For CEOs
Executive dashboards: the KPIs every CEO should see
Which KPIs belong on a CEO dashboard: profitability, growth, liquidity, efficiency and risk. How to design a scorecard people actually use.
Read articleKey takeaways
- A CEO does not need to master data engineering, but to know what to ask and measure.
- The value of data is in the decisions it enables, not the technology.
- Start from a business question, not the tool.
- Outsource the complexity and keep the result.
- Data culture is led by example.
Few topics cause as much anxiety in leadership as "the data strategy". It sounds technical, expensive and slow. But the CEO’s role in data is not to understand the architecture: it is to define what they want to achieve and demand that the data makes it possible.
The mindset shift
The most common mistake is to start from the technology: "we need a data lake". The right approach starts from the business: which decision do I want to make better? What am I not seeing that I should? Technology is the means, not the goal.
The three questions a CEO should ask
- What do I want to achieve? A decision, a saving, an opportunity.
- What data enables it and where is it? Internal, suppliers, external.
- How do I want the result? Dashboard, report, alert, AI.
What should NOT concern leadership
- Which processing engine to use.
- How pipelines are configured.
- How to size memory or storage.
- Which connector each source needs.
Business question
What to achieve?
Provider/team
Solves thecomplexity
Result
Decisionfunded
From project to data culture
The end goal is not a dashboard, but an organisation that decides with data by default. That is built by proving value in concrete cases and expanding gradually. A data culture is not decreed: it spreads from the first visible win, and it is led by example.
You do not need to understand all the complexity of data. You only need to know what you want to achieve.
In summary
A CEO leads the data strategy not by mastering technology but by defining the outcome and demanding the data delivers it. Start from a business question, ignore the technical plumbing, outsource the complexity and keep the result — and build a data culture by example, one visible win at a time.
Sources & further reading
Frequently asked questions
Do I need technical knowledge to lead the data strategy?
No. You need clarity on the business goals and a partner that translates those goals into working data solutions.
Where do I start from scratch?
With a single high-impact use case: a leadership dashboard, automating a report, or crossing two key sources. Prove value fast and scale.
How do I know if the investment pays off?
Tie each initiative to a business metric and review it. If the data does not change a decision, it is not adding value.
What should not concern me as CEO?
The technical plumbing — engines, pipelines, sizing, connectors. A managed service or team handles that; you focus on the outcome.
What are the three questions to ask?
What do I want to achieve, what data enables it and where is it, and how do I want to receive the result.
How is a data culture built?
By example and by proving value in concrete cases — it spreads from the first visible win, not from an internal announcement.
Turn this data into results
Tell us what you want to achieve. Data Layer connects, processes and delivers the result up and running, with no infrastructure for you to manage.