Horace presents the next class in The Critical MBA. Having too much of a fundamental footing could be a disadvantage when evaluating what theory might apply to a given situation. Could this be why so many fail to understand Apple? In the second half of the show, Horace and Anders discuss Amazon as retail goes online.
Apple paid $10 billion to developers in calendar 2014. Additional statistics for the App store are:
- $500 million spent on iOS apps in first week of January 2015
- Billings for apps increased 50% in 2014
- Cumulative developer revenues were $25 billion (making 2014 revenues 40% of all app sales since store opened in 2008)
- 627,000 jobs created in the US
- 1.4 million iOS apps catalog is sold in 155 countries
Putting these data points together with others from previous releases results in a fairly clear picture of the iTunes/Software/Services
The App ecosystem billings (what consumers actually pay) is shown in the red area above. 70% of those payments are transferred directly to developers and Apple reports the 30% remaining as part of its revenues. This view of the iTunes ecosystem shows the impact of Apps relative to the other media types. When we measure the payments to the content owners we can see that Apps also dominate:Notes:
- soon to be renamed Services and encompass everything under the heading of iTunes software and services today including content, apps, licensing and other services and beginning Q4 2014 it will also include Apple Pay. [↩]
1. Cyanogen. This company should develop a credible path for AOSP (non-Google Android) especially in India. I expect a lot of traction as OEMs who embrace Android reject Google.
2. iPad. Not as a consumer product but for the Enterprise. The iPad grows up into a solid product for business while being replaced by phones in consumer “jobs to be done”.
A few more ideas are listed here: The 2015 “Sleeper Ideas” List: Trends, Stocks, And Private Companies To Watch – Forbes.
As corporate romances go, IBM and Apple’s must rank among the most unexpected. As I wrote on the date they changed their Facebook status, the two companies were antagonists for the better part of twenty years and their rapprochement was met with a shrug mostly because yet more decades passed since.
Nostalgia aside, this new union is profoundly important. It indicates and evidences change on a vast scale. The companies’ antagonism was due to being once aimed at the same business: computing. Since the early 1980s, “computing” came to be modularized into hundreds, perhaps thousands of business models. It is no longer as simple as selling beige boxes. IBM was forced out of building computers and into services and consulting while Apple moved to make devices and the software and services which make its hardware valuable.
The convergence of interests which was consummated into a deal this year stems from the migration of computing around what has come to be called “mobile”. Apple intends to accelerate the adoption of its mobile platforms among the remaining non-adopters: enterprises–a group which, by now, qualifies as laggards. Simultaneously IBM intends to connect data warehouses at those same enterprises to their employed users.Notes:
- There was a time–when Apple was young–when enterprises were the innovators, early adopters. That role ended approximately in the year 2000 [↩]
This year’s Thanksgiving and Black Friday data from IBM shows a continuing pattern of growth for mobile devices. As the graph below shows, in the five years since 2010 mobile devices grew from 5% of the online shopping traffic to 50%. Traditional computing (desktop and laptop) made up the difference.
The graph also shows that sales value via mobile devices crossed over 25% of online spending. The fact that mobile shopping is not equal to mobile spending is due to the convenience factor of mobile. It’s more likely that users will spend idle time scanning for bargains or tracking down ideas from friends but wait until they are at home to make the final purchase decisions in front of a computer.
The transition to spending directly from a device is a slower process, but that process was also one that online had to undertake as buyers became comfortable with online commerce. When it comes to payment, buyers are understandably more cautious.
This does not change the prediction made last year that “the transition to post-PC consumption will also be practically completed by 2020”. That leaves six years for mobile saturation and a total transition time of one decade.
At that point I expect 90% of browsing and perhaps 75% of spending to be happening on devices. Some of this will undoubtedly be enabled by biometric authentication as shown by Apple Pay. Trust and ease of use in this technology will undoubtedly accelerate the transition making mobile payments more comfortable and secure than on the legacy computer.
What is less predictable is how much those devices will also be used to transact payments for the physical retail stores. In some scenarios it’s possible that by 2020 a majority of all shopping will be enabled by devices. That would subjugate the retail segment to the power politics of mobile platforms.
It is interesting therefore to note the mix between the platforms in the graphs above.Notes:
- There is also the matter of in-store discovery and advertising via NFC and bluetooth i.e. iBeacon [↩]
I tried to assess the opportunity of Apple Pay but found it to be mostly dependent on how quickly card payments will overtake cash. It seems that as payments move to a digital format they will move to a mobile device. The hurdle isn’t going from a card to a phone but from cash to card.
Data published in The Growth and Diffusion of Credit Cards in Society shows that between 1970 and 2001 households with at least one credit card in the US grew from 17% to 70%. More recent data shows 82% of US consumers have at least one credit card and 77% have a debit card.
The Total Addressable Market for Apple Pay then is dependent on how quickly this pattern repeats over the markets where iOS devices are in widespread use. Once cards are in use they are used with higher frequency and quickly overtake cash for the user.
The only assumption that needs to be made is that the device then replaces the plastic card. This seems a safe assumption as the benefits of the device as payment authenticator are high and the costs are negligible given a penetrated market.
The following graph shows an extrapolation of transaction volumes where Visa and MasterCard and Amex are showing moderating growth with UnionPay showing 20% constant growth through 2019.
Two more assumptions are needed: the share of transaction value captured by Apple Pay and the Apple Pay fee. I used 15 basis points ($15/$10000) as the assumed Apple fee and a share schedule as follows:Notes:
- Supporting these assumptions is a forecast from Nilsen showing total number of cards in circulation by issuer and a forecast of total transactions [↩]
Samsung’s smartphone ascent was breathtaking. From having essentially zero market share in the category in late 2010 to becoming the largest vendor took less than two years. In doing so it grew to become the largest phone vendor, smart or not–a goal which eluded them during the previous decade of effort. Samsung went on to capture not only the lion’s share of unit volumes, they also took almost all the profits in the Android mobile phone market.
And in a market filled with competitors. Literally hundreds of vendors and thousands of products were available at every conceivable price point. Samsung did away with HTC, LG, and Motorola. HTC, the first Android vendor (and first to market with Windows Mobile), Motorola, Google’s launch partner in the US and “Droid” brand partner (and future owner). Google’s own Nexus products. Samsung Galaxy ruled them all.
Galaxy swamped the Chinese market and the Indian market, the largest in the world. They were so powerful that they were singled out both by Microsoft and Apple for IP royalties.
All within two years or the average life-span of one smartphone.
But something went wrong in 2014. Growth in shipments suddenly stopped. This was not a problem with the overall market, which kept growing. The slowdown did not affect other vendors, especially the up-and-coming Lenovo and Xiaomi and the second and third tier vendors whose names are known only in the local markets they serve.
The result of this slowdown is shown in the following graphs:
In Q3 2014 Apple’s revenues were 5.3% higher than the upper end of their guidance. This is the highest error in guidance since the new range-bound reporting regime started two years ago.
The following graph shows the guidances given since 2005 and the actual revenues. The error (as a percent of upper guidance) is given in the second graph.
Samsung Electronics warned Tuesday that its third-quarter earnings would fall below market expectations. It did not cite a decrease in shipments but an increase in marketing expenses coupled with an unfavorable mix (i.e. more low-end units and fewer high-end units).
The headlines reporting the news emphasized the 60% forecast drop in operating income but the company also provided sales figures. Adjusting for exchange rates, the forecast revenues are shown in the following diagram:
Note that I also included Apple’s revenue history and forecast. Samsung’s revenues are shown on the right and Apple’s on the left using the same scale (each horizontal gridline represents $10 billion/quarter.
The explicit cause for the drop is a decline in prices and “increased competition”. However a few more questions need to be answered regarding long-term success in the markets Samsung competes in.
- The absence of a software platform fully within its control
- The absence of control over an ecosystem of content and apps
- The absence of services
- The lack of integration of software, services and hardware
- The absence of differentiation vis-a-vis other vendors
- The indefensibility of its low end offerings from low end disruptors
- The pattern of commoditization in all its markets
Samsung is a very big company but many very big companies came to become small companies. They all followed similar roads.Notes:
- Though one can’t be sure when there was ever decreased competition in its markets. [↩]
If software can be injected into an industry’s product it will bend to the will of the software writers.
This theory expands on Marc Andreessen’s observation that “software is eating the world”. The evidence is that software, coupled with microprocessors, sensors, batteries and networking becomes applicable to an increasingly larger set of problems to be solved. Software has “eaten” large portions of entertainment (e.g. Pixar, iTunes, video games), telecommunications (iPhone, Android, Messaging), various professions including journalism, management and law, and is entering transportation, energy and health care and poised over banking, finance and government.
As entry happens, asymmetries are enabled and disruption follows. This is the bending to the will of the writers–who tend not to be incumbents. The incumbents can’t embrace the changes in business models enabled by software without destroying their core businesses and thus, invariably, they disappear.
The pattern is easily observed but the speed and timing of it is difficult to predict and hence investment success is not certain. There are many entrants who try and few succeed and there are many incumbents who will survive longer than a prophet can stay hungry.
Nevertheless, this process of software-induced turnover in wealth–and, incidentally, vast, additional wealth creation–is inevitable.
But can we predict anything other than timing? For example, can we predict the next industry to succumb to this force?Notes: