The End of Productivity Theater

One of the more curious things I've noticed over the years is that organizations rarely set out to create unnecessary complexity.

Nobody wakes up and says, "Let's add three more meetings and another approval process."

Yet somehow it happens anyway.

A meeting gets scheduled because a decision feels important. A report gets created because someone wants visibility. A review step gets added because a mistake happened six months ago. Each decision feels reasonable on its own.

Then one day the organization looks around and discovers it's spending an enormous amount of energy coordinating work instead of doing work.

I've started thinking about this as productivity theater.

Not because the activities are fake. Most of them serve a purpose. The challenge is that over time the supporting structure around the work can become larger than the work itself.

It's a little like scaffolding around a building.

Scaffolding is incredibly useful while construction is happening. It provides access, support, and safety. The problem comes when nobody remembers to take it down.

Eventually people stop seeing the building altogether and only notice the scaffolding.

I sometimes wonder if the same thing happens inside large organizations.

Status meetings become recurring calendar fixtures long after the original need has disappeared. Dashboards multiply. Reports become more detailed. Communication expands to fill every available gap. Teams spend increasing amounts of time creating visibility into progress while making less actual progress.

What's fascinating is that AI may expose this dynamic faster than any management trend ever could.

When a system can summarize a meeting, write a report, analyze information, and generate recommendations in seconds, it forces an uncomfortable question to the surface.

How much of our effort was creating value, and how much was simply creating evidence that value was being created?

That's not a criticism of organizations. It's a consequence of managing work that is inherently difficult to observe.

Unlike manufacturing, knowledge work doesn't produce visible output every hour. Leaders naturally look for signals that progress is happening. Meetings, reports, presentations, and activity become proxies for momentum.

The problem with proxies is that over time they can become goals themselves.

What I've learned over the years is that most people think they're solving the problem in front of them. More often, they're responding to the incentives surrounding the problem.

If visibility is rewarded, people create visibility.

If outcomes are rewarded, people create outcomes.

AI may end up revealing the difference.

The organizations that benefit most won't necessarily be the ones that automate the most work. They'll be the ones willing to reexamine the assumptions behind the work in the first place.

Because the real opportunity may not be removing effort.

It may be removing friction.

And those aren't always the same thing.