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The Quantum Leap in Retail

In fiscal 2013 there were 395 million visits to Apple retail stores. In 2012 there were 372 million.

Screen Shot 2013-10-31 at 10-31-2.15.13 PM

The difference is approximately the population of Australia. This was in addition to the population of the US and Canada already passing through. Although this is a fun way to think about total traffic, it does not reflect performance of the stores themselves since new stores are always being opened. 21 new stores in 2013, to be precise.

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The better benchmark should be the number of visitors per store.

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This shows that, except for seasonal peaks, the visitors per store per quarter has been a fairly steady 240k since mid-2010. What’s more, this rate was also remarkably steady at around 160k/store/quarter from 2007 to 2010.

So what caused this quantum jump[1] in traffic?

Notes:
  1. “Quantum leap” is often used to mean “giant leap” but in the original usage it meant a specific, discrete jump []

The value of zero-priced software

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:

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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:

How many mobile platforms can a market sustain?

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.

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The iPhone company

The analyses of adoption of smartphones in the US and EU5 are remarkably consistent with each other. They also turn out to be consistent with the valuation of Apple.

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I show the stages of adoption overlaid with the derivative of the Logistic Function and Apple’s enterprise value. The derivative of the Logistic Function shows the speed of adoption, peaking at the inflection point when adoption ceases to accelerate and begins to decelerate.

When will the European Union Five reach smartphone saturation?

Thanks to Symbian, the EU5 countries (France, Germany, Italy, Spain and the UK) had an earlier start in the conversion of phone usage from non-smart to smart devices. According to published comScore data, in July 2010 the EU5 were at 26.6% penetration of smartphones and the US was at 22.8%[1].

However, with the aid of mobile operator subsidies, by the beginning of this year, the US caught up. According to comScore EU5 reached 57% penetration in March 2013 while the equivalent figure for the US was 58%.

Using the logistic curve model introduced last week, it’s possible to get an approximate categorization of the adopters of the technology:

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As with the previous analysis, the graph identifies the following dates:

Notes:
  1. The population is defined as adults using phones for themselves. Meaning it excludes children and phones purchased by companies. []

The Five Year Plan

Gartner reported that PC shipments totaled 80.3 million units in Q3. Subtracting an estimated 4.4 million Macs yields an estimated 75.9 million Windows PCs.[1]

This total is lower than the total shipped in the same period of 2008.

 

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The graphs above show the

Notes:
  1. The total will be less than this as some PCs will not ship with Windows []

Estimating HTC's post-traumatic life expectancy

In May 2012 I wrote:

The pattern may be that companies either have short post-trauma lives of about two to three years or relatively long post-trauma lives lasting 4 to 5 years. What determines this life expectancy and how long do RIM, Nokia and LG have?

via Post-traumatic life expectancy of phone vendors | asymco.

These comments came right after BlackBerry (then RIM) announced a loss and thus entered what I called the “post-traumatic” phase of its existence.[1] The observation I have been making is that once a company begins to generate negative operating margins from phone sales, that phone business never recovers.

The question then becomes one of gauging how long they have before the business is sold, dissolved or merged. Since that update, both Nokia and RIM have tentatively agreed to be sold. If the sales go through then we can update the graphs as follows:

Screen Shot 2013-10-04 at 10-4-11.01.11 AM

[Graph note: solid bars in the second graph indicate companies which exited and thus the duration of life post-trauma.

Notes:
  1. The analysis began earlier, in June 2011 []

Competing with a Mac

Publicly, Mr. Lazaridis and Mr. Balsillie belittled the iPhone and its shortcomings, including its short battery life, weaker security and initial lack of e-mail. […]

Internally, he had a very different message. “If that thing catches on, we’re competing with a Mac, not a Nokia,” he recalled telling his staff.

From How BlackBerry blew it: The inside story – The Globe and Mail

The whole article is worth reading, detailing as it does the decision process inside BlackBerry during the painful disruption of its core business.

What struck me most however was how similar their decisions were to those of Nokia at about the same time. Consider:

  • The engineering priorities placed on optimization around constrained hardware. Although engineers knew how to build the right products, the business priorities caused them to be deployed in the wrong direction.
  • The delays these misdirected efforts caused. Mobile phones have narrow windows of opportunity but long lead times. A strategic mistake is very costly and most probably impossible to remedy. In the case of BlackBerry, buying QNX came too late while for Nokia the deprecation of Symbian was catastrophically managed.
  • The feedback loop from network operators which shut down any initiatives for improved user experiences. Your best customers provide all the wrong information when the market is being disrupted. Ignoring them is impossible while complying is a strategic mistake.
  • The demand from network operators to develop “killers” to competing platform-based products[1] and the subsequent “jumping at the opportunity”.
  • Listening to large buyers at the expense of users. While BlackBerry was guided to omit consumer features from its enterprise buyers, Nokia never secured enterprise buyers of any significance[2]. Nevertheless it created the “E series” business-friendly phones which suppressed features like cameras and music.
  • The celebrity sponsorships and wasted promotional efforts in the face of structural failures.  This is manifested today by HTC as well.

The parallelism of this synchronized failure can be seen in the following graph showing smartphone volumes.

Notes:
  1. Ironically, Nokia was asked to do a BlackBerry killer []
  2. though they tried very hard to get them []

An interview with Niaz Uddin at eTalks

My thanks to Niaz Uddin for asking some good questions and posting my replies:

Horace Dediu on Asymco, Apple and Future of Computing | eTalks.

Full interview is here, excerpts below:

Niaz: Why do you study Apple?

Horace: Apple is an interesting company to study because its success comes from being a serial disruptor. This is a very rare type of success formula. I am trying to “reverse engineer” its operating model and I hope that such a model is one which others might learn from if they were to emulate it. The trouble is that very few others seem to want to emulate Apple. Why that is is also an interesting question.

Niaz: […] Do you think apple has lost its image that it has created over the years as a center of innovation and building excellent products?

Horace: I cannot comment on how Apple’s image is measured by people in the industry. I have been listening to commentary on Apple for about a decade and I have never seen any change in pattern. The company has always been perceived as a failure by a majority of observers. With respect to its products, I also do not see a change in the pattern established over the last decade.

Niaz: Are you optimist about the future success of Apple? Like after 10 years and then 20 years?

Horace: Let me put it this way: if there were no Apple then somebody will have to invent an Apple to do the same thing Apple does. In that sense I’m optimistic that there will be an Apple in some way in perpetuity.

Niaz: What will be the next big innovation from Apple?

Horace: I have no idea but it’s likely to involve refining new user interaction methods. Similar to the breakthroughs that came from the use of a mouse, a scroll wheel and a touch screen. It means making computers better at gleaning our intentions without our getting involved in explaining them.

Niaz: Will Apple, Google and Samsung be the major player for the future of computing? Or we can hope to see some new faces?

Horace: I am fairly sure Samsung will not be because they have not yet grafted software and services to their operating structure. I would give Amazon a higher probability in being a successful platform alternative.

Niaz: In 2011 you’ve written a blog post ‘Steve Jobs’ Ultimate Lesson for Companies’ on Harvard Business Review Blog and you have cited ‘A leader should aspire to do more. A leader should claim to have left a legacy not just on their company but on all companies.’ As you know Google, Amazon, Samsung, Facebook … all have learnt lifetime lessons from Steve Jobs. What do you think about the impact that Steve Jobs have created?

Horace: He led by example and like all great leaders sacrificed much as a way to inspire others to follow him. He also spent time in the wilderness and chose asceticism. This gave him authority. Many historical figures had the same quality. The problem is that few business leaders have it but I don’t see why they shouldn’t.

Much more on evaluating Tim Cook’s performance, the iPhone portfolio, the rise of Android, Microsoft/Nokia, wearable technology and disrupting Google. Check it out on eTalks.

 

S is for Service

One of the enduring mysteries of the iPhone has been its lack of a portfolio. After six years it seems that Apple has finally acquiesced that there should be one, albeit currently limited to two items. The second enigma is related to the price, namely why does Apple ask so much for its phones? At an average sales price of $600 it’s a shocking premium to the average phone, and with a six year run, a shocking resistance to the corrosive effects of competition.

The obvious answer to why Apple asks so much is because it can. Anybody would if they could. That’s a poor question. So the right question should be: why does anybody pay this much? One could answer that few do and it’s not a mystery that some feel better paying more simply because they can. But those who pay Apple’s prices are, mainly, not consumers. They are operators. Exactly 270 of them.

So then let’s re-ask the question: Why do so many operators pay so much for Apple’s phones? We can’t answer that with the psychological slurs usually directed at the brand. Surely Operators aren’t competing in beauty contests or need to soothe their collective egos. The decisions operators make on whether to range a phone are driven by hard economic realities: ARPU, churn, network costs, depreciation, ROI, etc. Some clearly can’t make the iPhone fit their economic models and indeed about two thirds of them don’t. But the most prominent[1] do. DoCoMo, the largest in Japan just did after holding out for five years. Verizon held out for years, as did T-Mobile. China Mobile’s acceptance also seems imminent.

But that still leaves the question of why are those operators who do carry the iPhone willing to pay so much for it? I only assume that their decision process is likely to be rational. Mainly because we have a large enough sample but also because there is a lot of money at stake requiring quite a bit of internal consensus and vetting before committment. We have to conclude that operators place the orders because they obtain value from the iPhone even when it’s priced at a premium to the average alternative.

The question which follows then is how do they obtain value?

Notes:
  1. Arguably the most important []