Ask a team what they want from a new reporting capability and you'll usually get a list of charts. That's fair enough. Dashboards are tangible and easy to picture. But starting with the visuals tends to produce screens that look finished and still leave people unsure what to do next.
Work backwards from a real decision
A more reliable approach is to start with the decisions people actually make. Which maintenance jobs get done first this week? Where do we put extra staff? Which services are costing more than we expected, and why? Each decision points to a handful of measures that genuinely matter, and tells you how accurate and how current they need to be.
- Who makes the decision, and how often?
- What do they use today, and how much do they trust it?
- What would they do differently if the information were better?
- How current does it need to be to be useful?
A worked example
Here's a simple, hypothetical example of what that looks like written down. It's not a client case, just the shape of the thinking.
- Decision
- Which overdue maintenance jobs get scheduled this week
- Owner
- Operations manager, every Monday morning
- Measure
- Overdue jobs by asset criticality and days overdue
- Definition
- A job is overdue once it passes its planned date and has no completion record. Agreed with operations and finance.
- Source
- Maintenance system work orders, joined to the asset register for criticality
- Refresh
- Daily overnight. Real-time adds cost without changing a Monday decision.
- Action
- Top ten critical jobs scheduled. Anything else overdue by 30+ days is escalated.
Trust is the real deliverable
Once the decisions are clear, the data work gets far more focused. You can see which sources matter, which definitions need agreeing and where quality problems will knock people's confidence. A modest report built on agreed data is usually worth more than an ambitious one that people quietly check against their own spreadsheets.
The goal isn't more charts. It's fewer moments where someone has to guess.