ROI & costs
How much a data infrastructure costs in 2026
A realistic breakdown of building and running a data infrastructure: people, cloud, licences and maintenance. And how to make it a predictable cost.
Read articleKey takeaways
- Data ROI = (net benefit ÷ total cost) × 100.
- Total cost includes people, infrastructure, licences and time to result.
- Benefits go beyond savings: better decisions, less risk, new opportunities.
- A consumption model improves ROI by removing idle capacity.
- Time is the most underestimated cost.
Investing in data is easy to justify on paper and hard to measure on the P&L. Without a clear return calculation, data projects compete at a disadvantage against more tangible investments. This guide gives you a simple formula and a framework to defend — or challenge — any data initiative.
The basic formula
Return is expressed as ROI = (net benefit ÷ total cost) × 100. Net benefit is value generated minus cost; total cost is everything you invested. The difficulty is not the formula but estimating both sides well.
The cost side
- People: the dominant cost, especially building in-house.
- Infrastructure: cloud, storage, processing.
- Licences and tools: BI, integration, security.
- Time: the opportunity cost of every month without results.
Time is the most underestimated cost. A project that takes nine months to bear fruit costs nine months of decisions made without data.
The benefit side: more than savings
- Efficiency: less manual work and fewer errors.
- Better decisions: margin, pricing, product mix.
- Risk reduction: spotting problems before they cost money.
- New opportunities: data products, segmentation, AI.
A worked example
A project costing €40,000/year that eliminates 1,200 hours of manual reporting (≈ €36,000), fixes a recurring billing error (≈ €20,000) and enables a pricing decision worth €60,000 in margin: net benefit = €116,000 − €40,000 = €76,000. ROI = (76,000 ÷ 40,000) × 100 = 190%.
How consumption pricing improves ROI
Paying for real consumption instead of fixed servers reduces the denominator: you do not invest in idle capacity. If the provider also optimises each process to consume less, cost falls without losing results, and ROI rises.
The best data project is the one that turns investment into decisions fastest.
In summary
Data ROI is (net benefit ÷ total cost) × 100, but the art is estimating both sides — including the easily forgotten cost of time and the benefits beyond direct savings. Consumption pricing plus optimisation improves the ratio by cutting idle capacity. Well-scoped projects often exceed 100% in the first year.
Sources & further reading
Frequently asked questions
How do I measure intangible benefits like "better decisions"?
Tie each decision to a concrete business metric (margin, churn, turnover) and estimate the impact of improving it, even conservatively. A prudent, documented estimate beats ignoring the benefit.
How long until a data project pays back?
With a managed approach and a scoped first use case, payback usually starts within weeks or a few months, because time to result is short.
What ROI is reasonable to expect?
It depends, but well-scoped reporting, pricing or efficiency projects often exceed 100% in the first year once all benefits are counted.
Why is time a cost?
Every month a solution is not live is a month of decisions made without data — an opportunity cost rarely on the budget but very real.
How does pay-per-use raise ROI?
It cuts the cost denominator by removing idle capacity, and with optimisation each process consumes less for the same result.
What is the biggest mistake calculating data ROI?
Counting only direct savings and ignoring better decisions, risk reduction and new opportunities — plus forgetting the cost of time.
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.