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Category Theory

Competing effectively against your most potent competitor

New market disruptions take root in non-consuming contexts. For instance, mobile phone photography began not because early phone cameras were good. They weren’t good at all but good enough when a camera was not within reach. The quality was poor but the photo taken would not have otherwise been taken, making a lousy photo better than no photo.

The result is that the total number of photos taken this year will be ten times higher than the total number of photos taken before the advent of mobile phone cameras.[1]

This rush to use the phone as a camera has meant that phone makers are keen to improve their product (so as to compete effectively with it against each other) and as a consequence they overtake the incumbent camera makers in quality as well as quantity.

The same phenomenon was experienced by fixed component “Hi-Fi” audio products. The quality of mobile music was poor but it was convenient and convenience translated into consumption and consumption translated into quality improvement and eventually the evaporation of usage of the traditional category.

Now consider how ad dollars are getting spent. The following chart shows the eMarketer forecast for ad spending mix across different media in the US.

Screen Shot 2014-07-02 at 7-2-8.12.01 PM

It would appear that the “Mobile” media is competing effectively against the other media types, especially the non-Mobile digital (i.e. PC-based experiences).

However, if we look at the absolute spending forecast the picture shows that Mobile is responsible for most of the growth in the overall spending.

Notes:
  1. The total number of photos taken in 2014 is likely to be around 880 billion. Prior to 2000 the total number of photos ever taken is estimated at 85 billion. []

The Disruption FAQ

Q1. What is disruption?

Disruption happens when the strong are defeated by the weak. More precisely it’s when those with unconstrained access to resources have them taken away by those with minimal or no resources. It’s a phenomenon that is in contrast to sustaining competition where the strong get stronger.

Q2. How can disruption happen? Don’t the strong always have an advantage over the weak?

The strong can be defeated when the fight is unfair. More precisely, “strength” is only a perception based on convention or historic precedent. The entrant may be weak in resources but may be strong in a way that is not seen as conventionally useful or valuable such as agility or a willingness to learn.

Q3. What makes a fight unfair?

A fight is unfair if the opponents fight according to different rules. This is also called asymmetric competition. Asymmetry is an important concept in game theory, economics and military science.

Q4: Is there a way to know disruption is about to happen?

Disruption theory is an attempt to reliably identify winning challenges. It includes a method of analysis of “the setting” of the fight and “the weighing” of the fighters. In other words, it measures whether the challenger is sufficiently asymmetric and whether the incumbent is flexible enough in their likely response. If there is insufficient asymmetry the theory would suggest the challenger will lose, and vice versa.

Q5: How often does it happen?

In some industries it happens quickly and in some industries slowly and in some never at all. Determining the cause of the rate of disruption is an important research topic. We can hypothesize that industries which show frequent disruption also show a high degree of wealth creation. The inverse is also true: industries that don’t get disrupted don’t create much wealth.

Q6. How do incumbents react to asymmetric challenges?

This quote (mistakenly attributed to Gandhi) describes it best: “First they ignore you, then they laugh at you, then they fight you, then you win.” The main test of asymmetry is to ask whether a challenger’s entry is ignored (or welcomed) by the incumbents. Most asymmetric challenges are not taken seriously because they initially benefit the incumbent. The side-effect is that it lulls them into a sense of security resulting in a lack of response. Challengers have the child-like advantage of rapid growth and learning while incumbents are encumbered by their size and lack of flexibility.

Q7: Why don’t challengers respond in kind?

Mainly because they don’t feel that they need to. The newcomer is either not seen as a threat or welcomed because the customers they obtain that are not seen as valuable. In some cases the business model of the entrant is contrary to that of the incumbent. In other words, the challenger makes money in a way that would cause the incumbent to lose money. Often the challenger is actually invisible because she misdirects attention. They may be seen as competing in one market with a certain set of competitors but their effect is in another market which never had to deal with a challenger.

Q8: If there are different ways disruption can be observed, doesn’t that mean there are different types of disruptions?

Yes. When a competitor challenges with a cheaper product that seems to perform poorly and has low margins and the incumbent accepts the entry because it allows them to concentrate on more profitable customers then this is called a “low-end disruption”. Here the asymmetry is in cost structure. The entrant has lower costs and accepts lower profit margins and may “make money” in new or different ways.

When a competitor misdirects attention by selling a product that draws usage from existing customers and adds non-consuming new customers because it enables new uses, then the incumbent feels no pain from the entry because they don’t sense a reduction in customers. We call this a “new market disruption“. The challenger gains a foothold and grows/evolves, eventually capturing customers exclusively. Here the asymmetry is in the basis of competition and measurement of “performance”. The new product does not actually do the same thing as the incumbent product or does a subset of valuable tasks poorly while excelling at menial tasks. The entrant may be highly profitable but they are not taking profits away from incumbents because they “grow the pie”, capturing value by fulfilling unmet needs.

Disruption can also happen to professions and institutions when less skilled individuals are enabled to perform complex jobs or when professionals can establish good enough services that used to take institutional support. This is called professional services disruption.

Technological change is often (but not always) the core enabler in creating disruptions. The analogy is that technology is a weapon that allows asymmetric combat but the combatant is the disruptor, not the weapon[1].

Q9: It sounds like the trick to spotting disruption is in perceiving when the fight becomes “unfair” and an outsider advantage is gained. Does the theory make this easy?

It makes it possible but not easy. Understanding when a basis of competition changes and where competition is shifting is still very difficult. It is notoriously difficult to sense when it’s happening to you because you are working toward a strategy with assumptions that have been tested and proven to be correct. In other words, you, your colleagues, your competitors and everyone you’ve ever met knows the rules of the fight. Insider status makes you an expert, your knowledge is far beyond a lay person’s and you have a track record of winning. Hubris and pride makes it difficult to accept a challenge from an ignorant outsider.

Furthermore, an outside analyst who is not suffering from these psychological weaknesses may not have the means to measure change because they don’t have access to market metrics. So you can’t typically hire a consultant to help you spot it. This is where the theory helps. If you are a practitioner then you can use the theory as a lens to see the patterns in the operating data.

The proper application of the theory requires domain knowledge or deep reading of weak signals. It’s best employed by incumbent operating managers analyzing their own industry. It’s a tool that can be used to overcome the perception of incumbent invulnerability. It is not a tool that can be used by armchair generals. They can pick up the lens but, not having any data to look at, they have have no patterns to recognize. (This last point is disputed. See comment.)

By the way, entrants don’t benefit much from it either because they act disruptively by instinct. They enjoy the freedom of having nothing to lose.

Q10: How long does this take? Isn’t a shift in competition natural over a few decades?

The speed of disruption is changing rapidly. It used to take decades but now it takes years and in some software industries it could be happening in less than one year. When it used to take decades it did not matter much because the “victims” of a disruption usually could spend a career in the firm being disrupted and would not have to adjust their behavior or assumptions. The consequences would have been felt by future generations. The rate of disruption today is so rapid that many careers and lives and families are having to deal with the consequences, sometimes more than once. Estimating the acceleration and scope of disruptive change is a great research topic.

Q11: Is the theory complete? Can’t we just write an app for it?

It’s not complete. It cannot be encoded as a deterministic algorithm. It’s not even likely that expert systems or neural networks or machine learning can help. This is because perception of change in competition is a skill informed as much by intuition as by data and rules. If the theory is developed further, through a process of theory building, then it might become an app.

Q12: If the theory is not complete, then isn’t it useless?

A theory is not useless if it’s imprecise or difficult to use. Data that would make conclusions precise is often missing or unavailable. The theory relies on weak signals and explains what used to be unexplainable. Many sciences developed from empirical analysis similar to where we are with disruption theory. Theories benefit from development.

Q13: Is the theory being developed further?

Yes. There is a process for theory building which has been ongoing for over a decade where many researchers, students of disruption and practitioners are contributing.

Q14: Can the theory be applied outside of business competition?

Yes, institutions can be disrupted as can individuals. Possibly even economies and states. This is because a growing technological base and communications enable asymmetries of ever-greater scope and speed. The research needed to establish how this happens is under way. However it’s important to know the limits of the phenomenon. Incumbents are getting wiser as they wield the theory and some “settings” show resistance to change and thus prohibit technological cores to be utilized disruptively. The study of these anomalies is essential to the process of theory building.

Q15: Is disruption a force of nature? Has it always existed? Will it never end?

Oral traditions suggest that people have been aware of disruptive forces for all of history. We feel it in the school playground and in many personal relationships. It’s in the Bible and the classics that predate it. It’s visible in all cultures. Disruption theory as applied to business and government is only an extension of this causal individual behavior into complex systems. It’s possible that awareness of it might cause the behavior to change, or, put another way, that if you observe and understand the phenomenon, that knowledge could cause it to stop happening. But the systems involved are vast and learning curves are long. Enlightenment may take a few lifespans.

Update:

Here are questions which have been added based on reader feedback. Please feel free to suggest others in the comments.

Q16: Isn’t Disruption just evolution of business models?

Business models evolve, but if the evolution sustains an existing incumbent then it’s not a disruption. If an evolution is  adopted by an entrant who then proceeds to strip the assets and profits from an incumbent then it’s a disruptive change. The key question is why do some changes get adopted and not others.

Q18: What have been the major improvements in the theory since its introduction in 1997′s The Innovator’s Dilemma?

From Clay Christensen’s work alone: New Market Disruptions, Professional Disruption, Value Chain Evolution Theory, Jobs to be Done Theory. The Innovator’s Solution including how to respond with autonomous self-disruption, the role of acquisitions, the study of Healthcare and Education as targets of (and anomalies to) disruptive change. The process of theory building. The Capitalist’s Dilemma and how economies create incentives and disincentives to disruptive innovations.  Many other contributions from researchers too numerous to cite here.

Q19: What industries cannot be disrupted

Industries which experience no disruptions are “anomalous” in that the theory suggests that technological progress forces change and technologies have proliferated in almost all industries..  Industries or institutions which have remained largely undisrupted include Energy, Education, Government, Healthcare, Airlines and Hotels. The study of these anomalies continues and explanations identify conditions that prevent growth. Dependencies on regulation, infrastructure, and absence of technological core enablers caused some of the atrophy to date. However signals of change are appearing in all these industries and paths to disruption are clearly possible.

Q20: How is it possible that companies which were claimed to be disrupted are still around and some which are claimed to be disruptors have vanished?

Being disrupted does not mean ceasing to exist. Being disrupted is a loss of a specific encounter, but not necessarily a terminal loss. Being a disruptor is a win in a specific encounter and not a guarantee of immortality. Indeed many disruptors come to be disrupted and the theory suggests sustainable growth requires self-disruption. Also a disrupted company can be re-configured post-disruption into another entity or can muddle along with limited value indefinitely. Sometimes they can rise up and become disruptors again.

Notes:
  1. See David vs. Goliath: using a projectile allowed David to overcome Goliath but only when wielded skillfully []

Ten years ago: Clayton Christensen on Capturing the Upside

You can hear this as an MP3.

[It's important to understand just how much the theory has evolved in the last 10 years. Much more perhaps than in its first eight.]

Doug Kaye: Hello, and welcome to IT Conversations, a series of interviews recording and transcripts on the hot topics of information technology. I am your host, Doug Kaye, and in today’s program, I am pleased to bring you this special presentation from the Open Source Business Conference held in San Francisco on March 16 and 17, 2004.

Mike Dutton: My name is Mike Dutton, and it is my pleasure to introduce to you today Clayton Christensen. Professor Christensen hardly needs an introduction. His first bestseller, “The Innovator’s Dilemma,” has sold over half a million copies and has added the terms “disruptive innovation” to our corporate lexicon. His sequel — and you have to have a sequel to be a management guru — is entitled “The Innovator’s Solution” and is currently Business Week’s bestseller’s list. Professor Christensen began his career at the Boston Consulting Group and served as a White House fellow in the Reagan administration. In 1984, he cofounded and served as chairman of Ceramics Process Systems Cooperation. Then, as he was approaching his 40th birthday, he took the logical step of quitting his job and going back to school, where he earned a doctorate in Business Administration from Harvard Business School. So, today he is a professor of Business Administration at Harvard Business School where teaches and researches technology commercialization innovation. Professor Christensen is also a practicing entrepreneur. In 2000 he founded Innosight, a consulting firm focused on helping firms set their innovative strategies. And according to a recent article in Newsweek, “Innosight’s phones ring off the hook, and the firm cannot handle all the demand,” very similar to all the startups in open source here today. So, please join me in welcoming Clayton Christensen.

Clayton Christensen: Thank you, Mike! I’m 6 feet 8, so if it’s okay, I’ll just…the mic picks up okay. I’m sure delighted to be with you, especially because there is blizzard in Boston today; my kids have to shovel the snow!

As Mike mentioned, I came in to academia late in life, and the first chunk of research that I was engaged in was trying to understand what it is that could kill a successful, well — run company. And those of you who are familiar with it, probably know that the odd conclusion that I got of that was that it was actually good management that kills these companies. And subsequent then to the publishing of the book that summarized that work, “The Innovator’s Dilemma,” I’ve been trying to understand the flip side of that, which is if I want to start a new business that has the potential to kill a successful, well — run competitor, how would I do it? And that’s what we tried summarize in the book, “The Innovator’s solution.” It’s really quite a different book than the “Dilemma” was, because the “Dilemma” built a theory of what is it that caused these companies to fail. And then in the writing of this solution, I’ll just give you analogy for where we came out on how to successfully start new growth businesses.

I remember when I first got out of business school and had my first job. I was taught the methods of total quality management as they existed in the 1970’s, and we had this tool that was called a “statistical process control chart.” (Do they still teach that around here?) Basically you made a piece, you measured the critical performance parameter and you plotted it on this chart, and there was a target parameter that you were always trying to make the piece to hit, but you had this pesky scatter around that target. And I remember being taught at the time that the reason for the scatter is that there is just intrinsic variability and unpredictability in manufacturing processes.

So, the methods that were taught about manufacturing quality control in the ‘70’s were all oriented to helping you figure out how to deal with that randomness. And then the quality movement came of age, and what they taught us is, “No, there’s not randomness in manufacturing processes.” Every time you got a result that was bad, it actually had a cause, but it just appeared to be random because you didn’t know what caused it. And so the quality movement then gave us tools to understand what are all the different variables that can affect the consistency of output in a manufacturing operation. And once we could understand what those variables were and then develop methods to control them, manufacturing became not a random process, but something that was highly predictable and controllable.

▶ Horace Dediu: “Transformation of Business and Society through Technology”

My talk on the future of things from Censhare’s FutureDay 2014 in Munich.

Who Solved the Capitalist’s Dilemma?

In The Capitalist’s Dilemma, Clayton Christensen and Derek van Bever introduce a powerful new theory which explains the relative paucity of growth in developed economies. They draw a causal relationship between the mis-application of capital in pursuit of innovation and the failure to grow.[1]

In particular, they observe that capital is allocated toward the type of innovations which increase efficiency or performance and not toward those which create markets (and hence long term growth and jobs.) This itself is caused by a prioritization and rewarding of performance ratios rather than cash flows and that itself is due  to a perversion of the purpose of the firm.[2]

For this statement of causality to be confirmed we need to observe whether it predicts measurable phenomena. For instance, we need to see whether companies which create markets apply capital toward market-creating innovations and whether companies which create value through efficiencies or performance improvements hoard abundant capital.

Over the entire global economy, the pattern of capital over-abundance is easy to see. The amount of cash or securities on balance sheets is extraordinary and unprecedented (estimated at $7 Trillion, doubling over a decade). However, growing cash is not a perfect indicator of inactivity. Cash is the by-product of earnings after investment. So if operating profits are growing and investment is growing, but not as fast, then it’s possible to grow cash while still growing investment.

The better measure is investment in capital equipment or, more specifically, purchases of plant, property and equipment.[3] Indeed, on a global scale, capital expenditure as a percent of sales is at a 22-year low.

CapEx is a good proxy for non-financial “investment”. It’s also a measure that can be easily obtained as companies report this activity in their Cash Flow Statements.

So the best method for assessing the theory’s predictive power is to look at market creators and measure their investment in PP&E. At the same time we need to look at market sustainers and measure their (probable) lack of investment in PP&E.

So here is my first attempt:

Screen Shot 2014-05-27 at 5-27-3.25.43 PM

It’s an admittedly small sample of companies that are not that dissimilar. But within this group, over the time frame of about 9 years, we can see how capital expenditures are growing.[4] This sample shows that for a few companies, the amount spent on capital equipment grew dramatically. Especially since they are in businesses that might be thought of as not capital intensive.

Notes:
  1. and, indirectly, in the increase in inequality and hence the destabilization of socio-political institutions []
  2. That being the creation of customers not shareholder returns []
  3. Operating expenditures can also be measured but they cannot grow inorganically due to most of the costs being related to skilled employment which has supply constraints. []
  4. Note that Apple’s data extends to the end of their fiscal year and reflects their forecast given last October in the 10-K filing []

Categorizing technologies

In the graph below the grey circles represent the US penetration (percentage of households which own) MP3 players.

Screen Shot 2014-05-19 at 5-19-7.55.22 PM

Superimposed on this sparse sample graph is a line showing the sales of iPod touch. This second graph has a different scale, shown with a gridline at 10,000, representing millions of units shipped by Apple. To smooth out seasonality I show the trailing four quarter average with a thick line.

The correlation is fairly evident. As iPod sales grew, penetration grew and “peak MP3″ was recorded in September 2010 while peak sales occurred at the end of that year.

It’s not a stretch to say that iPod touch sales are causal to MP3 penetration, especially since the iPod has remained the market share leader in the segment for a long time (at least 70% share) and that the iPod touch is consistently half or more of the iPod.

The absence of data for penetration beyond 2012 is therefore not a problem. We can assume that MP3 devices have a finite lifespan and, if not replaced, the penetration will decline.

I modeled both the increase and decline with a diffusion curve as follows:

Postmodern Computing (Summit)

Screen Shot 2014-05-12 at 7.03.42 AM

Steve Jobs famously said that Apple stands at the intersection of of Technology and the Liberal Arts. He said it more than once because he thought it was an important distinction of the company.

In an intuitive way, the message may have gotten through to the average person, but I don’t think professional observers and managers of technology have quite grasped what he meant.

It’s not a glib throw-away marketing phrase. I can imagine many other, more evocative ways of saying that Apple blends the hard and the soft; the heart and mind, if you will.

His choice of words makes me believe that he meant it as a fundamental blending of two disparate and considered-opposite concepts, rather like yin-yang: things which do not naturally mix but which are complementary, interconnected, interdependent, and give rise to each other.

This interaction however is not well understood and even more rarely exploited. The reason they don’t mix well in business in particular is that individuals are typically not trained in both. Our education systems (from where these phrases originate) are unwilling or incapable of providing us with a grounding in both, so individuals tend to absorb only one or the other.

But it turns out that the interaction between these nominal opposites have determined our world to date and will continue to determine our fate. A cursory review of history shows that the “soft”, perceptive and feeling-based disciplines always combined with the analytical and judgmental to create a future which neither could create alone.

I note how Apple uses this combination to an advantage and have also used this methodology myself to understand and sense the future. Taking this method further, I would like to share it with others. I would like to recognize some faint but powerful patterns and bare some of the more audacious conclusions of my analysis.

The method chosen is a forum we are convening called The Post Modern Computing Summit.

It’s a small gathering where we are inviting the most enlightened thinkers of the future of computing to lead us into its next age, and perhaps, tentatively, the next era of civilization.[1]

Notes:
  1. We’ll also answer the questions of where tablets are going, and where they will takes us, what is the future of apparel computing, what does intimate computing mean and who will benefit and who won’t. []

Innoveracy: Misunderstanding Innovation

Illiteracy is the inability to read and write. Though the percent of sufferers has halved in the last 35 years, currently 15% of the world has this affliction. Innumeracy is the inability to apply simple numerical concepts. The rate of innumeracy is unknown but chances are that it affects over 50% of us. This tragedy impedes our ability to have a discourse on matters related to quantitative judgement while policy decisions increasingly depend on this judgement.

But there is another form of ignorance which seems to be universal: the inability to understand the concept and role of innovation. The way this is exhibited is in the misuse of the term and the inability to discern the difference between novelty, creation, invention and innovation. The result is a failure to understand the causes of success and failure in business and hence the conditions that lead to economic growth.

My contribution to solving this problem is to coin a word: I define innoveracy as the inability to understand creativity and the role it plays in society. Hopefully identifying individual innoveracy will draw attention to the problem enough to help solve it.

One example is in the following quote:

“Lastly, nationally circulating tabloid Ilta-Sanomat gets a look at Nokia’s fabled tablet computer that was developed nine years before the iPad hit the market. According to the paper, Nokia had its own innovative tablet device ready in 2001, but unfortunately it never made it to the shops. A former Nokia expert Esko Yliruusi says that the project was suspended a heartbeat before the tablet hit the market because it was thought that there was insufficient demand for such a device.”[1]

To explain what’s wrong with this usage we need some definitions.

The definition of innovation is easy to find but it’s one thing to read the definition and another to understand its meaning. Rather than defining it again, I propose using a simple taxonomy of related activities that put it in context.

  • Novelty: Something new
  • Creation: Something new and valuable
  • Invention: Something new, having potential value through utility
  • Innovation: Something new and uniquely useful

The taxonomy is illustrated with the following diagram. The position of the circles shows the embedding of meaning[2]

Screen Shot 2014-04-18 at 7.54.26 AM

To illustrate further, here are some examples of the concepts.

  • Novelties: The choice of Gold as a color for the iPhone; the naming of a version of Android as “Kit Kat”; coining a new word.
  • Creations: The fall collection of a fashion designer; a new movie; a blog post.
  • Inventions: Anything described by a patent; The secret formula for Coca Cola.
  • Innovations: The iPhone pricing model; Google’s revenue model; The Ford production system; Wal-Mart’s store design; Amazon’s logistics.

The differences are also evident in the mechanisms that exist to protect the works:

  • Novelties are usually not protectable but since their value is very limited the copying is not seen to cause harm.
  • Creations are protected by copyright or trademark but are not patentable since they lack utility.
  • Inventions can be protected for a limited time through patents but can also be protected indefinitely by being kept secret. Their uniqueness may also be the means by which they can be kept a secret.
  • Innovations can be protected through market competition but are not defensible through legal means.

Note that the taxonomy has a hierarchy. Creations are novel, inventions are creations and innovations are usually based on some invention. However inventions are not innovations and neither are creations or novelties. Innovations are therefore the most demanding works because they require all the conditions in the hierarchy. Innovations implicitly require defensibility through a unique “operating model”. Put another way, they remain unique because few others can copy them.

To be innovative is very difficult, but because of the difficulty, being innovative is usually well rewarded. Indeed, it might be easier to identify innovations simply by their rewards. It’s almost a certainty that any great business is predicated on an innovation and that the lack of a reward in business means that some aspect of the conditions of innovation were not met.

The causal, if-and-only-if connection with reward is what should be the innovation litmus test. If something fails to change the world (and hence is unrewarded) you can be pretty sure it was not innovative enough.

Which brings us to the quote above. The fact that the Nokia tablet of 2001 not only did not succeed in the market but was not even released implies that it could not have been innovative. The product was only at the stage of perhaps being an invention (if it can be shown to be unique) or merely a creation (if it isn’t.) Furthermore, if the product is so poorly designed that it is literally unusable then it is just a novelty. A design, sketch or verbal description might be novel but it does not qualify as an innovation or an invention or even a creation. How far the depiction went toward making a dent in the universe defines its innovativeness.

Why does this matter?

Understanding that innovation requires passing a market test and that passing that test is immensely rewarding both for the creator and for society at large means that we can focus on how to make it happen. Obsessing over the mere novelties or inventions means we allocate resources which markets won’t reward. Misusing the term and confusing it with activities that don’t create value takes our eye off the causes and moves us away from finding ways of repeatably succeeding.

Recognizing that innoveracy is a problem allows us to address it. Addressing it would mean we could speak a language of value creation that everyone understands.

Wouldn’t that be novel?

Notes:
  1. A video showing the device is here, in Finnish. []
  2. The size of the circles also suggests degree of effort required and potential reward. Note that this is not a Venn diagram. []

Postmodern computing

There are 7.1 billion people on Earth. Coincidentally there are also 7 billion mobile connections.  Those connections are held by 3.45 billion unique mobile subscribers.[1] Unsurprisingly, the largest national mobile markets (by number of subscriptions) correspond closely to the most populous nations.

Screen Shot 2014-04-07 at 7.21.46 AM

Considering smartphones, last year 1 billion smartphones were sold and the number of smartphones in use is about 2 billion[2]

Given the rapid adoption of smartphones, it’s also safe to assume that smartphone penetration will follow population distribution. In the US, where comScore data is published monthly, penetration is following a predictable logistic curve.

Screen Shot 2014-04-07 at 7.55.13 AM

 

Assuming similar patterns world-wide we can forecast regional smartphone penetration. Screen Shot 2014-04-07 at 7.56.49 AM

This yields the following forecast for smartphone usage world-wide.

Notes:
  1. GSMA []
  2. There are also about 2 billion 3G/4G connections world-wide []

The price is right

One of the axioms of hardware business is that prices fall over time. The consumer price index for personal computers and peripheral equipment from 1998 to 2014 is shown below:

CUUR0000SEEE01_Max_630_378

The price index suggests that prices for computers should be 54% of 2007 levels. Charles Arthur illustrated this on a global basis using a separate set of data.

The data shows that the weighted average selling price (ASP) of a PC has fallen from $614.60 in the first quarter of 2010 to just $544.30 in the third quarter of 2013, the most recent date for which data is available.