How to Survive in a World of Disruption – Innovation in Large Organizations

The team at Innovation Leader had me over to share some observations on how to survive in a world of disruption in large organizations.

It’s worth a listen – here.

.
8:30: Not everyone is an innovator
15:15: How to find and foster innovation talent in your company

How to Keep Your Job As Your Company Grows

I know a change is going to come

If you’re an early employee at a startup, one day you will wake up to find that what you worked on 24/7 for the last year is no longer the most important thing – you’re no longer the most important employee, and process, meetings, paperwork and managers and bosses have shown up. Most painfully, you’ll learn that your role in the company has to change.

I’ve seen these transitions as an investor, board member and CEO. At times they are painful to watch and difficult to manage. Early in my career I lived it as an employee, and I handled it in the worst possible way.

Here’s what I wish I had known.


I had joined MIPS Computers, my second semiconductor company, as the VP of marketing and also took on the role of the acting VP of Sales. During the first year of the company’s life, I was a fireball – relentless in creating and pursuing opportunities – getting on an airplane at the drop of a hat to fly anywhere, anytime, to get a design win. I worked with engineering to try to find product/market fit (big endian or little endian?) and get the chip designed into companies building engineering workstations – powerful personal computers, all while trying to refine how to find the right markets, customers, and sales process. I didn’t get much sleep, but I was having the time of my life.

And after a year there was good news. Our rent-a-CEO was being replaced by a permanent one. Our chip was nearing completion, and I had convinced early lighthouse customers to design it into their computers. I had done amazing things with almost no resources and got the company on the radar of every tech publication and into deals we had no right to be in. I was feeling 10 feet tall. Everything was great… until the new CEO called me in for a chat.

I don’t remember much about the details, but I do remember hearing him tell me how impressed he was with what I had accomplished so far, then immediately the visceral feeling of shock and surprise when his next words were that now the company needed to scale, and I wasn’t the right person to do that… Wait! What??

For a minute I couldn’t breathe. I felt like I had been punched in the gut. How could that be?  What do you mean I’m not the right person??? Hadn’t he just listed all the great work I had done? He acknowledged it was a lot of progress but offered that it was a flurry of disconnected tactics without a coherent strategy. No one knew what I was doing, and I couldn’t explain why I was doing it when asked. “You’re just throwing stuff against the wall. That doesn’t scale.” I was speechless. Wasn’t that what the first year of a startup was supposed to be like?

Scrambling to save my job, I regained the power of speech, and asked him if I could be the person to take the company to the next level. And to his credit (which I only appreciated years later) he agreed that while he was going to start a search, I could be a candidate for the job. And to top it off he got me a coach to help me understand what taking it to the next level meant. In preparation I remember buying all the management books I could find and reading what little literature there was at the time about how small company management transitioned into a larger one.

And herein lies the tale….
I vaguely remember going to lunch with my coach, a nice white-haired “old guy” who was trying to help me learn the skills to grow into the new job. The problem was I had shut down. Even as we were meeting, I was obsessively thinking about the change in my role, my title and my status. “I don’t get it, I did all this work, and everything was great. Why does anything have to change?”  But I never shared any of how I felt with my coach. To do this day I am really embarrassed to admit that I have no idea what my coach tried to teach me over multiple lunches and weeks. As we went to lunch, all I could think about was me and how I was being screwed. I literally paid zero attention. In my righteous anger I was unreachable.

I shouldn’t have been surprised, but yet again I was, when a month later the CEO said, that the report from the coach said, “I had a long way to go”. The company was going to hire a VP of Marketing. I was devastated.

I quit.

It’s Not About Change – It’s About Loss
If you had asked me a decade later what had been going on in my head and why I handled this so badly, I would have simply said, that: 1) I was resistant to change, and that 2) I had made this all about me and never once considered that our new CEO was rightAll true – to a point.

It took me another decade to realize if I had been really honest with myself it wasn’t about fighting change at all. Heck every day something new was happening at our startup. I was agile enough to keep up with innumerable changes and I was changing lots of things myself. It was actually about something much more personal I wouldn’t admit to myself – it was that these changes made me fear what I was losing;

  • I felt a loss of status and identity – I had been judged inadequate to continue in my role and my stature and the value of my skills and abilities had dropped.
  • I felt a loss of certainty – I was now competing to hold a job I thought was mine forever in the company. At least that’s what I thought my business card said. Now I was adrift and didn’t know what the future held.
  • I felt a loss of autonomy – Up until now I used my best judgment of what was needed and I was doing what I wanted, when I wanted it. I was fine making up a strategy on the fly from disconnected tactics. Now we were going to have plans and a strategy.
  • I felt a loss of community – we had been a small tight team who had bonded together under extreme pressure and accomplished amazing things. Now new people who knew none of that and appreciated little of it were coming in. They had little trust and empathy with us.
  • I felt the process lacked fairness – no one had warned/told me that the job I was doing needed to change over time, and no one told me what those new skills were.

What was going on?
Researchers have found there’s a link between social connection and physical discomfort within the brain. “Being hungry and being ostracized activate similar neural responses because being socially connected is necessary for survival. Although a job is often regarded as a purely economic transaction, the brain experiences the workplace first and foremost as a social system.”

Looking back over the decades it’s clear that the new CEO was right. Even though these losses triggered something primal, I did need to learn discipline, pattern recognition, time management, separating the trivial from the important and the difference between tactics and strategy. I needed to learn to grow from being a great individual contributor to being a manager and then a leader. Instead I walked away from learning any of it.

I probably added five unneeded years to my career.

What should I have done?
Today it’s understood that all startups go through a metamorphosis as they become larger companies. They go from organizations struggling for survival as they search for product/market fit, to building a repeatable and scalable business model, and then growing to profitability. And we are all hard-wired for a set number of social relationships. This mental wiring defines boundaries in growing an organization – get bigger than a certain size, and you need a different management system. The skills needed from employees differ at each stage.

What I wish I knew was that if you’re an early company employee, it’s not likely that the skills you have on day one are the skills needed as the company scales to the next level. This sentence is worth reading multiple times as no one – not the person who hired you, the VC’s or your peers -is going to tell you when you’re hired that the company will likely outgrow you. Some (like your peers or even the founders) don’t understand it, and others (the VCs) realize it’s not in their interest to let you know. The painful reality is that products change, strategies change, people change…things have to change for your company to stay in business and grow.

What should my CEO have done?
When my CEO was explaining to me how the company needed to change to grow, he was explaining facts while I was processing deeply held feelings. The changes in the organization and my role represented what I was about to lose. And when people feel they’re going to lose something deeply important, it triggers an emotional response because change feels like a threat. It’s not an excuse for my counterproductive behavior, but explains why I acted out like I did.

Startup CEOs need to think about these transitions from day one and consider how to address the real sense of loss these transitions mean to early employees.

Loss of status? It’s almost impossible to take away a title from someone, give it to someone else and still retain that employee. Think hard about whether titles need to be formal (VP of Engineering, VP of Marketing, VP of Sales, etc.) before the company finds product/market fit and/or tens of people – as you can almost guarantee that these people won’t have those roles and titles when you scale.

Loss of Certainty? Startups and VC’s have historically operated on the “I’ll deal with this later” principle in letting early employees know what happens as the company scales. The common wisdom is that no one would want to work like crazy knowing that they might not be the ones to lead as the company grows. I call this the Moses-problem – you work for years to get the tribe to the promised land – but you’re not allowed to cross over. The company needs to give formal recognition for those individuals who brought the tribe to the promised land.

Loss of Autonomy? This is the time you and your employees get to have a discussion about the next steps in their career. Do they want to be an individual contributor? Manager of people and process? Special projects? These shouldn’t be random assignments but instead, offer a roadmap of possible choices and directions.

Loss of Community? Your original hires embody the company culture. Unless you have them capture the unique aspects of the culture, it will become diluted and disappear among the new hires. Declare them cultural co-foundersHelp them understand the community is growing and they’re the ambassadors. Have them formalize it as part of a now needed on-boarding process as the company grows. And most importantly, make sure that they are celebrated as the team that got the company to where it is now.

Loss of Fairness? Just telling employees “a change is going to come” it is not sufficient. What are the new skills needed when you scale from Search to Build to Grow – from tens to hundreds and then thousands of people? How can your existing employees gain those new skills?

Lessons Learned

  • VC’s, Founders and CEOs now recognize that startups grow through different stages: Search, Build and Grow
    • They recognize that employees need different skills at each stage
    • And that some of the original employees won’t grow into the next stage
  • But while these changes make rational sense to the CEO and the board, to early employees these changes feel like a real and tangible personal loss
    • Loss of Status and Identity
    • Loss of Community
    • Loss of Autonomy
    • Loss of Certainty
    • Loss of Fairness
  • CEOs need to put processes in places to acknowledge and deal with the real sense of loss
    • These will keep early employees motivated – and retained
    • And build a stronger company
  • For employees, how you handle change will affect the trajectory of your career and possibly your net worth

This post appeared in AngelList

Driven to Distraction – the future of car safety

If you haven’t gotten a new car in a while you may not have noticed that the future of the dashboard looks like this:


That’s it. A single screen replacing all the dashboard gauges, knobs and switches. But behind that screen is an increasing level of automation that hides a ton of complexity.

At times everything you need is on the screen with a glance. At other times you have to page through menus and poke at the screen while driving. And while driving at 70mph, try to understand if you or your automated driving system is in control of your car. All while figuring out how to use any of the new features, menus or rearranged user interface that might have been updated overnight.

In the beginning of any technology revolution the technology gets ahead of the institutions designed to measure and regulate safety and standards. Both the vehicle’s designers and regulators will eventually catch up, but in the meantime we’re on the steep part of a learning curve – part of a million-person beta test – about what’s the right driver-to-vehicle interface.

We went through this with airplanes. And we’re reliving that transition in cars. Things will break, but in a few decades we’ll come out out the other side, look back and wonder how people ever drove any other way.

Here’s how we got here, what it’s going to cost us, and where we’ll end up.


Cars, Computers and Safety
Two massive changes are occurring in automobiles: 1) the transition from internal combustion engines to electric, and 2) the introduction of automated driving.

But a third equally important change that’s also underway is the (r)evolution of car dashboards from dials and buttons to computer screens. For the first 100 years cars were essentially a mechanical platform – an internal combustion engine and transmission with seats – controlled by mechanical steering, accelerator and brakes. Instrumentation to monitor the car was made up of dials and gauges; a speedometer, tachometer, and fuel, water and battery gauges.
By the 1970’s driving became easier as automatic transmissions replaced manual gear shifting and hydraulically assisted steering and brakes became standard. Comfort features evolved as well: climate control – first heat, later air-conditioning; and entertainment – AM radio, FM radio, 8-track tape, CD’s, and today streaming media. In the last decade GPS-driven navigation systems began to appear.

Safety
At the same time cars were improving, automobile companies fought safety improvements tooth and nail. By the 1970’s auto deaths in the U.S averaged 50,000 a year. Over 3.7 million people have died in cars in the U.S. since they appeared – more than all U.S. war deaths combined. (This puts auto companies in the rarified class of companies – along with tobacco companies – that have killed millions of their own customers.) Car companies argued that talking safety would scare off customers, or that the added cost of safety features would put them in a competitive price disadvantage. But in reality, style was valued over safety.

Safety systems in automobiles have gone through three generations – passive systems and two generations of active systems. Today we’re about to enter a fourth generation – autonomous systems.

Passive safety systems are features that protect the occupants after a crash has occurred. They started appearing in cars in the 1930’s. Safety glass in windshields appeared in the 1930’s in response to horrific disfiguring crashes. Padded dashboards were added in the 1950’s but it took Ralph Nader’s book, Unsafe at Any Speedto spur federally mandated passive safety features in the U.S. beginning in the 1960’s: seat belts, crumple zones, collapsible steering wheels, four-way flashers and even better windshields. The Department of Transportation was created in 1966 but it wasn’t until 1979 that the National Highway Traffic Safety Administration (NHTSA) started crash-testing cars (the Insurance Institute for Highway Safety started their testing in 1995). In 1984 New York State mandated seat belt use (now required in 49 of the 50 states.)

These passive safety features started to pay off in the mid-1970’s as overall auto deaths in the U.S. began to decline.

Active safety systems try to prevent crashes before they happen. These depended on the invention of low-cost, automotive-grade computers and sensors. For example, accelerometers-on-a-chip made airbags possible as they were able to detect a crash in progress. These began to appear in cars in the late 1980’s/1990’s and were required in 1998. In the 1990’s computers capable of real-time analysis of wheel sensors (position and slip) made ABS (anti-lock braking systems) possible. This feature was finally required in 2013.

Since 2005 a second generation of active safety features have appeared. They run in the background and constantly monitor the vehicle and space around it for potential hazards. They include: Electronic Stability Control, Blind Spot Detection, Forward Collision Warning, Lane Departure Warning, Rearview Video Systems, Automatic Emergency Braking, Pedestrian Automatic Emergency Braking, Rear Automatic Emergency Braking, Rear Cross Traffic Alert and Lane Centering Assist.

Autonomous Cars
Today, a fourth wave of safety features is appearing as Autonomous/Self-Driving features. These include Lane Centering/Auto Steer, Adaptive cruise control, Traffic jam assist, Self-parking, full self-driving. The National Highway Traffic Safety Administration (NHTSA) has adopted the six-level SAE standard to describe these vehicle automation features:

Getting above Level 2 is a really hard technical problem and has been discussed ad infinitum in other places. But what hasn’t got much attention is how drivers interact with these systems as the level of automation increases, and as the driving role shifts from the driver to the vehicle. Today, we don’t know whether there are times these features make cars less safe rather than more.

For example, Tesla and other cars have Level 2 and some Level 3 auto-driving features. Under Level 2 automation, drivers are supposed to monitor the automated driving because the system can hand back control of the car to you with little or no warning. In Level 3 automation drivers are not expected to monitor the environment, but again they are expected to be prepared to take control of the vehicle at all times, this time with notice.

Research suggests that drivers, when they aren’t actively controlling the vehicle, may be reading their phone, eating, looking at the scenery, etc. We really don’t know how drivers will perform in Level 2 and 3 automation. Drivers can lose situational awareness when they’re surprised by the behavior of the automation – asking: What is it doing now? Why did it do that? Or, what is it going to do next? There are open questions as to whether drivers can attain/sustain sufficient attention to take control before they hit something. (Trust me, at highway speeds having a “take over immediately” symbol pop up while you are gazing at the scenery raises your blood pressure, and hopefully your reaction time.)If these technical challenges weren’t enough for drivers to manage, these autonomous driving features are appearing at the same time that car dashboards are becoming computer displays.

We never had cars that worked like this. Not only will users have to get used to dashboards that are now computer displays, they are going to have understand the subtle differences between automated and semi-automated features and do so as auto makers are developing and constantly updating them. They may not have much help mastering the changes. Most users don’t read the manual, and, in some cars, the manuals aren’t even keeping up with the new features.

But while we never had cars that worked like this, we already have planes that do.
Let’s see what we’ve learned in 100 years of designing controls and automation for aircraft cockpits and pilots, and what it might mean for cars.

Aircraft Cockpits
Airplanes have gone through multiple generations of aircraft and cockpit automation. But unlike cars which are just first seeing automated systems, automation was first introduced in airplanes during the 1920s and 1930s.

For their first 35 years airplane cockpits, much like early car dashboards, were simple – a few mechanical instruments for speed, altitude, relative heading and fuel. By the late 1930’s the British Royal Air Force (RAF) standardized on a set of flight instruments. Over the next decade this evolved into the “Basic T” instrument layout – the de facto standard of how aircraft flight instruments were laid out.

Engine instruments were added to measure the health of the aircraft engines – fuel and oil quantity, pressure, and temperature and engine speed.

Next, as airplanes became bigger, and the aerodynamic forces increased, it became difficult to manually move the control surfaces so pneumatic or hydraulic motors were added to increase the pilots’ physical force. Mechanical devices like yaw dampers and Mach trim compensators corrected the behavior of the plane.

Over time, navigation instruments were added to cockpits. At first, they were simple autopilots to just keep the plane straight and level and on a compass course. The next addition was a radio receiver to pick up signals from navigation stations. This was so pilots could set the desired bearing to the ground station into a course deviation display, and the autopilot would fly the displayed course.

In the 1960s, electrical systems began to replace the mechanical systems:

  • electric gyroscopes (INS) and autopilots using VOR (Very High Frequency Omni-directional Range) radio beacons to follow a track
  • auto-throttle – to manage engine power in order to maintain a selected speed
  • flight director displays – to show pilots how to fly the aircraft to achieve a preselected speed and flight path
  • weather radars – to see and avoid storms
  • Instrument Landing Systems – to help automate landings by giving the aircraft horizontal and vertical guidance.

By 1960 a modern jet cockpit (the Boeing 707) looked like this:

While it might look complicated, each of the aircraft instruments displayed a single piece of data. Switches and knobs were all electromechanical.

Enter the Glass Cockpit and Autonomous Flying
Fast forward to today and the third generation of aircraft automation. Today’s aircraft might look similar from the outside but on the inside four things are radically different:

  1. The clutter of instruments in the cockpit has been replaced with color displays creating a “glass cockpit”
  2. The airplanes engines got their own dedicated computer systems – FADEC (Full Authority Digital Engine Control) – to autonomously control the engines
  3. The engines themselves are an order of magnitude more reliable
  4. Navigation systems have turned into full-blown autonomous flight management systems

So today a modern airplane cockpit (an Airbus 320) looks like this:

Today, airplane navigation is a real-world example of autonomous driving – in the sky. Two additional systems, the Terrain Awareness and Warning Systems (TAWS) and Traffic Condition Avoidance System (TCAS) gave pilots a view of what’s underneath and around them dramatically increasing pilots’ situation awareness and flight safety. (Autonomy in the air is technically a much simpler problem because in the cruise portion of flight there are a lot less things to worry about in the air than in a car.)

Navigation in planes has turned into autonomous “flight management.” Instead of a course deviation dial, navigation information is now presented as a “moving map” on a display showing the position of navigation waypoints, by latitude and longitude. The position of the airplane no longer uses ground radio stations, but rather is determined by Global Positioning System (GPS) satellites or autonomous inertial reference units. The route of flight is pre-programmed by the pilot (or uploaded automatically) and the pilot can connect the autopilot to autonomously fly the displayed route. Pilots enter navigation data into the Flight Management System, with a keyboard. The flight management system also automates vertical and lateral navigation, fuel and balance optimization, throttle settings, critical speed calculation and execution of take-offs and landings.

Automating the airplane cockpit relieved pilots from repetitive tasks and allowed less skilled pilots to fly safely. Commercial airline safety dramatically increased as the commercial jet airline fleet quadrupled in size from ~5,000 in 1980 to over 20,000 today. (Most passengers today would be surprised to find out how much of their flight was flown by the autopilot versus the pilot.)

Why Cars Are Like Airplanes
And here lies the connection between what’s happened to airplanes with what is about to happen to cars.

The downside of glass cockpits and cockpit automation means that pilots no longer actively operating the aircraft but instead monitor it. And humans are particularly poor at monitoring for long periods. Pilots have lost basic manual and cognitive flying skills because of a lack of practice and feel for the aircraft. In addition, the need to “manage” the automation, particularly when involving data entry or retrieval through a key-pad, increased rather than decreased the pilot workload. And when systems fail, poorly designed user interfaces reduce a pilot’s situational awareness and can create cognitive overload.

Today, pilot errors — not mechanical failures– cause at least 70-80% of commercial airplane accidents. The FAA and NTSB have been analyzing crashes and have been writing extensively on how flight deck automation is affecting pilots. (Crashes like Asiana 214 happened when pilots selected the wrong mode on a computer screen.) The FAA has written the definitive document how people and automated systems ought to interact.

In the meantime, the National Highway Traffic Safety Administration (NHTSA) has found that 94% of car crashes are due to human error – bad choices drivers make such as inattention, distraction, driving too fast, poor judgment/performance, drunk driving, lack of sleep.

NHTSA has begun to investigate how people will interact with both displays and automation in cars. They’re beginning to figure out:

  • What’s the right way to design a driver-to-vehicle interface on a screen to show:
    • Vehicle status gauges and knobs (speedometer, fuel/range, time, climate control)
    • Navigation maps and controls
    • Media/entertainment systems
  • How do you design for situation awareness?
    • What’s the best driver-to-vehicle interface to display the state of vehicle automation and Autonomous/Self-Driving features?
    • How do you manage the information available to understand what’s currently happening and project what will happen next?
  • What’s the right level of cognitive load when designing interfaces for decisions that have to be made in milliseconds?
    • What’s the distraction level from mobile devices? For example, how does your car handle your phone? Is it integrated into the system or do you have to fumble to use it?
  • How do you design a user interface for millions of users whose age may span from 16-90; with different eyesight, reaction time, and ability to learn new screen layouts and features?

Some of their findings are in the document Human-centric design guidance for driver-vehicle interfaces. But what’s striking is that very little of the NHSTA documents reference the decades of expensive lessons that the aircraft industry has learned. Glass cockpits and aircraft autonomy have traveled this road before. Even though aviation safety lessons have to be tuned to the different reaction times needed in cars (airplanes fly 10 times faster, yet pilots often have seconds or minutes to respond to problems, while in a car the decisions often have to be made in milliseconds) there’s a lot they can learn together. Aviation has gone 9 years in the U.S. with just one fatality, yet in 2017 37,000 people died in car crashes in the U.S.

There Are No Safety Ratings for Your Car As You Drive
In the U.S. aircraft safety has been proactive. Since 1927 new types aircraft (and each sub-assembly) are required to get a type approval from the FAA before it can be sold and be issued an Airworthiness Certificate.

Unlike aircraft, car safety in the U.S. has been reactive. New models don’t require a type approval, instead each car company self-certifies that their car meets federal safety standards. NHTSA waits until a defect has emerged and then can issue a recall.

If you want to know how safe your model of car will be during a crash, you can look at the National Highway Traffic Safety Administration (NHTSA) New Car Assessment Program (NCAP) crash-tests, or the Insurance Institute for Highway Safety (IIHS) safety ratings. Both summarize how well the active and passive safety systems will perform in frontal, side, and rollover crashes. But today, there are no equivalent ratings for how safe cars are while you’re driving them. What is considered a good vs. bad user interface and do they have different crash rates? Does the transition from Level 1, 2 and 3 autonomy confuse drivers to the point of causing crashes? How do you measure and test these systems? What’s the role of regulators in doing so?

Given the NHTSA and the FAA are both in the Department of Transportation (DoT), It makes you wonder whether these government agencies actively talk to and collaborate with each other and have integrated programs and common best practices. And whether they have extracted best practices from the NTSB. And from the early efforts of Tesla, Audi, Volvo, BMW, etc., it’s not clear they’ve looked at the airplane lessons either.

It seems like the logical thing for NHTSA to do during this autonomous transition is 1) start defining “best practices” in U/I and automation safety interfaces and 2) to test Level 2-4 cars for safety while you drive (like the crash tests but for situational awareness, cognitive load, etc. in a set of driving scenarios. (There are great university programs already doing that research.)

However, the DoT’s Automated Vehicles 3.0 plan moves the agency further from owning the role of “best practices” in U/I and automation safety interfaces. It assumes that car companies will do a good job self-certifying these new technologies. And has no plans for safety testing and rating these new Level 2-4 autonomous features.

(Keep in mind that publishing best practices and testing for autonomous safety features is not the same as imposing regulations to slow down innovation.)

It looks like it might take an independent agency like the SAE to propose some best practices and ratings. (Or the slim possibility that the auto industry comes together and set defacto standards.)

The Chaotic Transition
It took 30 years, from 1900 to 1930, to transition from horses and buggies in city streets to automobiles dominating traffic. During that time former buggy drivers had to learn a completely new set of rules to control their cars. And the roads in those 30 years were a mix of traffic – it was chaotic.
In New York City the tipping point was 1908 when the number of cars passed the number of horses. The last horse-drawn trolley left the streets of New York in 1917. (It took another decade or two to displace the horse from farms, public transport and wagon delivery systems.) Today, we’re about to undergo the same transition.

Cars are on the path for full autonomy, but we’re seeing two different approaches on how to achieve Level 4 and 5 “hands off” driverless cars. Existing car manufacturers, locked into the existing car designs, are approaching this step-wise – adding additional levels of autonomy over time – with new models or updates; while new car startups (Waymo, Zoox, Cruise, etc.) are attempting to go right to Level 4 and 5.

We’re going to have 20 or so years with the roads full of a mix of millions of cars – some being manually driven, some with Level 2 and 3 driver assistance features, and others autonomous vehicles with “hands-off” Level 4 and 5 autonomy. It may take at least 20 years before autonomous vehicles become the dominant platforms. In the meantime, this mix of traffic is going to be chaotic. (Some suggest that during this transition we require autonomous vehicles to have signs in their rear window, like student drivers, but this time saying, “Caution AI on board.”)

As there will be no government best practices for U/I or scores for autonomy safety, learning and discovery will be happening on the road. That makes the ability for car companies to have over-the-air updates for both the dashboard user interface and the automated driving features essential. Incremental and iterative updates will add new features, while fixing bad ones. Engaging customers to make them realize they’re part of the journey will ultimately make this a successful experiment.

My bet is much like when airplanes went to glass cockpits with increasingly automated systems, we’ll create new ways drivers crash their cars, while ultimately increasing overall vehicle safety.

But in the next decade or two, with the government telling car companies “roll your own”, it’s going to be one heck of a ride.

Lessons Learned

  • There’s a (r)evolution as car dashboards move from dials and buttons to computer screens and the introduction of automated driving
    • Computer screens and autonomy will both create new problems for drivers
    • There are no standards to measure the safety of these systems
    • There are no standards for how information is presented
  • Aircraft cockpits are 10 to 20 years ahead of car companies in studying and solving this problem
    • Car and aircraft regulators need to share their learnings
    • Car companies can reduce crashes and deaths if they look to aircraft cockpit design for car user interface lessons
  • The Department of Transportation has removed barriers to the rapid adoption of autonomous vehicles
    • Car companies “self-certify” whether their U/I and autonomy are safe
    • There are no equivalents of crash safety scores for driving safety with autonomous features
  • Over-the-air updates for car software will become essential
    • But the downside is they could dramatically change the U/I without warning
  • On the path for full autonomy we’ll have three generations of cars on the road
    • The transition will be chaotic, so hang on it’s going to a bumpy ride, but the destination – safety for everyone on the road – will be worth it

Why Founders Need a Moral Compass

I’ve been thinking why the ethical boundaries of todays founder/VC interactions feel so different then they did when I was an entrepreneur. I’ve written about the root causes in an HBR article here and an expanded version here. Worth a read.

Stanford eCorner captured a few minutes of what I’ve been thinking in the video below.

If you can’t see the video click here

What Your Startup Needs to Know About Regulated Markets

Often the opposite of disruption is the status quo.

If  you’re a startup trying to disrupt an existing business you need to read The Fixer by Bradley Tusk and Regulatory Hacking by Evan Burfield. These two books, one by a practitioner, the other by an investor, are must-reads.

The Fixer is 1/3rd autobiography, 1/3rd case studies, and 1/3rd a “how-to” manual. Regulatory Hacking is closer to a “step-by-step” textbook with case studies.

Here’s why you need to read them.


One of the great things about teaching has been seeing the innovative, unique, groundbreaking and sometimes simply crazy ideas of my students. They use the Business Model (or Mission Model) Canvas to keep track of their key hypotheses and then rapidly test them by talking to customers and iterating their Minimal Viable Products. This allows them to quickly find product/market fit.

Except when they’re in a regulated market.

Regulation
All businesses have regulations to follow –  paying taxes, incorporating the company, complying with financial reporting. And some have to ensure that there are no patents or blocking patents.  But regulated markets are different. Regulated marketplaces are ones that have significant government regulation to promote (ostensibly) the public interest. In theory regulations exist to protect the public interest for the benefit of all citizens. A good example is the regulations the FDA (Food and Drug Administration) have in place for approving new drugs and medical devices.

In a regulated market, the government controls how products and services are allowed to enter the market, what prices may be charged, what features the product/service must have, safety of the product, environmental regulations, labor laws, domestic/foreign content, etc.

In the U.S. regulation happens on three levels:

  • federal laws that are applicable across the country are developed by Federal government in Washington
  • state laws that are applicable in one state are imposed by state government
  • local city and county laws come from local government.

Federal Government
In the U.S. the national government has regulatory authority over inter-state commerce, foreign trade and other business activities of national scope and interest. Congress decides what things needs to be regulated and passes laws that determine those regulations. Congress often does not include all the details needed to explain how an individual, business, state or local government, or others might follow the law. In order to make the laws work on a day-to-day level, Congress authorizes certain government agencies to write the regulations which set the specific requirements about what is legal and what isn’t.  The regulatory agencies then oversee these requirements.

In the U.S. startups might run into an alphabet soup of federal regulatory agencies, for example; ATF, CFPB, DEA, EPA, FAA, FCC, FDA, FDIC, FERC, FTC, OCC, OSHA, SEC. These agencies exist because Congress passed laws.

States
In addition to federal laws, each State has its own regulatory environment that applies to businesses operating within the state in areas such as land-use, zoning, motor vehicles, state banking, building codes, public utilities, drug laws, etc.

Cities/Counties
Finally, local municipalities (cities, counties) may have local laws and regulatory agencies or departments like taxi commissions, zoning laws, public safety, permitting, building codes, sanitation, drug laws, etc.

A Playbook for Entering a Regulated Market
Startup battles with regulatory agencies – like Uber with local taxi licensing laws, AirBnB with local zoning laws, and Tesla with state dealership licensing – are legendary. Each of these is an example of a startup disrupting regulated markets.

There’s nothing magical about dealing with regulated markets. However, every regulated market has its own rules, dynamics, language, players, politics, etc. And they are all very different from the business-to-consumer or business-to-business markets most founders and their investors are familiar with.

How do you know you’re in a regulated market? It’s simple– ask yourself two questions:

  • Can I do anything I want or are there laws and regulations that might stop me or slow me down?
  • Are there incumbents who will view us as a threat to the status quo? Can they use laws and regulations to impede our growth?

Diagram Your Business Model
The best way to start is by drawing a business model canvas. In the customer segments box, you’re going to discover that there may be 5, 10 or more different players: users, beneficiaries, stakeholders, payers, saboteur, rent seeker, influencers, bureaucrats, politician, regulators. As you get out of the building and start talking to people you’ll discover more and more players.

Instead of lumping them together, each of these users, beneficiaries, stakeholders, payers, saboteur, rent seekers, etc. require a separate Value Proposition Canvas. This is where you start figuring out not only their pains, gains and jobs to be done, but what products/services solve those pains and gains. When you do that, you’ll discover that the interests of your product’s end user versus a regulator versus an advocacy group, key opinion leaders or a politician, are radically different. For you to succeed you need to understand all of them.

One of the critical things to understand is how the regulatory process works. For example, do you just fill out an online form and pay a $50 fee with your credit card and get a permit? Or do you need to spend millions of dollars and years running clinical trials to get FDA clearance and approval? And are these approvals good in every state? In every country? What do you need to do to sell worldwide?

Find the Saboteurs and Rent Seekers
One of the unique things about entering a regulated market is that the incumbents have gotten there first and have “gamed the system” in their favor. Rent seekers are individuals or organizations with successful existing business models who look to the government and regulators as their first line of defense against innovative competition. They use government regulation and lawsuits to keep out new entrants that might threaten their business models. They use every argument from public safety to lack of quality or loss of jobs to lobby against the new entrants. Rent seekers spend money to increase their share of an existing market instead of creating new products or markets but create nothing of value.

These barriers to new innovative startups are called economic rentExamples of economic rent include state automobile franchise laws, taxi medallion laws, limits on charter schools, cable company monopolies, patent trolls, bribery of government officials, corruption and regulatory capture.

Rent seeking lobbyists go directly to legislative bodies (Congress, State Legislatures, City Councils) to persuade government officials to enact laws and regulations in exchange for campaign contributions, appeasing influential voting blocks or future jobs in the regulated industry. They also use the courts to tie up and exhaust a startup’s limited financial resources. Lobbyists also work through regulatory bodies like the FCCSECFTC, Public Utility, Taxi, or Insurance Commissions, School Boards, etc.

Although most regulatory bodies are initially created to protect the public’s health and safety, or to provide an equal playing field, over time the very people they’re supposed to regulate capture the regulatory agencies. Rent Seekers take advantage of regulatory capture to protect their interests against the new innovators.

Understand Who Pays
For revenue streams figure out who’s going to pay. Is it the end user? An insurer? Some other third party?  If it’s the government, hang on to your seat because you now have to deal with government procurement and/or reimbursement. These payers need a Value Proposition Canvas as well.

Customer Relationships
For Customer Relationships, figuring out how to “Get, Keep and Grow” customers in a regulated market is a lot more complex than simply “Let’s buy some Google Adwords”. Market entry in a regulated market often has many more moving parts and is much costlier than a traditional market, requiring lobbyists, key opinion leaders, political donations, advocacy groups, and grassroots and grasstops campaigns, etc.

Diagram the Customer Segment Relationships
Start diagraming out the relationships of all the customer segments. Who influences who? How do they interconnect? What laws and regulations are in your way for deployment and scale? How powerful are each of the players? For the politicians, what are their public positions versus actual votes and performance. Follow the money. If an elected official’s major donor is organization x, you’re not going to be able to convince them with a cogent argument.

The book Regulatory Hacking calls this diagram the Power Map. As an example, this is a diagram of the multiple beneficiaries and stakeholders that a software company developing math software for middle school students has to navigate. Your diagram may be more complex.  There is no possible way you can draw this on day one of your startup. You’ll discover these players as you get out of the building and start filling out your value proposition canvases.

Diagram the Competition
Next, draw a competitive Petal diagram of competitors and adjacent market players.  Who’s already serving the users you’re targeting? Who are the companies you’re disrupting?

I’ve always thought of my startup as the center of the universe. So, put your company in the center of the slide like this.

In this example the startup is creating a new category – a lifelong learning network for entrepreneurs. To indicate where their customers for this new market would come from they drew the 5 adjacent market segments they believed their future customers were in today: corporate, higher education, startup ecosystem, institutions, and adult learning. To illustrate this they drew these adjacent markets as a cloud surrounding their company. (Unlike the traditional X/Y graph you can draw as many adjacent market segments as you’d like.)

Fill in the market spaces with the names of the companies that are representative players in each of the adjacent markets.

Strategy diagram
Finally, draw your strategy diagram – how will you build a repeatable and scalable sales process? What regulatory issues need to be solved? In what order?  What is step 1? Then step 2? For example, beg for forgiveness or ask for permission? How do you get regulators who don’t see a need to change to move? And do so in your lifetime? How do you get your early customers to advocate on your behalf?

I sketched out a sample diagram of some of things to think about in the figure below. Both The Fixer and Regulatory Hacking give great examples of regulatory pitfalls, problems and suggested solutions.

Politicians
If you read Tusk’s book The Fixer you come away with the view that the political process in the U.S. follows the golden rule – he who has the gold makes the rules. It is a personal tale of someone who was deep inside politics – Tusk was deputy governor of Illinois, Mike Bloomberg’s campaign manager, Senator Charles Schumer’s communication director, and ran Uber’s first successful campaign to get regulatory approval in New York. And he is as cynical about politicians as one can get. On the other hand, Regulatory Hacking by is written by someone who understands Washington—but still needs to work there.

Read both books.

Lessons Learned

  • Regulated markets have different rules and players than traditional Business-to-Business or Business-to-Consumer markets
  • Entering a regulated market should be a strategy not a disconnected set of tactics
    • You need to understand the Laws and Regulations on the federal, state and local levels
    • You and your board need to be in sync about the costs and risks of entering these markets
    • Strategic choices include: asking for permission versus forgiveness, public versus private battles
  • Most early stage startups don’t have the regulatory domain expertise in-house. Go get outside advice at each step

The Apple Watch – Tipping Point Time for Healthcare

I don’t own an Apple Watch. I do have a Fitbit. But the Apple Watch 4 announcement intrigued me in a way no other product has since the original IPhone. This wasn’t just another product announcement from Apple. It heralded the U.S. Food and Drug Administration’s (FDA) entrance into the 21stcentury. It is a harbinger of the future of healthcare and how the FDA approaches innovation.

Sooner than people think, virtually all home and outpatient diagnostics will be performed by consumer devices such as the Apple Watch, mobile phones, fitness trackers, etc. that have either become FDA cleared as medical devices or have apps that have received FDA clearance. Consumer devices will morph into medical grade devices, with some painful and well publicized mistakes along the way.

Let’s see how it turns out for Apple.


Smartwatches are the apex of the most sophisticated electronics on the planet. And the Apple Watch is the most complex of them all. Packed inside a 40mm wide, 10 mm deep package is a 64-bit computer, 16gbytes of memory, Wi-Fi, NFC, cellular, Bluetooth, GPS, accelerometer, altimeter, gyroscope, heart rate sensor, and an ECG sensor – displaying it all on a 448 by 368 OLED display.
When I was a kid, this was science fiction.  Heck, up until its first shipment in 2015, it was science fiction.

But as impressive as its technology is, the Apple’s smartwatch has been a product looking for a solution. At first, positioned as a fashion statement, it seemed like the watch was actually an excuse to sell expensive wristbands. Subsequent versions focused on fitness and sports – the watch was like a Fitbit– plus the ability to be annoyed by interruptions from your work. But now the fourth version of the Watch might have just found the beginnings of “gotta have it” killer applications – healthcare – specifically medical diagnostics and screening.

Healthcare on Your Wrist
Large tech companies like Google, Amazon, Apple recognize that the  multi-trillion dollar health care market is ripe for disruption and have poured billions of dollars into the space. Google has been investing in a broad healthcare portfolio, Amazon has been investing in pharmacy distribution and Apple…? Apple has been focused on turning the Apple Watch into the future of health screening and diagnostics.

Apples latest Watch – with three new healthcare diagnostics and screening apps – gives us a glimpse into what the future of healthcare diagnostics and screening could look like.

The first new healthcare app on the Watch is Fall Detection. Perhaps you’ve seen the old commercials where someone falls and can’t get up, and has a device that calls for help. Well this is it – built into the watch. The watch’s built-in accelerometer and gyroscope analyze your wrist trajectory and impact acceleration to figure out if you’ve taken a hard fall. You can dismiss the alert, or have it call 911. Or, if you haven’t moved after a minute, it can call emergency services, and send a message along with your location.

If you’re in Apple’s current demographic you might think, “Who cares?” But if you have an aged parent, you might start thinking, “How can I get them to wear this watch?”

The second new healthcare app also uses the existing optical sensor in the watch and running in the background, gathers heart data and has an algorithm that can detect irregular heart rhythms. If it senses something is not right, up pops up an alert. A serious and common type of irregular heart rhythm is atrial fibrillation (AFib). AFib happens when the atria—the top two chambers of the heart get out of sync, and instead of beating at a normal 60 beats a minute it may quiver at 300 beats per minute.

This rapid heartbeat allows blood to pool in the heart, which can cause clots to form and travel to the brain, causing a stroke. Between 2.7 and 6.1 million people in the US have AFib (2% of people under 65 have it, while 9% of people over 65 years have it.) It puts ~750,000 people a year in the hospital and contributes to ~130,000 deaths each year. But if you catch atrial fibrillation early, there’s an effective treatment — blood thinners.

If your watch gives you an irregular heart rhythm alert you can run the third new healthcare app – the Electrocardiogram.

The Electrocardiogram (ECG or EKG) is a visual presentation of whether your heart is working correctly. It records the electrical activity of the heart and shows doctors the rhythm of heartbeats, the size and position of the chambers of the heart, and any damage to the heart’s muscle. Today, ECGs are done in a doctor’s office by having you lie down, and sticking 10 electrodes to your arms, legs and chest. The heart’s electrical signals are then measured from twelve angles (called “leads”).

With the Apple Watch, you can take an ECG by just putting your finger on the crown for 30 seconds. To make this work Apple has added two electrodes (the equivalent of a single lead), one on the back of the watch and another on the crown. The ECG can tell you that you may have atrial fibrillation (AFib) and suggest you see a doctor. As the ECG is saved in a PDF file (surprisingly it’s not also in the HL7’s FHIR Format), you can send it to your doctor, who may decide no visit is necessary.

These two apps, the Electrocardiogram and the irregular heart rhythms, are serious health screening tools. They are supposed to ship in the U.S. by the end of 2018. By the end of next year, they can be on the wrists of tens of millions of people.

The question is are they are going to create millions of unnecessary doctors’ visits from unnecessarily concerned users or are they going to save thousands of lives?  My bet is both – until traditional healthcare catches up with the fact that in the next decade screening devices will be in everyone’s hands (or wrists.)

Apple and The FDA – Clinical Trials
In the U.S. medical devices, drugs and diagnostics are regulated by the Food and Drug Administration – the FDA. What’s unique about the Apple Watch is that both the Electrocardiogram and the irregular heart rhythms apps required Apple to get clearance from the FDA. This is a very big deal.

The FDA requires evidence that medical devices do what they claim. To gather that evidence companies enroll volunteers in a study – called a clinical trial – to see if the device does what the company thinks it will.

Stanford University has been running a clinical trial on irregular heart rhythms for Apple since 2017 with a completion date in 2019. The goal is to see if an irregular pulse notification is really atrial fibrillation, and how many of those notified contacted a doctor within 90 days. (The Stanford study appears to be using previous versions of the Apple Watch with just the optical sensor and not the new ECG sensors. They used someone else’s wearable heart monitor to detect the Afib.)

Nov 1 2018 Update – the design of the Stanford Apple Watch study published here

To get FDA clearance, Apple reportedly submitted two studies to the FDA (so far none of the data has been published or peer reviewed). In one trial with 588 people, half of whom were known to have AFib and the other half of whom were healthy, the app couldn’t read 10% of the recordings. But for the other 90%, it was able to identify over 98% of the patients who had AFib, and over 99% of patients that had healthy heart rates.

The second data set Apple sent the FDA was part of Stanford’s Apple Heart Study. The app first identified 226 people with an irregular heart rhythm. The goal was to see how well the Apple Watch could pick up an event that looked like atrial fibrillation compared to a wearable heart monitor. The traditional monitors identified that 41 percent of people had an atrial fibrillation event. In 79 percent of those cases, the Apple app also picked something up.

This was good enough for the FDA.

The FDA – Running Hard to Keep Up With Disruption
And “good enough” is a big idea for the FDA. In the past the FDA was viewed as inflexible and dogmatic by new companies while viewed as insufficiently protective by watchdog organizations.

For the FDA this announcement was as important for them as it was for Apple.

The FDA has to adjudicate between a whole host of conflicting constituents and priorities. Its purpose is to make sure that drugs, devices, diagnostics, and software products don’t harm thousands or even millions of people so the FDA wants a process to make sure they get it right. This is a continual trade-off between patient safety, good enough data and decision making, and complete clinical proof. On the other hand, for a company, a FDA clearance can be worth hundreds of millions or even billions of dollars. And a disapproval or delayed clearance can put a startup out of business. Finally, the rate of change of innovation for medical devices, diagnostics and digital health has moved faster than the FDA’s ability to adapt its regulatory processes. Frustrated by the FDA’s 20th century processes for 21st century technology, companies hired lobbyists to force a change in the laws that guide the FDA regulations.

So, the Apple announcement is a visible signal in Washington that the FDA is encouraging innovation. In the last two years the FDA has been trying to prove it could keep up with the rapid advancements in digital health, devices and diagnostics- while trying to prevent another Theranos.

Since the appointment of the new head of the FDA, there has been very substantial progress in speeding up mobile and digital device clearances with new guidelines and policies. For example, in the last year the FDA announced its Pre-Cert pilot program which allows companies making software as a medical device to build products without each new device undergoing the FDA clearance process. The pilot program allowed nine companies, including Apple, to begin developing products (like the Watch) using this regulatory shortcut. (The FDA has also proposed new rules for clinical support software that say if doctors can review and understand the basis of the software’s decision, the tool does not have to be regulated by the FDA.)

This rapid clearance process as the standard – rather than the exception – is a sea-change for the FDA. It’s close to de-facto adopting a Lean decision-making process and rapid clearances for things that minimally affect health. It’s how China approaches approvals and will allow U.S. companies to remain competitive in an area (medical devices) where China has declared the intent to dominate.

Did Apple Cut in Front of the Line?
Some have complained that the FDA has been too cozy with Apple over this announcement.

Apple got its two FDA Class II clearances through what’s called a “de novo” pathway, meaning Apple claimed these features were the first of its kind. (It may be the first one built into the watch, but it’s not the first Apple Watch ECG app cleared by the FDA – AliveCor, got over-the-counter-clearance in 2014 and Cardiac Designs in 2013.) Critics said that the De Novo process should only be used where there is no predicate (substantial equivalence to an already cleared device.) But Apple cited at least one predicate, so if they followed the conventional 510k approval process, that should have taken at least 100 days. Yet Apple got two software clearances in under 30 days, which uncannily appeared the day before their product announcement.

To be fair to Apple, they were likely holding pre-submission meetings with the FDA for quite some time, perhaps years. One could speculate that using the FDA Pre-Cert pilot program they consulted on the design of the clinical trial, trial endpoints, conduct, inclusion and exclusion criteria, etc. This is all proper medical device company thinking and exactly how consumer device companies need to approach and work with the FDA to get devices or software cleared. And it’s exactly how the FDA should be envisioning its future.

Given Apple sells ~15 million Apple Watches a year, the company is about to embark on a public trial at massive scale of these features – with its initial patient population at the least risk for these conditions. It will be interesting to see what happens. Will overly concerned 20- and 30-year-olds flood doctors with false positives? Or will we be reading about lives saved?

Why most consumer hardware companies aren’t medical device and diagnostic companies
Historically consumer electronics companies and medical device and diagnostic companies were very different companies. In the U.S. medical device and diagnostic products require both regulatory clearance from the FDA and reimbursement approval by different private and public insurers to get paid for the products.

These regulatory and reimbursement agencies have very different timelines and priorities than for-profit companies. Therefore, to get FDA clearance a critical part of a medical device company is spent building a staff and hiring consultants such as clinical research organizations who can master and navigate FDA regulations and clinical trials.

And just because a company gets the FDA to clear their device/diagnostic/software doesn’t mean they’ll get paid for it. In the U.S. medical devices are reimbursed by private insurance companies (Blue Cross/Blue Shield, etc.) and/or the U.S. government via Centers for Medicare & Medicaid Services (CMS). Getting these clearances to get the product covered, coded and paid is as hard as getting the FDA clearance, often taking another 2-3 years. Mastering the reimbursement path requires a company to have yet another group of specialists conduct expensive clinical cost outcomes studies.

The Watch announcement telegraphed something interesting about Apple – they’re one of the few consumer products company to crack the FDA clearance process (Philips being the other). And going forward, unless these new apps are a disaster, it opens the door for them to add additional FDA-cleared screening and diagnostic tools to the watch (and by extension a host of AI-driven imaging diagnostics (melanoma detection, etc.) to the iPhone.) This by itself is a key differentiator for the Watch as a healthcare device.

The other interesting observation: Unlike other medical device companies, Apple’s current Watch business model is not dependent on getting insurers to pay for the watch. Today consumers pay directly for the Watch. However, if the Apple Watch becomes a device eligible for reimbursement, there’s a huge revenue upside for Apple. When and if that happens, your insurance would pay for all or part of an Apple Watch as a diagnostic tool.

(After running cost outcome studies, insurers believe that preventative measures like staying fit brings down their overall expense for a variety of conditions. So today some life insurance companies are mandating the use of an activity tracker like Apple Watch.)

The Future of SmartWatches in Healthcare
Very few companies (probably less than five) have the prowess to integrate sensors, silicon and software with FDA regulatory clearance into a small package like the Apple Watch.

So what else can/will Apple offer on the next versions of the Watch? After looking through Apple’s patents, here’s my take on the list of medical diagnostics and screening apps Apple may add.

Sleep Tracking and Sleep Apnea Detection
Compared to the Fitbit, the lack of a sleep tracking app on the Apple Watch is a mystery (though third-party sleep apps are available.) Its absence is surprising as the Watch can theoretically do much more than just sleep tracking – it can potentially detect Sleep Apnea. Sleep apnea happens when you’re sleeping, and your upper airway becomes blocked, reducing or completely stopping air to your lungs. This can cause a host of complications including Type 2 diabetes, high blood pressure, liver problems, snoring, daytime fatigueToday diagnosing sleep apnea often requires an overnight stay in a sleep study clinicSleep apnea screening doesn’t appear to require any new sensors and would be a great app for the Watch. Perhaps the app is missing because you have to take the watch off and recharge it every night?

Pulse oximetry
Pulse oximetry is a test used to measure the oxygen level (oxygen saturation) of the blood. The current Apple Watch can already determine how much oxygen is contained in your blood based on the amount of infrared light it absorbs. But for some reason Apple hasn’t released this feature – FDA regulations? Inconsistent readings?  Another essential Watch health app that may or may not require any new sensors.

Respiration rate
Respiration rate (the number of breaths a person takes per minute) along with blood pressure, heart rate and temperature make up a person’s vital signs. Apple has a patent for this watch feature but for some reason hasn’t released it – FDA regulations?  Inconsistent readings?  Another essential Watch health app that doesn’t appear to require any new sensors.

Blood Pressure
About 1/3rd of Americans have high blood pressure. High blood pressure increases the risk of heart disease and stroke. It often has no warning signs or symptoms. Many people do not know they have it and only half of those have it under control. Traditionally measuring blood pressure requires a cuff on the arm and produces a single measurement at a single point in time. We’ve never had the ability to continually monitor a person’s blood pressure under stress or sleep. Apple filed two patents in 2017 to measure blood pressure by holding the watch against your chest. This is tough to do, but it would be another great health app for the Watch that may or may not require any new sensors.

Sunburn/UV Detector
Apple has patented a new type of sensor – a sunscreen detector to let you know what exposed areas of the skin of may be at elevated UV exposure risk. I’m not big on this, but the use of ever more powerful sunscreens has quadrupled, while at the same time, the incidence of skin cancers has also quadrupled, so there may be a market here.

Parkinson’s Disease Diagnosis and Monitoring
Parkinson’s Disease is a brain disorder that leads to shaking, stiffness, and difficulty with walking, balance, and coordination. It affects 1/% of people over 60. Today, there is no diagnostic test for the disease (i.e. blood test, brain scan or EEG). Instead, doctors look for four signs: tremor, rigidity, Bradykinesia/akinesia and Postural instability. Today patients have to go to a doctor for tests to rate the severity of their symptoms and keep a diary of their symptoms.

Apple added a new “Movement Disorder API” to its ResearchKit framework that supports movement and tremor detection. It allows an Apple Watch to continuously monitor for Parkinson’s disease symptoms; tremors and Dyskinesia, a side-effect of treatments for Parkinson’s that causes fidgeting and swaying motions in patients. Researchers have built a prototype Parkinson’s detection app on top of it. It appears that screening for Parkinson’s would not require any new sensors – but likely clinical trials and FDA clearance – and would be a great app for the Watch.

Glucose Monitoring
More than 100 million U.S. adults live with diabetes or prediabetes. If you’re a diabetic, monitoring your blood glucose level is essential to controlling the disease. However, it requires sticking your finger to draw blood multiple times a day. The holy grail of glucose monitoring has been a sensor that can detect glucose levels through the skin. This sensor has been the graveyard of tons of startups that have crashed and burned pursuing this. Apple has a patent application that looks suspiciously like a non-invasive glucose monitoring sensor for the Apple Watch. This is a really tough technical problem to solve, and even if the sensor works, there would be a long period of clinical trials for FDA clearance, but this app would be a game changer for diabetic patients – and Apple – if they can make it happen.

Sensor and Data Challenges
With many of these sensors just getting a signal is easy. Correlating that particular signal to an underlying condition and avoiding being confounded by other factors is what makes achieving medical device claims so hard.

As medical grade data acquisition becomes possible, continuous or real time transmission will store and report baseline data on tens of millions of “healthies” that will be vital in training the algorithms and eventually predicting disease earlier. This will eventually enable more accurate diagnostics on less data, and make the data itself – especially the transition from healthy to diseased – incredibly valuable.

However, this sucks electrons out of batteries and plays on the edge electrical design and the laws of physics, but Apple’s prowess in this area is close to making this possible.

What’s Not Working?
Apple has attempted to get medical researchers to create new health apps by developing ResearchKit, an open source framework for researchers. Great idea. However, given the huge potential for the Watch in diagnostics, ResearchKit and the recruitment of Principal Investigators feels dramatically under resourced. (It took three years to go from ResearchKit 1.0 to 2.0).  Currently, there are just 11 ResearchKit apps on the ITunes store. This effort – Apple software development and third-party app development – feels understaffed and underfunded. Given the potential size of the opportunity, the rhetoric doesn’t match the results and the results to date feel off by at least 10x.

Apple needs to act more proactively and directly fund some of these projects with grants to specific principal investigators and build a program of scale. (Much like the NIH SBIR program.) There should be as sustained commitment to at least several new FDA cleared screening/diagnostic apps every year for Watch and iPhone from Apple.

The Future
Although the current demographics of the Apple Watch skews young, the populations of the U.S., China, Europe and Japan continue to age, which in turn threatens to overwhelm healthcare systems. Having an always on, real-time streaming of medical data to clinicians, will change the current “diagnosis on a single data point and by appointment” paradigm. Wearable healthcare diagnostics and screening apps open an entirely new segment for Apple and will change the shape of healthcare forever.

Imagine a future when you get an Apple Watch (or equivalent) through your insurer to monitor your health for early warning signs of heart attack, stroke, Parkinson’s disease and to help you monitor and manage diabetes, as well as reminding you about medications and tracking your exercise. And when combined with an advanced iPhone with additional FDA cleared screening apps for early detection of skin cancer, glaucoma, cataracts, and other diseases, the future of your health will truly be in your own hands.

Outside the U.S., China is plowing into this with government support, private and public funding, and a China FDA (CFDA) approval process that favors local Chinese solutions. There are well over 100 companies in China alone focusing in this area, many with substantial financial and technical support.

Let’s hope Apple piles on the missing resources for diagnostics and screening apps and grabs the opportunity.

Lessons Learned

  • Apple’s new Watch has two heart diagnostic apps cleared by the FDA
    • This is a big deal
  • In a few years, home and outpatient diagnostics will be performed by wearable consumer devices – Apple Watch, mobile phones or fitness trackers
    • Collecting and sending health data to doctors as needed
    • Collecting baseline data on tens of millions of healthy people to train disease prediction algorithms
  • In the U.S. the FDA has changed their mobile and digital device guidelines and policies to make this happen
  • Insurers will ultimately will be paying for diagnostic wearables
  • Apple has a series of patents for additional Apple Watch sensors – glucose monitoring, blood pressure, UV detection, respiration
    • The watch is already capable of detecting blood oxygen level, sleep apnea, Parkinson’s disease
    • Getting a signal from a sensor is the easy part. Correlating that signal to an underlying condition is hard
    • They need to step up their game – money, software, people – with the medical research community
  • China has made building a local device and diagnostic industry one of their critical national initiatives

The End of More – The Death of Moore’s Law

 A version of this article first appeared in IEEE Spectrum.

For most of our lives the idea that computers and technology would get, better, faster, cheaper every year was as assured as the sun rising every morning. The story “GlobalFoundries Stops All 7nm Development“ doesn’t sound like the end of that era, but for anyone who uses an electronic device, it most certainly is.

Technology innovation is going to take a different direction.


GlobalFoundries was one of the three companies that made the most advanced silicon chips for other companies (AMD, IBM, Broadcom, Qualcomm, STM and the Department of Defense.) The other foundries are Samsung in South Korea and TSMC in Taiwan. Now there are only two pursuing the leading edge.

This is a big deal.

Since the invention of the integrated circuit ~60 years ago, computer chip manufacturers have been able to pack more transistors onto a single piece of silicon every year. In 1965, Gordon Moore, one of the founders of Intel, observed that the number of transistors was doubling every 24 months and would continue to do so. For 40 years the chip industry managed to live up to that prediction. The first integrated circuits in 1960 had ~10 transistors. Today the most complex silicon chips have 10 billion. Think about it. Silicon chips can now hold a billion times more transistors.

But Moore’s Law ended a decade ago. Consumers just didn’t get the memo.

No More Moore – The End of Process Technology Innovation
Chips are actually “printed,” not with a printing press but with lithography, using exotic chemicals and materials in a “fab” (a chip fabrication plant – the factory where chips are produced). Packing more transistors in each generation of chips requires the fab to “shrink” the size of the transistors. The first transistors were printed with lines 80 microns wide. Today Samsung and TSMC are pushing to produce chips with features few dozen nanometers across.That’s about a 2,000-to-1 reduction.

Each new generation of chips that shrinks the line widths requires fabs to invest enormous amounts of money in new chip-making equipment.  While the first fabs cost a few million dollars, current fabs – the ones that push the bleeding edge – are over $10 billion.

And the exploding cost of the fab is not the only issue with packing more transistors on chips. Each shrink of chip line widths requires more complexity. Features have to be precisely placed on exact locations on each layer of a device. At 7 nanometers this requires up to 80 separate mask layers.

Moore’s Law was an observation about process technology and economics. For half a century it drove the aspirations of the semiconductor industry. But the other limitation to packing more transistors onto to a chip is a physical limitation called Dennard scaling– as transistors get smaller, their power density stays constant, so that the power use stays in proportion with area. This basic law of physics has created a “Power Wall” – a barrier to clock speed – that has limited microprocessor frequency to around 4 GHz since 2005. It’s why clock speeds on your microprocessor stopped increasing with leaps and bounds 13 years ago.  And why memory density is not going to increase at the rate we saw a decade ago.

This problem of continuing to shrink transistors is so hard that even Intel, the leader in microprocessors and for decades the gold standard in leading fab technology, has had problems. Industry observers have suggested that Intel has hit several speed bumps on the way to their next generation push to 10- and 7-nanometer designs and now is trailing TSMC and Samsung.

This combination of spiraling fab cost, technology barriers, power density limits and diminishing returns is the reason GlobalFoundries threw in the towel on further shrinking line widths . It also means the future direction of innovation on silicon is no longer predictable.

It’s the End of the Beginning
The end of putting more transistors on a single chip doesn’t mean the end of innovation in computers or mobile devices. (To be clear, 1) the bleeding edge will advance, but almost imperceptibly year-to-year and 2) GlobalFoundaries isn’t shutting down, they’re just no longer going to be the ones pushing the edge 3) existing fabs can make current generation 14nm chips and their expensive tools have been paid for. Even older fabs at 28-, 45-, and 65nm can make a ton of money).

But what it does mean is that we’re at the end of guaranteed year-to-year growth in computing power. The result is the end of the type of innovation we’ve been used to for the last 60 years. Instead of just faster versions of what we’ve been used to seeing, device designers now need to get more creative with the 10 billion transistors they have to work with.

It’s worth remembering that human brains have had 100 billion neurons for at least the last 35,000 years. Yet we’ve learned to do a lot more with the same compute power. The same will hold true with semiconductors – we’re going to figure out radically new ways to use those 10 billion transistors.

For example, there are new chip architectures coming (multi-core CPUs, massively parallel CPUs and special purpose silicon for AI/machine learning and GPU’s like Nvidia), new ways to package the chips and to interconnect memory, and even new types of memory. And other designs are pushing for extreme low power usage and others for very low cost.

It’s a Whole New Game
So, what does this mean for consumers? First, high performance applications that needed very fast computing locally on your device will continue their move to the cloud (where data centers are measured in football field sizes) further enabled by new 5G networks. Second, while computing devices we buy will not be much faster on today’s off-the-shelf software, new features– facial recognition, augmented reality, autonomous navigation, and apps we haven’t even thought about –are going to come from new software using new technology like new displays and sensors.

The world of computing is moving into new and uncharted territory. For desktop and mobile devices, the need for a “must have” upgrade won’t be for speed, but because there’s a new capability or app.

For chip manufacturers, for the first time in half a century, all rules are off. There will be a new set of winners and losers in this transition. It will be exciting to watch and see what emerges from the fog.

Lessons Learned

  • Moore’s Law – the doubling of every two years of how many transistors can fit on a chip – has ended
  • Innovation will continue in new computer architectures, chip packaging, interconnects, and memory
  • 5G networks will move more high-performance consumer computing needs seamlessly to the cloud
  • New applications and hardware other than CPU speed (5G networks, displays, sensors) will now drive sales of consumer devices
  • New winners and losers will emerge in consumer devices and chip suppliers
%d bloggers like this: