Category: Theory

Theory.

Assessing the Smart TV Opportunity

There has been increasing chatter about a new TV being developed by Apple.

My opinion on the subject was summarized in the post called Tele Vision. I contend that a TV cannot be smart until the content it delivers becomes smart. The logical conclusion is that the value chain needs re-integration so that the component which is not good enough (the content) can be improved along the dimensions that users value. And it cannot be improved unless the direction it needs to go into is aligned with the direction of the disruptive innovator. I won’t repeat the theory here, but it suffices to say that whatever will change television will do so by re-defining the core product not just the tools we use to consume it.

But today I wanted to address another question: how do we value the opportunity? In a back-of-the-envelope manner, can we tell if this business is big enough to try to fix.

The answer depends a lot on the business model of the disruptive entrant. The entry could depend on software or advertising or hardware or distribution, and each would have a different valuation.

But for the sake of calibration, I want to start with a proxy. The basic question of how many “terminals” exist to the value networks. How many units of TVs are sold and how many could a new entrant convert to a new paradigm?

I prepared the following chart showing the world-wide TV market with a highlighted subset of so-called “smart TVs” (source TRi). The market is shown from 2010 actuals through 2014 estimates. To make it more interesting I also added similar data for two other markets. Mobile phones and PCs with their own sub-categories of smartphones and tablets as equivalent “high growth” opportunities.

When considering the opportunity, the Smart TV volumes are small relative to either tablets or smartphones. Continue reading “Assessing the Smart TV Opportunity”

How did I get the iPhone number so wrong (part II)

Last quarter I was wrong because I thought Apple would throttle production of the iPhone 4 in the fourth quarter post-launch. “The reason growth would moderate was that Apple slowed production of the old model in order to switch out to the new model–we saw the same thing happen with the slowdown in iPad 1 and transition to iPad 2.”

As a result I seriously under-estimated iPhone volumes in the second quarter (FQ3). That failure led me to question whether the theory I was using in forecasting was still valid. When it came time for a new estimate I hesitated.

I had to choose whether to apply the old seasonality theory or to assume that the game had changed and that the product would now grow organically.

The first assumption would put the iPhone growth at 100%+ while the second would place it in the 60% to 80% range. I decided to dial in a figure somewhere in between at 90% but I’m not very confident in this

The result was an over-estimation by almost the same error as that of the previous quarter. Most of the other product lines were accurately predicted, but again, as a always, the whole forecast rides on the iPhone.

So where does that leave the theory? Continue reading “How did I get the iPhone number so wrong (part II)”

Clayton Christensen and Siri

At the Open Source Business Conference in March 2004 Clayton Christensen gave a presentation. It’s available as an audio file for download here: Clayton Christensen | Capturing the Upside. I strongly recommend listening to the whole thing because it’s the quintessential Disruption lecture.

It has relevance in many areas of analysis, but when I was trying to think of a way to characterize the potential for Siri I recalled one particular passage that I saw as almost clairvoyant. Seven and a half years ago, Clay said:

… the next time you go to a computer superstore, go to the voice recognition software shelf and pick up a box there that’s called the IBM ViaVoice.  Now don’t buy it, but just look at it!  They have a picture of the customer on the box, and it’s an administrative assistant who is sitting in front of her computer wearing a headset speaking rather than word processing.

Continue reading “Clayton Christensen and Siri”

How much do Apple's factories cost?

In the last two posts (How much does an Apple store cost?, The down payment on iCloud) I discussed two line items in the PP&E asset class on Apple’s Balance Sheet. In isolation, the data is interesting as it gives us an idea of the cost structure of stores and facilities being developed to sustain its current business model. In aggregate, it provides insight into Apple’s strategic intent.

To complete the picture, I will look at the third asset: “Machinery, equipment and internal use software.” It’s the yellow line in the chart below:

It’s plain to see at first glance that it’s the most significant asset. What does it represent and what conclusions can we draw about Apple’s strategy? Continue reading “How much do Apple's factories cost?”

Steve Jobs didn't

  • Steve Jobs did not create products. He created an organization that predictably and reliably created emotionally resonant products.
  • Steve Jobs did not make movies. He made a company that predictably and reliably made blockbusters.
  • Steve Jobs did not wrest market share from competitors. He created new markets that attracted and sustained competitors.
  • Steve Jobs did not design anything. He gave others the freedom to think about what jobs products are hired to do.
  • Steve Jobs did not re-engineer processes. He brought engineering processes to works of creativity and the creative process to engineering.
  • Steve Jobs did not develop new management theories. He showed by example that innovation can be managed.
  • Steve Jobs was not a visionary. He put the dots together and saw where they led.
  • Steve Jobs was not a futurist. He just built the future one piece at a time.
  • Steve Jobs did not distort reality. He spoke what he believed would become reality at a time when those beliefs seemed far fetched.
  • Steve Jobs was not charismatic. He spoke from the heart compelling others to follow him.
  • Steve Jobs was not a gifted orator. He spoke plainly.
  • Steve Jobs was not a magician. He practiced, a lot.

He had taste.
He was curious.
He was patient.
He was foolish.
He was hungry.

These things many others can do. Maybe you can.

The case against the Kindle as a low end tablet disruption

In an Harvard Business Review post Rob Wheeler makes the case for the Kindle Fire as a disruptive innovation. I believe that it is but crucially I disagree that the Kindle Fire is a low end disruption.

My assessment of the Kindle Fire is based on the two attributes which Amazon highlights as the key selling points which offer a basis of differentiation and potential for asymmetric competition: a low price and a new browsing model. I believe that these two attributes result in two opportunities: one for low end disruption and another of new market disruption. I reject the first and tentatively support the second.[1]

The price

It’s immediately obvious that the price point of the Kindle Fire is well below alternatives. That forms the basis of disruptive potential, but before we jump to analyzing the disruption hypothesis we should determine whether and to what extent Amazon profits from the device directly. Profitability gives us a clue to where Amazon will apply resources and thus establish its trajectory of improvement.

We know the margin on the Fire is low because we can calculate the bill of materials for 7″ tablets. Gene Munster of Piper Jaffray estimates that Amazon “loses” $50 for each unit sold. We also know that the design Amazon used is essentially very similar to the RIM PlayBook and was sourced from the same ODM. RIM priced the product at $499 but has struggled to find buyers and is reluctantly dropping the price. We also can estimate that Apple with a product having more than twice the screen size is keeping modest (~30%) gross margins for at a price point approximately double that of the Fire. It does seem that Amazon does not have much or any margin to dip into.[2]

So the Fire can be classified as a low price product. Does that make it a low end disruption?

Continue reading “The case against the Kindle as a low end tablet disruption”

Decoding Steve Jobs: Select Commentary from HBR.org – Harvard Business Review

Announcing a new HBS PRESS BOOK

Decoding Steve Jobs: Select Commentary from HBR.org

by Norm Smallwood, Kate Sweetman, Dave Ulrich, Rosabeth Moss Kanter, Jeffrey Pfeffer, Horace Dediu, James Allworth, Max Wessel, Rob Wheeler, Bill Taylor

Source: Harvard Business Press Books

14 pages.  Publication date: Sep 22, 2011. Prod. #: 10973-PDF-ENG

“The news of Steve Jobs’s retirement from Apple may be losing steam but observations on his legacy – and Apple’s leadership future – are only beginning. In recent years, leading thinkers have contributed their thoughts on the Jobs phenomenon on HBR.org. We’ve compiled a few of the best here, and we invite you to read them through the lens of business lessons to be learned.’ We’ve selected six pieces: two from after Jobs’s August 2011 announcement and four from before. We hope you will enjoy them, learn from them, and continue to turn to HBR.org for ideas and inspiration.

Available for download for $1.99 via Decoding Steve Jobs: Select Commentary from HBR.org – Harvard Business Review.

The tell-tale signs suggesting a platform's demise

In the post on OS turning circles, I used the concept of a radius of turning as an analogy for agility. One problem with the analogy is that turning in circles implies a return to a starting point or at least a closing of the loop. The idea is that there is lifecycle repetition. However, in reality, this does not apply to the world of operating systems.

An OS, as a platform, usually has a finite life. It is born, grows and usually reaches a point where it is no longer supported. Sometimes, a new platform is born to take its place from the original owner but more often a replacement comes from a new challenger company.

So rather than circles, the analogy of OS lifetimes may be more accurate.

If we do think of platforms as finite, then the natural question is what causes an end? We need to look for patterns which may indicate when a platform is reaching end of life.

The difference in this analysis is that the measure of “age” of a platform I use is not time per se but versioning. The logic is that each major version is a meaningful and significant improvement in a platform which needs to be delineated, marketed and celebrated. It embodies the business logic as well as the engineering logic of the platform custodian.

Taking the data from the last post I added a few more platforms: Symbian[1], PalmOS and Blackberry OS[2] to seek out patterns. I also separated the desktop/portable OS’s from Mobile OS’s and plotted these version-demarcated lifespans.

One thing to observe is Continue reading “The tell-tale signs suggesting a platform's demise”

OS turning circles: Questioning Windows' maneuverability

[Updated with Mac OS versions. See footnote 3.]

I’m glad Windows 8 is named the way it is. With Windows 7 Microsoft went to a numbering system which is much more rational than the mixed naming of the past. The number 8 actually corresponds to the actual sequential number of major versions of Windows released to date.

Windows proper actually did not start with what was called “Windows 1.0”. Windows actually started in April 1992 when Windows 3.1 was released. It was the first Windows which was an operating environment onto itself, apart from DOS. It was followed by Windows 95 (which we can call “2”), Windows 98 (“3”), Windows 2000 (“4”), Windows XP (“5”), Windows Vista (“6”), Windows 7 and now Windows 8.

Given this nomenclature and the dates of general availability of said versions, we can derive a measure of the frequency of upgrades. For example Windows “2” followed about 41 months after “1” and “3” took 34 months after “2”. If we continue this for all the versions, and assume “8” will launch by October next year, we can plot the cycle times of new Windows versions.

To make the story more interesting I added the same data for other OS platforms. OS X, iOS and Android have version numbers which correspond to the sequential order in which they were released. I am assuming that the numbering system (1.0, 2.0, 3.0 etc.) are meaningful and that major releases are given a new integer value.[1] Continue reading “OS turning circles: Questioning Windows' maneuverability”