Prologue 'where the thinking starts'


The process is the picture on the front of the jigsaw box. The data is the pieces. Understand the pieces, their shape and how they relate to one another, and the picture starts to emerge. Get the data wrong and no amount of process modelling will make the picture fit.

And there is a deeper point behind it:

Data is both the input to a process and the evidence left behind by it.

That is why a data-centric approach works particularly well when requirements or processes are still evolving. Processes can be redrawn, organisational responsibilities can change and systems can be replaced, but the underlying business facts tend to be more stable.

For example, an organisation may repeatedly redesign its customer complaints process, but the underlying concepts remain recognisable: customer, complaint, issue, date, communication, decision, outcome. Understanding those data relationships gives you a stable foundation from which the changing process can be understood.

Understand the data and much of the process reveals itself.

Data and Process
Idea Non-technical description Technical description Example
🧱 Data as the building blocks Processes need information to know what to do next. Data represents the entities, states, relationships and events on which process logic operates. An insurance claim needs customer, policy, incident and coverage data before the claims process can progress.
🧾 Data as the record of execution Data tells you what actually happened. Transactions, timestamps, status changes, events and audit records provide evidence of process execution. A claim moving from submitted → assessed → approved → paid leaves a data trail.
💡 Data as the foundation for innovation Once you understand the information properly, you can find new ways of using it. Well-understood data models enable analytics, automation, AI, integration and process redesign without repeatedly rediscovering the business domain. Claims history can support fraud detection, automated triage or predictive reserving.
🔍 Data as forensics When something goes wrong, the data is usually where you find out what actually happened. Event histories, lineage, transaction records and state changes allow root-cause analysis and reconstruction. A payment failure can be traced through claim status, approval, interface message and payment transaction data.
🧩 Data and process The process is the picture on the box. The data is the pieces that actually make the picture. Process models describe expected behaviour. Data provides the underlying state and evidence from which actual behaviour can be reconstructed. A BPMN diagram might say how claims should be handled. The data shows how they really were handled.