Barcelona, Spain - Today at Mobile World Congress, Nokia unveiled five new affordable handsets including a new family of smartphones debuting on the Nokia X software platform. Based on the Android Open Source Project AOSP, and backed by Nokias deep ties with operators, the Nokia X platform gives AndroidTM developers the chance to tap into, and profit from, a rapidly expanding part of the market.
Today's announcement is consistent with the declaration of Nokia is engaged in a "war of ecosystems." Note that this is in contrast to "a war of platforms" or a "battle of operating systems" or a "competition of devices."
Devices are commoditizing, operating systems are commodities and the Android platform is a commodity. Value will not be captured in any of these technology modules. Ecosystems are another matter. It's where Facebook (and its acquisitions) reside. It's where Google lives and it's where iTunes has been for a decade.
Nokia's adoption of AOSP as an operating system is consistent with the ecosystem strategy set forth three years ago, and is also consistent with Microsoft's competitive strategy.
Which is why I believe Microsoft is not only comfortable with this development but had agreed to it over a year ago when work on this initiative was already well under way.
In 2013 there were 18.8 times more Windows PCs sold than Macs. This is a reduction in the Windows advantage from about 19.8x in 2012. This decline is mostly due to the more rapid decline in Windows PC shipments relative to the more modest decline in Mac unit shipments. Gartner estimates that about 309 million Windows PCs were shipped, ((This figure is not published publicly but can be derived from subtracting Mac shipments from the total PC shipments which are published)) down from 337 million in 2012 (which was down from 344 million in 2011, the year PCs peaked.) I estimate about 16.4 million Macs were shipped in 2013 down from 17 million in 2012.
The history of PC shipments relative to Mac shipments is shown in the following graph:
I chose to graph the Mac data as an area with additional areas for iOS devices layered on top.
When comparing these platforms, the contribution of the Apple mobile platform becomes striking.
Nevertheless, it's still important to understand the role of the Mac. In years gone, the advantage of Windows was measured in multiples of Mac sales. That peak occurred in 2004 when there were 56 times more PCs sold than Macs. At that moment, when the Windows advantage peaked, the Mac sold 3.2 million units into a market where 182 million PCs shipped. This means the Mac had 1.7% market share.
And yet, remarkably, even with 1.7% share, the Mac did not disappear. The figure of 3.2 million units was not great and below the peak to date ((which was 4.5 million in 1996)) but it was enough to sustain Apple while it developed its next products. At the time the iPod was starting to grow rapidly and development on iPhone/iPad was already underway. The point being that there were new products. 3.2 million was a sufficient volume to preserve the company until such time when they would be ready.
Today the situation is quite different. The total number of platform products Apple sold in 2013 was about 260 million ((This includes my estimates for Q4. We'll have the exact figure in a few days.)) The total number of users Apple has is above 550 million. ((Possibly 600 million.))
Note the effect in the graph above. Even if we only consider the Mac, the Windows advantage has decreased considerably, and the platform was certainly not extinguished. The new form factor Mac Pro and the continuing improvements in the thinnest of laptops shows how Mac has not just survived but prospered as the underdog which easily captures the bulk of profits.
But the bigger story is how Apple's mobile platform has nearly reached the sales volume of Windows. In 2013 there were only 1.18 more Windows PCs than Apple devices sold. Odds are that in 2014 they will be at parity. ((The prediction I made in 2012 was that "it’s safe to expect a “parity” of iOS+OS X vs. Windows within one or two years". The data so far does not change this expectation.))
But will it last?
It's important to understand just how the quantities involved here have a quality of their own. The quantities themselves speak of a change. It's not convincing to suggest that what comes around goes around and a reversal of fortune can be reversed yet again when there are several zeros added to the end of the figures involved.
We have to understand that the Windows advantage itself came from the way computing was purchased in the period of its ascent. In the 1980s and 1990s computing platform decisions were made first by companies then by developers and later by individuals who took their cues from what standards were already established. As these decisions created network effects, the cycle repeated and the majority platform strengthened.
But it was the large companies who made the core decisions. In the 1980s if the Fortune 500 companies all standardized on Windows then their suppliers and customers would also standardize on it. Add governments and other institutions and 80% of the market is probably decided. There was concentration in decision making. In other words, in the 80s a platform could win by convincing 500 individuals who had the authority (as CIOs) to impose through fiat a standard on the centers of gravity of purchasing power.
Today, with mobile products there are billions of decision makers. 500 decisions mean nothing. In fact, Apple with at least 500 million loyal and wealthy users is considered to be in a precarious situation. That's partly due to the way other platforms like BlackBerry and Symbian found themselves in crisis with tens of millions of users. ((and hundreds, perhaps thousands, of corporate buyers deciding to support its platform exclusively. What IT does matters for little.))
The decision making process for buying computers, which began with large companies IT departments making decisions with multi-year horizons, has changed to billions of individuals making decisions with no horizons. Companies have become the laggards and individuals the early adopters of technology.
The fundamental shift is therefore in the quantity of decision makers and the quality of those decisions. Those who buy are also those who use and their decisions will be perhaps whimsical, maybe impulsive and not calculated, but fundamentally, in the aggregate, wise.
Ultimately, it was the removal of the intermediary between buyer and beneficiary which dissolved Microsoft's power over the purchase decision. It's not just unlikely that this situation will be reversed, it's impossible. Computing decision making has moved to the furthest edge where use has been for decades. The computer has become personal not just in the sense of how it's used but in the sense of how it's owned.
IBM Digital Analytics Benchmark (report is here) has published, for the fourth year in a row, US online shopping traffic data with a split between mobile and fixed online traffic. It reveals a pattern of consumer behavior which is quite startling: people seem to prefer to shop using mobile devices.
The data is shown below:
In terms of sources of traffic, mobile devices (including tablets) have increased from about 5% of all online traffic to 40% in four years. Last year the volume was 24% implying that 16 points of share were gained in one year. If that is extrapolated to next year then more than half of holiday shopping traffic in 2014 will be on mobile devices.
Put another way, next year less than half of users will hire a PC for the job of online shopping.
If this conversion from PC-based shopping to device-based shopping follows a logistic substitution curve then the conversion to devices will probably be 90% complete in another 5 years or by 2018 or 2019. I see no reason why this particular job to be done (shopping) should not be considered a proxy for other jobs as well. Therefore it's not a stretch to imagine that the transition to post-PC consumption will also be practically completed by 2020.
Within the data there is also a significant amount of detail beyond the mobile/non-mobile split in behavior. There is a distinction drawn between tablet and phone traffic and a further distinction between Android and iOS devices. ((The split between Android and iOS for tablets and phones was not published for 2013 but I extrapolated from previous years and assumed that 80% of tablet traffic was sourced from iPads vs 88% in 2012 and 99% in 2011. Note also that non-iPad traffic is assumed to be Android but that includes the Kindle and Nook products which are using partial and unsanctioned versions of Google's Android.))
This more detailed view of the traffic is shown in the following diagram:
A few observations:
The pattern of slowing tablet growth is likely due to the slowing growth in iPad sales. This itself is due to the lull in product launches as the shift to fall only iPad releases took place in 2012.
The consequence is that iPad traffic contribution only increased by 2 percentage points, from 10% in 2012 to 12% in 2013. Compare this with the doubling the previous year (from 5% to 10%).
Among phone users, both Android and iOS grew their contributions to traffic by roughly 100%. Android phone traffic increased from 4.2% of all traffic to 8.5% and iPhone traffic increased from 8.7% to 16.7%.
As we also know the approximate number of phone users for each platform (via comScore) then we can also determine the per user contribution of traffic of each platform. ((Note that this is phones only.))
The measure is "basis points of traffic per million users" and it is the result of taking the traffic data (in percent of total online traffic) and dividing by the population of users of a particular platform. The result is shown below:
The way to read it would be that each million iPhone users generated about 28 basis points of traffic while each million Android users generated about 11 basis points of traffic.
A way to compare these audiences would be to define the ratio between traffic usage by platform user. That ratio was
1.83 (iOS:Android) in 2010
2.16 in 2011
3.15 in 2012
2.51 in 2013
So, as far as phones are concerned, US iPhone users are about 2.5 times more likely to shop online than US Android phone users. The data is reliable: with the US population now over 65% penetrated with smartphones, these populations of users (totaling over 130 million) are vast and representative. As the technology is reaching deep into the late adopter segments the difference in behavior between iOS and Android usage is becoming easier to explain. We have to eliminate quirks of demographics or income or other possible causes.
The platforms themselves are becoming the last remaining suspects as causes for differences in the behavior of their users.
It may seem preposterous to suggest that a platform can affect shopping behavior but let's remember that the PC, the subject of this article, is a platform in itself. The migration of usage away from the PC to alternatives can only be explained by the alternatives being superior at the particular job that needs doing. The argument is naturally extendable to each alternative individually.
All theoretical and empirical diffusion studies agree that an innovation diffuses along a S-shaped trajectory. Indeed, the S-shaped pattern of diffusion appears to be a basic anthropologic phenomenon.
This observation dates as far back as 1895 when the French sociologist Gabriel Tarde first described the process of social change by an imitative "group-think" mechanism and a S-shaped pattern. ((Tarde was probably influenced by mathematician Pierre François Verhulst who first published the logistic function in 1845)) In 1983 Everett Rogers, developed a more complete four stage model of the innovation decision process consisting of: (1) knowledge, (2) persuasion, (3) decision and implementation, and (4) confirmation.
Consequently, Rogers divided the population of potential adopters according to their adoption date and categorized them in terms of their standard deviation from the mean adoption date. He presented extensive empirical evidence to suggest a symmetric bell shaped curve for the distribution of adopters over time. This curve matches in shape the first derivative of the logistic growth and substitution curve as shown below.
In the graph above I applied the Rogers adopter characterization to the data we have on the adoption of smartphones in the US. The latest data covering September is included.
The fact that smartphones in the US follow the theory is exciting, but what can we conclude about the adoption of specific platforms? There has been quite a bit of turnover in the leadership of the market in the first half of the time frame given. You can see this more clearly in the following fractional market share transformation.
Note that, with the exception of the iPhone, if each platform is studied individually, it would not follow a logistic (i.e. linear) pattern even though, as a whole, the technology does.
This then is the big puzzle: while we might be able to predict how smartphones will diffuse into society, we can't seem to predict how any single firm will fare. This means that an investor cannot make a credible "bet" on the technology ((Indeed investors often get burned when new technologies emerge. While the technology booms, individual firms supplying it often fail. See the history of transportation, communication, computing and energy.)). If they choose a single company as proxy, chances are they will lose. If they bet on a basket of companies then, again, chances are they will lose. There is usually one unforeseeably clear winner.
Before we get further into the question of picking winners or predicting the future division of share among rivals, we should understand the underlying causes for this pattern of adoption.
Rogers concluded that the learning behavior of individuals is the underlying cause of the symmetry of the diffusion process.
At the beginning, when an individual is confronted with a new (learning) situation they make many mistakes. These mistakes are gradually reduced (by learning) over time because more and more information is received and acts as a stimulus. The gain in learning per trial is proportional to the product of the amount already learned and the amount remaining to be learned before the limit of learning is reached.
Arnulf Grübler ((The Rise and Fall of Infrastructures, Physica-Verlag 1990)) explains:
This is exactly equivalent to the F(1-F) transformation of the logistic curve. It should be emphasized that these properties of the learning process were found in real learning situations and are confirmed by a large number of laboratory and field experiments. Thus each adoption of an innovation in a social system is equivalent to a learning trial by an individual. Thus, the symmetric diffusion pattern results from the way messages about an innovation are emitted and processed by social learning.
So these observers of the process assign learning behavior as the cause for adoption of a technology. Can the learning behavior be applied to individual platforms? It's tempting.
The hypothesis would go as follows: adopters are not only processing messages about the new technology but they are also trying different platforms as they enter and as they upgrade their phones. If we see platform choice as a learning process then if one platform has a natural advantage, it settles into a dominant position as users "learn" of its advantage. Conversely, if no platform has an advantage then platform "churn" repeats as rivals gain/lose positions of leverage in the market.
The pattern shown so far seems to point to Apple's iPhone having a logistic pattern indicating that it might be benefiting from a learning pattern. The alternative platforms may simply be jockeying for temporary advantage.
It's an interesting hypothesis. To be developed further we need to answer what any learnable advantage might be. I suspect it has to do with the ability to solve unmet and unarticulated needs. In other words, that the winning product solves a set of "jobs to be done" which are difficult to pin down and are perceived rather than defined.
Apple's latest product launch (new OSX, iPads, Macs and iWork/iLife) came with a change in pricing for software. OS X and iWork and iLife and updates are now made available free on new Macs and, in the case of the suites, on iOS devices as well.
Recall also that iOS updates are now free as well and that OS X had been reduced in price from about $129 to $29 with Snow Leopard in August 2009 and to $19 with Mountain Lion in July 2012. The iSuites have also dropped in price over time so the pattern of evaporating software prices is long-running.
But how fast and what is the impact? The historic performance Apple's Software business is not easily determined since it was always blended with additional businesses. Until September of last year, Software was reported as part of "Software and Services" and since then as part of "iTunes, Software and Services." Some assumptions allow the following picture to be drawn:
One additional wrinkle to the Apple software story is that OS X and iWork/iLife are not all the software titles available. Apple's software includes Pro apps as well as the non-free OS X server. The non-free software US prices are:
Aperture: $79.99
Final Cut Pro: $299.99
Motion: $49.99
Compressor: $49.99
Logic Pro X: $199.99
MainStage 3: $29.99
OS X Server: $19.99
Apple Remote Desktop: $79.99
Given that and additional assumptions can lead to the following picture of the components of Apple's Software sales (in $ million/quarter).
Given this picture of the software business and the change in pricing, here is my forecast for the third and fourth quarters (in $ million/quarter):
The foregone revenues could be as much as $450 million from what would have been received with existing pricing model.
So the question that naturally arises is whether this is "worth it". Whether by offering free software hardware or service revenues rise.
Perhaps. Certainly service revenue in the form of iCloud might rise with more usage of iWork and iLife. But I don't think that this is the calculus underlying the decision. Remember that Apple does not have a Profit/Loss accountability. It's not necessary (and perhaps not even preferred) that a division balances costs and revenues. ((The graphs in this post (and the preceding 1900 on this blog) were created using Numbers.))
Fundamentally Apple remains a systems company where software is a key element in its definition of value. That is not changing. What is changing instead is the bundling of application software with the systems software and the system itself. The presence of iWork and hassle-free updating of that suite (and the same for the OS) means that utilization rates will increase.
I believe the logic for Apple is that usage of the products determines their value and therefore placing powerful software in the hands of more users means they will value the entire system more. This leads to the notion of greater "stickiness" or "lock-in" but also to higher satisfaction and loyalty, rate of upgrades and even more third party purchases and yet more usage.
This is the virtuous cycle platform custodians seek to engender. This is what Apple is trying to build and the transition of apps into the system bundle is part of this re-enforcement.
One wonders how long before Apple's approach becomes the norm for other platforms.
Using logistic curves to measure diffusion of innovations is a powerful method of analysis. However there are limits to what can be learned. The methodology helps in understanding how quickly a pervasive technology is adopted. It assumes that the technology "fills all available space" within a market. It therefore also assumes that whatever problems the technology solves are universal problems.
Put another way, if a technology is not universally useful, it tends to peak before a market saturates. This "universality" condition is in evidence when observing that pervasive technologies are adopted not only by all members of one national market but also all nations and through all means of government and regulation. In other words that the jobs that the technologies are hired to do are so important that they bulldoze any and all obstacles placed in the path of adoption.
The only difference is one of timing. Some regions are quicker than others. Institutionalized obstacles essentially defer rather than deter adoption. They impede rather than block.
And I am pretty sure that smartphones solve universal needs and their adoption will be nearly 100%. They also have fairly low impedance given the speed of adoption (50% penetration in most large markets seems to come in less than 5 years.)
That's the story for the technology, but how value is captured is another story.
Who captures and how it's captured are questions of commerce not economics. They are informed by competitive advantage and business models. The puzzle seems to be that individual companies don't capture value in the patterns of Logistic curves. Or at least I don't think they do.
Consider the graph below.
It shows the transformation of a logistic curve into a linear representation. It's a log-scale graph of fractional shares of smartphones in general (Blue/green Lines) and individual platforms in the US.
The individual platforms are shown as (Platform x share of all phones/share of all others). This is a "logistic substitution trajectory". ((Fisher and Pry, 1971, proposed a similar model to study the replacement of old by new technologies. The basic assumptions of the Fisher-Pry model are: (1) The substitution process is competitive. (2) Once substitution by the new technology has progressed as far as a few percent (i.e., "lock-in"), it will proceed until a complete takeover occurs. (3) the rate of fractional substitution F1 is proportional to the remaining substitution 1- F1 possible. Source: Grübler, The Rise and Fall of Infrastructures Physica-Verlag 1990.))
The problem is that whereas the overall category (smartphones) reaches saturation, it's not at all clear that any individual platform does. At least from the data we have so far, there is far too much volatility in platforms to see a clear pattern of monopoly emerging.
I'm not sure if this is "proof" enough to convince anyone that this market supports any number of platforms, but it certainly disproves that there will be only one. ((The odd pattern here seems to be Apple's consistent (i.e. parallel) adoption. One hypothesis could be that Apple is different in solving the prevailing job to be done while rivals jockey for positional advantage.)) We're too far along for churn to convert existing users before saturation sets in.
One of the curiosities of the mobile phone market is how vast it is but also how heterogeneous it has always been. I wrote about this in 2010: Smartphone parochialism: How operator policies prevent or promote platform adoption. This observation was influenced by my time at Nokia where I became amazed at how differently users behaved in different countries.
There were many causes. Some cultural, some historical, some economic and some policy-driven. The result was that it presented a challenge to any company with global ambitions and indeed it was rare to see the same company do well in every market. Japanese companies did well in Japan, European companies did well in Europe and US (and Korean) companies did well in the US. Nokia was most successful because it was able to apply an European model more broadly (but not in the US). Samsung succeeded by simply adapting to each and every market with hundreds of products. But it was a particularly "provincial" market.
My assumption was that when smartphones would become the majority of phones in use there would be a normalization of behavior and thus a homogeneity of preferences. This is, after all, what happened in other platform games. PC form factors are globally consistent, PC operating systems are equally preferred around the world, FaceBook, Google and Twitter are also, unless censored, uniformly popular. Apple's iPod eventually also became a global phenomenon with no material difference in preference by market. Likewise for game consoles. ((Although Japanese do seem to prefer Japanese platforms more.))
However, a decade after the broad adoption of smartphones, the relative popularity of various platforms is still unevenly distributed. Prior to the iPhone, Symbian was strong everywhere but the US and BlackBerry was very strong in the US but weak elsewhere. Windows Mobile had footholds in some markets but little traction in others. Today the picture has changed but it's still a patchwork of preferences. Consider the following graphs.
They are the most detailed sets of data on platform phone purchases but they not the only data: We also know that Android is vastly more popular in India from web usage statistics. We know that BlackBerry is sensationally popular in Latin America and the Middle East. We know that within Europe there is a gap between North and South in iOS vs. Android and even more pronounced between East and West. We know that whereas iPhone was a huge hit in Korea upon its launch there, Samsung and LG swamped it in the last two years.
But the data shown above is the story of iOS being very popular in Japan and increasing its share in the US while being flat in EU5. Again these three markets are different but each contradicts the global picture.
Note the differences in trend not just absolute performance. This is what is puzzling. There seems to be a divergence between markets: Markets are become more islands onto themselves rather than one whole. This contradicts all the theories of how computing markets should behave (network effects, ecosystems, monopoly power, etc.) It implies that there is still a great deal of friction in the market; friction which I suspect to be due to the peculiar nature of telecom economics.
I wonder if this observation is, as usual, late on my part and that Apple's iPhone product marketing has seen it years ago.
When looking at the Race to a Billion data I noticed that some platform adoption ramps look quite different from others. It's not just a matter of "slope" or rate of growth but a distinctly different shape.
If you look at the graph below you might see the difference yourself.
First, note that the graph is logarithmic. A straight line on a log chart implies exponential growth (the y values are a constant to the power of the x value). However, none of the graphs show straight lines. None of the platforms follow exponential growth ((Except perhaps in the very early periods)).
Second, we can eliminate linear or logarithmic functions. They simply do not fit.
That leaves: polynomial or power. It's easy to test these alternatives for all the functions and it becomes clear that most of the platforms split into one of these two classes.
Here are the classes ((Some of the platforms had to be dropped because there was no easy fit. My observation is that some of these platforms went through some crisis or change in strategy during their history which caused the pattern of growth to change)):
Note that I added the formulas for the selected platforms.
I named these classes after their function types: "Power platforms" or "Second Order platforms" ((Note that all Polynomial functions found above are second order)).
This classification has two benefits:
It allows a clearer distinction in scope. Both may exhibit signs of network effects, but Power platforms seem to exhibit "global" or unlimited reach while Second Order platforms may have a strong upper bound on reach.
It allows more reliable forecasting. If a platform classifies as Power, the forecast could be created with fewer data points.
It allows us to guess at the causes of entry into each class for any potential platform challenger.
To illustrate the second benefit, I took the Android, iOS and Facebook power functions and modeled (i.e. extrapolated) them for a few quarters into the future. The result is shown below:
The forecast shows the following:
Android will reach 10 billion activations 10 years after its release (mid 2018)
iOS will reach 1 billion units sold by end of next year and 3 billion units by its 10th anniversary in 2017.
Facebook will reach 2 billion users by 2015 after the end of its 10th year.
My thanks to Kirk Burgess for providing this transcript:
Horace Dediu interview on CNBC Asia Cash Flow show - 10th September 2013
Chloe Cho (CNBC): Take us through what Apple is exactly trying to do?
Horace Dediu: Well, this is the first time in the six years of this competition in the smartphone market that Apple has broadened its portfolio. We have seen only a single product launch every year--this is very unorthodox in the industry. Normally each competitor [ranges] dozens of devices. Apple's entry has been asymmetric from the start, and now in its sixth year we are expecting to see, finally, a broadening perhaps into two separate products. The question will be whether [there will be] a significantly lower price point for the so-called 5C and whether that will change the average selling price overall for the portfolio. The average selling price has been remarkably steady, and remarkably high, typically around $600 for the duration of this products life. Something, again, unprecedented. My expectation is the new price point will be quite a bit lower than $600, starting with about $450, it might drop a bit further, [which] would cause the overall price range to come down as we have seen with the iPad; [where we] also had a price erosion happen as the smaller version came out.
Q: Horace, do you think they have got the timing right? Should they have done this a little bit earlier when the market wasn't so saturated and filled with cutthroat competition?
A: Indeed, I think. As I said, as a product with six years in the market it's a bit late; I expected this to happen last year. I think a lot of the momentum that has been lost in the past year in terms of sales growth has been because of the lack of low end. To note also will be whether they indeed expand their carrier footprint. We are expecting something new in Japan and possibly China Mobile. There is a second announcement happening with a few hours delay in China. This is again the first time that has ever happened.
Q: Horace, do you think they didn’t move down the value chain fast enough largely because they didn’t have a deal with China Mobile?
A: Well that's always a good question whether they are driven more by carrier channels or are they driven more by consumer market expectations. I think it's a bit of both. We do have this hybrid approach where they continue selling this older product for one or two years after the new product is launched--so the 4 and 4S are still available while the 5 is being ranged. This strategy is hybrid I say because this isn't truly a low end product, it is a stale product that is being put out there. This [strategy] may be driven more by consumer demand, not so much what operators are asking for. With the 5C we might be looking at a solution for operators in particular.
Q: Horace, how much do some these incumbents like Apple and Samsung need to be worried about Microsoft approaching their space?
A: I believe Microsoft will not be competitive in the near term. I don't think [during] the next year we are going to see a very impactful entry from Microsoft. What Microsoft is likely do is lower prices significantly on Nokia's portfolio and their pipeline as it is. That might cause more pressure on the pricing, but the problem has been that consumers have not really been taking up the Windows Phone platform very aggressively. It has been somewhat successful in Europe but not taking off elsewhere. I think Microsoft will be in an integration mode with the Nokia assets into 2014, but I would expect in a year from now we might see some new entry product that would be exciting. I think 2-3 years down the road we might see something from Microsoft that would excite consumers as well.
Q: There has been a lot of focus on which companies have a more integrated house, Apple or Samsung. In light of the fact that they are having to move into lower price points, in your view which is doing the better Job, Apple or Samsung?
A: Well Samsung is a great industrial enterprise and they are doing very well by broadening as much as possible their portfolio, even before the smartphone race started for them, which was in 2010, they were known for being one of the most prolific product creators out there. They actually had over 100 different mobile phones, not smartphones, just regular mobile phones that they would range, and Nokia were extremely concerned by this pressure they were getting from Samsung.
What they have seen since 2010 is the same thing, except with smartphones, and so they’ve been really prolific and covering the spectrum of price and screen and every other possible variant that could be made. I think however that Samsung hasn’t got a software platform under its belt. They could become a software player by taking over some of the control of Android as we have seen Amazon do, and thus really establish themselves as a platform player. They are doing so to some degree with the "Gear" product, and they might be doing something like this by launching their development conference this year.
But they aren't yet a platform player whereas Apple is, but then again we just don’t know what the politics of Android are with respect to forking it by an OEM as large as Samsung.
In the "Race to a Billion" there is a graph showing Android reported activations and iOS cumulative unit sales alongside cumulative console sales. The contrast between mobile phone platforms and game consoles is striking, with an order of magnitude difference in consumption. The best performing console to date is the Wii with about 100 million units sold so far.
[UPDATE: Thanks to Danny Nemer cumulative sales of Sony's PlayStation 2 (using production shipments from FY 2000-05 and recorded sales for FY 06-12) is 155.81 million units]
However, that is an incomplete picture of the game platform business primarily because consoles are not the entirety of the business. Mobile (but dedicated) gaming platforms have been sold for some time.
To give a better picture of the game business we prepared the following graphs. The first shows Nintendo's product lines with actual unit shipments (shown as colored dots in millions of units per quarter) and the trend (shown as trailing twelve months' average trend lines).
Note that fixed and mobile products are both shown on the same graph. The picture that emerges is that for Nintendo, its mobile platforms combined are more popular than its fixed consoles with a total of 186 million mobile devices sold since 2003.
There is also a pattern of generational change. The GBA, DS and GameCube era was superseded by the DS Lite, DSi, Wii era. The Wii era (or generation) was significantly more popular than the GameCube generation. If there is a problem however, it seems to be that the new generation devices or consoles are not forming a new era. The Wii U and 3DS are not growing nearly to the level of the previous generations and have faded quickly.
To summarize, the unit volume graph for Nintendo is below. ((This is a smoothed graph showing what sales would have been if they had been evenly spread out over a 12 month period. The actual sales would total to the same area but would be much more seasonal and thus noisy.))
To confirm that this is indeed disruption we should look at the pattern for another competitor in the console market: Sony. ((We would like to show the pattern for Microsoft but there is no regularly reported Xbox shipment data.))
The graphs above combine both Nintendo portable/consoles and Sony portable/console sales. Note the similarity in patterns of growth. It's one thing to suggest that Nintendo consoles have "failed", it's another to show that Nintendo consoles and portables have failed, and yet another to show that two competitors in the games business seem to be failing in unison across all their product lines. The cyclicality is also over a long period of time: The peak for the combined Sony/Nintendo was in 2008, five years ago.
The chief criticism to the industry-wide view of decline is that there is a new generation of consoles right around the corner. This is the eighth generation of consoles which, it is presumed, will bring growth back to the industry.
But the Nintendo 3DS, launched two years ago, was meant to kick off the eighth generation, and the PlayStation Vita was Sony's response. Then the Wii U was also billed as the successor to the Wii. They have so far failed to re-ignite growth. One might reply that they were merely appetizers and that the main course of the next gen are the PS4 and Xbox One.
Will they create growth again? Surely not for Nintendo, but I would argue that not for Sony or Microsoft either. There might be a burst of sales at launch as the hard core gamers upgrade, but they are unlikely to recruit new gamers the way the Wii did. In other words the PS4 and Xbox One are unlikely to win against non-consumption.
That is where mobile is the clear winner. More people will hire mobile devices for their primary gaming activity. And as mobile devices get inexorably better, they will be hired for use in the setting where consoles have been king: the living room.
The implications are that Nintendo, Sony and Microsoft are beyond the point of no return in this industry. Gaming, as a business, cannot be sustained as a platform independent of a general purpose computer. Like other "applications" that used to have systems built around them conforming to their needs (( Applications such as word processing, financial calculation, media editing, music playback, etc.)) the dedicated-purpose solutions came to be absorbed into the general-purpose platforms. And the modern general purpose computer is the smartphone. (( One interesting question is why didn't the general purpose personal computer absorb console gaming. My answer is that personal computers could not conform to the experiences around the "10 foot" interface and still function well at their main jobs. In contrast, mobile devices through screen sharing have the ability to be much more malleable.))
UPDATE: I added Microsoft console shipment data which became available after 2008.
According to the latest comScore survey data, 98 million Americans above the age of 13 don't use a smartphone as their primary phone. That's 41% of US mobile phone users.
What's more, 2.5 million more people first started using smartphones in the three month period ending May vs. the three month period ending in April.
The switching rate to smartphones is shown below:
It shows the number of new-to-smartphone users who switched every week. It can be considered the "speed of adoption". The latest figure is 583k/week, above the 572k/week average maintained over the last 41 months.
[I also added a three period moving average which shows a seasonal change in adoption. I also added a vertical line showing the point when 50% penetration was reached (August 2012).]
The switching rate by platform is shown in the following graph:
The data shows that churn between platforms (except for BlackBerry) is still negligible and that the majority of user losses can be attributed to non-smart devices.
To summarize, with penetration now at about 60% in the US, the rate of adoption of smartphones is not slowing in any perceptible way.
So not only is there no saturation, but there is no slowing of adoption of smartphones in the US, the most penetrated large market.
Globally, the penetration of smartphones is less than half of that in the US. About 4 billion people are about to switch.
Of course, they may not be willing to switch to what is currently offered to them in the market, but then again, the billion or so who adopted iOS and Android phones did not switch when the alternatives were BlackBerries, Palm, Symbian and Windows Mobile devices.
