The world is truly becoming flat when it comes to consumer tech and that has had (and is having) profound ramifications on the competitive nature of the global marketplace for consumer tech.  The global tastes and preferences of consumers are becoming homogeneous and while some subtleties still exist between geographic markets, these differences are quickly becoming marginalized.

Take for example mobile telephones. In the last 24-36 months we’ve witnessed the rise of global preferences for smartphones or traditional mobile telephony. Not news of course.  But what is perhaps interesting is that these preferences have largely materialized around a very few specific models.  Because of this, the global market has truly become a winner (can) take-all market. While mobile phone manufacturers will broker specific carrier deals within a given region, they are still selling the same handset across these markets for the most part. This has ramifications for accessory manufacturers and more broadly it has ramifications for the entire suite of devices, services, and software/applications within the accompanying ecosystem of a successful product – especially if the ecosystem is built around a specific OS.

Even when usage patterns differ across geographic markets do we care? Perhaps when it comes to the nuances of actually marketing a product or service, but because products and services will have all of the bells and whistles built in anyways there isn’t really much customization that needs to be done on a geographic basis.

But it does mean that the initial design of a device or service is extremely important.  It must scale globally.  Devices and services must speak a global design language.  Brands must work on a global scale. One need only look at Apple, Samsung, or Beats to see this working in practice.

In the last year or two there has been an explosion of massive online open courses (MOOCs).  These have come from a wide assortment of institutions. To date there has been tremendous experimentation but business models are still forming. As Cisco’s executive director for AsiaPac Andrew Thomson recently suggested one potential business model “could be that the content could become free, but you pay for the credential.”

MOOCs are essentially the mass digitization (and democratization) of education. In many ways, it is unfolding in the same way other “digitizations” have occurred. Namely, distribution and content are being commoditized which is drastically lowering the market price. However, a significant portion of education is the relevant signal.  So while digitization is commoditizing the content, the signal remains important.

By providing structure to something that is relatively unstructured – in the case of education an exam, a certification, or a degree – institutions are able to continue to monetize content that is increasingly being commoditized.

Most of the to-date successful web properties have built their success off of providing structure to relatively unstructured bits.  This is definitely the model of Google who has so far done certain aspects of that structuring better than others.  App stores create structure.  Amazon provides structure. If you look around, you’ll note the companies that have provided structure as their industries have digitized have found the most success and have been able to remain relevant.

At the root -this is the battle currently underway between traditional analog/physical players and their digital counterparts. This is what has unfolded with music, video, books, and now education. And because digital bits scale extremely well, companies operating in the digital environment can garner 90+ percent of a market.

 

A recent study from Gartner suggests nearly one in five business leaders expect to recruit a chief digital officer by 2014 and about 17 percent foresee appointing a chief data officer within the same time frame.

The development of the CDO position today is akin to the development of the chief information officer position a decade or more ago. A quick comparison between wikipedia’s full description for CIO and the sparse description for CDO shows just how new these developments are. While many CDOs work for content companies and are tasked with digitizing analog businesses, I expect the position to evolve to also encompass digitizing and monetizing business models that didn’t (and couldn’t) exist in the analog world.

At the end of January, Facebook announced they would partner with the suicide prevention group Save.org. The goals of the partnership are to research the online behaviors of suicide victims in the days and months leading up to their deaths in order to identify and detect patterns of potential suicides.

If successful, the research will identify common strings of those most at risk of committing suicide before they do it. If successful, this research could create the groundwork for the implementation of what I’ll call “digital safety nets” and aid in the prevention of suicides.  These digital safety nets are really just triggers that key a series of digital (and ultimately physical) responses to a given risk. At current, there is a vast amount of research going into the creation of digital safety nets for a swath of risks.

I’ve long been intrigued by the work being carried out by researchers at Northwestern who have been working with a mobile app platform they created call “Mobilyze.”  The mobile platform is designed to help those suffering from depression by prompting users to make changes in their surroundings and/or behavior to reduce or eliminate depressive symptoms. The platform is also designed to identify the patient’s state and provide intervention prompts like text messages or phone calls.

Many of the personal connected devices we see today take what we might already know and provide the information back to us in more exact terms.  For example, we know we exercised or walked or biked, but a given fitness device with an embedded GPS can tell us exactly how far we went or how much we did.  What we are seeing with the creation of digital safety nets is slightly different. Here these connected devices might take what we ourselves don’t know and provide us insight. These connected devices could develop the capability of identifying for us are own tells.

Yes – there are of course the risks of false positives.  But the alternatives are much worse.  And algorithms should get better and more refined (perhaps I’ll write a bit more about why this might not actually be the case in a future post). And while we are currently focused on behaviors with large negative outcomes, we could theoretically alter any behavior – simply through a  mix of digitization, inverted crowdsourcing or perhaps the use of quasi probe data, and finally digital prompts that subsequently exert influence on the behavior we are seeking to alter.

I wrote early this month about the features of connected wristwatches. Since this time there has been significant digital ink spilled discussing the connected wristwatch space with a focus on Apple’s potential foray into the market (see: 100 people are working on the Apple watch, Apple’s entry into wearable tech, On the Apple Watch watch, Apple watch that talks to your iPhone appears in patent, and a thousand more articles).

There is always some trepidation in throwing a number out for the potential addressable market for very nascent – and in this case nearly nonexistent – categories. A back-of-the-envelope forecast  for connected wristwatches will surely haunt me and in these exercises I always think of the cellular telephony forecast McKinsey constructed in 1980 at the request of AT&T (whose Bell Labs had invented cellular telephony).  McKinsey & Company predicted 900,000 subscribers by 2000 – only slightly less than the 109 million that actually existed by that year.

But with that caveat squarely attached, I want to walk through some of my thinking on this topic.

Background Assumptions

Today there are roughly 240 million adults in the U.S. living across about 119 million households  (There are about 314 million total living in the U.S., but for this estimate – and simplicity – we’ll focus on the adult population).  Roughly 87 percent of American adults have a cell phone and about 45 percent of American adults have a smartphone.

With these type of exercises, it is always important to remember two things: (1) rarely does a product see 100 percent adoption (and only a few tech devices have ever even seen household adoption above 85 or 90 percent), and (2) adoption follows logistic functions.  This second point means slow adoption in the early years followed by several years of accelerating adoption before eventually the second derivative of the growth function turns negative (adoption grow continues but at a slower pace).  While not always evident, the first derivative of the growth function often turns negative in the end (adoption/ownership actually declines as consumers move to new products and forego replacement).

I prefer the term connected wristwatch over “smart” watch because we are really talking about watches that primarily connect to the Internet by piggybacking on the connection of the smartphone or some other Internet-enabled device. Because most connected watches will leverage the embedded connectivity and functionality of smartphones the addressable market today is probably the 45 percent or so of U.S. adults that have smartphones.  Over the long-run many and perhaps most mobile phone users will likely adopt smartphones so the longer-run addressable market is probably closer to 80 percent or 85 percent of U.S. adults. This suggests a current addressable market of roughly 108 million individuals and a potential long-term addressable market of say 190-200 million adults.

Anything that attaches to mobile phones is by definition one of the largest addressable markets in tech because of the high ownership rate of the underlying device.  This is one of the largest reasons connected watches deserve the attention they are getting. But obviously not all smartphone users will adopt connected watches. The global watch market is itself a not small addressable market,  with some estimates suggesting a $45 billion global market. I’d guess 25 percent to 40 percent of this market is in the U.S.  The wristwatch market today is not surprisingly driven heavily by luxury brands and high-end watches.  The watch market has become more of a fashion accessory than the utility device it once was because individuals are using their mobile phones as their timepiece in most cases.  But these dynamics could reverse as the connected watch becomes more than just a timepiece device.

Without doing any real research, if I had to guess I imagine long-term attachment rates of perhaps 30 to 40 percent seem reasonable if the category is successfully established so you are looking at an installed base of maybe 60 million to 80 million owners in the U.S. If the category never materializes of course then you are looking at maybe one to two percent adoption over the life of the category.

The average smartphone is replaced roughly every 18 months in the U.S. and U.S. carrier subsidy models accelerate the replacement cycle compared to other markets. While smart watches are less expensive than smartphones they aren’t likely well suited for subsidy programs since they leverage the connectivity of the mobile phone.  But they would be influenced by fashion which might shorten the replacement cycle.  Guessing, I imagine connected watches would be replaced every 36-48 months.

Summarizing, here are my (early) basic assumptions:

  • Long-term (underlying) addressable market= roughly 200 million smartphone users
  • Attachment rates to that addressable market = 30 percent to 40 percent or 60 million to 80 million
  • Replacement cycle = 3-4 years
  • Density rates = 1.  I assume adopting consumers own about one on average.
  • Replacement rate.  In this exercise I’m primarily focused on initial adoption, but could also factor in replacement cycles. My starting estimate is that 80 percent of users actually replace the product. This 80 percent figure would fluctuate higher or lower depending on how committed users are to the device and I imagine it naturally decays over time. An 80 percent replacement figure suggests a pretty strong commitment to the device and an otherwise successful category.

With these starting assumptions, I’m suggesting the category is generally successful with the portion of the addressable market that adopts the technology relatively committed to the category.  Whether the category can bring value to the consumer and realize this potential (or even surpass it) remains to be seen.

Sizing the Market for Connected Watches

We are already getting a sense for early demand for connected watches.

0213 adoption

Kickstarter darling Pebble reports they’ve sold about 85,000 watches to-date. Here I use some relatively simple diffusion equations to approximate what sales would look like over the next 30 years given the assumptions above.  A few things to note in the following charts.

First, total U.S. sales hit about 220,000 this year and 320,000 next year. Annual sales break the million market for the first time in year 6 and subsequently annual sales peak in year 13 at about 5.8 million.  Over the 30 year period, 60 million devices are sold and if you consider replacement cycles another 47.7 million devices are sold just by replacing 80 percent of the first cycle of purchases. This latter figure grows if you consider multiple replacements over this forecast horizon.

Given the simplified model I’ve used, five percent of U.S. adults own the product within 9 years and 10 percent own it with 11 years. By year 24 adoption rates have reached 30 percent at which point I’ve assumed they reach their steady state.  If I were to project broader adoption then ownership rates would accelerate over the forecast horizon. In other words, we’d see a higher rate of ownership rates more quickly.

0213 cumulative adoptionI actually believe adoption rates are broadly accelerating.  I’ve written about this in the past. Information diffusion is happening more rapidly today. Potential buyers are learning more quickly about new technologies. Adoption rates are still following logistic functions but those logistic functions are being compressed over a shorter time period.  New products are finding life (or conversely death) much more quickly today.

The above approach is a simplistic model that suggests what adoption might look like given some average parameters and assumptions. Clearly, reality will look much different.  The first few hundred thousand units of any device are relatively easy to sell. I like to say there is a 50,000 unit market for everything.  It is the next few hundred thousand that are more difficult to sell.

 

Does the Entry of Apple Change these Estimates?

Maybe. By some estimates, Apple controls about half of the U.S. smartphone market so about 54 million U.S. adults have Apple iPhones. Presuming maybe five percent to ten percent of the installed base are early adopters of Apple products and buy within the first 12 to 18 months, so you are looking at maybe two to five million iWatches selling over the first 12 to 18 months. That figure is four to ten times what I estimated above. But I think an Apple entry influence is more of brand story than a product viability story. Long-run adoption dynamics and replacement cycles will be less influenced. I think Apple’s entry could shift the market and compress the adoption cycle as I discussed above, but I don’t know that it changes the market size for the category over a longer horizon.

What Do Connected Watches Do for a Company’s Bottom line? (ie Why Enter the Connected Watch Market?)

At the end of the day, companies like Apple are hardware companies.  As public companies they have investor communities they must appease.  They do this by growing both top-line and bottom-line revenue. They need to grow both sales (top-line revenue) and net income (bottom-line revenue). They do this by entering into new markets and selling more stuff.  At the same time, they must maintain (or increase) margin which ensures net income grows inline with top-line revenue growth.  Companies want to grow sales but not if it sacrifices profitability (obviously). Companies must think carefully about the type of new markets they enter.

Service markets are generally attractive new markets because they typically have relatively high margin.  This is one of the reasons you see companies from telcos to cable companies to utility companies to hardware companies entering into new service and entertainment markets.  It is also the reason you see companies like Cisco exit certain markets.  Cisco recently announced they were selling off their Linksys business and they completely shuttered what was believed to be a successful Flip division simply because these divisions had lower margins than they were accustomed to within their core business units.

For well over a year there have been rumors Apple would enter into the TV business. This would certainly help grow top-line revenue, but the impact on company margin is less clear.  On the other hand, connected watches are a category that are relatively margin rich so they represent a pretty attractive new market for a company looking to maintain margin while growing sales.

 

There is a misconception that engineering wins in the end.  It doesn’t. Perhaps it once did.  Certainly over the last 60 years of technology engineering won out more than it does today. But today, pure engineering is simply less powerful in influencing adoption and consumer use. This has become acutely evident over the last 24 months.

Nick Bilton hit on part of this in his New York Time’s column a few weeks ago entitled Disruption: Design Rivals Technology in Importance. One can certainly argue design – industrial design – at it’s purest level is engineering. But this element of engineering – design – is different than the engineering that dictates how a product functions, what it does, and all of the engineering that goes along with defining the embedded technologies of a device.

You can see how engineering historically influenced purchase decisions and how it now suddenly doesn’t.  Manufacturers use to market their devices with numbers – a classic engineering approach.  If model 8000 was good then clearly model 9000 is better. Let the numbers speak.  Let the specs define how useful the device is. But we’ve largely moved away from this approach.  Sure we still at times name things sequentially.  The iPhone 5 is “newer” and therefore probably “better” than the iPhone or the iPhone 4. But the iPhone experience isn’t really defined by a series of numbers. One of the touting features of the iPhone 5 is the inclusion of a secondary microphone on the back which is intended to cancel out ambient noise.

Last year I said 2012 was going to be the year of the interface.  I believe that is exactly what we’ve seen materialize.  For example, a large number of devices are now capturing information or performing other activities for the end user. But many of these devices lack much of a user interface.

fitbit

Think of devices like the new Fitbit Flex which was recently launched at the 2013 CES. The device itself doesn’t really have an interface. The device captures information, transmits that information to a cloud service (via bluetooth and the cellular or WiFi connectivity of the smartphone).  That service is essentially a curation service.  The Fitbit (cloud service) curates an experience for the end-user by aggregating the captured information and using algorithms to provide insights back to the end-user.  Those insights are provided back to the end-user not through the interface of the device – because remember the device doesn’t really have an interface – but rather through the smartphone. The smartphone becomes the interface for the device.  The smartphone becomes the interface for the curated experience delivered back to the consumer. I said recently that the smartphone has become the viewfinder for our digital life.  That is exactly what is happening here.

The engineering is clearly important. The engineering makes it all possible.  It still adds value and there is still a tremendous amount of engineering innovation taking place.  There is much more to come.  I think we have only scratched the service of what is possible when it comes to embedded MEMS technologies in consumer devices for example. But the really interesting things are happening at the application level.  MEMS sensors will digitize interesting information, but curation services will deliver value to the end-user. And because many/most elements of engineering can be replicated by others (especially given enough time), the interface is what differentiates the experience for the consumer.  Simply put, engineering continues to add value but the design of the experience is defining the ultimate value for the consumer.

Last week I spoke at an event at the Hanken School of Economics.  Timo Seppala also spoke and I’d like to highlight one of the points he made (you can read the underlying paper here). In talking about IP regimes, he argued there are two core types of patents – essential patents and platform patents.  The essential patents are fundamentally engineering patents. As Seppala and Kenney write, ” traditionally, the mobile telecommunications industry has been an industry where standard setting and ownership of the essential IPR, such as GSM (global system for mobile communications), 3G (third generation mobile telecommunications), LTE (long term evolution), and other similar standards that play a significant role in defining market structure and the positions of industry firms.” You can think of essential patents as patents that cover things like radio, transmission, and telephony engineering.

Platform patents are patents covering things like sensors, materials, optics, digital data, signaling, speech recognition, and picture communication). Seppala and Kenney point out that platform patents are becoming more numerous and in fact are becoming the majority of patents in the mobile device space.  More, companies like Apple, Google, and Microsoft come from a world of platform creation. They are each bringing mobile operating system (platforms) to mobile (and in the future other “smart”) devices.

We’ve seen significant leadership shifts within the mobile device marketplace over the last 24 to 36 months. Some of this shift is certainly explained by a shift in the way consumers are approaching these devices.  Consumers are perhaps focusing less on the pure engineering experience of devices and more on the platform experience of the device and in turn the companies who have approached marketplaces from a platform perspective have benefited.

The consumer experience is clearly influenced by the engineering of a device. But increasingly, the consumer experience is being defined explicitly by more than the engineering of a given device.

 

 

 

 

 

 

 

On my flight over to Helsinki a day ago, I read the December issue of the Harvard Business Review.  Several articles focused on disruption and I want to spend a minute sharing my thoughts on the topic.

Disruption is a fickle influence on business and while we often talk about about disruptive change being binary – you are either being disrupted or you aren’t – the truth is much more discriminating. Disruption has a strong time component and most disruption plays out over long periods of time.  In fact, it is often the function of time that dictates if disruption will in fact shift the competitive landscape.

The key to disruption materializing – moving from a simple nuance to a true disruptive force that changes how business is down and how organizations compete – is to what degree the given disruption scales.

Tomorrow I’m speaking on the disruptive force of digital. Perhaps no single force has been as disruptive as digital has to so many different sectors of the economy.  A big reason behind this is the ability of it to scale. Digital by it’s very definition scales infinitely. It is also worth noting that digital has taken a significant amount of time to become fully disruptive. Time allows truly disruptive forces to build momentum.  In the case of digital, it first gained traction in the music sector.  In fact, the first real digital device outside of computers was the launch of the CD player at the 1981 CES. After successfully disrupting the music industry, digital moved onto other, more difficult, sectors of the economy. Print. Imaging. Video.  Each one succeedingly challenging, but time had allowed digital to gain enough momentum (and prove that it could be disruptive) that it was able to be disruptive in these subsequent sectors of the economy.

As the Internet took hold in late 1990s and early 200os it simply allowed digital to scale more fully and consequently become more disruptive.

Earlier this week, CNET wrote about 5 Web Technologies to Watch in 2013. I completely agree with the 4th one listed: High-res images on the Web. Prevalent at CES next week will be what I’m referring to as “HD Everywhere.” We’ve already seen the resolution on mobile phones increase and we are now seeing that spread up the device hierarchy. Tablets and laptops with higher resolution screens will be on display and of course televisions pushing to Ultra HD 4K resolution – twice the resolution of 1080P HD – will be one of the big stories for the 2013 CES.  Naturally, once these screens become capable of rendering high resolution images users will increasingly want access to high resolution images.  While I don’t think we see a big move to high resolution web images in 2013, this move will naturally follow a growing installed base of high resolution screens.

I’d like to add one additional thought.  The Web is big.  It is blotted.  Most of us can remember searching for things on the Web and receiving back 21 search results. Today the same search returns 21 million search results. Search results are being overrun by what I call Web Debris – information that was once relevant and accurate but now simply floats across the Web.  Web Debris is hindering productivity and efficiency.  Rarely do I search for something today without applying time parameters (last day, last month, last year).  I think narrowing parameters will eventually become standard search criteria. Today Google and others preemptively guess what I’m trying to search for. I imagine the same approach could be taken with narrowing parameters.

Yesterday I was Los Angeles to participate in an event announcing several new additions to Entertainment Matters at CES which is entering it’s third year at CES.  In 2013, Entertainment matters will feature a variety of events and conference sessions, including: TweetHouse Presents, Innovations in Social Business, Digital Hollywood, Content in the Cloud, Variety‘s Entertainment Summit: Film & Technology and the 2013 IAWTV Awards Gala. CEA also announced it is expanding its content-focused tracks by introducing a new conference track, Content and Disruptive Technologies. This new track will included five sessions:

Recent research from Pew shines light on the digitization of the news:

  1. consuming the news digitally now surpasses physically reading the news.  In 2004, 24 percent of respondents got their news digitally while today 39 percent do the same. Fifty-five percent of respondents said they watched the news on TV yesterday which is still the highest of any form, but is down from 68 percent in 1991.
  2. Only a third of individuals under 29 years-old watch the news on TV – down from 49 percent in 2006.
  3. Today almost one-in-five get their news through social networks – up from one-in-ten just two years ago.
  4. As you can see below, today more than half of the readers of the New York Times do so digitally and the similar figure is high for other major newspapers.

Stats #2 and #3 above taken together paint the most interesting picture of the future.  Now it is certainly true that as individuals age, their preferences towards things like broadcast news might change.  But I believe the first digital decade will have a profound impact on how news is consumed in the second digital decade.

The future generation of news consumers want something different from their news.  Given the rise of connected devices, individuals no longer need to sit through linear news for information like local weather and sports.  News going forward will be significantly more compartmentalized.  We’ve seen some of this with the rise of specialized and focused news services.

The digitization of news is also impacted by geography. News that is hyper-local is best delivered online because broadcast news by definition has to serve a broader market.

Portable devices with integrated GPS can deliver hyper-local news when it is most relevant.  So the time function becomes an important component of news delivery in the second digital decade.

Finally, curation and relevancy will be an important element of news consumption.  Facebook is a curated service where the individual user establishes parameters which dictate which streams of information they receive.  Increasingly, individuals get to dictate which news items are most relevant to them.