Pete HitchenExecutive Leadership & Advisory

Ideas for leaders

Insights & frameworks

Three practical lenses for building confidence in data, agreeing what to measure and giving people a way to resolve problems together.

The five-stage framework

Crossing the Trust Chasm

The crossing happens when teams can demonstrate data quality, agree who owns decisions and apply controls consistently. That gives leaders a basis for deciding where AI can act.

  1. 01Reporting

    What happened?

  2. 02Dashboards

    Can I explore it?

  3. 03Trusted data

    Can I believe it?

  4. 04Governance

    Can everyone rely on it?

  5. 05AI

    Can a machine act on it safely?

Stages 3 and 4 turn confidence in individual reports into a capability the organisation can rely on.
Download the executive white paper (PDF)

01 / Decision confidence

Trust Chasm

The Trust Chasm is the gap between having data available and having enough confidence to act on it. It shows up when people reopen the same reporting debate, build their own extracts or delay a decision while someone checks the numbers.

Put it to work

Start with one recurring decision. Ask which figures people challenge, who can explain where they came from and what level of uncertainty the decision can tolerate. Give one owner the job of resolving the most consequential gap.

Which decision would we make differently if we trusted the evidence?

02 / Durable measures

Granite Metrics

Granite Metrics are the small set of measures a leadership team can use consistently over time. Their definitions should be clear enough that two teams can explain the same number and understand what drove a change.

Put it to work

For each measure, record the business question, definition, owner, source and review cadence. When the definition changes, record the date and whether past periods remain comparable.

Can we explain this measure and reproduce it next quarter?

03 / Shared ownership

Data Guild

A Data Guild gives people across business and technology a regular place to resolve shared data problems. Its work can include agreeing definitions, surfacing quality issues and helping teams apply governance in their day-to-day work.

Put it to work

Start with a few recurring issues that cross team boundaries. Bring together people who can make decisions or carry them out. Keep a short record of what was agreed, who owns the next step and when the group will check progress.

Which recurring issue needs a decision that no single team can make alone?

Working through one of these questions?

Tell me where the decision is getting stuck.

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