Accumulating data is no longer an advantage. What sets an organisation apart is how quickly and accurately it turns that data into decisions, and this is where strategic visualisation plays a specific role: it is the translator between raw data and business action. It is not decoration but a management tool.
This article is not about how to build a dashboard in a particular tool. It tackles two earlier questions: what each executive should see and what it takes for them to trust what they see.
From transactional KPIs to value KPIs
Many reports are still dominated by activity indicators: clicks, visits, number of orders, tickets opened. They are useful for running operations, but they say little about whether the business is moving towards its goals. More mature organisations have shifted their focus to value KPIs: metrics directly linked to strategy that enable proactive rather than merely reactive decisions.
That difference rests on three ideas:
- Strategic KPIs: tied to the objectives of senior leadership, such as customer lifetime value, profitability by segment or return on equity.
- Data storytelling: reports that tell a clear story and highlight trends, anomalies and opportunities instead of presenting a sequence of tables.
- Organisational alignment: a single version of the truth that avoids arguments about which figure is right and speeds up the response to market changes.
What each executive should see
Each leader needs a small number of indicators, specific to their area and connected with the value it creates. A starting proposal:
| Role | Focus | Value KPIs |
|---|---|---|
| Chief executive (CEO) | Growth, profitability and sustainability | Revenue growth; return on equity (ROE); digital maturity and innovation; Net Promoter Score (NPS) |
| Operations (COO) | Efficiency and cost optimisation | Operational efficiency; on time in full (OTIF); process cycle time; asset utilisation rate |
| Sales (CCO/CSO) | Acquisition, retention and customer value | Customer lifetime value (LTV); churn rate; customer acquisition cost (CAC); conversion by funnel stage |
| Finance (CFO) | Liquidity, solvency and risk | Operating cash flow; debt ratio; cash conversion cycle; gross and net margin |
| People (CHRO) | Talent, engagement and productivity | Key talent turnover; productivity per employee; engagement index; time to fill vacancies |
A few practical observations on this table:
- Indicators are read in pairs. LTV without CAC does not show whether value is being created; revenue growth without margin can hide growth that destroys profitability.
- Every KPI needs a single written definition. "Operational efficiency" or "productivity per employee" can be calculated in several ways; if each department uses its own formula, the board argues about numbers instead of deciding.
- Figures need context. A value without a target, a comparable period or a trend is hard to interpret. The minimum is to show the current value, the target and how it has evolved.
- Each indicator needs an owner who acts on it. If nobody can move a KPI, it does not belong on that role's dashboard.
The three pillars of a strategic report
Good design cannot rescue a report nobody trusts. Credibility rests on three pillars.
1. Data quality: the foundation of trust
"Garbage in, garbage out." A brilliant visualisation built on wrong data only amplifies the error and erodes trust in the whole system. The minimum requirements:
- Accuracy and validity: the data reflects business reality.
- Integrity: no missing values or inconsistencies.
- Consistency: the same KPI gives the same value in every report and system.
One practice that works is to show data trust labels next to the figures: the measured quality level, whether the indicator is certified, or the date of the last refresh. Users then know how far they can rely on each number, and quality problems stop being invisible.
2. Security and traceability: accountability for the data
Management information is sensitive by definition. It requires:
- Granular security: with row-level security, each user only accesses the data that concerns them, for example their region or business unit.
- Full auditing: traceability of where each figure comes from and a record of who accesses what.
- Regulatory compliance: adherence to the GDPR and any applicable sector regulation.
This pillar is especially important in self-service environments, where many people create and share their own analyses.
3. Usability for business users
The aim is to leave behind the "monolith report", a static document dozens of pages long, and move to interactive, adaptable dashboards designed around the user:
- Clarity and simplicity: every chart answers a specific business question. If you cannot say which question it answers, it should go.
- Self-service: filter, drill down and personalise without depending on the IT team.
- Mobility: a view designed for mobile that lets people understand the situation at a glance.
The result is users with autonomy, working on a validated and secure data foundation.
Common mistakes
- Starting with the chart rather than the decision. First define which decision needs to be made and with which indicator; then decide how to represent it.
- Putting everything measurable on the dashboard. More indicators do not give more control, just more noise.
- Ignoring definitions. Without an agreed KPI glossary, self-service multiplies the versions of the truth.
- Hiding quality. Presenting a validated figure and a provisional one with the same authority destroys trust the first time something goes wrong.
Where to start
Investing in visualisation is not investing in software but in the speed and accuracy of decisions. A sensible path:
- Sit down with each executive to establish which decisions they make regularly and what they need to know to make them.
- Choose four or five value KPIs per role and write down their definition, source and owner.
- Review the quality and security of the data that feeds them before designing anything.
- Build a simple first version, test it with users and improve it based on real use.
That is the real democratisation of business intelligence: putting informed decisions in the hands of the people who know the business best. At Bidatia we help define those indicators and build the reliable data foundation they depend on.
Frequently asked questions
What is the difference between a transactional KPI and a value KPI?
A transactional KPI counts activity: clicks, visits, orders logged. A value KPI measures something linked to a strategic objective, such as profitability by segment or customer lifetime value, and allows decisions to be made before the problem shows up in the profit and loss account.
How many indicators should an executive dashboard have?
Few. Four or five headline indicators per role are usually enough for an at-a-glance view; detail comes from filtering and drilling down, not from adding more charts to the front page.
What is a data trust label?
A visible indicator next to a figure that shows its quality level or certification status: for example, the percentage of records that pass the quality rules or the date of the last refresh. It stops a doubtful figure from being presented with the same authority as a validated one.
How do you combine self-service with security?
With row-level security, so each user sees only the data that concerns them, and with a common, certified data model that the business can explore freely. That way autonomy grows without losing control or consistency.