Product-Market Fit vs. Evidence-Market Fit in Digital Health
For technology companies, the concept of product-market fit is a methodological cornerstone of successful venture creation. The bare-bones definition of product-market fit is measurable by the extent to which a product, service or piece of technology actually has a value to a person or firm who is willing to pay for it. For emerging digital health companies, it is becoming increasingly clear that more nuanced concepts for measuring success could be helpful. I propose that the concept of evidence-market fit could be one of those semantic tweaks we can use to better serve digital health buyers, sellers, founders and analysts.
A service that accelerates mobile websites has product-market fit if enterprises are willing to pay a price to incorporate that service into their technology stack.
The latest Call of Duty game has product-market fit if gamers are willing to pay $70 in exchange for 40 hours of enjoyment shooting bad buys from their couch.
Sweet Greens and Chop’t have product-market fit if thousands of Manhattanites are willing to pay $12 for a fast and healthy salad on a regular basis.
Sweet Greens and Chop’t might not have product-market fit in a suburban environment with less density and different preferences. What works in Midtown may not work in Albuquerque.
Even with just a few large customers, product-market fit can exist. An arms manufacturer may indeed have product-market fit if the Tomahawk missiles they design and manufacture are only sold to the United States government and several other national defense departments worldwide. Product-market fit does not, by definition, require thousands of discrete buyers, merely a market of a certain size
A $15,000 virtual reality rig that can immerse people in fighter jet simulations with the fidelity of Star Trek’s Holodeck may not have product-market fit with consumers whose average budget for virtual reality is $300. However, product-market fit could exist with aerospace manufacturers and military groups at the $15,000 price point if they see a return on investment of over $15,000 and are willing to pay.
Let’s pause here and put this concept in context. Product-market fit has been an immensely important framework fur adjudicating the extent to which emerging products and technologies are actually solutions that actually solve problems that people or firms are willing to pay to solve. Although you could probably go back and find proto-theories about product-market fit in the management textbooks and McKinsey playbooks of the late twentieth century, the concept has really taken off as a decidedly “Bay Area” philosophy in the last fifteen years (and especially the last six years).
Digital health entrepreneurs know that the Silicon Valley gameplan —rapidly testing product-market fit with a minimum viable offering and using that feedback to rapidly decide whether a market exists — can hit limits when applied to enterprise health customers sourcing digital health solutions. This is especially true for digital health companies whose fundamental value proposition involves enabling measurable health outcomes. ‘Digital therapeutics’ has emerged since circa 2013 as a (somewhat ill-defined catch-all) for digital technologies (whether they be an app, a wearable, remote coaching or telehealth, or a combination thereof) that deliver measurable health outcomes through some non-invasive format that doesn’t involve ingestion or injection.
The fundamental disconnect emerges when you consider how this kind of value proposition differs from the traditional Silicon Valley model.
Imagine you are selling a Fortune 500 company a cloud storage solution in 2012. You have a solution that allows permission-based file sharing in the cloud at a scale that can support thousands of employees. Airline Company CIO meets you in Atlanta, you sit down and you demo the product in a limited fashion. You walk through their questions, their objections. You walk through some elegant product features that differentiate your offering from Dropbox and Box. You overcome the objections. And you present a contract. Fundamentally, as a soultions-based salesperson, you make some kind of evidence-based statement that goes something like this:
“We’ve found with our other clients that with cloud-based file storage, employees reported that the administrative overhead on coordinating file-sharing while working remotely went down by 40%. Remote salespeople were able to turn around deliverables 30% faster when working in the field.” Or something like that.
Now, the Airline Company CIO may believe your fundamental assumptions or she may not. She may agree that your product does what you claim, or not. She may agree with the extent to which it can move the needle for her company. Ultimately though, with enough theoretical models and case studies, that CIO can get on board with your solution and make a purchasing decision based on theory, analysis, data, strategic thinking and a whole other factors.
What the Airline Company CIO is unlikely to do is to ask that you provide a pre- and post- study or a randomized controlled trial that proves scientifically that your Dropbox/Box competitor does in fact save time when tested against a control group with the cloud service as the modified variable in the experimental arm.
This poses problems for founders and enterprise sales teams in digital health who are selling solutions that include claims related to health outcomes.
Your digital smoking cessation therapeutic might look something like providing a remote coach available through a smartphone app, a beautiful interactive curriculum on mindfulness and breaking addictions, and a monthly delivery of nicotine gum in decreasing quantities to help wean the participant off of cigarettes (Heads up: I am not suggesting this is the correct therapeutic combo, just offering it as a basic example of what might be involved in a digital therapeutic.)
Intuitively, this combination of features seems like it would easy to sell. With billions spent on the effects of smoking, who wouldn’t want to deliver a program that can address this is a holistic, targeted fashion, with clear thought put into what the user needs and how the product can be designed to help them achieve a goal.
The problem is, the health care buyer is much more likely to say “This sounds like something we’d want to engage with and pay for. We’ve wanted something like this for years. But I’m jaded. I don’t believe you. I don’t believe this works. Show my the evidence.”
You’ve got product-market fit. (“This is something we’d pay for.”)
But you don’t have evidence-market fit. How do you demo longitudinal 12-month outcomes and recidivism rates in a sales meeting?
The truth is, you don’t. Your work began long before the meeting because you came armed with real evidence to demonstrate that you have evidence-market fit (your customer might give you a funny look if you phrase it this way, but you get the idea).
And this is where the Silicon Valley model bumps up violently with the health care purchaser. Obtaining rigorous proof, including working with third-parties to validate outcomes is fairly alien to the Bay Area mindset.
As any digital health founder whose company drives value through health outcomes will tell you, this dichotomy between product-market fit and evidence-market fit can be difficult for investors (of the angel or VC variety) to wrap their heads around.
To use two animal metaphors in one sentence: the elephant in the room is that there is an implicit chicken and egg problem here. How do you get the customers without the evidence, and how do you get the evidence without the customers?
There is no easy answer and digital health founders will have to grapple with their own solutions to solving this. That’s why I strongly encourage founders to engage their stakeholders (investors, team members, advisors) on the concept of evidence-market fit, define a validation strategy, chip away at distrust with substantive data not sales-y sizzle, and above all use your data to keep telling your story over and over again.
Curtis Duggan is the CEO of Blue Mesa Health.