What Was Mobile?: A Broader Look At Tech

Benedict Evans recently wrote an enlightening post “The end of a mobile wave” where discusses what may come after smartphones.

I try to take a different view. I try to focus not on the devices or platforms that have come and gone, but on the underlying needs that have been satisfied. Hence instead of looking at voice, SMS and smartphones, I try to look at the need for communications (including the synchronous and asynchronous modes) and how they have been satisfied. Hopefully this will give us a broader view, and will also help us assess what the AI breakthrough may mean for us.

The needs that tech has satisfied

In my view, tech has been applied to three basic needs.

  1. The need to be entertained: This has come in the form of games, video, music, e-books, etc. Indeed, looking at the the disproportionate value that this category earns from the iTunes Store and the App Store, this is a huge need that tech has helped satisfy. In video, music and e-books, tech has almost already fully satisfied all needs. It is very hard to think of what tech could do more, other than reducing price (maybe indirectly through streaming services). Games however are a different story. We can see VR contributing hugely to the gaming experience, and we can expect further meaningful innovation in this area.
  2. The need for faster and more complex calculations: Originally computers were conceived for doing things like decoding encryption, calculating the trajectory of missiles and simulating atomic bombs. They were valued for the computing power. Today, we see computers controlling robots in factories, controlling huge industrial plants, navigating spacecraft, navigating self-driving trains, calculating the best way to travel to a certain destination (either by car or by using multiple public transport services), processing images for higher visibility, optimising logistic operations, designing new pharmaceutical drug candidates, predicting the best timing to sell or buy financial assets (for better or worse), and even playing Chess or Go. The current deep learning algorithms that have greatly improved machine learning techniques will most likely contribute to this area, on top of other automation/AI techniques that have been worked on for decades; deep learning will be a sustaining innovation that might or might not greatly contribute, depending on how well they perform at the task on hand relative to other techniques. Most of this innovation has happened in a way that has been mostly invisible to consumers. However, a lot of this has transformed how business is done and the efficiency that is attainable. I do not see any saturation in the needs for this market, and I expect technical advances to continue, with or without deep learning. Although on a much simpler but nonetheless much more broader scale, the digital spreadsheet pioneered by VisiCalc and improved on with Multiplan, Lotus 1-2-3 and MS-Excel have also contributed greatly to the need for complex calculations.
  3. The need for communication: Other than entertainment, the largest direct impact of tech on the lives of consumers has been in communications. In the early days of tech, word processors allowed us to write paper documents more efficiently (with easy editing). DTP software allowed us to even create publishing content quickly and cost effectively. Then with the advent of email and the Internet, communication and publishing suddenly became much, much simpler, cheaper and effective. Mobile build upon this trend, allowing people to be contacted wherever they were, first using voice or text, and eventually (with smartphones), using full email or other apps. With easy and cheap video calling now available, one would think that the need for communication has almost been completely satisfied and that we can innovate no further. However, anyone in the real world can attest that these tools are still no substitute for face-to-face meetings. Even with face-to-face meetings, intentions may not be clearly conveyed. The tools that we use, like PowerPoint, are woefully underpowered and inefficient. Therefore, I think that this need to has yet to be sufficiently satisfied. We are still waiting for the ultimate tool that will allow us to remotely communicate as if we were meeting face-to-face. We are even further away from telepathy-like tools that might free us from the limitations of human language, and to communicate as if our brains were directly wired together.

Hence my opinion is that there are still many needs that await a solution, and are upon the trajectory that tech has pushed us thus far.

Future tech and how mobile fits in

Mobile is ultimately about how we carry tech with us all the time. It is how we are entertained on the train. It is how we can access in real-time and on the go, the results of complex calculations. It is about how human beings can communicate better wherever they may be.

As I see it, none of these needs have yet been sufficiently satisfied. We need to do better. Therefore, there is a lot of room for improvement in the devices that we carry around. I cannot pinpoint exactly what these improvements should be, since they are also governed by the cutting-edge technology that is available. One thing is sure; the people and companies who can see beyond the current devices (the ones that have a track record of doing this) are the ones who will likely find what is still left to do.

(And no, I don’t mean the companies that simply say that AI will come next. Technology should never come first.)

Waves in tech and how Apple and other tech companies grow

When looking at the rhetoric around whether or not Apple has will or will not continue to grow rapidly, I often sense that people are not looking back at the history of tech and trying to understand how the tech giants grew in the first place. I’ll try to go into this a bit here, and from this, I’ll try to understand Apple’s chances of future growth and escape from maturity.


Tech did not grow by companies single-handedly creating new markets out of thin air. Instead, tech grew on top of waves. The successful companies are those that rode these waves. The unsuccessful ones were the ones that missed them, or fell off half way. There have been many waves in tech.

Digital productivity wave

This is the era when word processors and spreadsheets became popular (1980s to early 1990s). This created the first growth wave of PCs. Microsoft was the company that benefited the most from this wave. Both IBM and Apple initially rode this wave quite well, but they fell off half way.

Essentially, this was the digital productivity age. Word processors relieved us of the need to start out with a new sheet of paper every time we mis-typed a word (it allowed us to edit). Spreadsheets saved us from hours typing digits into calculators.

One thing to note is that the GUI revolution did not create a new wave, but instead empowered the ongoing digital productivity wave. The core job of tech remained more or less the same.

Internet wave

This was when the Internet took off and GUI-capable PCs made it accessible to mere mortals (mid 1990s to mid 2000s). Microsoft again rode this wave with Windows 95. The rise of the Internet also provided the wave which Amazon, Google, Facebook and others rode to become giant companies.

The Internet provided us with instant communication and information. It connected friends and co-workers via email. It connected shops and customers via the WWW. It allowed us to share photos via Facebook. It allowed us to find documents in the form of web-pages through search. This is significantly different from the previous digital productivity wave, which can easily be understood if you consider how the Internet wave changed how we presented our work. In the digital productivity wave, we still printed our work out onto paper. In the Internet wave, our work was shared digitally and instantaneously.

The Internet wave is still with us

The Internet wave has actually been very long. Starting in the mid 1990s, it is still going strong in 2016. The Internet companies are still growing, not necessarily because they are amazingly well run, but simply because the pie is growing. E-commerce is still a small portion of total commerce in the US and growing. Amazon is still riding this wave. Similarly, Internet ad spend is still a small fraction of total ad spend and this is what allows Google to continue to grow. The Internet is still growing, and in fact, this has been fuelled by none other than the iPhone which put the Internet in our pockets.

Apple’s maturity

Apple’s growth has slowed because although it dramatically expanded the time we spend on the Internet, it’s business model does not benefit proportionally with Internet usage. A single iPhone today is used much more on the Internet than it used to be in 2007. It is used for much more tasks, consumes much more data, and much more time is spent staring at their screens. However, Apple still charges basically the same amount of money per device. Apple does not earn significantly more money from the extended usage.

This is in contrast to Google and Amazon, both of which benefit proportionally from extended Internet usage. This is why Google still consistently grows at double digits whereas Apple’s growth comes and goes.

Finding the next wave

Although Apple could grow by finding a business model that grows in proportion to Internet usage (charging for content, services and payments), another way for Apple to escape maturity is to ride the next wave after the Internet.

Fundamentally, the Internet is about information and communication. Although these are very important facets of human existence, they are not the most important. Apple first entered the scene with digital productivity, and then rode re-ignited the Internet and communication wave with the iPhone. Similarly, Apple could provide tools to set fire the next wave.

One of these waves could be health. People living in developing countries spend their money on a plethora of things or which health is a huge portion. In fact, the money that we spend on health is much larger than what we spend on communication and entertainment (the current revenue centres of tech).

If Apple could find a way to benefit our health, keep us healthy, reduce our dependence on medication, improve the effectiveness of physicians, make health insurance more efficient, Apple would be opening the door to a huge market.

Thinking about Uber

The interesting thing about Uber and other services like AirBnb is that they are not just information services; they are the whole stack. Uber does not just notify taxi drivers where their customers are or assist payments; they provide the cars and the drivers.

In this sense, they operate outside of the Internet wave. They are entering the real world, and this is very different from what Microsoft, Google and Facebook have done before them.

This provides us with a hint at what the next wave could be.

What’s next for Apple

For Apple to find significant growth, they must find the next wave outside of the Internet. There is only so much left to do in communications if they continue with their business model of creating great products. Even VR has only limited potential if it is to stay within the boundaries of entertainment and communications.

If you look at where a individual in a developed country spends their money throughout their lifetime, housing, health, transportation, education are much larger than entertainment and communications. If Apple can successfully contribute to any of these markets, the current discussion of Apple maturing will soon seem utterly ridiculous.

Why The “Disruptive” Label Matters

In a recent “Critical Path” episode, Horace Dediu discussed the definition of disruption (00:46:40). Basically he outlines the boundaries of disruption theory and sets 3 criteria for Disruption.

  1. Entrant product serves customers who are over served by current incumbent product, or serves non-consumers.
  2. Asymmetry of motivation. The incumbent is not motivated to directly compete with the entrant.
  3. There exists a “Technological Core” that enables the entrant to continually improve the product.

Now this is totally great. It is great that the criteria for a “Disruptive Innovation” is clearly laid out, and that we can now identify whether a certain upheaval in the market qualifies for the Christensen-ish definition of Disruption or not. I totally agree with the criteria, as should, I believe, anybody who has carefully read Christensen’s books.

The problem is, if you have three criteria that you can answer with yes/no, then you have 2 x 2 x 2 = 8 possible situations. Only one of these Christensen Disruption. What are the others?

Furthermore, it becomes important to understand what it means to be a “Disruptive Innovation”. Clearly, Christensen does not intend “Disruptive Innovation” to describe all situation where there has been a significant disturbance in the market. He only talks about one. Then the question is, what makes his single segment so important? More importantly, why are so many Venture Capitalists upset and why do they complain so much when a single academic declares that the companies that they are investing in do not fit his criteria of “Disruption”?

The key to this question is to understand what the power of “Disruptive Innovation” is. The companies that are “Disruptive” are the ones that can benefit from this power. The ones that do not qualify cannot.

In any market competition, the companies with the more resources generally win. The weaker companies typically lose. However, this isn’t much fun. Venture Capitalists looking for incredibly high returns, are instead betting on small and weak companies that will somehow accomplish something that much larger companies cannot. They are essentially betting on David beating Goliath.

Sometimes smaller companies will out-manoeuvre larger companies by being more nimble. Sometimes the willingness of smaller companies to experiment with crazy ideas will allow them to win. However, until Disruption Theory, there was no theoretical framework that could predict which smaller companies would have a high probability of success. And there still isn’t any other.

Disruption Theory is still the only well accepted business theory that has been demonstrated to be capable of identifying (probabilistically) the winners from the losers. It is the only theory that gives us a path that David could take to reliably beat Goliath. It is the only well known wave.

Companies that qualify as “Disruptive” in Christensen’s definitions are the ones that could benefit from “Disruptive” dynamics, and who can ride the waves to beat the most powerful incumbents. This means that they can make the most of the resources (capital) that investors pour into them.

On the other hand, companies that do not qualify must take a different path. Although each individual path has not been fully explored, weak entrants will typically not survive on these paths. There is not well identified wave to ride. There may be other waves, but we can’t reliably count on them.

I hope that this describes what not being “Disruptive” in the Christensen sense means. It means that if you are not “Disruptive”, you are not riding Christensen’s wave. If you are a battleship, then you are probably OK, but that means that there isn’t much fun for the investors who poured billions of dollars to build the battleship. Unless you ride the wave, you probably aren’t going to get insanely high returns.

Peak Google?

When I look back at 2015, I am reminded that we started out with the idea of “Peak Google”. It was not only Ben Thompson, but other analysts too chimed in with this theme.

However, this hasn’t happened. At least not yet.Google’s revenue and profits are as strong as ever, and the end of search volume is nowhere in sight.

Google s first quarter under Alphabet continues strong growth in revenue and profit The Verge

The Verge

So were Ben Thompson and other analysts wrong?

Well the question really isn’t who is wrong or right. The problem is that the analysts were not providing enough information to be proved wrong or right in the first place.

In the case of Ben Thompson, he provides a disclaimer;

Still, I hope the subtle point I’m trying to make is clear: I think Google is quite safe when it comes to search, and that they will be a very profitable company for the foreseeable future. I just suspect we will all think differently about that dominance when it’s a small percentage of total digital advertising, just as we thought differently about IBM’s dominance of mainframes in the age of the PC, or Microsoft’s dominance of PCs in the age of the smartphone.

He makes it clear that one will be able to neither validate nor disprove his statement based on Google’s finances, and that he is talking about the fuzzy term “dominance”. And as expected, no clear definition of how “dominance” should be measured is provided.

And that’s what most shrewd analysts would do to cover their behinds, so that’s OK.

So how should we really think about the situation?

Companies don’t live forever

IBM and Microsoft seemed utterly invincible in their heyday and yet, they have lost a lot of their power now. There is a lot of discussion about how long companies will live, and right now, the average lifespan of a company in the S&P 500 is a mere 15 years. If we looked at tech alone, the lifespan would probably be much shorter. Hence even if you were to randomly predict that a company would decline in the next 5-10 years, you would still probably be right.

It’s harder to predict how companies will survive

Given that companies will tend to die in a short span anyway, discussing how they will die isn’t very constructive. It doesn’t add much value to the prediction that companies will die pretty soon anyway. It’s much harder, and much more relevant to discuss how they could survive. That is, one should presume that a company’s present business will surely decline. On top of this, one should strive to seek out what it’s next business could be. Regarding Google, calling Peak Google based on a prediction of the demise of its search advertising business doesn’t add much. It will happen, and no matter how hard you discuss, you will not get an accurate prediction of when. Instead, one should look at what Google’s next business could be, and if they are making significant progress on that. One should look at how Google could survive when (and it will surely come) the search ad business collapses.

When is almost impossible to predict

Let’s look at some very nice charts from Pingdom.com, showing revenue/profit trends for Apple, Microsoft and Google.



What you can see is that Apple posted record revenues up until 1995. Although they were starting to have issues with profits since 1993, there was little to suggest that they would experience a total collapse in 1996. Just like very few economists could see the Global Financial Crisis coming, complex systems often show catastrophic behaviour. That’s why predicting the when is so hard.


Proof of “Peak Google” has not come this year, and in my opinion, this shows more than anything that predicting the when is hard, almost impossible. Although Ben Thompson was shrewd enough to not make any predictions, some analysts were not. My advice would be to stop trying to predict “Peak Google” or peak anything for that matter, treat the decline of any business as a given, and focus on what that company may have in store for the future.

Adding Common Sense To Disruption Theory

Clayton Christensen has been working to limit the meaning of “Disruptive Innovation” to the definition the one that he uses in his books. By this, he aims to counter the absurd notion that “Disruptive Innovation” was supposed to explain every kind of market upheaval, hence its inability to do so suggests that the theory itself is invalid.

Some people have suggested that since Christensen stressed that “Disruptive Innovation” is not everything, a new theory for explaining the other phenomena is required. For example, in the HBR article, Christensen said that Uber is not disruptive. Then what theory can explain the market upheaval that Uber is causing?

My suggestion is that we don’t actually need a new theory. All we need is a good understanding of what areas “Disruption Theory” covers, and a little bit of common sense.

Let me explain.

First, we have to start with a good understanding of exactly what “Disruption Theory” covers and does not cover, and to see what the theory omits. To do this, I will focus on what I think is the core tenet of the theory; how the incumbent will respond.

In “Disruption Theory”, Christensen covers two options that the incumbent may take. These are,

  1. The incumbent responds directly to the entrant, and competes with it to drive it out, or to severely limit its penetration.
  2. The incumbent decides that it is not worthwhile to compete with the entrant at the low-end, and focuses on the high-end. The word that Christensen often uses is “flee to the high-end”.

Both of these options assume that the incumbent is capable of responding to the entrant, and beating it if it so wishes. Although this may be more common, there is however little reason why this should always be the case. This is the omission. It is very possible that in some cases, the incumbent is simply incapable of responding.

It is also clear from a logic point of view, that adding this will fully cover the scope of possible options. The incumbent either chooses to respond, or not respond. In the case he chooses to respond, he either succeeds in launching a response, or fails. There are no other alternatives, no holes left open to consider.

In the following table, I have added this third possibility in pink. This is the possibility that the incumbent did not have sufficient resources to launch an effective response to the entrant.

CommonSenseDisruption numbers

On observation of this third option, it becomes clear why Christensen did not bother to spend time elaborating this option. It is just common sense. That is why I took the liberty of filling up the pink boxes with what I consider to be straightforward reasoning.

In this third option, the incumbent is unable to mount a response, simply because it is weaker. It might be a smaller company with fewer engineering responses. It might not have the marketing might of the entrant, or its brand appeal may be much weaker. It might lack the bundling opportunities that the entrant has. Or, in the case of the quickly changing tech landscape, it might lack the expertise that is required of the next phase of computing.

In fact, I would say that a better explanation of why Christensen failed to predict the success of iPhone is because he misunderstood how difficult it would be for Nokia to adequately respond. He underestimated the resources required to create an iPhone competitor, and the know-how that Apple (and Google) had accumulated as software companies. He overestimated Nokia, Palm and Blackberry’s ability to create a similar operating system, despite trying hard either in conjunction with Microsoft, or by bringing in Jon Rubinstein to head the WebOS effort. Christensen failed to correctly assess the huge advantage that Apple had in terms of resources relevant to smartphone R&D, and instead only evaluated the resource advantage Nokia had in distribution, etc. He failed to understand that the R&D resources required to compete in the post-iPhone world were not the same as what Nokia already had, and were instead abundantly available at Apple and Google.

If the entrant’s new product is well received by the market but the incumbent cannot create a product that is competitive, then the incumbent will lose. The entrant does not necessarily need to position its product at the low-end because it can win at the high-end. There is absolutely nothing surprising about this; it is simply common sense.

To summarise my table, I believe that “Disruption Theory” left out just one option, and that has caused confusion. By filling this in, I think I have fully covered the options regarding what an incumbent could do (luckily, the omitted option was common sense, and so filling it in was trivial). It is my belief that how the incumbent responds is critical, and very often the key turning point. This is why I do not think that it is necessary to further sub-divide each incumbent response category based on other facets like cost-structure, for example. I believe that the outcome will mostly be determined by the incumbent response, and that sub-divisions will not lead to substantially different outcomes, hence sub-division loses any practical utility. (This is to say that sub-divisions that only predict the same result as the parent category are not very useful. For example a sub-division inside the “cannot respond” category that predicts that the incumbent will fall is not really worthwhile, because the “cannot respond” category already predicts the same.) Furthermore, I doubt that a detailed analysis of the “cannot respond” category is necessary since it is already common sense for the vastly more powerful to prevail. I would however appreciate any discussion on any aspect of my table.

Finally, I would like to discuss what this means for Uber, the controversial example that Christensen touched.

My understanding of Uber is the following.

  1. Uber is the entrant but is also the Goliath. As such, the Uber vs. taxi companies battle sits in the pink area of my table, the area where entrant Goliath predictably slays David.
  2. Uber has accumulated billions of dollars in venture capital which it spends heavily on customer acquisition, driver acquisition, marketing and government lobbying. This in stark contrast to the typically small and not-very-profitable taxi companies, which have not accumulated vast amounts of cash, and cannot spend tons of money for the same purposes as Uber.
  3. Uber is the world’s first global taxi company. It has benefits of scale in terms of its technology, branding and marketing.
  4. Uber’s valuation is dependent on its not being seen simply as a taxi company, but also as a company that can disrupt many other industries. None of these efforts have yet been successful, but nonetheless, investors are seeing huge potential opportunities. However, taxi companies have never been seen in this light. They cannot raise capital with the same promises as Uber.
  5. All this results in Uber being a Goliath in terms of the money it can spend, relative to local taxi companies. With vastly more resources at its disposal, it is able to invest in ways that its competitors simply cannot. Although there are no doubt other complicated reasons why taxi companies might have trouble launching an effective response, the enormous difference in cash cannot be ignored. Being Goliath, Uber will predictably slay the taxi Davids in the absence of regulation.
  6. Importantly however, the fact that Uber is not “Disruptive” limits its ability to fulfil its investors’ dreams, even if it demolishes taxis worldwide. Uber is definitely a better mousetrap, but the economics does not ensure sustainably low prices nor sustainable profits. It does not reduce the burden of insurance, gasoline costs, car maintenance costs nor car depreciation. It does not eliminate the fact that the driver still has to make a living. These are the major costs of a taxi ride, and without significantly reducing any of them, there is little systemic reason why an Uber ride would remain cheaper than a regular taxi. As a result, the market will not significantly increase. Most people are unlikely to suddenly be enlightened to the possibility that ditching their own cars and using Ubers exclusively would be cheaper for them overall. This is what it means to not be a Christensen “Disruption”, but merely my pink box upheaval.
  7. To be “Disruptive” to taxi industries, to bring taxi services to those who do not currently use taxis often, and to significantly expand the market, Uber has to either a) make taxis much easier to use for the people who currently have no access, or b) make taxis much cheaper. The first option is something that the green boro taxi program in August 2013 did in Brooklyn, with dramatic results. Applied to Uber, this would be like bringing taxis to rural areas where no taxi service is yet available. Option b) could be achieved by things like UberPool (which I don’t think is yet mainstream) or self-driving cars. UberPool is interesting and could fit the definition of “Disruptive Innovation” perfectly, if it worked. Of course, car pooling would compete more with busses than taxis, and we have to consider whether UberPool makes more sense. Self-driving cars are a bit too far out to sensibly evaluate.
  8. There remains the possibility that Uber will be disruptive to other industries, for example, automobiles. This is probably the rationale for its astronomical valuation. I personally don’t think much of the prospects, but instead of confusing this post with another controversial discussion, I will leave this for another time.


Cleared up the logic for Uber and added a few more details.


We might want to consider cases where the incumbent changes their mind. An incumbent may initially dismiss the entrant as non-significant and decide to “flee-upmarket”. After realising that the entrant is a larger threat then they initially envisioned, they may choose to respond. Whether that response is too late or not will depend on how strong the entrant has grown. If the entrant has grown to the point that the entrant is more resourceful than the incumbent, then the entrant will win. If the entrant has not, then the incumbent will win. This is a situation that is well documented in Christensen’s work.


With the pink category included, it is easy to see the large role that venture capital plays. Venture capital can instantly create Goliaths that dwarf the incumbents. Startups that have not accumulated any cash to date, can suddenly obtain resources many times larger than the incumbents’, if they can paint a picture that is sufficiently rosy to investors. Of course startups have to convince investors that the opportunity is much larger than the current market, much in the same way as Uber is pitching itself as more than a taxi company, but that is speculation-based, and startups do not necessarily have to provide hard figures.

In other words, the incumbents are at the mercy of the speculation that their industry could turn out to be but a small portion of a much larger enterprise. This does not always turn out to be true, as evidenced by how Google destroyed the RSS market (they obviously though that the RSS market would turn out to be something bigger that what it was), only to abandon it later.


Just to clarify, I do not wish to debate the adequacy of Uber’s current valuation, nor do I want to denounce it as a VC bubble. I am totally uninterested in how Uber managed to convince investors of its valuation. I do not care if Capital follows Opportunity, or if Opportunity follows Capital. The only thing I am interested in is that the entrant Uber has vast resources while the incumbent taxi companies do not. This to me is an indisputable fact.

I do say that the taxi business does not validate its valuation, but I do not intend to question its valuation based on future, speculative opportunities. That risk is for the investors to take. They’re not spending my money.

Thoughts on Disruption Theory

Just a quick list of my thoughts on Disruption Theory;

What does Disruption Theory predict?

This is very important. This is the “reason for existing” of any theory.

  1. Disruption theory is basically the prediction of how incumbents will react towards an entrant.
  2. Disruption theory predicts how incumbents will react. The prediction is based on an understanding of how attractive it will be for the incumbent to flee upmarket. That is, to abandon the low-end market and focus on the high-end. Incumbents will typically only flee up market if their business as a whole is not threatened in the short-term.
  3. If incumbents choose to react, and if the incumbents have huge resources relative to the entrant (which if generally the case), then incumbents are most likely to win.
  4. Conversely, if incumbents do not choose to react, the entrants will gain a foothold at the low-end of the market.
  5. If technological improvements and the profitability situation is favourable to the entrants, then they will progressively improve their product to the point that they will endanger, or even push out the incumbent.

So really, Disruption Theory does not directly predict success. It predicts how incumbents will respond, and it provides a general trajectory of how businesses will fare given their responses.

What is the predictive power of Disruption Theory?

The predictive power of Disruption Theory is similar to how the Newton’ Three Laws of Motion predict motion. If you are observing a curve ball thrown by a baseball pitcher, you need to consider Newton’s Three Laws, the Law of Gravity and aerodynamics. In particular, aerodynamics can be hard to predict and that is why we have air-tunnel experiment facilities (and no gravity testing experimental facilities). Disruption Theory is just one of these. Without good understanding of the other theories, the predictions of Disruption Theory will be inaccurate.

Furthermore, if the person applying the laws of physics to a curve ball does not know the speed of the ball, the angle to which it was thrown, the wind conditions, the rotation speed and more, then they will not be able to accurately determine its trajectory. This is despite the laws of physics being completely well known and defined.

Now the question is, is business more complicated or less complicated than a curve ball? If it is even comparatively as complicated as a curve ball, then it is reasonable to assume that even if Disruption Theory was 100% correct, we still wouldn’t be able to accurately predict the trajectory of a curve ball unless other laws were defined, and we knew detailed business conditions.

If you ask me, I’m convinced that business is more complicated than a curve ball.

Given the complication situation, the best we can hope from Disruption Theory is a probability percentage. This is like how we are given weather forecasts. Meteorologists don’t tell us exactly how the weather is going to be. They sometimes get it totally wrong. However, more often then not, they get it right and we are OK with that. Even despite the fact that the we fully understand the basic laws behind the weather, and have tons of data. It would be a monumental achievement if Disruption Theory ever reached the predictive power of a typical weather forecast. We can not reasonably expect more.

Faulting Disruption Theory because Christensen failed to accurately predict Apple’s fate, is like totally dismissing the basic laws behind the weather because a meteorologist made the wrong forecast once or twice. In short, it’s ridiculous.

Applying it to Uber

People in Silicon Valley seem to be very upset that Clayton Christensen said that their favourite company, Uber, was not “Disruptive” in his definition of the term.

Let me give my two-cents on the matter.

  1. I agree that Uber is not “Disruptive” in Christensen’s definition. It is clear that Uber is directly challenging the taxi industry, and that the taxi industry is motivated to respond. In particular, the taxi-industry is in no way fleeing upmarket.
  2. The consequence of not being “Disruptive” is simply that it will not follow the trajectory of what Christensen described. Incumbents will not flee upmarket and Uber will not drive them out through future improvements to its service.
  3. Whether Uber will ultimately succeed is a totally different matter. They are free to pursue their own trajectory. However, what Christensen described is a way for a weak entrant to overcome a powerful incumbent. Uber will not be able to leverage the power that the “Disruptive Trajectory” provides. It will not be able to succeed as a weak entrant. It has to become powerful, more powerful than the incumbents to succeed.
  4. Therefore, Uber will have to really on a brute-force approach. Fortunately, Venture Capitalists are happy to provide Uber with ample cash to spend on expansions and promotions. Uber as a result is able to use money-losing promotional tactics, something that the much smaller incumbents cannot. And clearly Uber seems too be compelled to use these tactics as they raise more and more money.
  5. An important point to note is that taxi companies are small all over the world. They operate very regionally, most often with a territory that covers only a few cities. Often, taxis are even self-employed. Taxis are also not a very profitable business, and hence taxi companies have not accumulated enough capital to spend on high-tech, let alone self-driving cars.
  6. Hence my understanding is that Uber is a Goliath entrant vs. the small incumbent Davids. Uber’s trajectory should be like how supermarkets obliterated mom & pop grocery stores. That is to say, you don’t need to know any kind of business theory, let alone “Disruption Theory” to see how it is going to end.
  7. Hence the real question for Uber is not whether it can push out taxis. Without any regulation, the answer is clear even without “Disruption Theory”. The question is will Uber be a sustainable business? Will it raise prices after venture capital runs out and there is no competition left? If they are forced to employ their drivers as employees and if they have to also pay for their driver’s cars, which is quite possible long term, can they still maintain current prices? If Uber becomes a monopoly, will they be any better than the regulated monopolies before them for both the drivers and the customers? I have serious doubts on this, and unless Uber discloses the sustainability of its business, commits to future low prices and the welfare of its drivers, I think that strictly regulating Uber makes a lot of sense. The last thing that you want is for Uber to kill your local taxi industry, and replace it with one which is just as expensive (potentially more) and where all the profits are funnelled to a Silicon Valley company far away. This is why we have anti-trust laws, for example, and this is why we regulate industries (like the public transport, mail, health and food industries) that directly affect the welfare of our citizens.
  8. Of course, there is discussion that Uber is more than just a taxi business. That it is a more general transportation/delivery service. This suggests that Uber does not compete only with taxis, but with busses, trains, subways, delivery trucks, Fedexes, Amazon drones, and more. Note the totally different economies regarding scale and costs, completely unattainable by people driving their private cars for Uber. Can Ubers compete with busses? Can Ubers compete with trains? Can Ubers compete with the Fedex delivery network? Can Ubers compete with Amazon drones? Can they ever be cheaper than these highly optimised systems, which use specialised vehicles but still aren’t too profitable to begin with? It’s easy to compare Ubers to taxis, but to the other businesses, not so much. It will be a much steeper challenge for Uber to disrupt these businesses, and even a phenomenally good mobile App is not likely to help much. Maybe it will work in regions with underdeveloped public transport infrastructure like California and some developing nations, but I don’t see it working like that in developed countries where auto lobbyists were not able to sabotage the development of public transport.

So in conclusion, Uber is definitely a threat to the taxi industry, but not because it is “Disruptive”. It is such a threat, probably just because it has the deepest pockets in the industry. It is a national supermarket network vs. a mom & pop store kind of battle.

Chromebooks and iPads in U.S. Schools

A recent blog on the New York Times described how Chromebooks are gaining in the U.S. education market (K-12). I have wrote quite a lot about Chromebooks on this block, and this article tells us that progress has been made on the part of Google. Of course, the market that is described in this article is quite small with only 13.2 million units annually, in comparison to over 300 million PC units (excluding tablets) sold worldwide, and as far as I know, Chromebook’s success in K-12 education has not expanded to other markets (including international). Nonetheless, this is good news for Google.

The comments section is also very good, with some specific examples of why certain schools decided to purchase Chromebooks instead of iPads or Windows PCs.

My broad-view understanding is that Chromebooks are serving pre-existing needs that are mainly administrative by nature, and are best understood as sustaining or efficiency innovations. The blog post and the associated comments strengthen my view.

The real problem as I see, it is that there is a huge amount of potential in bringing technology to the classroom, but there is still too little investment in terms of hardware, software, curriculum and teaching skills. Sustaining and efficiency innovations won’t take us there. They don’t provide administration with good reasons to invest more; they only give us reasons to spend less. We need empowering innovations (such as which the iPad promises to bring) for that.

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Understanding Where Tablets Can Go From Here

Before iPad sales started to slow down in 2013, the vast majority of analysts were bullish on tablets, predicting the imminent replacement of mainstream computing (PCs) by tablets. I’ll just pick a few articles to illustrate my point;

  1. John Kirk on Techpinions, Jan. 2014: How The Tablet Made An Ass Of The PC
  2. Ben Bajarin on Techpinions, Jun. 2013: How the Tablet is Killing the PC
  3. Horace Dediu on Asymco, Dec. 2013: When will the migration from PCs be complete?
  4. Ben Thompson on Stratechery, Jan. 2014: WINDOWS 8 AND THE COST OF COMPLEXITY

Although the degree to which each analyst strongly suggested a glowing future for tablets varies, there was a very consistent theme that tablets were in the process of replacing PCs.

In 2014, declining iPad sales (and declining Android tablet sales shortly thereafter) proved that these analysts were completely wrong, or at the very least, overlooking a very important piece of the puzzle.

For the record, I was questioning the conventional wisdom that tablets were replacing PCs back in January and February of 2014, before most pundits noticed that iPad sales were flattening (1, 2, 3), so I think I had a pretty accurate sense that iPad growth wouldn’t be so easy. I even said in Jan 2014;

So what I sense is the possibility that tablets (as computing devices) may have hit a roadblock in adoption, and this is due to the potential market being actually much smaller than envisioned. Much smaller than the PC market.

Now that Ben Bajarin has become openly bearish(subscription required) on tablets, I think we should take a step back and look at the market from a birds-eye perspective. We should question whether we really understand what is happening.

Understanding the complexity of the tablet PC market.

The tablet market is extremely complex. PCs were first hired mainly to do increase office productivity, and later to connect to the Internet. Smartphones, despite being very complex in what they can accomplish, are essentially uniform in the value that they provide to their users. However tablets are very different. They can be very different things to different people. Let me elaborate.

Jobs where the iPad is already a good fit

  1. A corporate executive’s/sales rep’s communication device: By this, I mean a device that is hired to handle simple emails and messaging, leaning on the reading aspect more than writing. You could also add a bit of presentations and accessing corporate web-based dashboards.
  2. A home entertainment device: Current tablets allow users to view a variety of video content and also provide a wide range of video.
  3. A home Internet device: Current tablets, especially the iPad is used for a variety of common consumer Internet tasks like viewing websites, posting on Facebook, replying to messages, etc.

These are the jobs which already existed, and in which the iPad could already be considered mature. Because the value proposition was clear and obvious, these are the jobs which drove the initial tremendous ramp up of iPad sales. In particular, we know that the majority of iPad usage happened in the home and not at work. Hence it is likely that items 2. and 3. were the main drivers.

The problem is, these jobs were equally well served by smartphones as a) better software became available for smartphones (e.g. Facebook moving from HTML5 to native) and b) smartphones got bigger.

Jobs where the current iPad is not yet a good fit

There are also a number of tasks where the iPad is not yet a good fit, more often than not due to the fact that the market itself has not yet been established.

  1. A field worker’s device: This is something that Ben Bajarin has noted in several articles. In the field, many workers still carry around paper documents and fill in paper forms. There is non-consumption of IT in these workflows. Tablets will inevitably be the instruments that bring IT to these areas, but it will have to be accompanied by customised software solutions designed for the task.
  2. Organised education: Although there is a lot of educational software for tablets which parents use to help develop their children’s skills, iPads are still just starting to be used in schools. I’m sure that the US is the leader in this area, but I’m sure there are still a large number of children who are not able to use personal iPads or other computer devices at school. The situation is even worse in other countries like Japan. The hurdle here is not in the tablets themselves, but in finding the best way to utilise tablets in teaching and training teachers to use them, and obtaining budget. There is also a lack of good teaching material for the teachers to use. This is an emerging market for which tablets are very well suited, but it requires much more than just tech. We have to wait for a lot of other infrastructure to catch up.
  3. Hardware as a service: Tablets can serve as the gateway for a service. For example, a cable TV company can include a tablet in your contract which you can use to view TV anywhere in your house, or save locally to view during your boring train commute. This has also been discussed many times, but the point is, this requires cable TV companies and/or other content distributors to get on board. This kind of negotiation will always take a long time to happen.
  4. A full replacement for PCs: In the long-term, it seems totally obvious to me that we will not be using PCs. Back in the 1990s, we were using computers that could not multitask efficiently and would crash many times during the day. In the 2010s, we are still using computers that can suddenly be infested with malware and have to protect by installing 3rd party software, and which degrade in performance over time requiring a fresh install. Although current operating systems have come a long way in addressing these issues, it is clear to me that a new approach to PC security and consistency is long overdue, and that the sandboxing approach taken by mobile OSes will eventually turn out to be the better path. Just like how we transitioned from cooperative multitasking systems without adequate memory management (Windows 95 and classic MacOS) towards full multitasking and memory protection (Windows XP and MacOS X), it seems inevitable that we will move towards fully sandboxed OSes for the vast majority of users. However, the capabilities of iOS are not yet sufficient to fully replace PCs. This will take time, but we have already seen Apple slowly address issues, first with iOS 8 extensions and now with many features in iOS 9. Given the current rate of improvement, by iOS 15 or so, it is totally reasonable to expect iOS to be able to fully replace PCs.
  5. New jobs: When you look at the impact that smartphones have had on our lives, one can clearly observe that it has hugely increased our consumption of computing. We browse the Internet in situations where it was previously unpractical. We all put our schedules into electronic devices. We share huge amounts of photos. Tech is not about device A replacing device B. Instead, it is about technology being used in new ways. It is about the situations where we couldn’t use tech, being converted to those where tech makes a significant contribution. In the same way, we should not try to find areas where tablets may replace current devices; we should try to find the remaining areas where people are not using technology. These are the areas where tablets can shine. There is no shortage of these areas, but we have to keep in mind that there is often a good reason why they have not been penetrated by tech. We have to keep in mind that in many cases, non-tech issues will have to be solved before tech can come in. A prime example of such out-of-the-box thinking is the recent collaboration between Japan Post, Apple and IBM to bring iPads to Japanese senior citizens.

What this complexity means

Because the tablet market is so complex and has many independent jobs-to-be-done, the sales data that we are seeing is simply an aggregate value that tells you very little about what is actually happening. The decline in tablet sales does not necessarily mean that the long-term prospects are dim because these data do not expose nascent growth segments. It is very likely that we initially saw rapid adoption due to jobs in the first category (jobs where the iPad was already a good fit), but this market levelled out as smartphones evolved. On the other hand, I expect the jobs in the second category (jobs where the iPad is not yet a good fit) are just getting started. However, jobs in the second category were not previously associated with IT and hence there is often little infrastructure in place and no budget allocated. This means that it will take time for the second category to gain significant traction. At the same time, it is hard to gauge the market size of the second category.

What we can expect is that in the mid- to long-term, jobs in the second category will definitely start to gain traction. Furthermore, as long as Apple keeps the faith, tablets will improve to the point where they can fully replace laptops in not only the common tasks, but in virtually all tasks. What we do not know yet is what the size of the tablet market will be at this point in the future.

Content Creation on Smartphone, Tablets and Watches

It surprises me that some people still say that smartphones and tablets are only good for content consumption, and not content creation.

That is only true if you totally ignore all the status updates on Twitter, Facebook, Instagram, etc. and declare that content on these social networks is too trivial and unimportant to be considered content.

One has to understand that the meaning of “content” has changed a lot with the development of technology. The content that was inscribed on the walls of the pyramids, for example, is very different from the random BuzzFeed article about Justin Beiber. Similarly, the content in the mobile age will be very different from the long-form blog-ish content of the Web 2.0 era. It will be more short form, more photos, and more multimedia. And for this type of content, smartphones generally trump PCs as content creation devices.

This will also be true of smartwatches. Whether or not smartwatches will become content creation devices depends not so much on whether they are good for writing long emails or blogs, but more on how communication forms evolve. And we can make a sure bet that the communication forms will evolve towards the most popular devices, hence if smartwatches become popular, then content will evolve to be better suited for these, which means shorter and more textual or emoji. With the huge strides being made in speech recognition, it is very likely that smartwatches will easily gain the capability to create these kinds of content.

What is important is that one has to recognise that both sides of the coin will evolve in concert. Saying that smartphones and tablets are not good for content creation basically shows how outdated your view of content is.

Sustaining Innovation and Disruptive Innovation in Cameras

A recent tweet from @charlesarthur on the camera market very nicely captured the difference between sustaining innovation and disruptive innovation. Let me explain.

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  1. Digital cameras started penetrating the consumer market around the year 2000. They were initially had very bad resolution and colours were inaccurate. Battery life was also a huge issue. Despite this, they took off in sales because you could view your photo immediately after you took it, and you didn’t have to go to your local photo processor.
  2. Initial deficiency is a hallmark of disruptive innovations. Disruptive innovations often start off as a “toy” that however provides significant convenience to low-end users. In this sense, digital cameras completely fitted the bill.
  3. However, if you look at the players in the market before and after the digital revolution, you notice that they are almost identical. The exception is that Casio gained significant market share (due to first mover advantage). Otherwise the main players, Nikon, Canon, Olympus all maintained their positions and enjoyed increased sales during 2000-2010. Clearly, digital cameras did not end up being disruptive to the film-camera market. Instead it was sustaining.
  4. The reason for this is that the incumbent film-camera makers were motivated to make the shift to digital. Digital cameras were significantly more expensive than film cameras and drove a replacement cycle that would not have been existent without the new technology. This was financially very appealing to the incumbents. There were technical hurdles like manufacturing the CCD cameras. However, there were modular CCD manufacturers who were willing to supply these to the previously film-only camera makers. Hence film-cameras makers were both willing and capable of making the shift to digital. This is why only Casio, with its first mover advantage, was able to gain significant footing among the film-camera incumbents.
  5. Since 2010 however, the incumbent camera makers have collectively seen a large drop in sales. This is due to cameras on smartphones. Instead of the traditional camera makers, the winners in this new market are Apple, Samsung, LG, HTC, etc. They are the smartphone makers. What happened here is unmistakably disruption.
  6. Smartphone cameras were also initially very poor compared to the regular digital cameras. Like digital cameras ten years before, they also started out as “toys”, which however provided significant convenience to the user because you could immediately upload the photos to the Internet. Technology-wise, smartphone cameras were no better than digital cameras were in the year 2000, relative to the incumbent products.
  7. The very different outcomes are a result of the difficulty of transitioning to the new market. I don’t mean difficulty in technology. I mean difficulty in flipping the whole organisation from top to bottom. For film-camera makers, it was relatively easy to transition to the digital-camera market. They were still selling cameras through the same channels to the same users. Film camera makers did not have to change their business models or their sales and marketing organisations at all. The only issue was technology and even this was easily overcome through modularity. However, for camera makers to transition to the smartphone market, they have to change their technology focus, their distribution channels, their sales and marketing organisations and everything else in between. This was too much for them to do. Instead, they focused on the higher-end of the market (digital SLRs and mirrorless cameras) where they could still thrive while maintaining their organisations and business models which worked, but only until smartphone cameras became good enough for all except the most demanding photographic tasks.

So there you have it. The takeaway here is that the most important element of a disruptive innovation is whether the incumbent is motivated and capable of embracing it or not. If the incumbent embraces the innovation, then disruption will not occur. However, if the incumbents don’t do so, then they will be disrupted.

It is usually not the technology that decides whether disruption will succeed or not, but rather whether or not the company organisation is capable of embracing it.