project. Buy-in achieved!

But buy-in for what?

Some weeks or months later, you come back to the same stakeholders, this time sharing an imminent eventuality, rather than a distant possibility. Now, the details that were peripheral are very salient, and near-term worst-case thinking replaces long-term optimism. Buy-in dissipates.

It doesn’t matter that the details are not new and you shared them before. What matters is that your stakeholders now have a completely different mental model of the initiative — one that is much more concrete and detailed. It feels like you are back at square one, because you are — needing to re-enroll people in a whole new, far more detailed conception of the project.

Co-creation is a tool to shift stakeholders’ construal level

Co-creation can be a bit of a buzzword. Sometimes people use “co-creation” to mean seeking feedback from a group of customers (we might call that a focus group). Sometimes people use “co-creation” to mean engaging many customers to contribute ideas for a new thing (we might call that crowdsourcing).

When we use “co-creation”, we mean something very specific: engaging customers and internal stakeholders so that they are working with low-level, concrete construals, rather than high-level abstract ones. That is, bringing groups together to collaborate on something that feels concrete, immediate, personal, inevitable.

Staying high-level and abstract is a good way to get superficial buy-in. People aren’t thinking about the nitty-gritty details, so they more readily agree. But usually those same stakeholders realize they care (very much!) about the details as the go-live draws near. By staying high-level, you are only deferring hard conversations until you are further down the path and it’s more frustrating and more expensive to make changes.

For us, co-creation is a way to help everyone get to a lower-level construal sooner, so you can create more lasting alignment and buy-in. There is a natural human tendency towards abstraction. Especially in a team setting, it’s a very pro-social instinct: we build stronger social relationships when we focus on the generalities where we agree rather than the specifics where we don’t. However, when an organization sets out to build something new, it becomes counterproductive. Staying abstract prevents us from making the trade-offs that are inevitable as a project moves from something theoretical in the far future, to something real happening in the here-and-now.

In our co-creation work, we have found three ways to help participants stay engaged with the concrete details, so that we can achieve lasting buy-in on both the high-level initiative and the detailed trade-offs that will make it work in reality.

1. Shrink personal distance

Social distance is an important driver of construal level. When something affects you or someone you know, you are more likely to attend to the details. That shapes who we invite to the session. Bringing customers to the table helps an organization think about the details that will matter to users, rather than focusing on the back-of-house implementation details that might otherwise be top-of-mind. Bringing cross-functional stakeholders together helps surface important details from across the organization, which are unlikely to be uncovered by a more abstract slide presentation.

But removing social distance isn’t just about getting people into the same room — it’s also about how you structure time together. If a session feels overly formal and didactic, social distance stays high. The best co-creation sessions create a new social context where every individual feels like they belong and have equal standing to contribute. Practically, we achieve that through things like informal dress code (no suits!), round tables, and social time together over meals. We also dedicate meaningful time to introductions, and use warm-up games that help people get acquainted on a more personal level.

2. Facilitate for concrete details

Psychologists who do empirical research into CLT have uncovered a variety of conditions that prime people to develop either lower- or higher-level construals.

• Words promote more abstract thinking, while pictures facilitate lower-level construals.

• Familiarity promotes a lower construal level while something that feels new will seem more abstract and distant.

• You can see and hear things that are quite far away, but can only touch things in arm’s reach, so tangibility promotes more detailed conceptions.

• Sellers tend to have more abstract conceptions than buyers, so priming people with an end-user’s mindset will help them think more concretely.

All of these effects are subtle, but we carefully structure our co-creation facilitation to take advantage of these priming effects and help participants think more concretely about details. We introduce well-known ‘analogues,’ so people have a familiar reference point. Our biomedical communicators bring a lot of images and visuals into the session, and make quick sketches throughout discussions to make ideas more concrete. We use markers and chart paper to turn a conversation about a website into something people can touch.

CLT research strongly suggests that co-creation will be more effective in person, and that is our experience. However, even within a virtual setting, there are ways to help people be more concrete. We have shipped participants markers and notebooks and incorporated them into activities, to help bring tangible elements to a zoom call. Whether virtual or in-person, we ask customers to share their stories to help everyone adopt that perspective. We frame questions in user-centered terms, and use first-person language. (“I’m the patient and I’ve just landed on this website. What will I want to click first?”).

3. Co-create the right things

Because co-creation is an approach that is designed to get people thinking about the details, it will be most effective when you apply it to the right level of problem-solving. Co-creation is not great for answering “why” questions, figuring out what is desirable, or making decisions about big-picture trends. That kind of work benefits from more abstract thinking. To the extent we want to touch on some of these higher-level questions in a co-creation session, we will group them at the start or the end, so we can have a clear transition from abstract to concrete.

Co-creation is most valuable when we already know what we are creating and why, and it’s time to figure out how we will build it. What features will turn an average website into an excellent one? And what trade-offs will result in the best output? When people are thinking more abstractly, they tend to focus on one feature at the expense of all the others. (“Just give me whatever car will be the fastest”). When we get participants thinking about details in a co-creation setting, they get better at thinking about how those different features interact, and are better at weighing the relative value of competing attributes. (“All the fastest cars are the most expensive and don’t have the trunk space I need.”)

By shrinking personal distance, priming details, and focusing on the right things, co-creation makes important details salient long before they become barriers.

Co-creation is a powerful tool because it upends the normal way we share information inside an organization. We bring people together and provide thoughtful facilitation to help stakeholders think more concretely about important details they would otherwise struggle to conceptualize. Those details really matter — for implementation and for customers. By surfacing them while we are early in the development process, we have more options, and making changes is relatively painless.

Perhaps most importantly, the buy-in you build through co-creation is deeper and more lasting. Stakeholders who participated in co-creation leave the session feeling like the initiative is much more imminent. They see your initiative in the same vivid detail you do, rather than just a vague outline, somewhere out there in the indeterminate distance. And that, ultimately, translates into a shared motivation and sense of urgency, so you can work together to turn co-creation outputs into a reality.

End Notes

For the last couple of years, this final section has been a selection of interesting links we’ve shared around the Workomics crew. But recently, we’ve ramped up the company LinkedIn posting, so you can find all that content over there. For now, I’m going to try ending the newsletter with a bit more of a personal hodge-podge.

• We took the kids to Ottawa for the Family Day long weekend, and had a great time outdoors at Winterlude and indoors at museums and such. We also spent lots of time visiting with old friends. Weekend trips are always tiring, in that you come back to a mountain of laundry, an empty fridge, and a full week. But to counterbalance, we had so much quality time with friends that the net effect of the adventure was actually energizing.

• I decided to suspend normal morning responsibilities during the Olympics, so that we could spend the breakfast hour watching the action from Italy. Snowboard cross and short-track speed skating were particular favourites (alongside, of course, the curling). However, My 7-year old has issued strict instructions that we must never mention the men’s gold-medal hockey game EVER AGAIN.

• This month I read Ann Patchet’s The Dutch House and Geraldine Brooks’s March, both of which were very good. I have also been reading Little Women aloud to the children. It’s a bit of a project due to the length, but both boys love it, and really identify with the struggles of the March girls. It was also fun to read Little Women and March simultaneously. In her afterword, Brooks says, “Nobody in real life is such a goody-goody as that Marmee.” I appreciated having March’s less goody-goody portrayal to counterbalance Alcott’s saintly mother, whose example I definitely cannot live up to!

Speaking of Marches….wishing you all a great one!

In comradeship,

S.

Back in the fall, I had the delightful opportunity to meet Krista Lee Hynes, co-founder and managing partner at Ignite Financial in St. John’s, Newfoundland. Having had a few different entrepreneurial ventures in her life, Krista Lee has always been ready to bet on herself and her ability to forge her own path. But I think equally, her story is one of seizing opportunities to collaborate with others — from her very first venture doing a theatre program for kids, to the partnership at the core of Ignite, to her current forays into financial empowerment with other entrepreneurs. It’s a nice testament to how backing yourself doesn’t equate to making the journey alone.

Many thanks to Krista Lee for taking the time to chat. I hope you’ll enjoy reading her story.

In Comradeship,

S.

A conversation with Krista Lee Hynes

This instalment in our Women’s Entrepreneur Series is an interview with Krista Lee Hynes, co-founder and managing partner at Ignite Financial. Ignite is a holistic financial planning business based in Newfoundland. Alongside Ignite, she has an independent practice of financial counselling and empowerment, and partners with other entrepreneurs to conduct events.

In this interview, Krista Lee shares how she went from theatre major to financial advisor, how she made the decision to set up a corporation with her business partner, and how she folds community impact into her work.

Susan Bartlett: Why don’t you start by telling me a little bit about your professional journey, and what led you to where you are right now?

Krista Lee Hynes: My professional journey seems to rewrite itself every year or so. I’ve always been very entrepreneurially-minded, but when I was in grade six, I decided I was going to do theatre. (I didn’t realize that there was such a thing as business school.) I’m very glad that I did theatre. I learned a lot about myself, honed my public speaking, got over tons of odd little insecurities, and met some lovely people. But I was only halfway through my first year when I realized, “I don’t wanna be an actress for the rest of my life!”

That was when the entrepreneurial spirit kicked in. I opened up a small theatre production company and did a couple of small stage productions over a couple of years. After that, someone approached me about developing a theatre program for kids, which ended up being its own venture with another woman. That helped me understand the more administrative side of running a business, but the two of us were the be-all, end-all of the business. I got burnt out, as tons of entrepreneurs do. I was done with being my own boss and having to make my own paycheque, so I took a job doing marketing and sales for a local radio station.

All to say, I came to financial planning from a unique perspective. I’ve been in the industry for 14 years, so it’s definitely the thing that has stuck the longest.

SB: Tell me more about those 14 years. How did you go from “I’m going to get into financial planning” to starting Ignite Financial?

KLH: Most people get into finance either with a bank or an umbrella firm like Sun Life or IG. I didn’t want to go the bank route because I knew I wanted to be able to build my own firm out of it.

I started as an individual advisor under Sun Life Financial. I was looking up names in the phone book, trying to convince people who knew me as “Theatre Krista” that I know what I’m talking about. I was also female and relatively young—in my late 20s. I once met a client in the mall with his dad, and he said, “I can’t believe you’re letting a woman handle your money.” People would wonder what would happen if I had a baby. My own father thought I was crazy for the first couple of years, because as an entrepreneur I wouldn’t have any maternity leave income.

And sure enough, I was less than three years into building my business when I did get pregnant. so everybody was right. (No, just kidding.)

SB: Kidding aside, how did you navigate that period?

KLH: Early on, I got a piece of really good advice: the minute somebody can do work that you’re doing for cheaper than what it costs you to do it, then you need to hire. I was getting a lot of meetings, getting in front of people, doing a good bit of business. I didn’t have time to make follow-up calls and confirm appointments, which was resulting in clients missing meetings. So, I hired someone for a few hours a week at minimum wage.

When my daughter was born, that employee was there to keep things afloat. I took six weeks off and my husband, Drew, God love him, took paternity leave for the rest of the time. I dove back in and I did all of the work things. Drew would bring my daughter in and I would breastfeed her in my office in between meetings and have a little bit of baby time. I definitely took less time than I should have, but because I was so new, it was a crucial time for building my business.

I made compromises in the business too. I had been working on my CFP designation, because I felt that education was really important to building my credibility and my business. But sleep deprivation doesn’t make for a good student, so I put that on pause. I just kept showing up for my clients and making sure that they understood how I could help them, and that I was here for them if they had any questions.

When my daughter was around a year and a half old, I resumed the CFP. That’s when things really changed for me. Financial advisors are a dime a dozen. When I had my CFP, I could talk about stuff that not everyone else necessarily can. That gave me a competitive edge and really helped me build my practice.

SB: Your business is an interesting setup in that you’re under a well-known name, but actually, it’s all on you. There’s $0 of revenue unless you go and get it. And so, it’s really starting from scratch in a brand-new industry. It’s a big leap of faith.

KLH: It was. Actually, this is something about me that maybe makes me a little bit weird, but I don’t feel fear when it comes to business. If I look at something, I don’t immediately think about all the things that could go wrong. I’m really excited and passionate about the opportunity, and what might happen if I put my all into it. I can just see all the good things that can happen.

I don’t want to sound cocky or conceited. I genuinely see it as my Achilles heel in some ways. But what is the worst-case scenario? I’ll go get a job somewhere. I didn’t have the fear at the outset that I probably should have.

In those early days, all I had to lean on was the Sun Life brand. People didn’t know me, and the ones who did weren’t taking me seriously. I could bring a more senior advisor from Sun Life to sit beside me on key meetings. That gave me an authority and legitimacy that maybe I wouldn’t have had on my own.

But even so, I realized very quickly that I didn’t want to hang my hat on Sunlife. I want to hang my hat on me. I always want to rely on myself. My husband tells me I’m a horrible employee. It’s true. I don’t like having to wait on other people to get things done. I don’t want my security or my well-being to rely on anybody but me.

SB: Tell me more about the decision to go into partnership and form Ignite.

KLH: My business partner approached me. He had a block of business he was looking at buying from some retiring senior advisors, but it was too big for him to do by himself. He thought we would work really well together. I knew the blocks of business he was buying, and I felt honoured that somebody saw what I was doing, liked what I was doing, and wanted to launch something together.

Of course, we had a lot of conversations before we went ahead. We started with an informal alliance to test the waters and do our due diligence. The biggest thing for me was understanding his core values. What’s really important to him? Is he going to be a complete workaholic and in the office all the time and expecting me to miss things with my family? Do we have the same philosophy on employees? I’m always very invested in staff. I want to make sure they are well-paid, and I want to make sure we have enough of them. I don’t want to be doing something that someone else could do better.

If there was one challenge, it was how we communicated at the beginning. We weren’t great at it, but we were both very open to working on it, and we never “went to bed angry,” so-to-speak. Our ability to both have the arguments and work through them was really reassuring to me.

We worked alongside each other for two years before buying the business and we’ve been together ever since. For me, a big part of being a business owner is building something bigger than yourself. Together, we can build something bigger than either one of us could individually.

SB: You also have a financial empowerment practice, which is a little bit different. Can you tell me more about that?

KLH: I’ve added a financial counselling practice within the last year, because I saw a real need. That practice is really about the mental and emotional blocks that we can create or that can be created for us through debt, a death, divorce, or any transition in life. We work on debt management from a practical perspective, but we also talk about your relationship with money and the human behaviour side of it.

I’m trying to poke money into existing spaces for wellness and self-care. Physical health, mental health, and financial health are inextricably linked. From my work in finance, I see that women, gender-diverse people, and people in racialized and marginalized communities are always hit the hardest when it comes to finances. I’ve worked with other entrepreneurs to bring financial wellness into existing events.

My counselling clients are exclusively female. Women have had more restrictions on our access to lending and financial services. Until the mid-1970s, we had to have a husband’s or father’s signature to be able to open a bank account or a credit card. Statistically, women have less investments than men. Women entrepreneurs have less access to funding. Many of us will have more time compression and time gaps in our career journeys. We need some empowerment within this community to give people the voices and resources, so they can advocate for themselves on financial matters.

SB: The business model is obviously very different between counselling and wealth management because the clients have very different abilities to pay. I’m curious how you think about that.

KLH: I’m very interested in social enterprise and the running of social enterprise. That’s where I feel the next big leap for my journey is going to be.

We have a huge housing crisis in Newfoundland and Labrador, as we do in most of Canada. To me, it all links back to finance. If someone is paying an exorbitant amount of rent, of course they will have problems with debt and financial security.

But to me, it’s not just about individuals managing their money. It’s also about exploring the deficits within our community that prevent people from building financial wellness. If I’m really going to help people, what are the opportunities where I can help people rehabilitate and find that financial security?

SB: What does success and legacy look like for you and your business?

KLH: To me, success is being able to take care of your family, but also being able to take care of your community. You are never just one person. Every decision we make has ripple effects locally and globally. Success to me is being able to live in accordance with that value.

We don’t often take time to sit back and say “what is enough?” or “what is satisfaction?” That has been my biggest shift in the last few years: to really define those goals. People tell me all the time that retirement isn’t achievable. Usually it is, but you have to understand exactly what it looks like and put in the work. But then you also can’t keep moving the dial. For me, once I hit that goal, I can give some of that back. I don’t need to keep it all for myself. When my daughter is older, I want her to be exceptionally proud of me and the good things I’ve done in the world. That, to me, is legacy.

A meta-analysis published earlier this month advises that in the face of adversity, you will do better to abandon your goals and adopt new ones. “Goal adjustment,” they call it. Researchers being researchers, they have all manner of provisos, limitations, and further study required. Nevertheless, I am glad to have scientific validation that it is not just okay but preferable to let some of the balls drop.

Mailbag: Social Change and Career Choice

I’m a mid-career professional and a mother of two school-aged children. As I’m contemplating my next career move, I started to wonder: should my work just be my work, with most of my contribution to community and societal improvements coming from activities outside of work? Or should I seek work that aligns the kind of community and societal change I’d like to effect? Does greater impact come from one approach versus another?

~M, Toronto.

Let’s start by saying the quiet part out loud: In general, the more a job is focused on contributing to society and community, the less it pays. It’s not an immutable law of physics, but wages in the charitable sector consistently lag the private sector, and typically there’s a trade-off between doing good (for the world) and doing well (for yourself, financially.) M’s question is really about how to think about that trade-off. is an economist at Wharton whose recent book Having It All gives us some helpful frameworks.

Social purpose and the disutility of labour

One concept Low talks about is the “disutility of labour.” Work is assumed to have a number of negatives or downsides (things that create “disutility” for you) — that’s what distinguishes work from leisure or hobbies. But the amount of disutility varies from job to job, and from person to person. If you really value social and community contributions, you’ll have lower disutility in a job that lets you make those kinds of contributions. It can be perfectly logical to give up some amount of salary to do work you find more meaningful.

However, Low would be quick to warn you against over-indexing on just that one element. The overall disutility of your labour is made up of many things: the commute, the predictability of hours, how much you like your colleagues. Every job is a package deal, and you should consider all the ways it will add and subtract disutility.

It’s also important to think carefully about the day–to-day experience of doing your job. Mission and purpose are important things, but tend to get lost in the humdrum of the day-to-day. Meanwhile, challenges like homelessness or climate change are wicked problems. You can expect wins to be few and far between and resources to be scarce relative to the scale of the tasks at hand. Your day-to-day experience might be dominated by frustration at the lack of progress against big, systemic challenges. You won’t get the same macro level sense of purpose from something like selling cellphone plans or opening bank accounts. But those jobs can carry a lot of day-to-day satisfaction at the micro level, as you help individuals and make their day a little bit better. This isn’t advice to go work for an evil company. But it is advice to weigh the actual satisfaction you will get from your actual work, not just the higher-level mission.

Squeezing out other contributions

If our social and community contributions are not coming from our jobs, then we are left with contributions outside of work. But the viability of that option is going to hinge rather crucially on how many hours are left after you clock out for the day. If, like M, you’re a knowledge worker who is fortunate enough to be able to weigh competing career options, chances are high that your work is “greedy,” and your hours are long. The more hours your job consumes, the less “outside of work” time you’ll have for other contributions.

For M, the calculus is even tougher, thanks to something Low calls “The Squeeze.” Here is a chart from Low’s research into women’s time use over different periods in their lives:

Although individual women will go through the phases at different ages, the graph shows that for women with childcare responsibilities, there are three different eras. In two of them, the combination of childcare and household responsibilities is low enough that volunteering for social or community causes ‘outside of work,’ could be a reasonable plan, even with a greedy job. But in the middle era, which Low calls “The Squeeze,” the burden of housework and childcare increases substantially. In that season of life, a plan to make contributions to society alongside responsibilities at home and at work is much less realistic. There aren’t enough hours in the day.

Rethinking models for social contributions

M is far from an outlier. According to Deloitte, 9/10 of Gen Zs and millennials consider “purpose” to be important to their job satisfaction, whether that is through the work itself, or in how a job enables contributions elsewhere. Employers know this, which is why corporate volunteer programs are on the rise. The challenge with these corporate programs is that they tend to be shallow, episodic, or even self-interested. It’s hard to make meaningful contributions to thorny social challenges with just a handful of hours each quarter. The volunteer activities tend to be optimized for team cohesion and ease of logistics rather than true social impact. The causes are often picked for alignment with the corporate bottom line, rather than personal commitment to a cause.

For someone like M, the current state of corporate volunteer programs falls short of the real change she’d like to effect. How do we make space for sustained societal contributions when jobs are so greedy? Can we reimagine corporate volunteer programs to be more effective? We can perhaps take inspiration from service clubs, which brought together professionals from many different industries and firms to tackle really big things like the eradication of polio. What M needs — what all of us need — is a viable avenue to make meaningful and contributions to the causes we care about, in a way that can live alongside professional commitments, even when life is squeezed.

Workomics Staff Picks

A round-up of some of Workomics’s favourite links from the past month:

• The Workomics team really identified with this post about “Personal Business,” as we too strive to do things that are “high-quality and idiosyncratic.” More idiosyncracy, please!

• Speaking of idiosyncrasy, this cartoon about AI peas gave us a chuckle.

• But still we worry about what AI-in-everything means for our collective ability to think deeply and invent wonderful new things. This New York Times article worries about how AI might deepen inequality. “Bluntly: Making healthy cognitive choices is hard.” Is it ever.

• One of those healthy choices inspiring us this month: cultivating a sense of awe. Peter Wehner writes in The Atlantic about how experiencing things like nature, art, and extraordinary feats of human accomplishment create a sense of awe. Awe, in turn, lowers our feelings of stress, and provides us with a greater sense of purpose, meaning, and a connection to our fellow humans. Sounds like something we could all use.

Wishing you all a little awe and wonder to go along with whatever might be stretching or squeezing you over the festive season ahead. I’ll be back with another newsletter early in the new year.

In comradeship,

S.

By now, most of the country is on the bandwagon, celebrating the wins and lamenting the losses. In my house, it has been especially wonderful to watch two small boys discovering sports fandom for the very first time1. The thrill of victory and the agony of defeat are so visceral when you are seven or nine, rooting for your team to win the Big Game.

After the wins, they playact every highlight, reenacting imaginary base hits and strikeouts. After the losses, the tears and frustration are very real. They are too young for cynicism or nonchalance. Their emotions are outsized by adult standards, lacking the experience and perspective to know that it’s “just a game.”

And yet.

It’s also them learning to really, really care about something — to love it even — when they have no control and the outcome might be bad. It’s them learning to feel big feelings, and to manage them. It’s them learning that life goes on even after a devastating loss.

Those are all big, scary things to learn. Maybe it’s easier to learn them here, when it’s just a game. Maybe baseball heartbreak is a dry run for the more profound disappointment and grief that life will inevitably bring our way. Maybe sports fandom is balm for all of us, reminding us that even when the worst happens, there will be a new season, and we will cheer again.

(But also, this time, I really hope we get the thrill of victory. Go Jays!)

Three principles to make AI work for people and teams

Meet Daisy: An AI Case Study

Daisy2 is a Regional Sales Enablement Specialist for a large multinational in a heavily regulated industry. She works with sales executives in her region to help them build skills and deliver better outcomes for customers and the business. Daisy comes to the role with deep subject matter expertise: her previous roles in the company include being a sales executive herself and managing sales executives as part of a cross-functional team.

The core of Daisy’s job is meeting with sales executives to coach them, educate them, and help them troubleshoot. Once a quarter, Daisy runs a more formal workshop that brings small groups together for an in-person learning day.

Daisy’s company recently rolled out a generative AI model; under the hood, it’s one of the more popular commercial models, customized for the organization. The tool is available to everyone in the organization, but so far it’s been presented as a tool for experimentation. Daisy is the kind of person who loves exploring new ways of working, so she’s eager to try out the new tool.

Daisy, meet genAI

With this quarter’s workshop coming up, Daisy notices that her region’s sales data are lagging the country for one specific product. Having done the role herself, Daisy has no trouble pinpointing the issue — it’s a more complex product for the sales executives to wrap their heads around, and customers in her region tend to have a deep skepticism of products like this. There is a product team who owns training content, so Daisy turns her attention to the workshop itself — but this time with GenAI.

“I find it’s really helpful to invite the AI to ask me additional questions,” says Daisy. “I won’t just ask for a workshop agenda and give it my requirements. I’ll always finish with something like, ‘please ask me anything else you think would be helpful for creating the agenda.’”

“In this case, the AI came back with questions about the experience of the workshop participants, whether it was remote, hybrid, or in-person, and a few other details. I really feel like that back-and-forth exchange creates much better output.”

“The workshop agenda was fantastic. It gave me an icebreaker activity and a bunch of suggestions for ways to make the session more interactive for the sales execs. A few of the suggestions wouldn’t work, but I just cut those out and adjusted accordingly. The whole thing took me ten minutes.”

For now, Daisy’s corporate genAI tool will only output plain text, so she builds the deck for the workshop herself. But Daisy continues to think about how she can incorporate AI into her workshop prep. For the customer role-play exercise, she has AI generate the customer profiles.

“It’s a perfect task for an AI,” reflects Daisy. “Because they’re meant to be fictional, I don’t have to worry about hallucinations.” The genAI at Daisy’s company has two different settings: Inventive and Accurate. Daisy used the “Inventive” setting for all the workshop prompting, but she has used “Accurate” in other instances, where she’s looking for more of a succinct summary while minimizing the risk of inaccuracy.

After the product team delivers the content to the sales execs, Daisy takes the zoom call transcript and prompts the AI:

Use the content from this text to prepare a series of questions and answers that can be used in a quiz show format in a workshop.

“The AI did a great job coming up with the quiz questions, and it probably saved me about 30 minutes. I just copied and pasted them into the presentation.”

GenAI workshop, meet the real world

Daisy delivers her workshop four different times for different groups of sales executives, and it is very successful. Afterwards, several sales execs admit to having been less comfortable with the product category and said they found the workshop very valuable. Some even requested the workshop be repeated for other products.

How about the AI component? “The quiz show format was a huge enhancement. The sales executives really got into it. That was 100% the bot — coming up with the idea, producing the quiz. I wouldn’t have done it on my own.”

Apart from that experiential element, though, Daisy thinks the main benefit was time-saving. “Ultimately, I would have delivered a workshop on that topic with or without AI. But I spent less time on prep, and I think the participants enjoyed the experience more.”

Daisy sits on her company’s AI committee, and she brought her workshop forward as a case study. There was a lot of interest, and people were quick to glom on to best practices like “encourage the bot to ask you further questions.” For Daisy, the AI has so far been nothing but additive to her work.

“For me, it’s all about the time I spend with my sales execs. The time I saved with AI is golden, because it lets me spend more time actually talking to my sales execs, and less on the prep.’

Lessons Learned from Daisy

Daisy’s experience seems like a poster child for how AI can be a positive force within organizations. What made it successful? We see three distinct elements that helped AI work so well for Daisy.

1. To get the most out of AI, emphasize the human skill of problem framing

People sometimes refer to prompting as a skill, or talk about “prompt engineering.” Daisy certainly finds that the specifics of a prompt can make a difference, especially for tricks like inviting questions from the AI. However, the real human skill is much broader than that: problem framing.

Problem-framing is a well-known element of most human-centred design methodologies. The idea is to come up with a frame that is broad enough to invite many possible solutions, but narrow enough to be actionable. In design, they are often termed “How Might We?” questions, and they are not the start of the process, but rather something that happens partway through, informed by research into the problem space, business priorities, and customer needs. It’s common to cycle through multiple How Might We options before moving forward.

In Daisy’s case, we see the power of human-driven problem framing. Based on a combination of data and her own insight , she articulated the challenge: “How might we help sales executives more effectively present Product X to reluctant customers in this market?” It was only with this frame in place that the AI became a valuable tool. Then, Daisy could leverage AI for the workshop agenda, the role-play customer profiles, and the quiz show content.

In any organization, there is a wealth of tacit information held in the heads of individuals and inaccessible to generative AI. Having people like Daisy frame problems grounded in their own insight and knowledge allows AI to become a more valuable tool for the organization.

2. To make AI use rewarding, prioritize human needs for self-determination

Daisy is very clear on the benefits of AI for her: less time spent on prep and PowerPoint decks means more time spent on real human interactions. Armed with the AI, Daisy chose to use it to make more engaging in-person experiences for her stakeholders: add a quiz show! Put in an ice-breaker! Make those role-play case studies more realistic!

We have seen this play out elsewhere. As AI-driven technology has become increasingly proficient at reading medical scans, the number of radiologists hasn’t declined. Rather, radiologists spend more and more time on human interactions — teaching, consults, patient procedures that rely on imagery. Given a choice, people tend to use AI to boost the time they spend with other people, increasing their feelings of relatedness.

“Given the choice” is an important element here. No one is mandating Daisy use AI, either explicitly (AI usage informing performance reviews) or implicitly (productivity targets that are impossible without AI.) She retains autonomy over when and how AI is incorporated into her workflow.

With that autonomy, Daisy chooses to deploy AI in an area of relative weakness: workshop design and facilitating. AI is a way of bolstering and extending her expertise in products, customers, and sales, giving her newfound feelings of competence in the workshop domain (and probably in the domain of AI too!)

Relatedness, autonomy, and competence, are often cited as keys to human motivation and flourishing. When AI is deployed in ways that respect those three core human needs, it can make jobs better and more rewarding. But we certainly see examples where AI is implemented without regard for self-determination. Software engineers who are required to use AI have their autonomy severely limited, while the AI supplants their core expertise, lessening their feelings of competence. Often the result is less time spent with coworkers and teammates, lessening a sense of belonging.

AI that respects human needs for relatedness, autonomy, and competence can be a force for good. But if the goal is mere efficiencies without regard for self-determination and motivation, the result may be short-term financial savings, but a loss for team culture, individual motivation, and sustainable growth.

3. To make AI a vector for lasting change, introduce it incrementally

At Daisy’s organization, AI is being introduced incrementally:

• The current AI won’t give her PowerPoint slides — just plain text.

• Technical training content continues to be produced by human beings.

• Lessons learned from using AI are being shared through formal organizational channels

You could instead imagine a big-bang approach to AI: Let the AI determine the focus area for the workshop, generate the content, perhaps even deliver the workshop. Roll it out everywhere all at once, with no mechanism for crystallizing best practice or course-correcting mistakes. The value of a big-bang is that you scale AI faster. The downside is that… you scale AI faster.

Organizations are incredibly complex systems. Small changes in one part of the system can have unexpected ripple effects elsewhere, and those effects may take some time to fully emerge. When the changes are more gradual, as they are for Daisy, there is a chance to see the short- and long-term implications unfold, amplify the things that work, and roll back the things that don’t.

Imagine it turns out that an AI outputting fully-baked slides leads to inaccuracies or non-compliant content — problematic in a highly-regulated industry! Because of their incremental approach, Daisy’s company would be able to more quickly identify such consequences, and fine-tune their AI toolstack to one that finds the right balance of risk and reward.

By contrast, throwing maximal AI tools at everything all at once makes it harder to identify what’s working, and opens the possibility of both catastrophic consequences and outsized gains. For some organizations, the promise of disruptive transformation might be worthwhile, but for many (most?), a more incremental approach will enable more lasting change.

Gradual introduction of AI in isolated parts of the broader system makes it easier to see where and how AI adds value. That, in turn, makes it easier to build advocates for AI and drive voluntary adoption. But just as importantly, an incremental approach lets us see where the costs of adopting AI outweigh the benefits. It creates space for constructive criticism, so that the unhelpful aspects can be adjusted, or rolled back.

The annals of technology-led transformations are littered with big-bang systems changes that crashed and burned. In most of the ways that matter, AI is just another technology, so most organizations will be best served by a phased approach that lets them go slow, test and learn, and then propagate and iterate.

Indeed, the core of Daisy’s case study is that she and her organization are approaching generative AI the way you might tackle any kind of new method or tool or tech. They are:

• Leading with curiosity and experimentation.

• Letting the people on the ground find real use cases in ways that make sense for their roles and their business objectives.

• Applying best practices in change management.

Perhaps it doesn’t sound as sexy or as innovative. But it is, by and large, how sustained transformations come to pass.

Workomics Staff Picks

A round-up of some of Workomics’s favourite links from the past month:

• We loved looking at these amazing microscopic photos from Nikon’s annual Photomicrography Competition. The shot of pollen caught in a spider web was a group fave.

• It’s interesting to think about some of the broader implications as CAR T treatments emerge for illnesses that affect larger patient populations. How will different healthcare systems allocate scarce capacity when so many seriously ill patients can benefit from new treatments?

• We spend a *lot* of time thinking about how to best communicate things like efficacy and side effects, so it was intriguing to think through how those elements play out for placebos and nocebos.

• Apropos of nothing, we had fun looking through this library of spurious correlations. Be sure to click through and read the AI-generated papers explaining why (e.g.) per capita consumption of margarine has declined in lockstep with the divorce rate in Maine!

So it was a nice change of perspective being home last month, watching those same technologies deployed meaningfully by my 70-something parents. Dad is recovering from surgery (hi, Dad!), so getting up from his chair is currently a struggle for him. How wonderful that he can ask Google to turn on the light or adjust the music for him, and save his energy for a walk in the sunshine. Likewise, how wonderful that he has a handheld device that lets him message his friends (and kids), read the news, and control his hearing aids. He is so much more connected with the outside world than he would have been 20 years ago.

We read so much about how technology is creating an epidemic of loneliness. For young people, social media and smartphones are crowding out in-person interactions in unhelpful ways. Absent their devices, young people would be congregating together IRL. But for elderly folks (sorry, Dad!), it’s a different story. Their phones are more likely to supplant isolation and foster more connection.

It’s a good reminder that technology cannot be evaluated in a vacuum. Much depends on who is using it, to what end, and what it is supplanting.

Initial Thinking on a Company AI Policy

Informed by our broader perspectives on the role of generative AI, we have been working towards a company AI policy. It’s still very much a draft-in-progress, as befits a technology-in-progress. Our goal is to be pragmatic but cautious — to tread the middle ground between hype and prohibition.

Our AI policy is for a particular kind of company: one that is small-on-purpose, whose value proposition is not scale. A company that competes on things like excellence, thoughtfulness, creativity, and rigour. It is also a company that values flourishing at work, even over profit2. We want our work to have space for things that are only available through consistent effort and practice: old-fashioned things like mastery, craftsmanship, self-understanding. If your organization operates on different principles, then your AI policy should be different too. We are sharing it as an imperfect starting point, with thoughts and feedback very much welcome.

Definition and Scope

The AI governed by this policy is specifically generative AI. That means:

• models trained on very, very large data sets

• models general enough to be used for a variety of different purposes.

It encompasses Large Language Models (LLMs) and more sophisticated agentic AIs. The underlying mathematical approach doesn’t really matter, but it’s often neural networks, reinforcement learning, or deep learning.

When you see “AI” referenced in this policy, it doesn’t apply to AI-based tools with a narrow use case, like removing part of an image in Photoshop. It also doesn’t apply to smaller data sets. If your dataset can be manipulated in Excel, feel free to do as much fancy math as you like.

This policy also focuses on deliberate, intentional use of AI. As generative AI becomes increasingly pervasive, it’s nearly impossible to avoid. This policy is not intended to cover every incidental AI output that you might encounter, such as AI overviews on a search query. If in doubt, please assume the policy applies.

This policy will change frequently in response to:

• AI technology evolving

• New features or products being introduced to our existing technology stack.

• Clients changing their policies and/or expectations

• Discovering areas that are unclear or nonsensical.

If you have an idea for a change, let’s work together to update the policy.

When and whether we use AI

We use AI only after we have weighed the risks and benefits. Before using AI for a work task, we think about three key questions:

1. Does this use comply with client policy and other Workomics policies?

For any client-based work, the most important question is to understand the client’s policy. Currently, our client policies run the gamut from “I hope you’re putting this into Copilot,” to “Any and all uses of AI are forbidden, up to and including linear regression.” (!!). Always, always know the client’s policy. If the client policy says no, your choices are to not use AI or work with the client to get an exception approved in writing. In addition, whether client work or not, any use of AI must comply with other Workomics policies, including the general IT security policy and the research and privacy policy. In particular, if you are intending to use AI tools for research-related tasks like transcription or synthesis, it’s important that you also seek the appropriate consent from the research participants.

2. Do we maintain control over the data?

You can use AI if and only if we maintain control over the data. “Data” for this purpose means additional files or information you provide to the AI to support the query, rather than the query itself.

It is okay to use AI tools to make general queries, in much the same way as you might use a search engine. For instance, you might query ChatGPT, “What does acronym XYZ stand for,” because the AI is not relying on any Workomics or client data. It is not okay to provide a file without taking additional steps to validate the AI tool.

When using AI with any Workomics or client data, we only use tools where the input data is not used to train future models. We’ll keep an internal list of allowable AI tools that satisfy this requirement and otherwise comply with our IT security policy. If you have a new AI tool you would like to use, please get explicit permission to have it added to the list. We’ll review this list regularly.

You may only provide the AI with a finite data set. Each file must be explicitly provided by a person. That means AI tools are off for platforms like Slack, Google, Box, or Zoom, and we do not enable direct API access to any of our files or data. You may provide copies of files from these platforms to allowable AI tools.

3. Does the benefit of using AI outweigh the benefits of the alternatives?

There are benefits to having a human being do the work the old-fashioned way:

• The quality of the output is often higher. AI tools tend to produce output of “average” or “acceptable” quality, or outputs that are missing important context.

• It builds and maintains human capabilities. Excellence is the result of consistent practice; our skills and judgement can atrophy if we don’t use them regularly.

• We have very high confidence in the accuracy of the output as a result of having done the detailed work that led to the final deliverables.

• Doing work is intrinsically rewarding for the people doing it.

The benefits of using AI should outweigh these benefits of humans doing the work. In general, that will happen when we have to process large quantities of information (something AIs are very good at), and where the processing of the data is somewhat peripheral to the core deliverables our clients want us to provide.

A good example is using AI to support synthesis of interviews. AIs are generally better than people at finding patterns in large data sets, so the use of AI adds quite a lot. Interview synthesis is one of several inputs to overall analysis and recommendations, so there is plenty of opportunity for us to build and maintain our capabilities and make sure we are delivering high-quality, differentiated outputs to our clients. Having conducted the interviews, we can be confident the AI hasn’t introduced any hallucinations or inaccuracies. And finally, doing detailed coding of interview data is often time-consuming drudgery, so we are replacing a less pleasant task with more rewarding, higher-value work. As an added bonus, interview transcripts are a finite data set, and there are a number of AI tools that don’t use input data to train future models.

By contrast, we should be reluctant to deploy AI where it is displacing our ability to practice our core skills, where our motivation is time-saving or producing “more” (rather than “better”), or when there is a good chance we’ll spend more time than we saved trying to correct AI-generated “workslop.”

How we use AI

If we have made the decision to use AI, that is not a carte blanche. We use AI judiciously, so that we are minimizing the downsides and maximizing the benefit. As we gain more experience with using AI, this section will expand to reflect lessons learned.

Our use of AI should be additive.

AI should always be “in addition” to old-fashioned human work, not instead of. If we are using AI, it should build upon the subjective experiences we have had in the real world: interviews we have conducted, workshops we have facilitated, ideas we have exchanged, sources we have read and interpreted, expertise we have built.

Equally, our use of AI should be supplemental — an optional add-on that could be taken away without diminishing the core. If our deliverables are mainly the result of prompting an AI, then our clients have no need for us. We must consistently deliver something they cannot get by prompting a model.

Our use of AI should be transparent.

For both ourselves and our clients, it should always be clear whether an output is AI-generated. If you are using AI, keep track of the “meta data” that you used to produce it: the specific prompts, the model used, the dates it ran, the data provided, the different iterations you rejected en route to the final version. The meta-data should be stored in an accompanying read-me file that is easily linked to the AI-generated output. This level of documentation helps us stay accountable for our use of AI, and helps keep the human in the loop — especially any future humans who might otherwise access your output without realizing it was AI-generated.

Our use of AI should be eco-conscious.

AI is known to have high consumption of both energy and water. Accurate assessments are hard to come by, but a recent study published in the MIT Technology Review estimated the energy consumption for a 28-query marketing task3. They concluded that the task represents 2.9 kwh of energy usage. The actual carbon footprint of the 28 tasks depends on a wide variety of factors (load on the grid, where the data centres are physically located, etc.), but it’s somewhere between 600g and 1,200g of carbon dioxide, or about what you might emit over 5km of driving4. Water estimates are even harder to come by, but recent disclosures from Google indicate that each query consumes 0.26 millilitres of water. That means our 28-query marketing task is using about half a tablespoon.

These numbers are not negligible, but you will generate almost 150x that much carbon on a one-way flight from Toronto to Newark5. Remember too, that generating the same outputs without AI still consumes energy. When we think about the carbon and water impacts of AI, what really matters is the aggregate use around the world — both how much it is used, and for what kinds of tasks. The International Energy Agency believes it’s plausible that the energy savings from AI-driven optimizations could outstrip the additional energy usage from data centres. Of course we might also end up in a future where everyone uses AI to generate billions of unnecessary cat videos. The applications and frequency matter.

At Workomics, we are not using AI to reduce energy costs. However, in the context of the other environmental impacts of our business activities (driving, flights, heating and cooling offices, etc.), the judicious use of AI tools is reasonable. We should, nonetheless, be mindful of the environmental impacts, and lay off the cat videos.

Our use of AI should be voluntary.

It is somewhat trendy to make the use of AI mandatory, to terminate employees who can’t be “upskilled” with AI. That is not our approach. We recognize that there are real ethical quandaries when it comes to AI. Commercial models are generally trained on the output of writers and artists without permission or compensation. There are cases before the courts where traditional media companies are suing AI companies for copyright infringement. Anthropic has agreed to pay $1.5-billion to authors after training its models on books from pirated websites. It’s fair to have moral qualms about how these models were built, and to worry about the future harms that might come from AI. On the other hand, not adopting AI may significantly harm your future professional opportunities and earning potential. To the extent that AI is used to solve hard problems and benefit society, it can be a force for good.

In situations where we have this kind of moral ambiguity, we don’t believe it is our role as a company to either mandate or prohibit the use of AI. Our policy is to encourage AI to be used judiciously, and to pair it with advocacy for fairer systems. However, we do allow individuals to be “conscientious objectors” — to not use AI as a matter of personal principle, on a use-case-by-use-case, platform-by-platform basis. We ask you to not reject all uses of AI categorically, but to consider each case on the merits. Your choice to not use AI may affect the kinds of projects you are able to work on.

For now, that is possible because using AI is not existential to our business and doing your job without AI doesn’t create an undue burden for your colleagues or your clients. However, it’s hard to predict the future path of a technology. Someone in the 1980s could eschew the fax machine for their whole career with no issues, but would not have been able to avoid adopting email, eventually. All to say, we can imagine a scenario where AI is existential to our business, so we reserve the right to mandate AI use in the future, if necessary.

Workomics Staff Picks

Sticking with the theme, the Workomics team has been sharing lots of links about AI recently.

• As reported by Gizmodo.com, a study in The Lancet Gastroenterology & Hepatology found that while AI initially helped physicians better detect colon cancer, when AI was removed, it caused physician detection rates to drop below original levels. This further supports the studies published by Microsoft and MIT that suggest long-term AI reliance may erode the ability to effectively reason and problem-solve.

• A recent study shows that when used by more experienced coders, AI can amplify team impact by reviewing code, suggesting improvements, or contributing to projects in additional languages. Junior developers’ use of AI, meanwhile, was limited to accelerating their own tasks with less impact on a project’s bigger picture.

• This is your brain on LLMs. This study shows that standard academic tasks like writing an essay produce the strongest and widest brain connectivity when writing a paper using just the ideas in their head, rather than employing tools like search engines or LLMs.

• A study from the London School of Economics shows that when used to summarize notes in long term care homes, LLMs often created visible discrepancies between genders in the summaries generated. This could lead to negative care outcomes and patient experiences, as well as require hours of additional work by PSWs to verify and fix.

That’s just a sampling — it seems every day brings some new perspective on AI, what it means, where it’s going. Even so, a lot of the biggest changes still seem just over the horizon…perhaps still a long way off, perhaps here before we know it.

In Comradeship,

S.

In Comradeship,

S.

An conversation with Shiri Levy

This installment in our Women’s Entrepreneur Series is an interview with Shiri Levy, the co-founder and Chief Scientific Officer at Histone Therapeutics. Histone is an epigenetic therapeutics company, which means they focus on developing medicines that target the proteins that turn genes on and off. The company was founded in 2021, initially based on Shiri’s scientific discoveries she made as a post-doctoral researcher at the Ruohola-Baker Lab at the University of Washington.

In this interview, Shiri explains the science behind Histone Therapeutics, talks about the learning curve moving from academia to industry, and reflects on being a woman and a mother in a male-dominated industry, and the challenges and rewards of advancing a cutting edge technology.

Susan Bartlett: Let’s dive in: tell me about your company. Why does it exist, and what is it striving to do?

Shiri Levy: Histone Therapeutics is an epigenetic therapeutics company, which means your next question will be “what does epigenetic mean?”

Epigenetics is everything that happens on the DNA. Right now, there are all kinds of incurable diseases — whether it’s cancer, autoimmune disease, degenerative diseases, or even aging itself — where cells previously functioned well, and now they don’t. With epigenetics, we can reset the cells (how they behave and how they are regulated), so the cells can go back to their typical function. The company exists to create a platform that can potentially tackle many different diseases.

People are familiar with the terms “genetic code” and “DNA”, but in order to regulate DNA there are proteins that turn on or off the expression of genes. At Histone, we have developed technology to turn genes on, and this has allowed us to create genetic medicines. We use our medicines to wake up sleeping or lazy genes.

I have four kids. When I go to wake them up in the morning, it’s a different approach for every kid — whatever works best for them. Our technology is like that — developing different ways to wake up sleepy genes, in the way that works best for each particular gene. We always describe it as “a therapy for genes, not gene therapy.”

Our company is not the only one working on epigenetics. But we exist in a unique category that we believe is more likely to be safe for patients. First, we deliver our proteins using mRNA (just like the COVID-19 vaccines), where other companies use viruses, which can cause an unwanted immune response. Second, we are non-enzymatic. Enzymes are always “doers” — like an alarm clock you can’t turn off — and that is also tricky for patient safety. Our approach is reversible, so a gene that is turned on can also be turned off.

SB: Four kids and a start-up. Your days must be very full.

SL: I sleep very little. I don’t go on vacation so much because I need to stay tuned to work. I get a lot of support from my husband who’s my biggest fan. There is a toll, but I do it because I love it. I love the science, the business aspect, the research, all of it. I’m learning so much and pushing the boundaries of what we can do with therapeutics. It excites me to bring it to the patient. For that, I don’t mind missing a baseball game. I’m in this really specific place in my life where it's all worth it.

SB: You’re still in a fairly early stage of clinical development. Do you have particular diseases in mind right now that you’re working on as a target?

SL: We have very specific diseases in mind. When you have a broad platform like our technology, it’s a blessing and a curse. We have a universe of opportunities, but we have to make choices about what is the right thing to do for the technology and for the patient. It’s what we think about day and night. We need to clearly understand the unmet need first. There’s no need to develop a drug if there is no advantage to it. We have identified numerous areas where we think our technology has an advantage over current treatments, and where we also think there is potential to make a drug that is simple and safe.

Right now, we are exploring indications in degenerative and metabolic disease. For instance, we have received grant funding from Friends of FSH Research to create a drug for FSH Muscular Dystrophy. If we can strengthen muscle in that disease, imagine what we could do in other diseases as well!

SB: Big goals! I’m curious about your journey towards starting Histone Therapeutics as a company. Many scientists might stay in a more academic environment. What made you want to create a company to commercialize your science?

SL: I invented a technology and I saw its merits. I thought gene activation could solve a lot of problems — we’re always trying to silence or block genes. Look what a good job our genes do when we’re healthy!

At the university, I saw companies being spun out, but there weren’t many women doing it. When you look at PhD students and postdocs, 50% are women, and they are so smart and so innovative. Where are all the women spinning out companies? The tomboy in me just screamed, “What about us?”

I decided it was my time to shine. I had a unique, audacious opportunity. I’m very comfortable in the unknown, and I can operate well in fear. I decided to take the risk — either to succeed big or fail big.

SB: You took the lack of women as a call to arms to give you the extra push to do it.

SL: I couldn’t have done it by myself. Kim Emmons from the Washington Research Foundation was encouraging me ever since I invented the technology. She told me I should do something with it, think about commercialization. In Seattle and in the biotech world there is a strong connection of sisterhood. And now I’m the one pushing others. When I see women around me with new technology, I try to help push them out of their comfort zone. That is where life begins.

SB: Commercialization was outside your comfort zone, compared to scientific research.

SL: Four years ago, when I started thinking about a startup, I was the rookiest of rookies. I come from a blue-collar family, first generation to go to college. I didn’t grow up in a home where you talk about things like shares and marketing. It was all new territory for me to navigate. But I’m very comfortable in the unknown, and I operate very well with uncertainty and risk.

I knew I would need support to transition from academic research to the business world. I’m very grateful to my co-founder Gregory Block and the entire team at Histone. There are so many elements that come into play besides the science: executive management, business development, IP and licensing. Our focus is on making a drug that is superior to what already exists today.

SB: It’s a long journey to get to a clinically superior drug. Where are you in that journey, and what does it look like on the road ahead?

SL: We are early. Right now, we have data from experiments with mice, demonstrating that our technology works as expected in animals. We are working on formulating our technology into an mRNA medicine.

You can’t talk about the road ahead without getting into the zone of AI, and all the tools that are available to us today. We use AI in so many aspects of the company, from helping us figure out the most promising indications to identifying the best delivery mechanisms. In most applications, AI hallucinations are a problem, but in the lab we let the AI hallucinate as much as it wants to come up with the next generation of proteins. We learn a lot from AI, and we believe AI-enabled small teams speed up the process of bringing novel therapies to the patients who need them.

But as a therapeutics company, at the end of the day, we have to come up with the data. We have to do the experiments and figure out if we have a product that works — or doesn’t work — in patients.

SB: How do you think about building culture of an organization?

SL: I think relationships and trust are the most important thing. In a company like ours, we have to be comfortable making mistakes, and confident enough to debate ideas and disagree. That only happens when everyone feels a level of responsibility and accountability towards the organization and what it’s trying to do. It’s like a pyramid: At the bottom, you have the foundation of trust and relationships. We have to trust each other first of all.

We have a small team who are all very, very tight and comfortable with one another. Because we have that trust, we can feel safe debating the right path. I always bring all my emotions. To me, it’s not a disadvantage — it’s an advantage. When we have a great experiment, we celebrate. When something completely doesn’t work, we cry. It’s okay. It’s all in the realm of humanity. We don’t need to behave in a rigid corporate manner. We have to be true to ourselves. I’m a woman, a mother, a daughter, a wife, as well as a scientist. I bring it all to the lab with me.

SB: What’s the long-term goal for you and for Histone?

SL: I’m ready to do whatever it takes. My “why” is to help one child. If there is one mom who doesn’t have to sit at the bedside in the hospital while her kid suffers with a degenerative disease, that is why we’re doing what we’re doing. We have to make sure the technology gets all the way to patients.

We’re at the beginning of understanding the power of epigenetics. What I’d like to happen is for Histone to grow and grow, bringing new exciting molecules to the clinic. That would be my audacious goal.

A shutdown is very different from individual vacations because everyone is off at the same time. In the lead-up, there is a shared focus on making it to the break. This spring at Workomics was particularly hectic, and our July shutdown was a bright light at the end of the tunnel — something to galvanize and motivate us like little else can. Unlike a week of vacation, there’s no hand-off to over-burdened colleagues, and you don’t return to a full inbox and context to catch up on. The work just stops, for once assuming its proper place in your life: set aside for the people that matter most, for unstructured time to do as you please, for real rest and rejuvenation.

In a client services business, it is not easy to shut down for a full week. It takes advance planning and communication. We choose weeks that tend to be vacation-heavy and less productive anyway. Even so, a closure will sometimes inconvenience clients who have urgent timelines that clash with our planned downtime. That’s why, as much as you plan and communicate, you also need conviction: this is not open-heart surgery, and the corporate deadlines can wait; the value we offer outweighs the temporary inconvenience of a week away; the rest and downtime is in fact integral to that value, and to our ability to sustain it in the long run.

It’s not perfect, either. Most of the team will be disconnected for most of the week. But a couple of people will take a meeting to keep a critical deliverable moving forward. Someone else will monitor inboxes to be ready for research that starts next week. Others will (ahem) finish up their newsletter. But the concessions are small ones, made smaller because there are no new assignments piling up, no last-minute meetings dropping into your calendar. During a shutdown week, for once it feels possible to actually get ahead.

The secret ingredient is the coordination. We have one client who also shuts down for this first week, and it’s magic. From the beginning of the year, every project is planned with the understanding that everything will pause for the first week of July. It’s actually much easier and more efficient compared to working around the key stakeholders’ interwoven vacations the rest of the year. The only downside is that it’s only one client and only one week. How much better would it be if it were all the clients for two or even three weeks?

Human beings are not designed to work at full speed, without a break. We are healthier, happier, and more productive when we rest. Alas, capitalism will take every available hour, if you let it. Someone has to confine it — draw a box around the time work can have vs. time it cannot. Drawing those lines is hardest when it falls to the individual, protecting their own vacation and drawing boundaries around their own off-hours. It’s much easier when an organization sets a limit for everyone. Now, you are not protecting vacation time just for you, but for the collective. It feels less open to debate. And it is easier still if it can happen on an even larger scale: a whole industry, or even a whole country. As ever, the Nordics got there first — the whole country of Norway shuts down for three weeks each July.

If it sounds idyllic, that’s probably because it’s ideal. If anyone is spearheading a movement for a North American equivalent, please sign me up.

Workomics Staff Picks

Some links from the team this month:

• With increasing time spent in front of screens, employers like Deloitte have started to offer subsidized Lego and puzzles as part of their employee wellbeing program. We love the inclusion of tangible problem-solving. And also, those Lego sets ain’t cheap.

• As more companies send employees back to the office 4+ days a week, workplace biohacking becomes a more relevant trend. This Worklife article runs down how everything from carbon dioxide levels to light quality can affect productivity, and how companies are increasingly using technology to achieve optimal environments.

• In the medical realm, we were super interested to read about the early success of off-the-shelf stem cell therapy for treating diabetes. When implanted in patients, the manufactured cells started sensing glucose and secreting hormones almost instantly, allowing patients to stop taking insulin. What an exciting scientific development!

Happy summer!

In comradeship,

S.

So, you can view this month’s essay as coming from someone with higher-than-average understanding of the field, or you can view it as coming from someone so short-sighted and foolish that she didn’t feel like AI and natural language had enough potential. Both are probably true.  

As with all my writing, this post was generated without any assistance from GenAI, and indeed started as old-fashioned, handwritten notes. Because of the subject matter, I took special care to keep track of all the links I read while working on this newsletter. Bye and bye, I will feed them into a GenAI and see what kind of essay comes out. Perhaps it will undo all my convictions and I will wish I had skipped the struggle of writing altogether. 

Where I did have help was from the Workomics team. They have a singular ability to question the status quo, surface new perspectives, and insist on better. They pushed me to think more deeply on this topic, and I’m grateful for it.

In comradeship,

S.

GenAI, capitalism, and human flourishing

It’s hard to write about Generative AI and Large Language Models without writing about capitalism. That’s the point of GenAI, isn’t it? To further the capitalist ideal of maximizing profit? 

Certainly, that is what the LLM purveyors are selling us: lower your costs while creating many more outputs many times faster than mere human beings. The output is not especially good, but there is so much of it and it is so instant! Who cares about excellence when you can have seemingly infinite volume with fewer of those expensive human beings?

This is the moment where capitalism has lost the plot.

Market capitalism is a system that incentivizes people to maximize efficiency in pursuit of material wealth. It has been very effective in that aim. Economist Brad Delong estimates that an unskilled laborer in 1870 London would have produced roughly the equivalent of 5,000 calories in economic value each day. In other words, not enough to feed his family. Today, an unskilled worker in London produces the equivalent of 2.4 million calories a day — enough to feed her own family and several hundred others besides. 

That tremendous leap forward in material well-being is in large measure the result of market capitalism and how it incentivizes corporations and individuals to apply technological progress in pursuit of profit. To be sure, we struggle mightily to distribute the resulting wealth as equitably as we should, but after many thousands of years of humanity, we no longer struggle with not having enough. Capitalism must surely be credited with an assist. 

Today, at the societal level, we don’t need more of anything. Indeed, most of us struggle under the weight of too much. Too much carbon. Too much plastic. Too many ultra-processed calories. Too much endless, unfulfilling content in endless, unfulfilling social media feeds. (Capitalism gets an assist here too.)

Nevertheless, here we are, still blithely organizing our society around the pursuit of efficiency and material wealth. Except now we stand on the cusp of a new paradigm that will allow us to create nearly infinitely, with ever less human intervention. 

What is a human being for?

In capitalism, corporations are pure vehicles for maximizing profit: more output for less input, without limit. The economists like to pretend that human beings are built along similar lines, but it’s more complicated than that. Yes, we often eschew effort when we can. But left to our own devices, people are forever volunteering for unnecessarily-challenging undertakings: running marathons, baking bread, writing email newsletters, climbing mountains, raising children, playing Bracket City on hard mode. 

Psychology professor Michael Inzlicht has coined the term “effort paradox” to capture this notion that effort is sometimes avoided and other times valued. He posits that effort is a mechanism for creating meaning and purpose. Only by expending effort can you feel a sense of mastery. Too, it is a form of social currency — a way to demonstrate your commitment to a group or a cause. Effort is also valuable as an antidote to boredom. People don’t actually like to do nothing for very long, and will seek out ways to spend effort once boredom sets in. 

GenAI and LLMs undercut all of these positive attributes of effort. Knowledge workers who are required to integrate AI into their workflows bemoan the loss of meaning and purpose in their work. Human-human relationships are displaced by human-AI transactions. People are consigned to babysit the AI rather than drive the work themselves, representing a loss of agency and autonomy in favour of reaction and monotony. 

From a capitalist perspective, none of that matters. The system is working as intended: seek profit, minimize the effort and cost, let the invisible hand take care of the rest. If that means people no longer write their own words, it is no different than when people stopped being blacksmiths. Mustn’t stand in the way of progress. 

The struggle is real; the AI is not 

Except that language (and creating more generally) is not just some mechanism for generating revenue. It is fundamental to what it means to be human. Writing is not easy, but it is how we get clarity of thought, how we invent new ideas, how we disseminate them to others who might use their own words to build on our ideas and make them better. 

If the LLMs do all the writing, what do we lose? 

The written word on the page has value as output1. But the messy, frustrating, difficult process of writing is not a problem to be solved. The inefficiency is a feature, not a bug. Setting aside questions of quality, relying on the output of an LLM robs you of the benefits that come through expense of your own effort. Your understanding will be surface-level. Any objections you run into will render you inert — unable to counter because you haven’t done the heavy lifting yourself. You won’t be motivated to see your ideas through because they are not really yours. The output will be forgotten and discarded as easily as it was acquired. 

Language, writing, and creating are also mechanisms for discovery and decision-making. When you set out to write about, say, AI and capitalism, the ideas do not emerge fully-formed like Athena from the head of Zeus. Rather, the ideas take shape through thousands of small decisions about words and structure, each one clarifying, refining, defining. When you let GenAI do the work, you delegate most of those decisions2. 

Delegation of decision-making is a radical departure from all the automation that has come before. Whatever technical wizardry we deployed, the decision-making still resided with the human beings who designed, built, and ran the machinery. Many decisions were taken away and hidden from front-line workers, but some human somewhere still made the decision before it was programmed into the machine. The GenAI models are different, because they are making all of those small decisions on our behalf, without us ever knowing what was considered and ultimately discarded.

We lose something real when that happens. Recent research surveyed workers who use GenAI at work at least once a week. The researchers found: 

“While GenAI can improve worker efficiency, it can inhibit critical engagement with work and can potentially lead to long-term overreliance on the tool and diminished skill for independent problem-solving. ”

The kinds of work that workers did also shifted, with seeking, generating, and doing, displaced by verifying, combining, and supervising. The issue is that the cognitive skills are not switches you can turn on and off at will. We see that when people rely on GPS directions rather than building their own mental maps, the region of the brain associated with mapping literally shrinks. Cognitive skills that aren’t practiced and maintained will atrophy. 

We need a certain amount of struggle — grappling with ideas, making trade-offs, doing hard things. It’s how we maintain and expand our capacity to think, and also how we figure out what we think. Written outputs are valuable and useful, but the process of creating them is what is essential to us as humans. We need effortful pursuits to flourish. 

Human flourishing is the point

When capitalism was first emerging in the 18th century, there wasn’t enough food or shelter to go around. In that context, it seems preferable to have productivity gains from division of labour, even though it replaced fulfilling work for craftspeople with repetitive drudgery on an assembly line. “Not starving” is pretty foundational to human flourishing. 

The world we live in now is very different. Mostly, we are applying GenAI to create “more” where we already have too much. If we prize efficiency and profit above all else, the LLMs seem inevitable. But the capitalist paradigm of efficiency and profit sprung from the trade-offs of a bygone era. The world today is already abundant in material wealth, and approximately no one thinks AI will help distribute it more equitably. LLMs maximize efficiency at a ludicrous scale, but in exchange, we forsake fundamentally human things like discovery, learning, autonomy, relationships, purpose, fulfillment.

We should be very sure the payoff is worth it. 

Assessing the payoff will require corporations to be something other than profit-maximizing machines in the capitalist ideal — to grapple with their own version of the effort paradox. Sometimes, effort should be minimized; other times, not.

To wield AI effectively, organizations will need to have a real clarity of purpose — a reason to exist that goes beyond producing a particular output as profitably as possible. They will need to think deeply about when and how AI helps or hinders. Is near-term efficiency worth it, if the result is a long-term decline in the organization’s capacity to create, innovate, differentiate? If there is no one who can supervise the LLMs in 10 years time, because the AIs took the on-the-job learning opportunities away from junior employees? If the LLMs are commoditized and all your competitors can produce the same blandly average offerings? 

Ultimately, the decision to leverage GenAI is not unlike the decision to outsource. There’s nothing wrong with it, when it’s a supporting role, in the areas where “adequate” is all you need. But if you outsource the core of your offerings, sooner or later your customers will realize you are just a middleman and cut you out. 

Equally, there are some problems out there where we really should privilege efficiency above all else.  If you’re using AI to develop new cancer drugs, go with God. I hope market capitalism makes you really rich because you invented new treatments and reduced human misery. 

But there are all kinds of other problems where prioritizing efficiency and applying AI is to deeply misunderstand what it is to be human, what makes for a happy life. If you are using AI to call your parents for you, or write your guide to summer, or make your video game, or teach your course, then you have been led astray. When an AI makes these things, the best-case is a mid output that adds to the noise. It’s pointless. Even if there is—improbably—financial profit to be had, you have inflicted a net cost on society and robbed yourself of something meaningful. 

But when a real live person makes these things, that’s a very different premise. Human beings are in the arena, connecting with each other, expanding their understanding of the world, making compromises, striving for better. It will be inefficient and effortful. The result might be mediocre or it might be profound. Either way, humans and humanity will have benefitted from the pursuit.

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Workomics Staff Picks

Some links from the team this month:

• We thought this article on VR in patient experience was super cool: Research recently published in the Clinical Journal of Oncology Nursing revealed that VR tours of Venice, Agra, and the Ecuadorian Amazon can positively impact patients' side effects during longer infusion sessions (e.g., chemotherapy and other cancer treatments). 

• This article explores how focused attention is one of our most important tools, and that it requires us to have actual systems for preserving it, so that we can do our best work, and so that we can help preserve our teammates’ focus as well. Distractions will happen; we can be prepared with systems for how to deal with them, and certain cases, even welcome them.

• Our own Michelle Thompson-McCune was one of four featured voices on Tom Lietz's Storylinking podcast, talking about ways to build engagement with groups.

• Anne Helen Petersen digs into the question of whether people are bad at their jobs, or if the jobs are just bad. As work gets faster and more demanding, burnout, poor training, and unclear expectations are making it harder to do good work. Maybe it’s time to stop blaming individuals and start redesigning the way work actually works.

There, a discarded pirate costume, next to a treasure chest with a false bottom hiding doubloons. Alongside that, a pirate ship with three-inch high plastic pirates. Seafaring adventures, played out at different scales. 

Here, it’s a costume of medieval chain mail, with helmet, bow, sword, shield, and (incongruously) a light sabre. Did the pirate and the knight meet in battle? Hard to say.

Then a pile of history books — Rescuing Titanic, What Caused the War of 1812, A Teen’s Guide to the Russian Revolution. So busy acquiring facts, storing them away, making sense of the world that was and, perhaps also, the world that will be. 

A game of Battleship, partway through. They might have been interrupted by a call for dinner, but more likely by mutual accusations of, “Cheater!” — trying to sneak illicit peeks at each other’s ship locations. 

On the chair, a Thomas the Tank Engine puzzle, just started. Thomas was a constant in toddlerhood, but he has been mostly outgrown. For one day this week, he was not. 

A large drawing of a tank. No doubt it is a specific model of tank, but I, clueless mother that I am, couldn’t tell you.

The whiteboard has gained an annotated drawing of a British Blue falkin [sic]. (P.s. this is imaganeri).

Next to it, paints and brushes and little jugs of water with abstract water colours in pretty pastels. 

Deflated balloons, scattered every which way. Without a doubt, these were blown up and then let go, so they would fly around the room making splendid fart sounds. 

Diary of a Wimpy Kid books in every corner. This is how they learn about the world of middle school that is not as far away as I like to pretend. 

On another day or in another mood, I might be annoyed by the mess. But not tonight. Tonight I have been away from them, missing their jokes and bedtime stories and endless questions. Tonight, all I see is corroboration of rich inner lives, of all that they are exploring and imagining and becoming. 

And I am sad for these few days I have missed, and glad that I am home again, because these days of boyhood and play never felt so fleeting.

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Balancing the pursuit of new

Organizations love new: new products, new markets, new policies. New is an exciting inflection point that opens up a world of possibility. It’s all fresh starts and green fields that organizations can fill with stuff: new features, new sales aids, new marketing. New comes with clarity and purpose and urgency. It gives organizations (and the people in them) the chance to show how innovative and creative and impactful they are. 

That’s not to say organizations always excel at new. Execution and results can range from terrible to outstanding. But regardless of outcome, new is organizations’ comfort zone1. They have a roadmap and milestones to follow, all on the path to delivering the next new thing.

The trouble with not-new

Alas: every new thing eventually becomes not-new2. Not-new is a lot harder. You are at a kind of anti-inflection point, on a much flatter (but hopefully still rising) trajectory. The gaps are few. If you’ve done your job well the first time around, the stuff you’ve already done is…pretty good actually! Could you make improvements? Likely. But will the juice be worth the squeeze? Will the incremental time and money actually return value to the organization? Even after you factor in the opportunity cost of what else you could do with that time and money?

And that right there is the crux of the problem. Those questions are rarely even asked. If you do ask them, the organization is poorly equipped to answer them. Worse still, new is what gets rewarded.

Suppose you ask the questions, and realize you are past the point of diminishing marginal returns. In fact, you should just double down on your two or three most successful tactics, exactly as they are today, and drop everything else. Not because those tactics are perfect, but because any money you spend improving them won’t result in new revenue. 

That might be the right thing for the business, but when it comes time to hand out bonuses, raises, and promotions, “I did the best thing for the business,” almost always loses out to “I made a shiny new thing.” And so, products have bloated features, sales teams are overwhelmed with infinite offerings, and someone always seems to be redoing the positioning (again). 

There is a real cost to these misaligned incentives. The organization spends money on things that don’t add commensurate value. But also, complexity incurs a cost in and of itself, and one that is rarely accounted for.

Balancing with Prioritize-and-Optimize

These kinds of incentives can only be changed at the institutional level. Organizations need to make it okay — even celebrated — to be in prioritize-and-optimize mode. It’s truly a great accomplishment: you’ve done a great job at making a new and shiny gadget. And now the reward is that you get to shift into Prioritize-and-Optimize. Make it a thing. 

As part of making it a thing, you’ll need to rethink your measurement. When it isn’t neglected entirely, measurement tends to focus on whether a tactic met its goal as a standalone initiative. That’s what matters in new. But in Prioritize-and-Optimize, we’re interested in whether a tactic delivers better than others, and whether it justifies its opportunity costs. To answer those questions effectively, we have to collect different data, so that we can compare across tactics and contextualize results with their opportunity costs.

Prioritize-and-optimize should also come with a strong bias towards pruning activities and tactics. People are loss-averse, so they hate to take things away. But the inherent costs of complexity mean you should err on the side of ruthlessness. “What did you stop doing this year?” should be the key question in Prioritize-and-Optimize, and it should almost always have an answer. 

One of the reasons organizations love new is that people love new. It’s exciting and rewarding to make something new happen. But when new is relentless, it can actually hinder performance. People need rest — to ward off burnout and to provide a moment for reflection and learning. Prioritize-and-Optimize should be framed as an opportunity to deepen understanding and get better at your craft. When you hop from new thing to new thing, you rarely grapple with the finer details of what worked in practice. Because Prioritize-and-Optimize typically carries less urgency and more predictability, it affords a period of rejuvenation and learning that keeps both the organization and its employees healthy and flourishing. Now, if Prioritize-and-Optimize becomes a permanent state, it starts to be indistinguishable from stagnate-and-atrophy. Instead, think of Prioritize-and-Optimize as a passing season, with people rotating in-and-out, feeling rested, grounded, and hungry for the next round of new. 

Likewise, Prioritize-and-Optimize is not a permanent state for any given area of the business. Markets change. New competitors enter. Technology opens up a game-changing possibility. Inevitably, there will be new inflection points to capitalize on, and it’s critical not to miss them because you were in Prioritize-and-Optimize. In many ways, inflection points are easier to spot when the team is not consumed by delivering something new. But false positives are a real risk3, where the bias to new leads you to switch out before you’ve really had a chance to optimize or prune anything. Organizations need a way to evaluate when to switch back to making new. The most effective criteria will be outward-looking, so that you are switching into new in response to specific changes in the needs of your customers, or broader market dynamics. 

New is great. Sometimes, what exists is not good enough and you need to re-do it. Sometimes, new is the spark you need to energize the organization or win back market share. Sometimes, new is the next growth engine for the organization. We all love new. 

The point is that organizations are programmed for new by default. In any initiative, there is going to be a point of diminishing marginal returns. Organizations rarely recognize it, and rarely respond to it by doing less. They pour the same amount of effort (and expense) into new, even when the possible payoff is markedly less. Deliberate reprogramming to make Prioritize-and-Optimize a valued state of being, is one way to overcome the bias towards new, and find a better balance. 

Workomics Staff Picks

Some links from the team this month:

• We enjoyed this article about the hidden meanings behind our favourite tiny artists’ creations from the Atlantic (gift link).

• Some of us have been sparking joy with custom stickers, inspired by Jukebox’s great deal.

• Our team has been raving about The Pitt for many reasons, including its medically accurate depictions of ERs. Read more of our take here!

• There’s a lot of talk about AI everywhere we look, but like Tressie McMillan-Cottom says, most of us are using it for pretty “mid” tasks that aren’t worth the hype. (And that’s if you avoid the worst case of AI-as-parasite!)

• The average four year old laughs 300 times in a day, but once you enter the workplace, the laughs become few and far between. This article summarizes some of the research on humour in the workplace, and made us grateful for all the ongoing hijinx in the Workomics slack channels. 

I have fond memories of shoveling out snow forts and tobogganing and watching old reruns on Betamax. But most especially I have fond memories of how the world just stopped. If you had plans, they were cancelled. If you had deadlines, they were deferred. The trappings of daily life were revealed for what they were — insignificant in the face of the natural world. Especially as it happened so often, I think it helped to keep everything in proper perspective. Nothing is so important that it can’t be pre-empted by a winter storm, but everything is to be relished, because the next time it might be snowed out. 

We had a small taste of that this month here in Toronto, as half a meter of snow came down in four days around a long weekend. School was cancelled, activities were called off, and everyone hunkered down at home. It turns out that grown-up deadlines don’t get deferred in quite the same way as grade school homework, but the many cancellations still had the effect of creating some rare space to breathe and just…be. We had a weekend where it was possible to read a novel cover-to-cover and catch up on admin and take the kids sledding and watch a movie and clean the house and take a nap. In a world where there is never enough time, such a surfeit of time was magical.

Magic fades, of course. In the aftermath of the long weekend, the traffic is terrible and there is endless griping about (lack of) snow removal, and all the pretty, fluffy snow has descended into slushy, icy muck. But with luck, the rejuvenation from a few days of rest will linger, and all the many scheduled and deadlined things will stay in proper perspective.

Figuring out Flexible Work

Let’s begin with a concept from social philosopher Christopher Nguyen: value capture. 

Value capture occurs when an agent’s values are rich and subtle; they enter a social environment that presents simplified — typically quantified — versions of these values; and those simplified articulations come to dominate their practical reasoning.

The agent is you. Your rich and subtle values are particular to you, but let’s say that some of these are in the ballpark:

• “Work hard, but also have time to relax and hang with friends.” 

• “Do good work that makes a difference for people.”

• “Learn new skills and improve existing ones.”

• “Enjoy collaborating with colleagues on interesting projects.”

• “Earn enough money to support myself and do fun things.”

The social environment you have entered is the workplace. Your workplace no doubt has many different values, but there is one simplified, quantified value that is present in almost every workplace and has been since the dawn of industrialization: the number of hours you spend at work.

In many jobs, that value is quite explicit: workers are paid by the hour, or the company bills by the hour. But even in those cases, the number of hours you spend at work is not what is truly valued, either by organizations or individuals. The true values are more subtle and more nuanced, harder to quantify, harder to assess. 

“Hours worked” is not an unreasonable simplification. It can be compared across different kinds of jobs. It is readily observable and trackable. There is a non-inverse relationship between hours worked and output produced. 

However, it’s a much worse simplification than it used to be. 

When all work happened at a physical workplace, it was easier to observe and track. When more kinds of work were grounded in physical and mechanical throughput, the relationship between hours worked and output was more direct and predictable. 

For modern knowledge workers, the relationship between “hours at work” and “value of work produced” is quite tenuous. You can be in back-to-back meetings from 8am to 6pm, and produce very little in the way of valued output. You can have a creative breakthrough in the shower, when you’re not really “working.” The hours you spend sitting at your laptop or being present in a physical office are poor predictors of value produced. 

Even so, there are countless jobs where the relationship between hours and value remains tightly linked. ER doctors and ICU nurses must be in the hospital with patients. Teachers must be in the classroom with students. Waitstaff and chefs must be in the restaurant with diners. “Being present and available” is a primary source of value, quite apart from whatever gets accomplished during that time. The same is true for those knowledge workers having breakthroughs in the shower. Nowadays, it relies less on physical proximity, but being present and available for clients, colleagues, and internal customers is valuable in and of itself.

What is not valuable is “hours spent at work.” It’s an example of pure value capture: for generations, we have organized work around a simplified, easy-to-count proxy. It dominates our thinking, making it more difficult to find new ways of approaching flexible work, because we have lost sight of what really matters.

A values-driven approach to flexibility

At Workomics, our work is flexible-by-design. You can work from home. You can work from the office. You can log in from Mexico or Thailand or the UK1. You can get a haircut or head to the gym or meet your contractor in the middle of the day. You can start your workday at 10:43 am. You can leave at 3:15pm. Our employment agreements do not actually specify a required number of hours at work each week. Instead, we say this:

Workomics team members and clients live and work across North American time zones. The shape of the work changes day-by-day: sometimes it calls for independent heads-down time, sometimes it requires high levels of responsiveness, sometimes it demands intense collaboration. You should be sufficiently connected so that your availability and responsiveness does not impede your colleagues’ productivity, the quality of your work, or the satisfaction of your clients. As a rough guideline, most days you should plan to be available for meetings and synchronous collaboration for at least six hours between 8am and 9pm Eastern Time.

As a policy, it’s unusually non-prescriptive on when work happens and how much of it you need to do. We loosely suggest that “most days” you should be working at least 6 hours inside a wide 13-hour window. But the bulk of the policy is focused on what we really value — that people are structuring their work days so that the work is high quality, the clients are happy, and no one’s progress is blocked because someone else is getting a haircut. 

It’s also a policy that requires good faith on both sides. If employees take it as an invitation to do as little work as possible, or employers take it as freedom to regularly expect responsiveness at 8:30pm, the whole system breaks down. 

Several things enable this level of flexibility:

Vast swaths of predictability. If you know what your deliverables are, when they are due, and what good looks like, then flexibility is easier. And indeed, Workomics puts considerable effort into rigorous project planning with realistic contingencies specifically so we can have the level of predictability we need to work so flexibly. For their part, employees accept the project schedules as natural limitations on flexibility, and adjust their schedules to meet deadlines and attend key meetings. 

Nonetheless, we are a client services business, which means we are often faced with changing or emerging client needs that require responsiveness or adaptiveness. Our flexible work needs to be balanced with reciprocity and shared accountability for outcomes. Last month, we had a big deliverable that required a last-minute, weekend push, and there wasn’t a person in the company who wasn’t logging in over the weekend to pitch in and get the work done. The company affords employees enormous flexibility as long as the work gets delivered. The employees reciprocate that same level of flexibility in the rare cases it’s required to do the work. 

Our day-to-day flexibility is enabled by a counterbalancing rigidity for paid time off. Vacation must be formally requested and approved via email. Planned days off are tracked centrally, and we stop accepting requests for weeks that are over-subscribed. We do this because flexible work is much harder when a team is short-staffed: there are fewer people to cover the gaps or handle any surprises. In order to maintain flexibility for people who aren’t on vacation, and to have vacations where people can be fully disconnected for multiple weeks, planned absences need to be carefully managed. 

Finally, we recognize the limits of our baseline flexibility. Because there are deliverables and deadlines (sometimes aggressive!), because there is an expectation of reciprocity, so that sometimes work bleeds into personal time; because there is less flexibility in time off, it’s hard to fully segregate work time from personal time. And yet many of our staff want to have dedicated chunks of time where they can teach or take a course, pursue a creative project, or further a business venture. For those cases, we offer more formal flexible work arrangements. In those cases, employees take pro-rated pay and benefits, in exchange for protected time where they know they will not have to be present and available.  

It’s hard to break free of value capture. When a sick kid or a renovation takes up most of your day, you still tend to think in terms of “making up the hours.” You need to regularly remind yourself that the important thing is delivering the work and meeting the deadlines. But if we want to really grapple with flexible work, we can’t focus narrowly on the number of hours, when you start and stop, or where you sit to do the work. Individuals value a wide array of things — yes, the ability to dictate their own schedule and balance personal and work priorities. But they also value work they feel proud of, camaraderie and collaboration, learning and growth, helping others (colleagues, clients) achieve goals. Policies for flexible work should reflect the breadth of those values and how best to achieve them within the confines of a given business model. 

Workomics Staff Picks

Some links from the team this month:

• We've been having a great time incorporating Made Manifest's Pebble Talk into our weekly game plan meetings. They're a curated set of ice-breaker-style questions that make it really easy to build in a few minutes of fun conversation and team-building before we get down to business. 

• Some pharmaceutical companies are helping to connect patients to prescribers directly via Telehealth, as a patient marketing technique. This approach is facing scrutiny as lawmakers investigate how patient requests for medications and prescribing behaviour may be influenced.

• Inspired by this paper, we had a lot of fun discussing who on the Workomics team hears the words when they are reading silently, and who just sort of “absorbs” the information without hearing the words. (I am an absorber, 100%)

• In the spirit of shameless self-promotion, I did a podcast appearance back in December on Tom Lietz’s podcast Storylinking. We had a really great conversation about co-creation as a tool for breaking down organizational barriers, and how co-creation intersects with storytelling. You can give it a listen wherever you get your podcasts. 

Stay warm out there — spring is just around the corner!

In Comradeship,

S.

But Christmas will come regardless, and whatever preparations have been done will turn out to be enough. And more than ever, I’m looking forward to a couple of weeks away from laptops and to-do lists.

For this holiday edition of the newsletter, I’ve got a new instalment in our women entrepreneur series. I sat down with Lindsay Housman earlier this year, and learned all about her company Hettas, the research they’ve done to design their running shoes for women, and how she’s building an organization with flexibility at its core. I hope you enjoy the conversation as much as I did.

Wishing everyone a wonderful holiday season and all the best in the new year head. See you back here in 2025.

In Comradeship,

S.

An conversation with Lindsay Housman

This installment in our Women’s Entrepreneur Series is an interview with Lindsay Housman. She is the CEO of Hettas, a female-specific performance running shoe brand. Hettas launched just over a year ago, in November 2023, with three different shoes that vary by workout preference. Lindsay and Hettas were recently named the grand prize winner of the 2024 High Five Grant for Moms, and last month, the Hettas Alma Cruise shoe received a very nice write-up in Canadian Running magazine. You can purchase Hettas shoes through their online store and specialty retailers.

In this interview, Lindsay talks about how Hettas emphasizes women-focused research, her philosophy on flexible work, and the challenges of fundraising as a female founder.

SB: Tell me a little about Hettas. What do you do and what makes you special?

LH: Hettas makes running shoes specifically for women. Hettas came to be through my own experience with athletics and sports. I’ve been a lifelong recreational athlete, but I experienced many foot issues, which seem to be getting worse as I get older. If I have this much foot pain now, how am I going to be active when I’m in my 80s? That was what inspired me to start learning more about the athletic shoe industry.

It blew my mind that shoes, to this day, are still largely developed, tested, and researched based on male anatomy and physiology. I was thinking about myself, the type of impact that my body puts on my feet through sport, and what a difference it would make if my anatomy had been considered. Would I still have this much foot pain? Is there a better way to make shoes fit for women, if we start by considering their physiology?

We wanted to back our shoes with research and make that research public. We partnered with Simon Fraser University to research female biomechanics to inform our development and testing process. The result is three models varying in firmness. The fit is the same across all three, but they have a very different feel in their firmness and propulsion which makes them suited for different types of runs.

Community is also a big element of our brand. Running is part of the social fabric that connects our customers to their communities. We believe in the power of community to offer support and social connection and to hold you accountable to your training schedule.

SB: Tell me more about your focus on research. Partnering with an academic institution is hard when you’re launching a business, because there is an up-front investment but the commercial pay-off is a ways off.

LH: The bigger brands have large internal research teams, but that information isn’t easily accessible to the public. We know there is a large gap in research for women’s healthcare, and it’s the same when it comes to sport and performance. Women have largely been excluded from sport and performance research for hormonal reasons. It’s a variable to control for, whether it’s your monthly menstrual cycle or your hormonal phase of life.

Women are not represented in the sports science research. We wanted to understand how hormones affect women’s bodies, muscles, tendons, and ligaments, and how we should be considering shoe design at different hormonal life stages and during your monthly menstrual cycle. These are the kinds of answers we’re looking for.

When we chose to partner with Simon Fraser, we knew it would be a long lead time. Research projects take time to set up. However, we’ve been able to act on the research when it’s in a draft state. Research we did in 2022 is under peer review to be published in 2025 but we’ve had access to it since August 2022.

Working with the university has also given us access to their labs to do mechanical shoe testing. Those research and test cycles are much quicker, allowing us to iterate on the shoe design.

SB: How do the shoes get to market and how does your organization get the brand out into the world?

LH: Doug Sheridan is our shoe partner and co-owner. He has been in the athletic shoe industry for over forty years. We have one full-time employee who is a recent university graduate. We also work with an elite athlete, Rachel Cliff, who helps us build community and training plans. She works for us part-time while recovering from an injury and being a mom to a toddler. We work with a marketing advisor and we also have a sales advisor with a lot of expertise in specialty retail. Most of us are juggling other jobs or training.

For the two and a half years leading up to the launch, we were focused on product development, research, marketing, and building the website. We had contractors helping us with PR, social strategy, and graphic design. For now, we’ve transitioned our marketing to be more grassroots — working with micro-influencers, run clubs, and so on. We’re currently doing a capital raise, and once we complete that, the plan is to bring more of those marketing capabilities back.

For now, we’re focused on sales. That means getting the product into specialty retail stores, building operational processes to support specialty retail, and partnering with our specialty retailers to become part of their community.

SB: I’m curious how you think about building a sense of organization and culture, in a position where your one full-time employee is a recent graduate and everyone else is juggling a variety of different endeavours.

LH: I’ve always run flexible teams. One key to flexible teams is being transparent about the organization’s values, purpose, and mission. When you find people who are aligned with your mission, your culture, and your values, it’s easier to have flexibility and juggle multiple jobs because they’re passionate about the work to begin with.

We are also very supportive of making mistakes and failing. Often, I see teams fall down because there’s a culture of fear around reaching out for help, asking for support, or making a mistake. When you’re a remote team, running lean and fast, the reality is the chance for errors is higher. You have to take those as learning opportunities and ensure that everybody knows that it’s okay. It’s part of what stage we’re at. This helps us foster a willingness to ask for help and to take a risk within the team.

SB: I imagine it’s a bit tricky to get the right level of time in a role, when the job’s remote, flexible, and people are juggling a bunch of other things.

LH: I have a completely different philosophy on work and being in office. The traditional in office 9 to 5 doesn’t work for me or many women I know, particularly for women who tend to have more responsibilities with family or elder care. It hinders promotion. When my twins were preschoolers, I lived in Australia and had a job at a company that was 90% female. Most of us at the company had children under the age of ten. I ran their IT department, but I worked a half-day on Monday to take my kids to swimming lessons. The company’s leadership was open to me being at a senior level and working four days a week. They understood that there were things in my kids’ lives where I wanted to participate.

It really shaped what I saw as a healthy work environment. People didn’t feel compromised in their choices, and the amount of output was outstanding.

When I moved back to Vancouver, I started leading the IT department at Native Shoes. I had a tight budget, and I needed a lot of specialist skills. I adapted what I learned in Australia to create a team of specialists, most working less than five days a week. It’s been seven years, and everyone who started with me on that team at Native is still there today. It’s not just about being a mom. I had one woman working four days a week while doing a psychology degree. We worked flexibly around her course.

That’s the philosophy that I’ve brought to Hettas as well. Not everybody is a mom, but everyone has different things that are important to them. As we scale, we’re figuring out how to create a flexible environment where each employee has space in their job for what’s important to them, so they can feel like their whole self.

SB: You’re still doing the Native Shoes role. How do you integrate that with running Hettas?

LH: I consult at Native Shoes two and a half days a week, which is two days of meeting availability, and then people can message me at any point. That’s down from four days a week.

Right now, what I get from the Native portion of my life is a lot of stability. I know my team; I’ve worked with some of them for seven years. They’re independent, so I’m much more of a steward, an escalation point. There’s a lot of newness at Hettas, where I’m having to learn things like marketing and sales. There’s something nice about going back to a stable boat. Start-up life brings a lot of emotional highs and lows — lots of learning and fire-fighting. Native is less of a roller coaster.

SB: You mentioned you’re raising capital. Can we talk about funding?

LH: My husband and I personally funded the first two research studies out of Simon Fraser. The first 18 months were funded by my husband and me and family and friends. Doug, our product partner, has funded the shoe development. There has been a lot of bootstrapping.

It’s really challenging to raise money for consumer-packaged goods in Canada. Investors like tech. They like to know that there are contracts and set revenue streams; investing in a consumer-based product is a lot riskier. We were really fortunate and did some initial raises with angel investors and friends and family.

Last year, we went to the US with a goal of raising $2-million USD. That proved really challenging — 2023 was a tough environment. Venture capital is challenging at best. I was doing a lot of it on my own, trying to get meetings. It was nearly impossible to get past an initial first meeting. After we did a small bridge round that raised just under $200,000, I looked for help in all sorts of places: a group called Female Founders Collective, a female-focused accelerator, a program called Power to Pitch, hiring an advisor.

But the other thing I did was bring my husband back on the fundraising trail.

Female founders raising alone get less than 2% of venture funding. Having a man in the conversation takes the rate from 2% to 30%. I’ve done all that work with accelerators and advisors, and all the meetings we’ve had so far have come through him. It’s like time-travelling back to the 50s when you used to need a man to sign for your car loan. Showing up as an accomplished woman with a strong career background doesn’t matter.

When I look at the hoops that women have to jump through to raise money, I find it very frustrating. The pitch competitions are not about your business idea or your capability to run a business. It’s about the sales pitch only, not the work that comes afterwards. There isn’t enough time to get in-depth on what you are building. I feel like change is coming and there are a lot of advocates for women. But at the end of the day, funders are largely male and have an unconscious bias and look for founders who are similar to themselves. It’s harder to relate to a woman pitching, especially if she’s pitching a female-specific product.

SB: Change is coming but it is also way too slow. I would describe you as having a very feminist business — not just led and owned by a woman, but specifically focused on empowering women. Can you talk a bit about that?

I believe that the confidence, leadership, and teamwork that comes from girls and women in sport is beneficial throughout our lives, not to mention the benefits for mental and physical health! We really look at the shoe as a vehicle to support women in sport, through community-building, education, research, and give-back programming.

SB: How do you define success for Hettas?

LH: I get e-mails from athletes that tell me how the shoes have helped them. Maybe they thought they weren’t going to be able to run the Boston Marathon because they were developing an injury, but we’ve been able to provide a product that provided them relief. Success to me is knowing that the work that we’re doing is making a difference.

If Hettas has strong financials but we were not making an impact in the world of sports and athletics, I would not see that as a success. Of course, we need financial success to survive, but it’s the impact on women in sport that gets me most excited.

I’m tired from moving three times (!) in a month. (Finally moving back home, though.)

I’m tired from endless renovation decisions. (What tiles do you want? What colour grout do you want? What pattern do you want the tiles in? What edging do you want for the tiles?)

I’m tired from not living in my own space for 3.5 months, living out of a suitcase, not having my own stuff, not be able to put anything properly “away.”

I’m tired from the constant logistics of day-to-day parenting, made all the more complex for being out of our routine. 

I’m tired from the typical year-end bolus of work, where the mad dash to finish up this year overlaps with the mad dash to start the next year off on the right foot.

I’m tired from trying to cram in Christmas prep on top of everything else. (Can we get the Christmas tree the same weekend we move? If the kitchen counters are going to be in two weeks from now, when can I do Christmas baking?)

The best solution to tiredness is rest, but that can’t come for a while yet.

The next-best solution is to ask for help with all the personal, day-to-day things. But you see, it’s hard to ask for help. 

Asking for help and the value of autonomous help-seeking

Imagine asking someone for help. Could be something large or small, professional or personal, asking a stranger or a friend. You might be concerned about a few different negative outcomes. 

1. You might worry about rejection. The person you ask might say, “no,” and that feels bad, and still leaves you needing help.

2. Even if the person says yes, you might worry about imposition. Perhaps others experience your request for help as an inconvenience or a burden. 

3. You might worry that asking for help projects a lack of competence or self-reliance. The act of asking highlights some kind of personal gap or deficit. 

Ick.

But here’s the interesting thing: asking for help is asymmetrical. We are liable to worry about these negative outcomes when we are the asker. But if you instead imagine yourself as the askee — the person receiving the request — your first instinct is usually quite the opposite. When people ask us for help, we want to provide it. We are happy to help.

This asymmetry shows up again and again in psychological studies. A Stanford researcher conducted a series of experiments that had people ask both friends and strangers for assistance across a variety of settings. The pattern was very clear. People asking for help:

• Overestimated the possibility of rejection. Almost everyone who was asked to help agreed right away. In broad observational studies, the rate of “request fulfillment” is as high as 88%. Generally, when you ask for help, people will say yes. 

• Underestimated how positive helpers would feel about helping, and misattributed their reasons for helping. 74% of requestors in the study thought people would agree to help out of some sense of social pressure or obligation, but only 2% of helpers reported feeling that way. Helpers generally helped because they wanted to, and felt positive for having helped. 

What about being perceived as incompetent? Here again, people’s intuition is 180˚ from what psychologists have found in field experiments. Asking someone for help or advice makes them think you are more competent. This is especially so if you are asking for help on a difficult task, or in an area where the person you are asking has expertise. But don’t stress too much: researchers found that asking for help with easy tasks doesn’t have negative effects on how people perceive your competence either. 

Psychology field experiments are not the real world, and there are certainly other studies that have more mixed results with different variables. But consistently across the literature, we are too pessimistic in our expectations of how others will respond to requests for help. We underestimate how much people want to help, and how much positive feeling they derive from helping. In many cases, asking for and receiving help is a win-win, but our own misaligned expectations create a barrier towards asking.

The best kind of help-seeking at work

When it comes to the workplace, not all requests for help are created equal. 

Researchers distinguish two different kinds of help requests. Autonomous help-seeking is when you are asking for help in building knowledge and skills that will allow you to level up your capabilities. Think of it as asking for coaching or professional development (“teach me to fish”). Over the long-run, autonomous help-seeking lets you tackle similar challenges independently. Dependent help-seeking, by contrast, is more short-term focused: you are looking for immediate assistance, rather than building your own capabilities. This kind of help-seeking is asking someone else to take care of something on your behalf (“give me fish”). 

In professional contexts, autonomous help-seeking is preferable — it’s associated with greater employee self-confidence and feelings of greater competence at work, which generally contributes to well-being. When it comes to performance reviews, autonomous help-seeking is associated with positive performance ratings, whereas dependent help-seeking is associated with negative performance ratings. That correlation isn’t terribly surprising: autonomous help-seeking sounds like, “help me do my work,” whereas dependent help-seeking sounds more like “do my work for me.”

What is surprising is some recent research showing that autonomous vs. dependent help-seeking is not an artifact of individuals. Rather, people seek help based on the environments they work in and the kinds of stressors that are causing them to seek help. 

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Autonomous help-seeking as a sign of organizational health

If you need help because of factors like complex work, level of responsibility, or time pressure (“challenge stressors,” in the researchers’ parlance), you will tend to engage in autonomous help-seeking. People perceive challenge stressors as opportunities for learning and growth, so the long-term capability-building of autonomous help-seeking is a natural fit. 

In contrast, if you need help because of things like role ambiguity, red tape, or office politics (“hindrance stressors”), you will tend towards dependent help-seeking. Hindrance stressors drive people to focus on meeting the minimum requirements without incurring penalties, so help-seeking is short-term and utilitarian.

Of course, it’s eminently possible for hindrance and challenge stressors to co-exist in the same work environment. What happens then? Bad news: hindrance stressors seem to crowd out challenge stressors, and people fall back to dependent help-seeking behaviours. 

With this lens, we can see autonomous help-seeking is a strong signal of organizational effectiveness. When you regularly see that kind of help-seeking it means that people:

• Are challenged in their roles. 

• Feel psychologically safe enough to ask for help where they need it.

• Avoid the inefficiency and churn that comes from struggling solo with a challenge.

• Grow and learn, increasing organizational capability overall

• Are not unduly burdened with needless obstacles to completing their jobs. 

Many organizations are attuned to psychological safety as an important cultural baseline. Without that sense of safety, people don’t feel they can admit to errors or gaps, and they won’t ask for help. Psychological safety is an important area of focus, but this recent research suggests that organizations must do more. If you want the right kind of help-seeking, you need to minimize hindrance stressors. Red tape, politics, and role ambiguity are not just minor annoyances. They are the enemies of productive, growth-oriented, autonomous help-seeking, and have an outsized impact on your culture. 

In short, we should strive to create a culture and climate where asking for help is the norm, and support our teams in asking for help more often. But equally, we should stamp out bureaucratic inefficiencies and so that people are challenged by the work itself, rather than the obstacles in their way.

Workomics Staff Picks

Some links from the team this month:

• Whisper is OpenAI’s audio transcription tool. A recent AP article highlights how It’s prone to hallucinating things that were never in the original audio file. By some estimates, “nearly 40% of the hallucinations were harmful or concerning because the speaker could be misinterpreted or misrepresented.” That seems especially problematic when these tools are used in a healthcare context to transcribe doctor-patient interactions. Open AI says the tool should not be used in high-risk domains, but AI audio transcription software remains available and in use in clinical settings. 

• We love good storytelling, we love impactful visuals, and we really love our coffee. So we *really* loved this video from coffee guru James Hoffman. He cleverly breaks down a cappuccino into its key components and uses clear visual language to debunk a common myth about how to make a stronger cup of coffee

• An article from the MIT Sloan Management Review was making the rounds this month, talking about how organizational structure contributed to the Boeing 737 Max debacle. The researchers' hypothesis is that a core problem was that relevant engineering expertise was too diffuse in the organization, which didn't allow for appropriate feedback loops between experts (learning from each other, updating mental models, etc.), while also preventing experts from having the needed organizational authority to insist on a safer course of action.

• Just in time for Black Friday, the Workomics crew shared some of their favourite desk lamps. Work in brightness over the dark winter months ahead (no affiliate links…just stuff we like):

  • The Benq Screen Bar Pro illuminates both your desk and your back wall to alleviate eye strain. It has an independent dial to change brightness and temperature. 

  • Some of us like less fancy versions of the screen-bar-style lamp, at less fancy prices 

  • We love the white Canvas lamp with its built-in mount for shooting overhead video. We don’t love the $$$$$ to have it shipped to Canada!

  • The Philips Hue lamp is a fave, but maybe not as much as “task” lamp as a “vibes” lamp

  • The Miady desk lamp is dimmable, has different temperatures, a flexible goose neck, and a great price point.

Happy end-of-November! Wishing everyone great Black Friday deals, a bare minimum of red tape, and all the help you need. Plus maybe a little sleep too.

In Comradeship,

S.

What is surprising to me is how discombobulating the whole process has been. For nearly 20 years, my professional life has been filled with scope and schedules and change orders and status updates. I am very familiar with those things, and have a set of expectations about them — what they mean, how they change, how they are communicated. There is a very (very) large delta between those expectations and the reality of my renovation.

For instance: In my work, I often rely on subcontractors to deliver parts of projects. I define a scope with my subcontractors, and they provide me with their schedule. I integrate their schedule and then communicate it to my client. However, I am still accountable for the schedule. Depending on the subcontractor and the type of work, I might add a little extra time to the schedule for back-and-forth. If there are complications that delay the schedule, then I explain them, and provide an updated schedule.

This is not how it is working in renovation-land. My builder brings in a mason to deal with crumbling brickwork. For reasons of safety and so on, other work needs to stop while the bricks are redone. Sure, that makes sense. But in renovation-land, it seems that the schedule now resides with the mason, and no one else can influence it, communicate it, or even speculate about it. No one is telling us what other work can still progress, or what the schedule will be when the mason finishes. It’s just “well, the mason is working today. Everything needs to be completed in its order of operation.” We have a project manager, and she pushes to get answers on the schedule, but she also treats the schedule as something exogenous to her, rather than something she owns and manages.

No one is accountable for schedule. It belongs to the bricks.

There are vagaries in renovation-land that I don’t have to deal with in my professional life. The mason can’t work when it rains. You can arbitrarily declare your PowerPoint or your newsletter “finished” in a way you can’t with a brick wall. Builders are out working at job sites every day, not sitting at computers where they can easily make Gantt charts. I get all that, but we’ve been living in temporary accommodation for more than two months, and no one will tell us when we might be able to move home.

I’ve come to understand it as a kind of culture shock. Renovation-land is culturally a different place. The words are the same, but they mean different things. The norms and behaviours are not what I expect. My intuition is unreliable. I long for things to go back to “normal.” I have all the feels — frustration, irritability, helplessness. More than the budget and schedule overruns themselves, that is what makes this whole adventure so discomfiting.

Meanwhile, if you need me, you can find me and my family in a teensy basement apartment, our second temporary accommodation in as many months. Hopefully, by the time I write next month’s newsletter. I will be back in my own home. But I really can’t say for sure. It’s renovation-land, so the schedule belongs to no one. Or maybe the bricks.

Hierarchy, knowledge work, and gender equality

Let’s talk about hierarchy. It has an uneasy status in the current cultural moment. It feels trendy to eschew hierarchy: companies increasingly trumpet their flat structures as a feature in job ads1. Even so, hierarchy remains a pervasive default — a “taken-for-granted belief in managerial power as the primary mechanism for ensuring performance.2” 

Hierarchy has its merits. A fairly robust academic literature shows hierarchy is very good at clarifying roles and responsibilities to enable reliable execution of known tasks in stable environments. That same literature finds hierarchy is less effective when teams need to:

1. solve complex, non-routine problems

2. collaborate across functional boundaries

3. adapt to changing conditions

4. apply specialized, intensive knowledge to execute the work.

Those four characteristics are, of course, the defining features of modern knowledge work, so you can see why organizations increasingly tend towards flatter structures over taller ones. 

That doesn’t make flat structures an unalloyed good. In the study of flat hierarchies in job ads, Hurst, Lee, and Frake (2024) discovered that women are less likely to apply for jobs that tout a flat hierarchy in the job description. When they unpacked the reasons why, women cited three main reasons for preferring more hierarchy:

1. More hierarchy offers more opportunity for promotion and career advancement

2. Less hierarchy burdens them with more work

3. Less hierarchy makes it more difficult to fit in. 

Hurst, Lee, and Frake don’t suggest that a flat organizational structure is automatically problematic. However, their findings do suggest that we can’t just throw out hierarchy without carefully considering what will take its place. Given that hierarchy is less effective for modern knowledge work, how might we design flatter structures that avoid negative unintended consequences?

Hierarchy at Workomics

Workomics is what Lee and Edmondson (2017) define as a self-managing organization (or SMO):

• Workomics has no reporting relationships whatsoever, such that, “the notion of ‘reporting’ to someone who has ‘authority over’ you becomes anathema.” 

• While not formally defined, Workomics employees hold decision rights that, “cannot be superseded by someone simply because s/he is the ‘boss.’” 

• Project teams at Workomics are free to organize as they see fit — that is, “the work group, rather than the individual, is the essential unit of work, and control is exercised internally by group members.”  

Workomics has a flat structure because that makes us better at the key elements of knowledge work — solving complex problems, collaborating cross-functionally, adapting to change, applying specialist knowledge. However, we are also a firm that is predominantly women, so we thought it would be interesting to unpack how our approach to flat hierarchy attenuates— we think — many of the equity challenges that can arise in a flatter structure. 

Lee and Edmondson’s research provided a helpful framework for understanding how we have designed our own (lack of) hierarchy. Across different domains, they categorize SMOs based on the degree of centralization — that is, the degree to which things are determined by a single “boss” figure vs determined by individuals doing the work. The six domains are:

1. Work execution

2. Managing and monitoring work

3. Design of the organization and the work

4. Allocation of work and resources

5. Management of personnel and performance

6. Firm strategy. 

Lee and Edmondson draw a distinction between SMOs and organizations that strive to be “less” hierarchical or flatter while still maintaining managerial authority and reporting relationships. In those organizations, only the execution of work is decentralized, and partially so. By comparison, in true SMOs, multiple domains are partially or fully decentralized. 

Our hypothesis is that decentralizing only work execution is a primary source of equity concerns that make women3 less likely to apply to flat org structures. Consider:

• In the absence of hierarchy, organizations might fall back on more patriarchal norms, making it more difficult for women to exert influence or have their voices heard. 

• If work is not managed within the strictures of hierarchy, women may find they are stuck with more of the workplace’s “invisible labour.” 

• Without a hierarchy to create seats at the table based on role, participation might rely on “old boys’ networks” from which women feel excluded. 

• Without formal hierarchy, women might find their contributions less likely to be recognized. 

If our hypothesis is correct, then decentralization of other domains at work is important for creating org structures that are both flat and equitable. In the case of Workomics, we think there are three domains where our choices to decentralize (or not) have made a big difference. 

1. How we design the organization and the work

2. How we allocate work and resources

3. How we do personnel and performance management

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How We Design the Organization and the Work

As is common in small companies, the organization and the work is designed around individuals’ interests, aptitudes, and bandwidth. These are mutually understood at a very fine-grained level, so people are working with their superpowers most of the time. The challenge is that individualized approach to organizational and work design often comes with an implicit hierarchy. 

The twentieth century capitalist model tends to devalue the work of people who execute, relative to the people who set goals, make plans, and direct the work. When that model emerged, a lot of execution work was repetitive and low-skilled. But in modern knowledge work, what we think of as “execution” is complex and ambiguous. The folks who do the goal-setting and plan-making are often lacking the specialized and intensive knowledge needed for successful execution. And yet, even when organizations lack formal hierarchy, they tend to default to an informal hierarchy, where the work of setting goals and making plans is somehow “more than” the work of carrying out those plans. 

At Workomics, we make a conscious effort to value work differently, and prize execution in particular. There are individuals who contribute best by working in ambiguous concepts, making decisions that draw on broader perspectives and connect dots. There are individuals who contribute best by working on tangible deliverables, making decisions that draw on deep, specialist knowledge and elucidate details. The relationship between these two ways of working is deeply symbiotic: each serves the other, making them more effective. 

We strive to value them both equally in the organization — in terms of financial compensation, but also by creating a culture where everyone shows deference to the expertise of doing the work.

How We Allocate Work and Resources

At Workomics, allocating work and resources is the only domain that is fully centralized — the decision to take on a project or a client is not made collectively. Someone thinks carefully about what the organization wants to achieve; what we have the capacity to take on; how many people (and which people) should be assigned; the approximate size and shape of the work. 

Organizationally, someone is in charge of defining “enough” — enough resources, enough revenue, enough ambition. Importantly, “enough” is a two-sided concept — most organizations are clear on what “too little” means, and so are we. But we are equally dogmatic about “too much.” 

That’s because knowledge work is practically infinite. If you are in the business of making widgets, you reach a point where the widget is made and you are done. In the knowledge economy, “done” is elusive — there is always something you could add or improve. If you do knowledge work in a non-hierarchical organization without a guardian of “enough,” workloads can grow uncontrollably. 

We have centralized the allocating (and re-allocating) of work and resources, making sure there is enough for the job at hand, and determining when enough has been done.

How We Do Personnel and Performance Management

To the extent there is performance management at Workomics, it is decentralized and informal. There is no career ladder to climb, and everyone joins the team understanding that. 

Workomics is, however, still a company with owners. There are people who get to decide whether employees will continue to draw their paycheques. That kind of power imbalance fundamentally creates hierarchy, no matter how much you decentralize any other decision rights. 

One way we address that power imbalance is through transparency on termination. In employment contracts, we specify how much working notice and severance employees will receive. In team meetings we discuss things like runway and operating capital, so employees know what to expect for the months ahead. These steps mitigate some of the effect of the power imbalance, but the imbalance itself remains. 

However, we believe that the nature of knowledge work actually reduces the power imbalance. Managerial authority is classically described as “irrevocable from below,” as if the workers have no other viable option. In a capital-intensive industrial assembly line that was perhaps the case. But modern knowledge workers are highly-skilled individuals. In our case, they are charged with self-managing their own work. Any one of them could easily ply their trade elsewhere, and thereby revoke managerial authority. 

In modern knowledge work, the more apt classical phrase is “consent of the governed,” meaning that workers who are subjected to rules have the power to agree or disagree with them. As long as there is a traditional shareholder structure, the managerial work of making decisions — especially hard ones about people’s livelihoods — still has to happen. But if the legitimacy to make those decisions only exists as long as employees are consenting to the model, then hierarchy shifts to a more balanced power dynamic.

Workomics is a small firm, doing particular kinds of work, so there are limits to what can be generalized from our model. However, we do think that our choices around decentralization help allay the specific concerns Hurst, Lee, and Frake uncovered in their research. 

• Because we highly value execution work, even over managerial work, it is easier for employees to feel like they “fit in.” Their unique skills are valued for what they are, and we are not asking people to map themselves into a broader organizational model. 

• Because we have fully centralized allocation of work and resources, people don’t have to worry about overwhelming workloads. There are sometimes still too-busy weeks, of course (allocation is rarely perfect). But over the long-run, workloads are in a sustainable equilibrium. 

• Because we don’t have promotions at all, there is no concern that things like pay increases and title changes might be handed out capriciously. Because we operate from the principle of “consent of the governed,” there is a more balanced power dynamic, even in the domain of hiring and firing decisions.

Workomics Staff Picks

Some links from the team this month:

• We thought the NOBL Academy’s Change Chart Blueprint was pretty nifty! It’s a straightforward tool to be used in the early stages of a change to help leaders take a step back, ask helpful questions, and figure out how to focus on the right problems and solutions.

• We do a lot of disease state education around here, so we’re always keen to read perspectives from others:

  • We often grapple with branding trade-offs, as many physicians will avoid anything that is overtly from a pharma company. Creating thoughtful, high-quality content with subtle branding can make a big difference in practitioners’ willingness to use those materials. There is lots of other good tactical advice on disease state campaigns in this phamax Digital post.

  • Beyond those tactical decisions also lie ethical considerations, like balancing patient and HCP education without being sensational. Successful disease awareness campaigns carefully weigh business objectives with the needs of the public, and are mindful for how marketing may positively and negatively impact the target audience. This two-part post by the Association of Health Care Journalists explores a disease awareness campaign that may have tipped the scales and created educational content that could harm rather than help patients.

• Over at The Cut, we thought this was an interesting look at people’s relationship to work, telling a cautionary tale about “the dream job” and how career priorities and aspirations are shaped by our experiences and change over time.

Wishing everyone a safe and sugar-filled Halloween. We’re going back to our usual neighbourhood to hand out candy, and I’ll be taking a ninja and a Darth Vader out for trick-or-treating tonight. Such fun!

In Comradeship,

S.