Acqusitions in Digital Health: Nokia + Withings
Building Out the Healthcare Internet of Things
Apologies for the gap in posts. I’ve been working on bits and pieces of different types of blog posts over the last week.
Personalized and digital health, by way of technology’s rapid nature, moves fast. There are two events that have occurred this week I would like to draw attention to with respect to digital health. One will be about the Internet of Things (IoT), the other, about APIs and frameworks (we will see clear linkages to my prior posts regarding iPhones as infrastructure).
Each will have a different flavor, and they’ll all be up by Sunday 31st at 11:59pm. They are as follows:
- Case Study: Nokia + Withings — We’ll be discussing the recent acquisition of Withings by the telecom giant on by Nokia on April 26th, 2016 and what this means in this article! Many, many connections in different aspects of information and communications technology (ICT).
- Case Study: Apple’s CareKit —The intersection of ICT and Digital Health, when personalized, is fundamentally about clinical data. Apple launched CareKit on April 28th, 2016. I will be discussing the state of APIs and programming frameworks (will also talk about ResearchStack and FHIR), which links back into my prior blog posts about about how Apple is building iPhones as infrastructure.
… and now for something completely different, I introduce Penn Jillette from Penn & Teller in the next section.
Withings & The Three Propositions of Healthcare IoT
Put simply, Withings (founded: 2008, slogan: Inspire Health) is a consumer electronics company that designs products that are part of the Internet of Things, such as Internet-connected scales and watches with vital sign tracking (heart rate, oximetry, steps taken, etc). I want to highlight that not all of these products are “wearables” — you do not always keep them on. For example, you do not wear a scale.
I like this ad/promo video as an introduction to Withings because it encapsulates two core principles: (1) why digital health is so difficult and (2) why wearables not sufficient for a fully comprehensive personalized health intervention.
Penn describes how he lost over 100 lbs. using Withings products. It’s pretty amusing too, in that Penn & Teller kind of way:
Now, what I think is perhaps most striking about this ad is when Penn goes:
“And yes, there is a trick to losing weight! Wanna hear it? Tricks take a lot of work. It took Teller and I six months how to pull a rabbit out of a hat. Tricks take time and you have to have the right tools.”
I want to call out how striking this message is, because I think Withings’ marketing message is, at its core, realistic. This in stark contrast to the vast majority of marketing messages for other products or services, which imply (1) quick or instant gratification and/or (2) the product does the hard work for you.
Digital health, by way of contrast, recognizes the exact opposite.
- Proposition 1: There is no quick or instant gratification, i.e. time-series data is incredibly important
- Proposition 2: You work with the product, i.e. the product does not exert effort purely on your behalf and you exert effort
This is the dynamic that makes studying digital health unique from the study of other goods. Withings is effectively saying: we know this is hard, we know this and you know this — but we’re the ones that can help guide you along the way, and along this journey. This is important because it underlies the very foundation of what digital health is about. By the definition of chronic disease, there are no one-shot solutions (contrast this to a 100% contemporaneous service like Uber — that’s one reason why there is no Uber for healthcare). These health conditions necessarily take time, and so, time-series data is ever more critical — this is only enabled with ICT. The range of biometric data that needs to be tracked necessarily means the following:
- Proposition 3: Specialized, non-mobile phone devices must be made (scales, blood pressure cuffs) that collect relevant data, and connect them in what may be called an Internet of Things strategy for actionable, clinically-relevant results.
These are the Three Propositions of Healthcare IoT. I would argue that Proposition 1 & 2 are the assumptions that underlie overall Digital Health strategy, and that Proposition 3 follows from the joint assumption of Digital Health with IoT. Taken together, from these premises, any given digital health IoT business strategy should follow.
Inspiration from Earnings Calls — Penn’s Unscripted Interview
I understand that marketing is marketing, and certainly Penn, as a magician, is a good salesman. That being said, Penn seems to be the type of person to not endorse a product just because he is being paid, but rather, if he truly believes in it. His unscripted interview describing the utility of Withing devices in weight loss is revealing because it underlies principles of IoT. Similar to how good analysts read between the lines on executives’ earnings calls, I will look to do so with this interview to glean insights about IoT’s value-add to digital health services:
3:40 — “There’s all sorts of ways to let the weasel inside you lie about how fat you are. The Withings scale sends that right out [to friends].”
- Takeaway: Chronic disease is as much of mental and psychological one as it is a physiological one. Instant data transfer, enabled by an IoT strategy does not lie and is particularly objective. This enforces a positive feedback loop by piggybacking on the network effects of iPhone or telecommunication infrastructure.
4:21 — “As my weight fell off, I lost, for over three months, .9 pounds a day.”
- ICT is most efficacious because it allows people to determine rate or change data (not stock): the fact that Penn even knows the his specific .9 lbs/day loss rate is a testament to ICT’s impacts.
7:07 — “There’s nothing that you can buy that will make you healthy. There’s nothing. You have to do it with information, and work, and decision-making.”
- Personalized medicine is not about product per se, it is more deeply about how data from that product enables a better process.
9:47 — “And all of that is him [Penn’s friend]. And then a little part joins in with his doctor. And then a tiny part joins in me and his friends. It’s all him. And, tying all those together, is Withings.”
10:57 — “The Internet gives you nothing. It gives you nothing. It’s the people on the Internet that give you stuff. And what the Withings scale and what the Withings blood pressure cuff do is they help friends help you in the most important thing you can do.”
- Chronic disease management is unique, exactly because it is so personal. And because it is so personal, communication is key. An IoT strategy leverages your existing networks and inserts your health data in a social context that matters, and a clinical context (with doctors) when needed.
To be fair, I am not saying that Withings is magic — you still have to diet, you still have to see your doctor. What I am saying, and what others are saying, is that Withings, as IoT, makes a given process easier by digitizing routine, physical processes.
Aggregation in Personalized Health: IoT Strategy
So, this is all consistent with what was previously mentioned with respect to personalized health. From a business and self-serving perspective, what is Withings trying to do? Much like Apple does by providing infrastructure, they are doing so by providing value upstream through the function of aggregation.
This aggregation is critical because we can see that data is more useful in aggregate — it provides a “better picture” of the individual and that collection can then be parsed out as necessary to different downstream sources, whether it’s direct to a doctor or to a 3rd party piece of software. This is upstream value capture, and data aggregation is crucial to this, because whomever holds the data most likely holds the value.
A theme (read: slight obsession) in this blog has been infrastructure. Apple has the iPhone; that is immovable as the end point. The next logical step is Health IoT infrastructure, capturing relevant and individualized clinical data and disbursing it via API. Here is what is important to note: the company generating the data and allocating it has competitive leverage. Since routine is critical to improvement in personalized health, a patient’s decision to change their Health IoT infrastructure could result in very high switching costs. This dynamic explains the market entry and competitiveness of the space: companies want to lay claim early.
Withings is not the only one fighting for this still-contested space; Apple, as a extremely vertically integrated company, seems to be looking downstream and entering in some capacity as well.
Nokia’s Acquisition of Withings
Digital Health is projected to grow with a CAGR of 21% in the span of 2015–2020, as reported by P&S Market Research. Nokia is a classical example of traditional telecommunications company — this is the definition of traditional infrastructure. Having had sold it’s mobile phone division to Microsoft in 2014, it now focuses on telecommunications infrastructure and large-scale industrial projects, which is their main revenue driver. Then how does their acquisition of Withings for $192 million, a decidedly consumer electronics company, play a role? The CEO of Nokia Technologies — the subsidiary responsible for R&D and technology licensing — Ramzi Haidamus, states:
Then I started asking questions — which of these technologies has the best chances to work in the market from a timing perspective?
Digital health is something that comes very natural to Nokia. It’s a brand that’s known for a solid, reliable brand.
I would argue that Nokia’s entry into the Internet of Things is in line with the idea that (1) the mobile space is already lost to Apple or Google and (2) value capture in IoT is currently a Wild West of opportunity, and the timing is right. Nokia may have lost and divested in mobile infrastructure war, but the battle over IoT infrastructure, especially with respect to the delivery of personalized healthcare, has just begun. As with Mobile First, everything flows from this core assumption—as Nokia recognizes, infrastructure is no longer static, but tied to the mobility of the user — the patient — themselves.
Next Case Study: Apple’s CareKit
I’ll next be talking about the second component of infrastructure: APIs and the competition surrounding it, and how that impacts personalized health.