Does IoT need assistants or coaching?

I recently read Carnegie Mellon University is working on a new high tech assistant called Gabriel.  Apparently Gabriel will help you find restaurants and more quickly assemble IKEA furniture.  Now Carnegie Mellon is renowned for its work in robotics, materials, and artificial intelligence (AI) and I have high expectations for their work.  But my first thought when I read what to expect from this new program was: “Really? Do I really need more technology to help me find the best Kung Pao chicken or assemble a Scandinavian coffee table?” (By the way I approach IKEA assemblies like brain teasers and I feel I am a quitter if I have to get help.)  If that is how Gabriel is going to work isn’t this “whisper in my ear” assistant just a more automated, audio version of search?  I know, we live in an information world and more immediate access to the right information always has value.  But I don’t see an “assistant” as the kind of disruptive use of artificial intelligence that we need.

I know that the Carnegie Team has much higher goals, but what kept my attention in this article is actually what I didn’t find – the word “coach.”  I spend a lot of time these days working on the application of the IoT to healthcare and coaching is an everyday subject.  In fact, I could argue that it is an overused word.  I have been researching the science of coaching and how it can be used to help patients change their behavior and live healthier lives.  When I read that Gabriel “whispers” in the user’s ear I thought about the NFL quarterback helmets and wondered “Does Mike McCarthy whisper in Aaron Rodger’s ear?”

Seriously, what defines a coach and how do we automate that skill?  Google Now and Siri, by any definition, are assistants already so I would argue that if we don’t do more than present previously available information aren’t we just making a smarter search engine?  Theo Priestly recently wrote a great piece on this very subject forecasting that the consumer focused companies like Google and Apple were going to win the race to AI in IoT because they understand this need much better than the academics and traditional industrial companies.  But Priestly is still talking about big data analytics.  Analyzing game films is only one part of coaching.

Good coaching is one of the most effective behavior change tools and behavior change is the most sought after function in both digital health and the Industrial IoT.  Health systems don’t just want patients to do as they’re told, although that will help tremendously, they want them to improve their behavior and be healthier on their own.  Companies don’t just want workers to follow rote instructions, they want them to become better problem solvers and make the company smarter. The problem is good coaching does not have a recipe, an algorithm if you will.  When you search for a definition of coaching with Google you don’t even find one clear definition.  Good coaching is like innovation – you recognize it when you see it but you’re not sure how to reproduce it. 

Coaches don’t just help players call the right play and avoid errors; they help them get better at whatever it is they want to do.  Coaches ask questions and help the subject improve to the point where they perform at their desired level on their own.  Coaches can improve the performance of those who already outperform them.  Think about how hard it must be to coach a player of Aaron Rodger’s skill level.  I want to say that coaching is a uniquely human activity, but I am not sure that mothers in the animal kingdom don’t coach their offspring.  But I am sure that any automated coaching solution is going to need intelligence, artificial intelligence.  So the Carnegie team is on the right track with their technical approach, but the daunting question is “Can one be a good coach without emotional cognizance?”  Based on what I see on the sidelines during the NCAA Final Four I would say “No.”

Most of the patient engagement apps that I have seen thus far avoid this whole subject by keeping “a human in the loop.”  Human-in-the-loop doesn’t scale so at this point I would say this is recognition of how hard it is to automate coaching AND how important coaching is to behavior change.  An assistant can help me know what to do, but a coach will make sure I actually do it and do it right. 

We are seeing all kinds of new wearables at CES again this year.  Most if not all of them intend to help us live our lives better through the use of the data they generate and the activities they monitor.  I hope the Carnegie Mellon team moves quickly past the assistant stage and finds the Vince Lombardi algorithm.

PS: I knowingly created a pun with the predicate noun in the title  :')  

Looking for something new in the 2016 IoT New Year’s lists

My analysis of the Year End Analyses and New Year Prognostications.

I took a new approach to reading the year end technology reviews and New Year’s prognostication lists this year. On December 31st I read all of the Best and Worst of IoT in 2015 along with the Year-in-Review analyses.  Then on January 1st I read all of the N-things-to-look-for and M-things-that-will-make-IoT-great in 2016.  I figured this phased approach would give me a better view of the consensus of the analysts along with the ability to see if the upcoming CES 2016 reports validated any of the prognostications.

So I started with the year-end analysis.  I found four themes – two measured conclusions and two familiar excuses:

  1. Home Automation is still an emerging market.
  2. Wearables continue to surprise everyone with their adoption and market growth.
  3. The lack of standards is preventing users from experiencing true IoT value.
  4. Security concerns are preventing adoption.

I haven’t checked yet but I will bet if I were to go back and look at 2013 and 2014 I would have pretty much the same list.  Home Automation has been an emerging market since I first worked on Internet-in-the-Home in 1998 at Honeywell.  Fitbit continues to be the poster child for the “surprise” of consumer desire for wearables and Apple Watch seems to be meeting expectations.  The only good excuses are those that are sustainably believable. 

“The dog ate my homework.”

“We don’t have a dog.”

The need for clearer standards and better security are definitely believable and I don’t see either need going away anytime soon.  So no one is going to get flamed for complaining about IoT standards or the need for better security.  But we still have to do our homework.  Again, not new.

Let’s look ahead to 2016.  Again, I found four themes:

  1. Wearables are going continue to be a strong performer in IoT
  2. Home Automation is going to finally go mainstream in 2016
  3. 2016 is the year that an IoT standard is going to emerge
  4. This is the year that IoT companies will make security a priority.

I admit I have done some selective summarizing here.  I read the usual discussions of Big Data and LTE-U, 3D printing and connected cars.  But in the end my analysis of the prognosticators is that they love the technology push.  They talk about how the technology will improve and then customers will adopt.  Yes, a single standard increases interoperability, but if users aren’t demanding the application it won’t increase adoption.  Security is certainly something about which users care, but I am not aware of an app or company’s going out of business because of a security breach yet.  Target executives suffered the “Big Breach” but the company doesn’t seem to have any permanent wounds.  One home automation CEO advises that consumers should look for 128-bit encryption.  I just read The Code Book and am a mathematician so I have some insight into why that is important, but I seriously doubt the average home owner even knows what a “bit” is.  128-bit encryption is a technology push. 

The technology push is easy because so many OEM’s practice it.  Look at the Samsung HDTV – SmartThings announcement for CES 2016.  This is the ultimate technology push.  If you can’t get people to buy something just give it to them.  Certainly they will like it once they use it.  Apple said the same thing about home automation with HomeKit last year.  I have no doubt that both 2016 as a year and CES as an event will have a lot of exciting new product announcements, but I do not recognize technology push as something new for IoT.

But not everyone is practicing the technology push.  I would argue that Fitbit and most of the wearables companies are winning because they are more focused on the user – they have to be.  Yes, they suffer churn and not everyone needs to count steps, but the wearables makers are doing something right because they are surprising the analysts with their success instead of their failure.  Wynn Grubb of PlumChoice has a nice article on the better approach to creating adoption in the IoT – make things customers want.  Simple, but unfortunately new for much of the IoT.

If the New Year prognostications are this year's New Year’s resolutions, then IoT companies don’t have much that is new.  No one is forecasting that one company is going to dig down and find the killer app for Home Automation.  No one is forecasting that one company is going to use IoT to dramatically reduce costs in healthcare.  No one forecasting a specific application is going to succeed in the IoT.  Many are willing to bet on infrastructure because infrastructure is a political promise – everyone believes in infrastructure.  But without users infrastructure is just window dressing – expensive window dressing.

I hope I am wrong.  I hope we don’t have just another year of standards discussions and security analysis.  I hope CES 2016 surprises us with products that we immediately realize we have to have and will go out and buy.  I hope we don’t just keep reading about the technology push. 

Here’s to focusing on solving real problems that matter with the IoT this New Year.

Wrong approach to wearables? – For sure.

The dialogue on the value of wearables in healthcare heated up recently leading to the question "Is healthcare taking the wrong approach to wearables?"  The answer is that many are taking the wrong approach -- a system-centric approach.  But others see the value in the Patient Generated Health Data and the opportunity for the devices to help patients affect their own outcomes. 

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Product Realization in the IoT: Making the complex simple.

The other day someone asked me how I define “product realization.”  The question is one I have considered recently because the problem has changed significantly over my 25 years as a product developer.  Historically "product realization" was defined in a practical sense by CEMs (Contract Electronic Manufacturers) with the leader probably being Plexus who still uses it as a tagline. CEMs and Original Equipment Manufacturers (OEMs) used the term in an operational manner which led to being defined in ISO 9001:2008.  Product Realization in that context was basically a process that anyone who could, as a single point of contact, design and manufacture a product. Expanding from manufacturing to Product Realization services was a primary CEM strategy from the late 1990’s to mid-2000’s during which many acquired design firms to expand their value to existing customers and capture new customer relationships earlier before manufacturing decision criteria became purely cost.

However, some CEMs are not using that language as much anymore.  Today their message is about information.  I suspect the change is partly because “product realization” has become dated in marketing speak, but also because of the Internet of Things (IoT) has changed the capabilities necessary to accomplish the objective.  Outsourcing and partnering in IoT ecosystems have changed the use of the term.  Today traditional Industrial Design firms like Frog, who previously were looked at as strictly creative design resources, are claiming to do product realization.

The transformation has been driven by the problems faced by branded product owners – the OEMs.  In the 1990's the primary OEM pain to be addressed was the transition from design to manufacturing created when the OEMs started to outsource manufacturing.  The CEMs addressed this by adding engineering.  Today the primary issue being addressed by OEMs is systems integration and business model transformation in the more complex connected world and the more diverse technology ecosystem.  Porter and Hepplemann recently did a deep dive on these changes in Harvard Business Review in the second of their two part IoT strategy expose.  Today an OEM has to add ongoing cloud services to their physical product so anyone who thinks of themselves as systems thinkers or design thinkers, which design firms like IDEO and Frog are, will feel empowered to say that they can do product realization because they can figure out what they need to build the system and then find and manage or find and recommend the necessary ecosystem suppliers.  “System Integrator” is the new buzzword and from Silicon Valley to Main Street we see SI’s emerging everywhere a vertical is gaining traction in the IoT. 

The challenge with the product development landscape now, as affected by IoT, is that product or solution realization has a much longer and ongoing life cycle -- it's more complex.  Whereas the traditional CEM definition more or less ended with the shipping and sale of the product, in the IoT product realization has to include the ongoing delivery of the digital service including data analytics.  The data analytics is usually not even defined at the point of product launch but can have great value if done with the right domain knowledge.  In that case the value is defined and the sold after the product realization service is sold, i.e. a post-sale add-on for the supplier.

Product realization today is more complex so the challenge for OEMs is managing the new complexity.  We see how both OEMs and those who serve OEMs have responded.  Major OEMs like GE and IBM create their own IoT platforms.  Branded holding companies like Parker-Hanifin invest in or acquire value chain suppliers to gain expertise as have traditional OEM development tool vendors like PTC and Autodesk.  The OEMs now struggle with the complexity of launching solutions in the IoT, so today a product realization firm is one that follows Gall’s Law and tenants of creating complex systems.  Today product realization is accomplished by those who make the complex simpler – but not too simple.

A sensors perspective on Wearables

The launch of the Apple Watch and recent Fitbit IPO has intensified the evaluation of wearables as an ongoing part of the Internet of Things and many are saying the honeymoon is over.  But many of the reviews I have heard or read take the wrong perspective.  As sensors wearable devices connect us to the digital world and their value  is determined by how they are applied in our everyday life.  

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