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Short, useful reads on Lean, AI², and the questions that move strategy forward.
Most AI proofs-of-concept work. Almost none reach production. The gap is rarely the model — it's everything around it.
Demos are optimised for the gasp. Operations are won on the metrics no one claps for — queue time, rework, lead time.
Leadership knows where the work is hard. The map almost always shows the cost is somewhere else — in the queues between steps.
A roadmap full of good ideas is not a strategy. Strategy is the discipline to leave good ideas on the table.
Most AI programs start with the tool and look for a problem. We start with the waste and let it choose the tool.
Two questions that cut through most strategy decks faster than any framework. Here's how we use them.
AI² is your business expertise multiplied by what AI can now do. The order of operations matters.
The goal is not to remove people from the decision. It's to give them a sharper decision to make.
The interesting AI decision is rarely which model. It's how much of the surrounding system you should own.
Work flows sideways across an organisation. Most companies are managed up and down. That mismatch is where value leaks.
The cost of a wrong call falls as the bets get smaller and the loops get faster. Design for that, not for being right.
The first move in most AI programs is to build a data platform. The better first move is to use what's already on hand.
Because the gap we kept seeing was not a shortage of AI — it was a shortage of the discipline to point it at the right problem.