I was recently talking to a business owner, trying to understand his business better.
I asked a simple question: "What were your sales numbers?"
The answer came — but it wasn't clear if it was good, bad, or even close to target. That's was a strong reminder: a single data point is meaningless unless you see it in context.
Numbers without reference don't tell us:
- Did we meet the target?
- Are we improving or declining?
- What story is the trend telling?
- How does this compare to last week, last quarter, or to the average?
This is also where dashboards often fail. They end up as collections of raw data, without perspective, insight or story.
When you design a dashboard, the right questions to ask are:
- In what context should each data point be seen?
- What comparisons actually help you understand progress or lack of it?
- How can the structure allow you to drill down and locate the problem?
Because without this, a dashboard is just another fancy chart on your screen.
At INT, we look at dashboards in a very specific way:
Start with a handful of high-level metrics that show where the company stands, and where we want to go. The "goal level projects" are decided and tracked from here.
If something looks off, then drill into the next level of KPIs.
Avoid showing all KPIs at once — it creates noise, not clarity.
Use deeper layers only when the broad numbers raise a red flag. Find the root cause of the problem, and possible solution. And, then set the responsibility and timeline for the same. This gets us "hot fix projects", which we set, and track.
But here's the warning. Sometimes one cause may improve the headline metric, while another hidden factor is quietly building up and will hurt later. That's why second-level KPIs are still important — not for daily distraction, but for catching risks before they surface. There should be dedicated time to look at problems which are "cooking slowly"
Remember - exception is a rule!
To me, the true purpose of data and dashboards is simple:
- Show where the company stands vs. where it was meant to stand.
- Highlight gaps clearly. Highlight emerging risks and warning signs.
- Allow you to dig deeper into the cause.
- Enable decisive action.
- And if you can trace the problem back to its root cause, that's even better.
Because in the end, data is not about reporting numbers.
It's about telling the story — and helping you act on it.
If you are the decision maker - demand KPI and data accordingly. And if you are presenting performance or KPIs, make sure you share your story (the real one - not a good looking one), cause and effect understanding, and suggested solution.