Data-driven
organization
The framework

Six dimensions.
One connected system.

A data-driven organization grows through the conditions around everyday decisions. See how people, data, responsibilities, and technology support one another.

01 / Understand the systemChapters 1–4
  1. 01

    Notice the friction.

    Which recurring decision is harder than it needs to be?

  2. 02

    Trace the system.

    Which handoffs, incentives, or boundaries keep producing it?

  3. 03

    Connect the dimensions.

    What would a change need, enable, or shift elsewhere?

  4. 04

    Choose the next constraint.

    Which bounded change does the evidence support now?

When the explanation does not hold, return to the observed work.
From a visible problem to a challengeable explanation and one responsible next change. Revisit the questions whenever the work gives you a reason.
02 / The six dimensions · Chapters 5–10

Strengthen what matters.

See how capability grows across the system, as progress in one dimension changes what the others can support.

Six dimensions, in relationship15 connections
The six dimensions develop together, at different ratesSix radial axes represent People, Data Quality, Data Architecture, Data Governance, Automation, and AI. Every dimension connects to all five others, giving fifteen undirected connections. A filled shape changes through an illustrative planning workflow. Its unnumbered distances are not measurements, maturity levels, or transferable permissions. The written story below explains each moment.
People
DataQuality
DataArchitecture
DataGovernance
Automation
AI
An illustrative development story
Moment 01 / 07

Start where you are.

One weekly planning decision depends on private knowledge, uneven data, and workarounds. Start with the capabilities the work already has.

Explore the relationships

Each dimension changes the others.

Select a dimension to follow its five connections. Each relationship is a question to test in real work: what does this change need, enable, or make harder elsewhere?

  1. 01See the starting point
  2. 02Create shared meaning
  3. 03Build a dependable route
  4. 04Connect everyday operation
  5. 05Add a bounded AI use
  6. 06Reinforce shared support
  7. 07Strengthen the response

One possible path for one planning workflow. The area illustrates capabilities growing together at different rates, not measured company maturity. The rings are visual guides, not levels.

Framework and illustrative relationships: authors’ synthesis.

03 / Chapters 11–15

Make progress last.

A local result becomes useful beyond its first moment when the organization can support, question, adapt, and, when necessary, end it.

Chapter 11

Start small. Leave something dependable.

Keep exposure bounded and responsibility complete.

Chapter 12

Test fit for reuse.

When another consumer needs it, establish what can travel and what must change.

Meaning + lifecycle
Chapter 13

Make responsibility workable.

Place authority, capacity, funding, and incentives around the work they must support.

Authority + support
Chapter 14

Let evidence challenge the result.

Observe outcomes, behavior, risk, and who carries the burden. Name the response.

Evidence + response
Chapter 15

Choose the next turn.

Act within the evidence. Renew after material change.

  • Advance
  • Repair
  • Narrow
  • Hold
  • Retire
Keep the protected function and continuing responsibilities in view.Return to the next constraint
Three equally useful ways into the book

Follow the argument / Start with your problem / Open a practical tool

How far can this contribution reach?

Support comes
before wider use.

A useful local contribution and a dependable shared capability make different demands. Ask what the evidence supports for this decision, in this context.

Bound the contribution

Make one contribution and its limits visible for a named use.

Make it dependable

Establish that the contribution can be supported in everyday operation.

Prove fit for reuse

Test whether it fits a materially different context and can be sustained there.

Coordinate support across contexts

Support wider use with the responsibilities and capacity it requires.

Renew after
material change

Review the contribution when important conditions change or its validity expires. Establish what can still be supported, what needs to change, or what should end. Renewal is separate from operating reach.

These questions describe a scoped contribution. They do not assign a maturity score to a company.

What makes the approach practical

Choose the next
responsible change.

Start with the work.

Examine a real decision or workflow before selecting a platform, program, or organizational structure.

Respect the boundaries.

A missing hard condition cannot be offset by strength elsewhere. Keep simpler, local, and manual routes available where they fit.

Let evidence change the route.

Advancing is one option. Repairing, reducing reach, holding a supported route, or retiring a use may be the responsible result.

Stabilize, repeat, reuse, and scale with feedback describe work within a change. They are not a fixed sequence, and completing them does not prove that wider use is supported.

The architecture of the book

A route into the argument.
A way back to practice.

01Chapters 1–4

Understand the system.

Start with a real decision. Follow the friction, see the dependencies, and choose the next useful change.

02Chapters 5–10

Strengthen what matters.

Enter through People, Data Quality, Data Architecture, Data Governance, Automation, or AI. Work on the contribution your decision needs.

03Chapters 11–15

Make progress last.

Connect delivery, reuse, responsibilities, evidence, and renewal. Return to the next decision with what you have learned.

Three equally useful ways in

Follow the argument / Start with your problem / Open a practical tool

From the book to your organization

Make your next
decision a better one.

Bring the framework into a leadership conversation, a workshop, or your next event.

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