The business case
Where the return on an operational data platform actually comes from, four value levers, the cost of doing nothing, and what not to promise.
The cost of doing nothing
What it costs to leave operational data uncontextualised, the recurring losses, the compounding ones, and how to put a number on both.
Where to start
Choosing a first DataHub project narrow enough to finish and valuable enough to fund the next one, with a 90-day plan.
Value paths
Six proven ways to get value from DataHub, what each one requires, what it returns, and how long it takes.
AI agents
Why AI agents reason faster and more accurately against a knowledge graph, the use cases that work today, and how agents can write and operate their own integrations.
Product discovery
How to find the work in your organisation worth handing to an AI agent, score the candidates on your own numbers, and build the first one so it survives production.
Measuring the return
The metrics to baseline before you start, what to measure at 90 days and at a year, and the leading indicator that matters most.
Board briefing
A board-level paper on an operational data platform: what is being proposed, the options considered, what it returns, what could go wrong, what is being asked, and how the board will know it is working.
Industry examples
The same platform and the same four building blocks, modelled five different ways, led by a worked oil-and-gas example on cutting chemical use at a processing facility.