The Critical Path #158

Horace interviews Whitney Johnson about her new book Disrupt Yourself. How can the theory of disruptive innovation be applied to you? How can you disrupt yourself?

Source: The Critical Path #158

Fluid Coupling

When exactly did enterprises become late adopters of technology? We know that they were some of the first buyers of computers. IBM sold tabulating and later computing machines to businesses starting in the 1910s. During the 1980s it was businesses which bought PCs in significant numbers to augment, and later replace, their centralized computing resources. Networking was in use in government and in business long before consumers saw any value in it.

In my talks I often point out that if you wanted to create a near-monopoly in computing in the 1990s all you needed was to convince 500 people to adopt your technology: the IT managers of the Fortune 500. If the largest companies used your product then they would impose the standard on all their suppliers and distributors and pretty soon there would be no alternatives.

So what happened during the last decade or so?

Today IT departments are known as the Information Denial department.  I recall that when the DVD first became an option on desktop or laptop computers, IT departments were first to decline the option (presumably because it would be used for entertainment rather than work.) When instant messaging first became available, it was IT departments who blocked the ports. When mobile devices with cameras became available signs went up that no cameras would be allowed on company premises. When USB sticks became available, USB ports started getting glued shut. When iOS became available, no devices running it were allowed on the network. Then came Facebook, Instagram and dozens of social media.

This pattern of not only a refusal to adopt but an outright ban on new technologies by enterprises made them fall off the radar of technology developers. Quite simply everyone outside the supply chain into enterprises stopped developing new markets around them. From venture funds to developers, enterprises fell out of the business plans.

The enterprise stood as a place of “legacy” and “security” which prevented mobile or other forms of computing. Paradoxes emerged wherein an administrative assistant had more computing power in his pocket than the CEO had in her data center; where the same assistant would know what was happening faster than any of the bosses. Homes had better connectivity than offices and productivity at small firms increased faster than at big firms. Incidentally, even the slowest enterprises were faster then the government. The bigger the firm, the slower and stupider it seemed. Were large firms employing dumb managers or did being a manager in a large firm make you dumb?

One resolution to this paradox might be that mobility and the movement of processing onto consumer devices increased the cadence of product development to such a degree that the purchase cycle and dollar amounts involved ran out of the range which companies could absorb.

A simple way to explain it is this: A company takes longer to decide to purchase a device than the device’s shelf life. In other words, by the time all the salespeople and committees and standards setting and golf playing and dining and site visits would be completed, the object whose purchase was being discussed would be discontinued.

A more onerous issue is that companies have procedures for accepting technologies (capital expenditures) which require high degrees of interaction and decision making. In order to step though these procedures, the vendors need to have sales people who need to invest lots of their time and therefore need to be compensated with large commissions. If those commissions are a percent of sale then the total sales price needs to be large enough “to make it worth while to all parties”. As a result, paradoxically, an enterprise technology must be sufficiently slow and expensive to be adopted.

Mobility was disruptive to enterprise because the new computing paradigm was both too fast and too cheap to be implementable.

This implies that the problem with enterprises is not the stupidity of its buyers. They are no less smart than the average person–in fact, they are as smart with their personal choices for computing as anybody.  The problem is that enterprises have a capital use and allocation model which is obsolete. This capital decision process assumes that capital goods are expensive, needing depreciation, and therefore should be regulated, governed and carefully chosen. The processes built for capital goods are extended to ephemera like devices, software and networking.

It does not help that these new capital goods are used to manage what became the most important asset of the company: information. We thus have a perfect storm of increasingly inappropriate allocation of resources to resolving firms’ increasingly important processes. The result is loss of productivity, increasingly bizarre regulation and prohibition of the most desirable tools.

Which brings us to the latest announcement of collaboration between the new disruptor of computing Apple and the vendors supplying Enterprises like IBM and Cisco.

Apple was the loser in the standardization of computing during the 1990s but is the winner in the mobilization of computing during the 2010s. The company positioned itself in both cases on consumer computing but it never gave up on enterprises.

The approach of Apple seems to be to enable the larger suppliers of technology to enterprises to bundle iOS as part of the acceptable set of services and products. In essence, Apple is complying with the requirement to be slow and expensive in order to be adopted. It can maintain the cadence of product development while attaching itself to the purchase cycle of the enterprise.

In a way it’s like an automatic transmission in a car. Operating through gears, the engine can rev at a different rate than the wheels turn. Occasionally, shifting happens but the fluid coupling keeps both the engine and the wheels from absorbing any damaging shocks.

Influencer Insights Podcast | Kea Company’s Influencer Insights

Over the last couple of years we have been witness to the rise (and fall) of new research initiatives. What defines them, and what drives them to take on the market as they do? Hosts Thom and Derk Erbé are joined by Phil Fersht, Michael Coté, William Tincup and Horace Dediu. The panel drills down on new types of industry analysts and how they will change the IT research landscape.This is the third and final part of this podcast.

Source: Influencer Insights Podcast | Kea Company’s Influencer Insights

The Critical Path #157

Horace discusses the recent market turmoil and takes listener questions on everything from Alphabet to SpaceX.

Source: The Critical Path #157

The Critical Path #156

Horace and Anders discuss Uber’s transportation business and discuss how software modularizes the world. In the second half of the show, they take listener questions posted to Twitter using the hashtag #CriticalQuestion.

Source: The Critical Path #156

(Much) Bigger than Hollywood

Eddy Cue seems like a nice guy. I can’t say that for sure as I’ve never met him, but he seems to be amiable enough. Maybe it’s because he has a seat on Ferrari’s board of directors. Maybe it’s because he enjoys dancing.

Or maybe it’s because he’s in charge of the only real “division” at Apple. All the other senior managers have functional roles. Eddy has a bona-fide business unit called Services.

Services is Apple’s division of many things. It has the iTunes stores (Music, Video, Apps and iBooks). It has Software with consumer bundles like iWork and iLife and Pro tools like Aperture, Final Cut Pro and Logic Pro. It still has OS X as a product, though revenues are pretty low as updates are now free. It also includes Services with iCloud, Apple Music and Applecare.

These things are not iPhones or iPads but they are many and all together they form a modest little unit. I say modest because not much is said about it. When seen in contrast to the other Apple product lines, it’s hard to be impressed. In the graph below it’s the purple area.

Screen Shot 2015-08-25 at 5.56.19 PM

Apple does not help much. Occasionally  Apple offers updates on iTunes/Services using various (rarely the same) metrics. For example, in early August, Eddy Cue offered an update during an interview with USA Today on Apple Music relating how many users there were one month after the service started (11 million).  It was worth a few headlines.

However he also noted in passing that the App store did $1.7 billion in transactions during July. If you convert that to a yearly run-rate it comes out to about $20 billion/yr. Digging through previous announcements, the equivalent figure for 2014 was about $13.7 billion. Nice growth.

But is $20 billion of “transactions” of any significance?

Impetus | Transcribing Asymcar

Due to some research and related writing I’ve been working on which revolve around the potential for disruption in the auto industry, I have wanted the ability to quickly search the Asymcar and The Critical Path podcasts to locate material I remember hearing. Naturally, this is difficult at best with the material in audio format only.  I know that an edited version of the first year of TCP was presented in a book format some time ago. But since Asymcar contains much of the content that I needed to referenc

Source: Impetus | Transcribing Asymcar

Podcast: The New Industry Analysts, Who Are They? (Part Two)

Over the last couple of years we have been witness to the rise (and fall) of new research initiatives. What defines them, and what drives them to take on the market as they do? Hosts Thom and Derk Erbé are joined by Phil Fersht, Michael Coté, William Tincup and Horace Dediu. The panel drills down on new types of industry analysts and how they will change the IT research landscape.

This is the second part of this podcast. The first part can be found here.

Source: Podcast: The New Industry Analysts, Who Are They? (Part Two)

Podcast: The New Industry Analysts, Who Are They? (Part One)

Over the last couple of years we have been witness to the rise (and fall) of new research initiatives. What defines them, and what drives them to take on the market as they do?

Hosts Thom and Derk Erbé are joined by Phil Fersht, Michael Coté, William Tincup and Horace Dediu. The panel drills down on new types of industry analysts and how they will change the IT research landscape.

Source: Podcast: The New Industry Analysts, Who Are They? (Part One)

The Alphabet of Google A and Google B

For the last few years, I’ve been proposing that the way to conceptualize Google is as two separate entities: Google A and Google B.

Roughly speaking Google A was the R&D[1] organization and Google B was SG&A[2]. You can find the operating expenses of running each of these organizations in the company’s income statement.  In the last quarter R&D was about $2.8 billion and SG&A was about $3.5 billion[3]. The two entities are further distinguished as follows:

  • Google A was led by Eric Schmidt and Larry Page and Google B was led by persons unknown, but mostly represented by the “Chief Business Officer” Omid Kordestani.
  • Google A spends money. Google B collects money.
  • Google B sends a check to Google A while Google A sends data to Google B (which then sells it on to advertisers and collects money).
  • Google A communicates frequently with optimism and enthusiasm about the future. Google B remains quiet.
  • Google A solves problems of humanity, Google B solves problems for advertisers.
  • Google A has users, Google B has customers (to whom it sells users.)

In summary, Google A is altruistic, Google B is pragmatic. Google A engages in research, Google B engages in commerce. Google A operates in a structure similar to a Bell Labs for the good of humanity[4],  Google B operates in a structure similar to AT&T and collects monopoly rents but without any government oversight.

This was an effective construct for analysis which explained to me much of how Google operated and how it made decisions. So what do we make of Google’s new Alphabet? Is this a dissolution of the Google B/Google A dichotomy?

My initial answer is no. We don’t have a change in this core structure. What we have instead is a split of Google A into Google A and Google A+.

A+ is the crème de la crème of the altruistic Google A. It’s the stuff that really does not make money. It’s the laboratory of Bell laboratories. It’s the moonshot manufacturer. It’s the incubator where hobbies are hatched. It’s the funder of ventures.

After A+ is carved out, Google A and Google B remain exactly as they were, now under a new CEO. The previous CEO no longer has any day-to-day input in the running of Google A and is no longer soiled by association with Google B.

Alphabet is therefore the “holding company” of Google A+, Google A and Google B. I can only suppose that the separation of A+ from A (and the previous A from B) allows the founders to distance themselves even further from the purchase decisions which, through pricing signals, determine where value lies and how resources should be allocated. That must be a great relief.

  1. Research and Development []
  2. Sales, General and Administrative []
  3. Sales and marketing was $2.1 billion and General and Administrative was $1.5 billion []
  4. Using a definition of Good as established by the founder []