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.