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Agent Readiness

How ready are you for agents that act?

Most organisations can already run a model. Far fewer can let its output change something without a person retyping it. Twelve questions, about four minutes, and the score is on screen the moment you finish — no form in the way.

Data foundation

An agent cannot act on a number it cannot get, or trust one it cannot trace.

Demand, stock and capacity can be read together for the same period without manual reconciliation.
Key figures have one agreed definition across departments — "on hand" means the same thing everywhere.
Operational data is available at least daily, not as a month-end extract.

Decision clarity

Automation needs a decision with a known owner, a known input set and a known success measure.

The recurring operational decisions are written down, with who makes each one.
For at least one of them, we could state the inputs and the rule a good decision follows.
We measure the outcome of those decisions, not only the activity around them.

Governance and trust

The question is never whether the model is clever. It is who is accountable when it is wrong.

We know which decisions may be automated and which must stay with a person.
An automated action would be logged with its reasoning, its inputs and its approver.
We have a stated position on where data may be processed and by whom.

Execution path

A recommendation that a human must retype into another system is not automation.

Our core systems can be written to through an API or an integration layer, not only through their screens.
There is an approval step an automated action could be routed through.
An action taken in error could be identified and reversed.
Reading the Result

What the score actually tells you.

A low score is not a verdict. It usually means one dimension is holding the others back, and that is a smaller problem than it looks.

0–39

Reporting

The organisation can describe what happened. Decisions are made from exports and experience. Start by writing down one recurring decision and the inputs it really uses — not the ones it is supposed to use.

40–59

Analysing

Prediction exists somewhere, usually in one team. The gap is the handover: the forecast is produced, then a person carries it to the system where the action happens.

60–79

Recommending

Recommendations reach the people who act on them, with reasoning attached. The remaining work is usually governance: agreeing which actions may proceed without a signature.

80–100

Acting

Agents can be given real scope: bounded decisions they execute, logged and reversible, with people supervising the exceptions rather than the routine.

Go Deeper

Get the written breakdown.

The score tells you roughly where you stand. The breakdown tells you which single change moves it most, based on what we see in organisations that answered the way you did.

  • Your four dimension scores, with the two questions dragging each one down.
  • The decision we would automate first in an organisation shaped like yours.
  • What would have to be true before that decision could run without a person.

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