The Data and Integration Layer

Part 3 of AI Transformation: From Ambition to Impact AI initiatives create value at scale when they operate inside the analytical and operational context of the business. Outside of it,…

Why AI initiatives fail

And why the explanation is organisational, not technical Enterprise AI is not failing because the models are weak. It is failing because most organisations are not designed to absorb, validate,…

from insdustry to information thinking Illustration

The Productivity Trap

A familiar management reflex still dominates organisational thinking: if we optimise output per unit of time, everything else will follow.

Productivity is assumed to be unambiguously good. More productivity, better outcomes. Organisational success is framed as the aggregation of individual efficiency: more features shipped, more reports generated, more emails processed, more meetings attended.

For a long time, this logic worked. In an industrial economy, productivity thinking was the correct response. Materials were stable. Processes were linear. Environments were predictable. Scientific management, time–motion studies, and standardisation delivered extraordinary gains. They helped build the modern industrial world.

But we no longer operate in that context. Applied to information work, productivity thinking produces pathological outcomes.