Managing Complements

Most software companies fall short of perfection, and that’s just the way it goes. It’s routine for most software firms to slap beta on the product and ship.

Most companies aren’t Apple, however. In case you missed it (and if you did, where have you been?), Apple released imperfect mapping software for the latest iPhone. The Washington Monument ended up on the wrong side of the street. Bus routes didn’t appear in many major cities. Mere glitches for most firms, but for Apple it was embarrassing. The firm has not quite learned how to do beta.

Lost in the ensuing brouhaha was a fundamental economic question. To wit: is it best to own a newly invented and complementary piece of software that works with lots of other software? Even Siri doesn’t have an obvious answer to that question. Let’s consider it.

The Prevailing View

Talk to the management at leading technology firms in the same market, and the similarities in opinions are striking. Most hold roughly the same set of opinions, beliefs, and ideas about how specific actions lead to successful business outcomes. For lack of a better phrase, I call this the “prevailing view.”

The prevailing view is an important aspect of every market. It can persist for a long time, and it can change, sometimes slowly and other times quickly. In common speech, momentous changes define the divide between one era and the next.

Where does the prevailing view come from, and how does it shape economic outcomes? That is this column’s topic.

Does Google get a good ROI in KC?

What in the world is Google doing with its high speed network in Kansas City? Does Goggle expect the revenue to exceed the costs of building the network? Dave Burstein has some numbers to illuminate the question.

Dave Burstein is a communications junky for the major communications junky. He covers many topics in communications markets, and he obsesses over finding the true facts, not merely the sound bites. Last week he provided an outline of the basic economic parameters behind Google’s investment in high speed broadband in Kansas City, and his notes make for interesting reading about the project.

I would guess that most readers of this space are not junkies. I know how to read what Burstein writes. The purpose of this post is to provide a translation.

A Big Payoff

Google and Apple are two of the most profitable companies on the globe today. They seem to share little in common except that achievement. They took very different paths to the stratosphere.

Google, after all, is less than a decade and a half old, a child of the web with a successful approach to advertising, built around a search engine and many services to enhance the user’s experience. Apple is more than twice as old. Its original product, personal computers, makes up a fraction of its sales today, while its future profitability lies with a mix of software in iTunes and new hardware introduced in the last decade—namely, phones, tablets, and portable music devices.

What economic insight emerges from setting these two firms next to one another? A brief discussion of both of their businesses will reveal something trite and something deep. The trite part is this: Some settings produce lots of market value, and some firms capture large parts of that value, but those rarely happen together. The deep part forms the key insight today: these examples are fabulously profitable because they are unique.

The grocery scanner and barcode economy

Think about the world of bar codes and scanners. What was life like before their invention? This post offers an appreciation for this staple of modern retail life.

Give the barcode its due. The widespread deployment of barcodes and scanners reduces the costs of keeping accurate and timely inventories. It happened quietly in the last few decades and had numerous consequences.

Think about it. The number of products on the shelf of a typical retail store has increased by tens of thousands. The accuracy of cashiers has increased tremendously because the cashiers do not have to pause to read the price tag. Firms keep better inventory so the frequency of stock-outs — missing items — also has declined.

More to the point, all of that happened because somebody took the time to develop the bar code. Somebody made effort to get everyone in the industry to invent the equipment to take advantage of barcodes.

Among the influential people in that effort was a fellow named Alan Haberman. He passed away last week.

I never knew the man, so I cannot wax eloquent about his life. But I know something about bar codes, as well as the economics of value built around such symbols. Modern life could not exist without them. That is why this post is not a eulogy. It is an appreciation.

It would be an exaggeration to say that barcodes set me on my life’s intellectual path, but they were an influential example when I was a fledgeling and impressionable scholar. The bar code was one of the three canonical examples of the new era unfolding before us in the 1980s, a world of new standardization and increased interoperability. (VCRs and PCs were the other two). Those three examples, as well as a few others, did motivate my interest in the economics of this phenomenon. As readers of this space know, I have stayed here because new examples arise all the time, and in such diverse areas as WiFi, travel intermediaries, the MP3 player, smart phone, and in many places online.

Alright, maybe I am (a little) nuts, but read on.

In appreciation to Haberman’s life’s work, this is an opportunity to wax on a bit about the joys of the scanner economy. Once you begin to recognize the economics of bar codes, you realize that these economics are everywhere.  I hope you find this interesting, illuminating, and a little amusing.

Digital Dark Matter

Astrophysicists draw on the term “dark matter” to describe the unseen parts of the universe. Many symptoms, such as the rotational speed of galaxies and gravitational effects, indicate the presence of dark matter. Yet, our present science lacks the appropriate concepts and tools for measuring directly what we only see indirectly today.

Economists need a similar label for some important building blocks of the digital economy that we do not measure using standard tools. Many indirect symptoms indicate their growth and importance. Many labels have been proposed—invisible infrastructure and private provision of public goods, for example. These labels capture a grain of truth, and, yet, miss something, too.

Let’s just call it “digital dark matter” and review what we know.

An Economic Perspective on Revolutionary US Inventions

American Heritage marked the twenty fifth anniversary of its magazine, Invention and Technology, with an engaging theme. The editors picked their top twenty five revolutionary inventions in the United States.

Before reviewing the top 25, let’s admit to the obvious. Editors compile lists with full awareness that no list will be definitive. Almost by definition, any educated reader will disagree with someone else’s assessment of the twenty five most revolutionary inventions.

Rather, lists are a contrivance, a device to generate a thoughtful discussion about a topic.

Well, so be it. The editors at Invention and Technology succeeded with me. I would like to offer some alternatives to their list, using an economic sensibility. Economics provides a perspective that differs from a technologists’ perspective, emphasizing new modes of production and improvements in human welfare, namely, the economic impact of invention.

More to the point, this essay will stress what is “missing ” from the list compiled by Invention and Technology. Among the missing are hybrid corn, McDonalds, the cellular phone, the commercial Internet, the assembly line, fast drying paint, the IBM System 360, the birth control pill, and PCR.

In addition, this essay ends with observations about the drawbacks to conceiving of invention too narrowly. I end with several honorable mentions for institutional inventions found uniquely in the US. These were performed at the FDA, within venture capital, and by the traitorous eight (pictured on the right).

I hope you will react to this essay. In other words, you should feel free to disagree, and respond with your own nominees for revolutionary inventions.

Why large firms can’t innovate: Don’t generalize

Recently Robert Scoble published a provocative essay about why Google has difficulty innovating. His answer was provocative, but unbalanced. His answer stressed that Google, like any large firm, has a problem with innovation linked to small teams. The post raises many interesting points, and I recommend reading it.

Perhaps the best feature of the post is Scoble’s incessant piling on of stories. He brings in a few Microsoft stories to bolster the notion that Google’s problems resemble the problems found at other large software firms who had a history of innovation but lost it.

I will admit that it suckered me in. Comparing Google to Microsoft is a bit of a team sport in high tech blogging these days. I have engaged in it myself in these very pages. That does not make the observation valid, however.

More to the point, Scoble’s observations do not generalize. Large firms have difficulty innovating in some contexts. This should come as no surprise, since, after all, firms are built for some sets of problems and not all problems. Hence, no firm is good at everything. Google is large, so it faces challenges in some contexts. What else is new?

(By similar reasoning, by the way, small firms have a hard time innovating in some contexts too. Nobody ever gets exercised over that. But when a large firm faces problems….oh, what hand wringing!)

So here is the big point. While it is very interesting to hear about one rich firm’s problems competing with start-ups, that observation, by itself, does not give anything like a complete picture. This post will consider in what sense Scoble’s observations were incomplete.

Why care about incomplete analysis? Perhaps you will want to read this before you go and short all your Google stock.

Gateway economics

It has become fashionable among Internet and Web watchers to notice threats on the horizon to the open Web. For example, in garish colors, Wired magazine’s September 2010 issue declared the open-access Web dead. Jonathan Zittrain’s 2008 book, The Future of the Internet and How to Stop It, developed a related thesis in great detail (as well as much more).

Economics tends not to take such an alarmist approach to the future of the web, viewing it with more equanimity or acquiescence, depending on your perspective. Today I want to illustrate that approach by discussing a specific practice, gatekeeping, which is an anathema to many openness advocates.

Gatekeeping encompasses two related activities. In one case, a vendor controls and manages a user’s access to proprietary content, charging a fee for access. Famous recent practitioners include Rupert Murdoch, whose company, News Corp, owns the Wall Street Journal. His company does not allow unrestricted viewing of online articles from the Journal. From time to time Murdoch publicly mutters a threat to block search engines from indexing his site if such blocking could lead to more revenue.

In a second type of gatekeeping, a vendor uses proprietary code to control and manage a user’s, developer’s or advertiser’s experience. The most famous practitioner of this approach was Bill Gates. Recently Steve Jobs, whose rules for iPhone app developers change frequently, has been getting all the attention for restrictive practices.

Let’s take a closer look.

Digitization and Value Creation

Often, the simplest economic questions are the hardest to answer. Consider these: How much economic value did the massive decline in the cost of digitization in the last two decades create? And, would a similar level of decline in the next decade create the same amount of value?

These are surprisingly difficult questions to answer. Do not get me wrong. Obviously, large cost declines create new value. How much value? We can look deeply at the past but still find it hard to answer that question with any precision. Many factors enhance or limit the extent of value created. If we cannot analyze the past, surely predicting the future is fraught with challenges.