Metrics people can trust
Agree definitions for production counts, downtime, quality and OEE, with clear boundaries and ownership.
Make factory data useful to the people running the factory.
Build a dependable picture of output, downtime and quality before investing in more dashboards or advanced analytics.
Discuss this serviceA dashboard can look precise while hiding inconsistent definitions, missing events and unreliable inputs. Useful manufacturing data starts with the operating decision, then traces back to the measurement and its source.
Agree definitions for production counts, downtime, quality and OEE, with clear boundaries and ownership.
Map sources, assess completeness and timing, and prioritise collection and transformation improvements.
Design views and review routines around the decisions made by operators, maintenance and plant leadership.
A practical pilot can start on one production line. Consider how data collection will behave during power or network interruptions and how operators can correct incomplete or misclassified records.
Yes. Existing records can reveal useful patterns and data gaps. Start by defining the decisions and validating the data before selecting a collection platform.
Usually the first step is dependable data, clear definitions and an agreed operating use case. Advanced analytics should follow when the underlying information and business case justify it.
Tell us what is happening on your factory floor.
We’ll start with the right questions.