Most organizations don't lack metrics. They have an excess of numbers and a scarcity of indicators that guide decisions.
Dashboards with dozens of charts, spreadsheets updated every week, data-heavy meetings, and in the end, the same unanswered question: what do we need to change right now?
This article answers the question that precedes all others: how to build an indicator that truly matters?
What makes an indicator truly matter?
Define Bernard Marr KPIs as “questions the organization needs to answer to know if it is on the right track.” And this definition is more rigorous than it seems: an indicator that does not answer a management question is not an indicator, it is data.
And for an indicator to truly matter, it must meet four simultaneous criteria:
| Criterion | What does it mean in practice |
| Linked to a goal | There is a clear strategic or operational objective to which it responds |
| Guideable by their companion | The person responsible for the indicator has concrete actions they can take to influence it |
| Measurable with useful frequency | The measurement frequency is aligned with the pace of the decision it supports |
| With goal set | Without a goal, there is no benchmark for success — any number feels acceptable |
If an indicator does not pass these four filters, it is worth questioning whether it should exist on the management dashboard. After all, overloaded dashboards are the main reason teams stop looking at them.
Read more: Project management indicators
Outcome indicators vs. effort indicators
This is the most important, and most neglected, distinction in the construction of management dashboards. And Kaplan and Norton introduced it in BSC under the terms lagging indicators and leading indicators.
Understanding it completely changes the way you build your dashboard.
Understand!
Lagging indicators
They measure what has already happened. They are the reflection of past decisions and actions. Furthermore, they are important for evaluating performance, but ineffective for correcting the course:
- Revenue generated in the quarter;
- NPS calculated after the cycle ends;
- Period churn rate;
- Accumulated profitability.
The problem: When you see the bad result, it is already too late to avoid it. After all, outcome indicators are lagging.
Leading indicators of effort
They measure causes, not consequences. Therefore, they are predictors of future results.
They allow intervention before the problem takes root:
- Number of sales visits made during the week (revenue predictor);
- Average customer response time (NPS predictor);
- Adherence to the onboarding process (churn predictor);
- Training hours per employee (productivity predictor).
Rule of thumb
A well-constructed management dashboard combines both types: lagging indicators to account for the past and leading indicators to guide actions in the present.
The ideal proportion varies by hierarchical level: the more operational the team, the greater the weight of leading indicators. And the more strategic, the greater the weight of lagging ones.
How to build an indicator: the SMART method applied
The SMART framework, proposed by George T. Doran in 1981, is the most widely used reference for defining goals and indicators in corporate contexts.
The acronym defines five attributes that every good indicator must have:
| Attribute | Application to the indicator |
| S — Specific | The indicator measures exactly one thing. No ambiguity about what is being measured. |
| M — Measurable | Data exists, is reliable, and can be collected with a defined frequency. |
| A — Achievable | The target associated with the indicator is challenging, but achievable. Unattainable goals generate disengagement. |
| R — Relevant | There is a clear strategic or operational objective that justifies the existence of this indicator. |
| T — Time-bound (Temporal) | There is a defined deadline for the goal and an established measurement frequency. |
In addition to SMART framework, it is essential to define the complete datasheet of the indicator before creating it on the platform. After all, an indicator without a datasheet is a source of conflict: different people interpret the same number in different ways.
Minimum data sheet of an indicator
Check out the minimum data sheet for an indicator:
- Person in charge: Who is the owner of this indicator? Type: Result (lagging) or effort (leading)? Polarity: Higher is better or lower is better?
- Indicator Name: clear and self-explanatory name;
- Linked objective: What strategic or operational objective does it address?
- Calculation formula: How is the value calculated? What are the variables?
- Data source: Where does the information come from? Who feeds it?
- Refresh rate: daily, weekly, monthly, quarterly?
- Goal and tolerance: What is the target value? What are the attention and alert ranges?
The 5 most common mistakes in creating KPIs
Below are the main mistakes made by leaders when creating indicators:
Error 01: Indicators without a linked objective
Creating metrics “that can be measured,” without a clear management question behind them.
Result: dashboard full of numbers that no one uses to make decisions.
Error 02: Goals without historical baseline or market reference
Define the goal based on intuition or the manager's aspiration, without anchoring in historical data or industry benchmarks.
Remember that arbitrary goals quickly lose credibility.
Error 03: Confusing output with outcome
Output = what the team produced (number of emails sent, hours worked). Outcome = the result generated by that work (response rate, output per hour).
That is, output indicators measure effort, not impact.
Error 04: Diffuse responsibility
Metrics with multiple owners, in practice, have none at all. Therefore, the rule is simple: one metric, one owner.
This does not prevent multiple areas from contributing to it, but there is always someone responsible for the update and the action plan in case of deviation.
Error 05: Excess of indicators on the dashboard
Croll and Yoskovitz (Lean Analytics, 2013) coined the concept of “OMTM — One Metric that Matters.” The principle is not that you have a single indicator, but that you know which indicator is the most critical at any given time.
Remember: dashboards with more than 15 to 20 indicators tend to scatter attention rather than focus it.
Configuring indicators in Actio
With the technical specifications defined, the configuration in Actio follows a structured workflow:
- Link the indicator to a previously registered strategic objective or perspective;
- Define the calculation formula and the data source (manual or via integration);
- Configure the update frequency and the person responsible for filling it out;
- Define target, attention band and alert band (traffic light);
- Classify the type: lagging or leading;
- Review the dashboard: if you already have more than 15 active indicators, prioritize before adding more.
Critical point: Actio allows you to set up automatic alerts when an indicator enters the attention or alert range. Use this feature to ensure deviations are noticed before follow-up meetings, not during them.
Conclusion
The indicators that matter are not the easiest to measure, they are the ones that answer the right questions. Therefore, before creating any metric, define the objective, identify whether it is an outcome or effort indicator, fill out the technical sheet, and validate it with the person in charge.
Remember: a dashboard with 10 well-constructed indicators generates more action than a dashboard with 50 random numbers.
Frequently asked questions about indicators with methodological depth
Check out some of the most common questions on the topic below:
A data point is simply a raw number without operational context (e.g., 500 calls handled). An indicator, on the other hand, provides context and answers a specific management question (e.g., % of calls resolved on the first contact), linking the data to an objective, a target, and a responsible party to guide decision-making.
Excess metrics dilute team attention and lead to analysis paralysis. According to the concept of One Metric that Matters (ONM), the greater the number of numbers on a dashboard, the lower the leadership's ability to identify what is truly critical at the moment.
In other words, lean dashboards ensure focus on executing what generates real impact.
When there is no internal data history, the goal must be anchored in industry benchmark research, market averages, or initial sampling diagnostics. Avoid setting arbitrary goals based on management guesswork, as unattainable goals demotivate the team and lose technical credibility.
Methodological references of this article
→ Kaplan & Norton — The Balanced Scorecard (HBR, 1992) and Strategy Maps (2004)
→ Bernard Marr — Key Performance Indicators: The 75 Measures Every Manager Needs to Know (2012)
→ George T. Doran — Thereʼs a S.M.A.R.T. Way to Write Management Goals (1981)
→ Alistair Croll & Benjamin Yoskovitz — Lean Analytics (2013)
