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A factory does not need another dashboard simply because a dashboard can be built. It needs a better way to recognise a loss, understand it and change the conditions that cause it.
That is a useful starting point for digital manufacturing strategy: identify a problem in the operation before choosing a platform.
Make the opportunity concrete
“Improve performance” is an ambition. “Reduce material lost during changeovers on this line” is a problem that a team can investigate. It has a location, a process and an observable outcome.
Before building a use case, agree on three things:
- The loss: what is being wasted, delayed or constrained?
- The baseline: how will the team measure the current situation?
- The owner: who can change the way the work is done?
Connect information to a decision
Every proposed data product should have an answer to a simple question: what decision will become easier, faster or more reliable?
| Operational question | Useful information | Possible response |
|---|---|---|
| Where is material being lost? | Loss by product and process step | Investigate recurring causes |
| What interrupts production? | Downtime with operational context | Prioritise reliability work |
| When is energy being wasted? | Consumption by operating state | Review idle operating practices |
The response is part of the use case. Displaying the information is only one step.
Prove the improvement close to the work
Start with a bounded use case. Establish a baseline, agree how success will be assessed and involve the people who will use the result. Compare performance in comparable operating conditions, and make uncertainty explicit.
A useful pilot tests whether a new way of working improves the operation.
Build for repetition
Once an improvement has been demonstrated, document the process, data definitions, ownership and operating routine that made it work. Those become the starting point for the next line or factory.
The goal is to make a proven improvement repeatable.