Theory of Constraints

I recently finished "The Phoenix Project", a novel about a struggling company that turns itself around by fixing its IT processes. It's heavily inspired by Eliyahu Goldratt's "The Goal", which introduced the Theory of Constraints: a framework for analyzing system performance that's deceptively simple yet powerful.

The core insight: Every system has exactly one constraint that limits its overall throughput. Any improvement effort that doesn't address that constraint is wasted effort.

This ties back perfectly to my recent post about saving doctors from admin overhead. If physicians are the constraint in a healthcare system (and they almost certainly are), then any innovation must protect or alleviate that constraint. Improvements elsewhere in the system don't just fail to help. They can actively make things worse.

Speedups upstream of the constraint overload it further. Streamlining patient intake just means the waiting room fills up faster. You haven't increased the number of patients the doctor can see. You've just made the bottleneck more obvious.

Speedups downstream of the constraint get starved. Hiring more lab technicians or buying faster equipment sounds productive, but those resources sit idle waiting for test orders. The physician can only order tests for as many patients as they can actually see. The expensive lab equipment becomes an underutilized asset.

That's why even wildly successful AI initiatives that cut some tasks’ time by 90% can fail to deliver business results if they don't address the true constraint. You've optimized the wrong part of the system.

So before launching your next improvement initiative, ask: What's the real constraint in this system? And is what we're doing actually helping it?