The productivity trap Steve Jobs spotted in 1992

First, apologies for my relative silence over the last month or so – somewhat deeply involved in writing a new book

A splendid article follows which most of the C-suite should read before waving their wallets at all the exciting new software products forever being sold to them on the market

It makes so much sense, and applies to so many organisations

Just published by the Fernandina Observer, Florida, USA

It’s written by Deryck Burnett, Founder and Chief Technology Advisor of Megabite in Fernandina Beach

In 1992, Steve Jobs stood in front of a room of business students at MIT and did something you almost never see a tech legend do.

He admitted he’d wasted 10 years.

Not on the wrong product.

On the wrong kind of productivity.

Jobs had been reading the work of Paul Strassmann, a man who once ran information systems for the Pentagon and had spent years studying hundreds of companies, trying to figure out what separated the winners from everyone else.

Strassmann found something uncomfortable.

The businesses that spent most of their technology budget making managers’ lives easier — nicer reports, faster email, prettier presentations — tended to be the less successful ones.

The businesses that pulled ahead spent their money somewhere else: on the actual work. The factory floor. The delivery route. The thing the company actually does to earn a dollar.

Jobs had a name for the first kind. He called it “management productivity.”

He called the second “operational productivity.”

And he confessed that his life’s work up to that point — the personal computer — had been aimed squarely at the first one.

I’ve thought about that talk a lot lately, because we’re living through the biggest test of it in a generation.

You’ve probably run into Microsoft’s Copilot by now — the artificial intelligence assistant that’s been quietly added to Word, Excel, and Outlook.

Microsoft pulled off something no company ever has: it placed this tool on nearly every business computer in America, automatically, whether anyone asked for it or not. If distribution were the whole game, Copilot would already have remade the working world.

It hasn’t.

Microsoft has sold more than 20 million of these AI seats to businesses — a staggering number — and it’s earning billions of dollars a year from them.

But look at how they’re actually used, and something odd turns up: only about a third of the people who have Copilot reach for it regularly. Most of the seats a company pays for sit quietly untouched.

Why?

Because for most people, Copilot helps with management productivity. It drafts the email. It sums up the meeting. It builds the slide deck. All handy. None of it touches the thing that’s actually slowing the business down.

And there’s the trap — the same one Jobs spotted more than 30 years ago.

It is very easy to spend money looking busy: dashboards, reports, an AI that writes your memos.

It is much harder to spend it fixing the one bottleneck that’s genuinely costing you.

The first feels productive. The second is productive.

I see this every week here in Nassau County.

A business owner tells me they want “better technology,” and what they usually mean is they want to see more — a dashboard, a report, a screen full of numbers.

But numbers on a screen don’t fix anything. They mostly tell you what you already suspected.

The better question is never “what can I measure?”

It’s “what’s the one thing that, if it ran a little smoother, would change my whole week?”

Maybe it’s the checkout line. Maybe it’s how a repair gets scheduled. Maybe it’s the 20 minutes every morning someone loses re-typing the same information into three different programs.

That — the unglamorous, specific, on-the-ground problem — is where technology finally earns its keep.

Not the prettiest dashboard.

The fixed bottleneck.

So the next time someone tries to sell you software for everything it lets you see, ask them a different question.

Ask what it lets you fix.

Steve Jobs worked out the difference in 1992.

Three decades and one AI revolution later, it’s still the most useful question you can ask.


 

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