quantified self—5 years 5 lessons

5 years, 5 lessons

Quantified Self: The next frontier in mobile healthcareIEEE Communications Society SCV + TiE SV 19 Sep 2013Rajiv Mehta • [email protected] • 650/823-3274

Rajiv MehtaTiE & IEEE: QS the next frontier in mobile healthcare, 19 Sep 2013 2

September 10, 2008

The first meeting of QS was at the home of Kevin Kelly, on September 10, 2008. About 30 of us were there.

• The very first speaker showed us something unexpected. He had been recording his activities, some as brief as 5 minutes, for the past 3 years! He showed us color-coded charts of this data. And then, astoundingly, he asked us what he might learn from it. And that started the conversation.• The speaker in the photo is Seth Roberts, a Berkeley professor, who has been doing self-tracking and self-experimentation for decades. • The guy in the middle with a yellow t-shirt with red letters is Tim Ferris, who has since gone on to write the bestselling book “The 4-Hour Body” based on his own self-experimentation. • I’m the guy up front on the left of the picture.

That first meeting was almost exactly 5 years ago.


1. Market size2. Sensors3. Feedback loops4. Engagement5. Value

From these 5 years of experiences, I’m going to highlight 5 things that seem especially pertinent to pursing business opportunities: the market size; the key topics of sensors, feedback loops, and engagement; and the question of what value users are finding.


#1 Market Size Niche or mainstream?

First the issue of market size. Ironically, for a topic that’s all about data, it’s hard to get clarity on the size of the market. Is it still a niche, just early adopters, or is this already mainstream? It’s confusing ... there’s a mess of indicators.


USA-WestSan FranciscoQSXX-SFSilicon ValleySan DiegoSeattleLos AngelesNorth BayPortlandHawaiiBerkeleySanta BarbaraDavis/SacramentoBoulder/DenverSan FranciscoSalt Lake CityPhoenix/ScottsdaleReno/TahoeOrange County

USA-EastNew YorkBostonQSXX-BostonWashington DCChicagoPittsburghPhiladelphiaLouisvilleHoustonRaleighVermontAustinNashvilleMinneapolisDentonDallasAlbanyAtlantaHuntsvilleMemphisChampaign, ILLansingIndianapolisSouthwest FloridaGrand RapidsCharlotteColumbusClevelandCincinnati

EuropeAmsterdamLondonParisBrusselsEdinburghSpainDublinMunichBerlinHelsinkiCzech RepublicHamburgAachen/MaastrichtGenevaPolandBudapestStockholmCopenhagenMilanStuttgartCologneGroningenAthensBerlin (English)ZurichRuhrgebietOslo

AfricaCape Town

AustraliaSydneyMelbourne

South AmericaRio de JaneiroBuenos AiresBogota

CanadaTorontoVancouverMontrealOttawa

AsiaTokyoBeirutSingaporeDubaiBangkokBeijingTaiwanShenZhenHong KongSeoulBangaloreMumbai

Let’s look at QS itself. From that modest beginning, QS has grown rapidly. When I last looked, we had 96 meetup groups around the world — including new ones in Mumbai and Bangalore. We’ve had 4 conferences, 2 in the Valley and 2 in Amsterdam, and the 5th one is coming up in San Francisco next month.

Speakers at QS events generally talk about their own experiences. We ask them: What did you do? How did you do it? What did you learn?

For the past couple of years we’ve also asked for a show of hands: “How many of you are at a QS event for the first time?” Usually about half the people raise their hands. That’s amazing. This is obviously growing fast. Still, the total number of people who have attended at QS event is admittedly a very small percentage of the population.


Gartner’s Hype Cycle for Emerging Technologies 2013

This is Gartner’s famous “hype cycle” chart, where technologies proceed from some innovation trigger, through the peak of inflated expectations, crashing down into the trough of disillusionment, along the way to the plateau of productivity. Regarding QS, Gartner seems to want it both ways. As you can see, QS is placed on the left side of the chart reflecting its newness. But, they’ve noted it as a light-blue dot indicating they think it will reach the plateau stage in just 2-5 years. So, it’s supposed to go from something new to something mainstream practically overnight. On the other hand, they’ve put “Mobile Health Monitoring” technologies further along the chart, but with a dark blue dot indicating it’ll take 5-10 years before that is mainstream. Gartner seems to be saying that QS will become mainstream sooner than the technologies that drive it.

Rajiv MehtaTiE & IEEE: QS the next frontier in mobile healthcare, 19 Sep 2013

Pew Internet “Tracking for Health” 2013

7For some more confusion, a recent Pew Research survey found that 70% of American adults say that they track at least one health indicator. That’s pretty darn mainstream. However, half of those people that track say they just track “in their head”. Overall, they found that only about 11% of American adults use apps or devices for tracking.

But, is this an overcount? Even 11% seems much beyond an early-adopter, niche market. Some argue that this is in fact an undercount, because the sales of home glucometers, scales, blood pressure cuffs, etc. is higher than this 11%.

Pew has deep experience doing such surveys, so the numbers must be correct. But they don’t feel right, and so there has been lot of conversation online and off about how to reconcile these results with common experience.

One issue that comes up, is that of perceptions: not everyone who is currently tracking thinks of what they’re doing as “tracking” — they’re managing their diabetes, not tracking their glucose level.

Rajiv MehtaTiE & IEEE: QS the next frontier in mobile healthcare, 19 Sep 2013

ABI Research, Feb 2013

8

100 Million (2014)

300 Million (2019)annual wearable device shipments

61% of wearablesare sports / activity trackers 2013

Business Intelligence, Apr 2013

Some industry forecasters are quite bullish. Here’s one middle-of-the road forecast. It would seem this is already a significant business.

Rajiv MehtaTiE & IEEE: QS the next frontier in mobile healthcare, 19 Sep 2013 9Finally, many crowdfunding campaigns for personal trackers have had success.* Instabeat, based in Beirut, is a gadget that attaches to your swim goggles, tracking your performance while you’re in the water.* Lumoback is a local company focused on posture. We’ll be hearing more about it from CEO Monisha Parkesh in a few minutes.* Beddit, from Finland, provides a thin film strip that you place underneath your sheets for sleep sensing. It’s very accurate and unobtrusive.* Emotiv, based in San Francisco, has head gear for measuring brain waves.* And Scandu, also based locally, is developing the Star Trek tricorder.

Clearly there are many that want such products.


Self-reflection... not a new idea

It’s also worth mentioning that this idea of self-reflection, self-analysis is nothing new. The Buddha, and many other philosophers before and after him have been teaching us the value of paying attention to one’s self. Something that’s a few thousand years old can hardly be thought of as new.


#1 Most everybody’s doing it ... but they don’t call it tracking, and they may not use technology

Bottom line ... self-tracking is commonplace. If you can tap into what people are already doing, the market could be huge.


#2 Sensors

Next, let’s talk about sensors. The availability of cheap, small sensors sparked the Quantified Self movement.


Shiny new toys

There’s lots of excitement about these new technologies — after all, the technical possibilities explored by the first panel is partly what lured you here today.And it feels like we’re just barely scratching the surface, that there is a lot of innovation to come in this space.

The shininess of the new devices, their gadgety novelty, often is what attracts people to self-tracking in the first place. This is not to criticize these gadgets. If they inspire people to consider their wellbeing, that’s fantastic. But it’s more than just the excitement of a new toy ...


“The real voyage of discovery consists not in seeking new landscapes, but in having new eyes”

Marcel Proust

Marcel Proust said “The real voyage ... eyes”

These new sensors, just like the telescope and the microscope before them, open new worlds to us. Each new sensor allows us to see something new about our universe, something that’s always been right there in front of us, but that we weren’t able to see before. Sensors, and the new data they provide, are absolutely essential to this space.


Human sensors

However, interestingly and unexpectedly, these new sensors have reminded us that we all possess some in-built sensors, that work quite well.

Many of those who have done self-tracking have discovered that, with practice, they get very good at knowing their numbers. People using pedometers pretty soon just know about how many steps they’ve walked that day.People using sleep measurement devices soon know how they’ve slept and what their “sleep score” is just from how groggy they feel that morning, and so don’t need to look at the sensor data.

Rajiv MehtaTiE & IEEE: QS the next frontier in mobile healthcare, 19 Sep 2013 16And if you look around, you see that such perception skills are commonplace.Any good mechanic is able to grab the right wrench or the right screw without getting out his calipers.

Rajiv MehtaTiE & IEEE: QS the next frontier in mobile healthcare, 19 Sep 2013 17Artists differentiate between many subtle color differences just using their eyes, and piano tuners just use their ears.


“new eyes”

vs.

teaching us to see

Basically we’ve found that while the new sensors do open our eyes to things we had not perceived before, that we often learn to continue perceiving without the crutch of the sensors.So, are these new sensors giving us new eyes, or simply teaching us how to see?And do we measure the success of a new sensor by how often it is worn, or rather by how much more accurately the user perceives his world whether or not he continues to use the sensor?


Making sense of sensors

Another key issue about sensors is making sense of the numbers.


“What we discover in nature is not really a matter of what exists; what we find is determined by our ability to understand”

Peter Hoeg

Another novelist, Dane Peter Hoeg, had this to say “What we discover ... understand.” (In “Smilla’s Sense of Snow”)

Can you understand what the data is showing?Figuring out what the data means, what you should do, whether or not you should even pay attention to it ... these are not trivial issues.

Many people looked through telescopes when they were first invented. Only a few, like Galileo, understood what they were seeing.


WeatherBaseballElectionsPokerEarthquakesWall Street...

This challenge -- making sense of the data -- is a challenge in many, many fields.Nate Silver made his name initially by brilliant baseball analysis, then got even more famous by predicting elections much more accurately than all those pundits. In this great book, he covers many fields.


#2 Sensors ... are catalysts, and sometimes critical

So, these exciting new sensors are indeed very valuable ... but not every single one, and not always ... and don’t underestimate the value of those real people that the sensors are attached to


#3 Feedback Loops

A hot meme in this space is feedback loops

Rajiv MehtaTiE & IEEE: QS the next frontier in mobile healthcare, 19 Sep 2013 24Wired magazine captured the zeitgeist in a June 2011 article. Thomas Goetz, such a good writer, captured the essence of why so many are excited about the potential of feedback loops. It seems so straightforward: measure what’s important, compare to your goal, make a change, measure again ... and you should quickly reach your goal.

And you’ll find many success stories in the QS community. People who have been able to make significant improvements in their lives by being able to get and respond to data about themselves.You’ll hear later from Sky Christopherson, who will share with you some amazing stories of his own achievements and those he’s worked with using such techniques.

But also true is that the experience of many QS experiments is that often the goal is not reached, despite the measurement and tinkering.

Rajiv MehtaTiE & IEEE: QS the next frontier in mobile healthcare, 19 Sep 2013 25As anyone who is an IEEE member knows very well, feedback loops are not a new discovery.

This great poster by Dubberly Design shows that the basic idea is used in many fields. So, there is deep knowledge about feedback loops that helps explain the lack of success.


Control-Goal Mismatch

On key point is that your actuator, the thing you can control, has to have a meaningful impact on the variable you’re trying to control. Otherwise the feedback loop isn’t going to work out as planned.You can set your home thermostat to whatever you want ... it won’t make any difference to the temperature outside.


“like applying sunscreen and claiming it protected you from a nuclear meltdown ... wholly inadequate to the scale of the problem”

Nate Silver, The Signal and The Noise

Sometimes it seems the controls at your disposal just aren't good enough.As Nate Silver says it's “like applying ... problem”.

You can track your weight, and eat more broccoli and walk 10,000 steps, and still not have much impact on your weight. If your body’s weight set-point is responding to other, more powerful stimuli, your body will just adjust itself to compensate for all that broccoli and walking.


Time lags

Simple feedback loops are often no match for complex systems.And one major complexity, when it comes to our bodies, is the time lag between a change in diet or environment and whatever it is that you’re tracking.


Tighter feedback loops?

There’s a tendency to think that more information, faster information, and more responsiveness is always better. One wants to tighten the feedback loop.


“When there are long delays in feedback loops ... foresight is essential. ... If a decision point in a system is responding to delayed information the decisions will be off-target ... if action is taken too fast, it may nervously amplify short-term variation and create unnecessary instability. ... Overshoots, oscillations, and collapses are always caused by delays.”

Donella Meadows, Thinking in Systems: A Primer

Recipe for disaster

But in fact, that’s often a recipe for disaster.

Donella Meadows notes that “If a decision point ... unnecessary instability.”Time lags play havoc with feedback loops.

Many experienced self-trackers have learned not to react too quickly. The difficulty is knowing when to wait and when to react. ...


#3 Feedback Loops — triggers for reflection, not instant response

So, if you’re going to build a business around some smart sensors that are going to help people know what to do, proceed with caution.

You’re safer promising feedback for the person’s own reflection, rather than promising to tell them the “right action”.


#4 Engagement

Another hot meme is engagement ... motivation, behavior change. The idea that these new tools are going to get you to do what you should be doing.


QS experiments $$ or “points” public commitments social support

This is a very popular idea. Many in the QS community have struggled with changing their own behaviors, and so have developed tools to help themselves. They want to hack their own behaviors, and help others do the same. There have been lots of experiments. • People have tried money or points, that you win some for doing the right thing or you lose some for missing your target. • People have tried public commitments, motivated by either the support that comes from people cheering you on, or the shame of failing publicly. • People have tried social support ranging from very social sites, to small groups, to very private.

Interestingly, all this QS experimentation mainly seems to have confirmed what the experts have been saying all along ...


B. J. Fogg

BJ Fogg is a Stanford professor, a well known and popular lecturer and consultant on technologies for behavior change. One of things he stresses is that motivation is most likely not the problem. He advises: Don’t build tools to increase motivation. Build tools that makes things easier to do.


B. J. Fogg

BJ emphasizes that for a behavior to happen, both motivation and ability are required. And, in practice, the problem usually is that something is simply too hard to do. BJ also emphasizes that a trigger is necessary, something has to remind you at-the-right-moment that you should do something. Too much energy is being focused on motivation, when ability and triggers are often what’s really lacking.


Decades of behavior research conclusion

Rewards may provide small motivational boost for routine, boring tasks requiring no creativity

There’s also decades of research that external motivation hardly ever works.External rewards — carrots & sticks — only work, a little, in very specific situations.At other times, they are not just useless, but often counter-productive.

Daniel Pink's book "Drive" is a wonderful lay summary of this field.


Decades of behavior research recommendation

Make it easier for people to do what they want to do

Things that have been successful in the QS world so far — such as the original Nike + system, or the MyFitnessPal or RunKeeper apps — have made it easier for people to do what they already wanted to do.

Just note that in this context the idea of “easier” also includes making things more pleasing, fun, beautiful, etc.


#4 Engagement — support intrinsic motivation

So, based on the experience of successful QS products and of decades of behavior science, you’re better of building a business supporting what people want to do, than on nagging them to do what you think they’re supposed to do.


#5 Value

The final lesson I’ll share with you from the QS experience is what value people are getting from self-tracking.It may surprise you.


Appearance: Success Stories

Many of the QS presentations you’ll hear are of successful experiments — people tracked something, made some adjustments in their lives that resulted in a positive change. People like presenting successes.


Reality: Goals not achieved

Only when you talk with people informally do you learn that in fact most of the time people aren’t very successful in achieving the change they seek: they haven’t lost a lot of weight, significantly improved their sleep, etc. Specific improvements have been hard to come by.


Why? It’s hard!

Why? Partly because its just plain hard ... I’ve just described some of the complications.


Why? Bad sciencePoor experiment designNot based on evidence

Just anecdotesPlacebo effects“Messy” dataPoor analysis

And partly because many people seem to have a very poor grasp on the basics of science, on the basics of doing experiments. Almost all of the QS experiments I’ve come across have been bad science.


And yet ... Experience worthwhile Learn something valuable

And yet, almost all the people who did those flawed experiments seem to have found the experience worthwhile, and have learned something valuable. They’ve come to this learning from doing the experiment. They get satisfaction from doing something, from paying attention, from learning something about themselves.


Finding the finding

We talk about “finding the finding”, the unexpected discoveries. I tracked my own sleep only to discover I didn’t have a sleep problem. But in the process came to better appreciate the normal ups & downs of life. Another QSer tracking energy expenses couldn’t make much impact on her budget, but came to learn how much she enjoyed the meditative rhythms of line-drying her clothes. The meta-learning is often far more valuable than the actual data, the experiment results.


#5 Value is in the doing, in the engagement

A possible lesson to be drawn is to make sure you design products or services such that don’t preclude this possibility.If your solution is too paternalistic, you may make such learning impossible.

Pay attention to what Steve Jobs said.


Next local meetup: Sep 25 Conference: Oct 10-11quantifiedself.com

[email protected] • 650/823-3274

If you want to tap into these early adopters yourself, you’re welcome to come to QS activities.The next local meetup is next week in San Francisco.And the next conference is just a month away.

Thank you.