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Bob Metcalfe has been predicting the imminent collapse of the Internet in these pages. Since your employer looks to you for technical expertise and advice, and since Dr. Metcalfe is a Recognized Industry Pundit (RIP), you’re probably worried about having recommended building that big Web site.
I’ve decided to offer a different perspective on the problem so you can trot out a second RIP to counter the effects of the first. (Also, if Dr. Metcalfe and I quibble in print you get to gripe about the incestuous nature of the press in Ed Foster’s gripe line, post items in our Forums on InfoWorld Electric (www.infoworld.com) and otherwise feed the liberal media conspiracy.)

Anyhow …the Internet scares people. Commonly described as an anarchic agglomeration of unplanned interconnections, it makes no sense to those who believe central planning is the key to quality.

Many of those same people, Dr. Metcalfe included, also say they believe in the power of laissez-faire capitalist economics. In other words, they believe in the power of Adam Smith’s “invisible hand” that uses market forces to regulate the interplay of independent agents.

From the perspective of general systems theory, this is nothing more than the use of negative feedback loops to create stable systems. (If you’re not familiar with the concept, it just means that inputs listen to outputs, adjusting themselves when the output drifts off course.)

Laissez-faire capitalism says shortages lead to higher prices which reduce demand, eliminating the shortage. Higher prices motivate an increase in production capacity, increasing supply which then reduces price, increasing demand. The result: A self-regulating system with no need for external controls.

Why does Dr. Metcalfe, who believes in this kind of self-regulation for the economy, not believe it will work for the Internet? After all, money comes in along with increased demand. Increased demand leads to supply shortages (poor response time). These shortages certainly can result in higher prices. They also can result in more companies getting into the business, and in existing Internet providers increasing the bandwidth they make available. It’s a pretty basic example of the very same kind of self-regulated economic system most cherished by the all-government-regulation-is-bad crowd.

This doesn’t mean the Internet won’t catastrophically fail this year. Laissez-faire capitalism breaks down in several different circumstances. Here are two:

Any time individuals or organizations compete for a common resource, market forces just plain don’t work.

This is called “First pigs to the trough.” It’s also known as the tragedy of the commons. In merry olde Englande, farmers grazed their cattle on public grazing land – the commons. After awhile, some farmers figured out the more cattle they grazed on public land the more they profited. When all farmers figured it out the cattle overgrazed the commons, ruining it.

Market forces don’t regulate use of a commons – market forces ruin it, leading to the need for external regulation by, for example, the government. Regulation isn’t always a bad thing, despite current political cant.

Another, very interesting way negative feedback loops (including pure free-enterprise economics) lead to unstable results comes from feedback delays. Bring up your spreadsheet and model the “logistic” equation (a very simple negative feedback system): v(t+1)=kv(t)*(1-v(t)). Plot it for a hundred values or so, starting with k=1.1 and v=.01. You’ll see a smooth s-shaped curve.

Change k. Between 2 and 3.5 the curve oscillates. From 3.5 to just over 4 it becomes chaotic, jumping around randomly. Somewhere between 4.01 and 4.001 it crashes to extinction. The lesson: Once feedback isn’t immediate, the value of a constant changes not just the scale of a system but its very nature. The results are unpredictable.

(You’ll find other fascinating tidbits like this in the excellent book, A Mathematician Reads the Newspaper by John Allen Paulos.)

So Dr. Metcalfe may be right – the Internet could turn out to be an unstable, chaotic system.

But I doubt it. I have more faith in free enterprise than that.

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|In: Organizational Effectiveness|Last Updated:

Ever since mass acceptance of the personal computer, its proponents have sold it on how much it would improve productivity in the workplace. Ever since, economists and accountants have tried to find the productivity gains, without much success.

Try to take away employees’ PCs, though, and you’ll have the same success you’d have removing rifles from NRA members – you’d have to pry it from their cold, dead fingers. Hence, the “paradox.”
We’ve been talking about measures for the last several columns, and it seems appropriate to wrap up the subject (for now) with a column on productivity and how to measure it.

Step 1: Make sure productivity is a useful thing to measure.

The plain fact is, productivity just doesn’t apply to every role in an organization. That’s why so many intelligent and ingenious people have tried to develop white-collar productivity measures and failed.
When you measure productivity, you’re measuring how much stuff a person, group, or machine can make in a unit of time. Widgets per hour. Applications per day. Pages per minute.

Productivity only matters in repetitive processes that produce or handle similar items. The concept comes from factory work. A factory manufactures a particular kind of thing, and lots of it. The more things it produces in the same amount of time, the smaller the capital and labor cost of each item. That translates to lower prices and higher margins, both Good Things (to use the jargon of Economics).

Some white collar jobs do involve repetitive processes. Call centers, insurance claims processing, mortgage application processing, all have a lot in common with factory work. And in fact, automation demonstrably increases productivity in these areas.

Interactive voice response systems demonstrably generate 400%+ returns on investment. Just the screen-pop feature of computer telephone integration can shave 15 seconds from each telephone call – often a 5 to 10% productivity improvement. Some imaging and workflow systems have literally doubled claims-processing productivity. Measurably.

The only repetitive process in many jobs, though, is attending meetings.

To prove the point, let’s take the ultimate example: a Hollywood screenwriter. Let’s devise a good productivity measure – I know, words typed per minute! Yup, when we make a movie, let’s get our script from the fastest typist.

Well, I don’t know how fast Steven Spielberg and his friends type, and I don’t care. Productivity doesn’t matter at all. Audience appeal is what matters, and guess what? You just can’t devise an objective measure to predict it. You have to rely on judgment.

Productivity is just one measure of Effectiveness, a more general measure of value. For a factory worker the two are more or less synonymous. For a screenwriter, productivity has nothing to do with effectiveness.

That’s one reason we’ve failed to find any productivity improvements from the introduction of computers to the workplace – we’re measuring the wrong thing. What we need are measures of effectiveness, and we have to realize a nasty little fact: often, the only measures of effectiveness are subjective.

There’s another reason for the productivity paradox. Technology has enabled a complete transformation of the workplace. People type their own memos rather than dictating them and running them through several manual revisions. Often, they write e-mail messages instead and dispatch them immediately rather than printing anything at all.

Financial analysis now involves graphing dozens of variations of a financial model instead of running a paper tape three times to make sure you keyed numbers in right.

Research now involves searching on-line databases and the Internet, instead of making trips to the library or asking your company librarian for help.

Basically, the jobs we hold now may have the same titles as 15 years ago, but they have little in common.

Statisticians call this “non-stationary data” and they don’t let you use it in analyzing trends. (I was hoping to use a related term – heteroskedasticity – but couldn’t work it in. Maybe next time.)

Productivity paradox? I don’t really care if I’m productive at all. I care how effective I am. That’s what you should care about, too.

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