Automated operations reporting
Hand-built reports cost hours every week and cannot be defended when someone asks where a number came from. Why operations automate reporting, and how to build pipelines that hold up.
analysts stop collating and start analysing
the same measure means the same thing
every figure traces to its source record
The challenge
Daily and weekly operations reporting is commonly assembled by hand from the ERP, equipment telemetry, the maintenance system and a set of spreadsheets that live on one person's drive. Definitions drift between them, so cycle time, utilisation and availability come to mean different things depending on which report is open.
Reporting built this way is slow, fragile and hard to defend, and operations also answer to regulators, joint venture partners and boards who expect a figure to be traceable. Analysts and superintendents require reporting they can stand behind, produced from governed data rather than reassembled every morning.
When it's time to act
The signs we commonly see when this initiative is due.
- Monday starts with an analyst stitching exports together before anyone can see last week.
- Two reports quote different figures for the same measure and both are technically right.
- The report does not go out because the person who owns the spreadsheet is on leave.
- An auditor or joint venture partner asks where a number came from and the answer takes a week.
- Definitions drift a little every time a report is copied for a new audience.
How we deliver it
Report audit
Catalogue every report, its consumers, and the single agreed definition of each measure.
Source mapping
Map ERP, telemetry and maintenance data to those measures, including gaps and quality issues.
Pipeline build
Automated extract, transform and load into a dimensional warehouse with conformed definitions.
Validate and trace
Rule-based checks on every load, with lineage from any reported figure back to source records.
Deliver
Scheduled reports and dashboards, run in parallel with the old process until trusted.
Report audit
Catalogue every report, its consumers, and the single agreed definition of each measure.
Source mapping
Map ERP, telemetry and maintenance data to those measures, including gaps and quality issues.
Pipeline build
Automated extract, transform and load into a dimensional warehouse with conformed definitions.
Validate and trace
Rule-based checks on every load, with lineage from any reported figure back to source records.
Deliver
Scheduled reports and dashboards, run in parallel with the old process until trusted.
Our approach
- Understand where the reporting burden actually falls and which numbers get argued about, by sitting with the people who assemble the reports and the people who act on them.
- Assess the current reporting process against your internal definitions and any external obligation you carry, so the target is agreed before anything is built.
- Start from decisions, not data: agree a single definition for each operational measure with the people who use it.
- Build automated pipelines from the ERP, equipment telemetry and the maintenance system into a dimensional warehouse modelled on Kimball star schema principles.
- Apply validation rules on every load, flagging missing timestamps, incomplete records and out-of-range values before they reach a report.
- Preserve lineage so any figure in the daily report or an external return traces to source records in one click.
- Run the automated report in parallel with the manual process until the operations team signs off on the numbers.
Tools and methods
The value it creates
- Manual collation disappears from the weekly routine, and the daily report lands at a fixed time whether or not anyone is in early.
- One agreed definition per measure ends the duelling-spreadsheet problem between operations and maintenance.
- External returns are produced from governed data with full lineage, which makes them faster to prepare and straightforward to defend under audit.
What changes
Reports assembled by hand each morning
Pipelines that land the report at a fixed time
A definition per spreadsheet
One agreed definition per measure
Figures that cannot be traced
Lineage from any number back to its source records
Analysts collating
Analysts analysing
Where these initiatives fail
The failure modes we design against.
- Automating the existing spreadsheet, drift and all, instead of agreeing definitions first.
- Skipping validation gates, so the pipeline delivers wrong numbers faster.
- Cutting over before the parallel run has earned the operation's trust.
- Leaving lineage undocumented, which rebuilds the defensibility problem the project was meant to fix.
Common questions
Which systems can the pipelines draw from?
The common set is the ERP, plant historians and telemetry, and the maintenance system: SAP and Pronto Xi extracts, AVEVA PI and OPC UA sources, and SQL databases all feed the same warehouse. Anything with an export or an API can usually be brought in.
What happens when a source system changes?
The dimensional model isolates reports from source structure, so a source change is absorbed in the load layer rather than breaking every report built on top of it.
Can our own analysts still build and adjust reports?
Yes, that is the goal. The platform is a governed foundation your analysts build on, and handover includes the definitions, lineage documentation and training to do it.
Key terms
Plain-language definitions from our glossary for the concepts this page leans on.
Standards and further reading
Reference points we draw on where they suit the work. We also work to client internal standards and established site practice.
- DAMA Data Management Body of Knowledge (DMBOK) (DAMA International)
- ISO 22400-2:2014 KPIs for manufacturing operations management (ISO)
- Guidelines library for mining technology and interoperability (Global Mining Guidelines Group)
- Dimensional modelling techniques (Kimball Group)
- ISO 8000-110:2021 Data quality, master data exchange (ISO)
- ISA-95 enterprise-control system integration (ISA)
Further reading
Articles and calculators on the methods behind this work.
- Digital transformation on a working mine site (article)
- Agriculture solutions (solution)
- Building software that runs a 24/7 operation (article)
Related projects
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