Data ROI and the business case

External data is an investment, and investments need a business case. This guide covers building the case and measuring ROI for external data.

Available across the EU. DataSupplier sources and delivers this data in all 27 European Union countries — including Germany, France, Spain, Italy, the Netherlands and Poland — and across the EEA, in the format and cadence you need.

Why a business case matters

Data spend competes for budget, so it needs a case that links data to outcomes and quantifies value against cost. Without one, data is seen as cost, not value.

Linking data to outcomes

Start from the decision or process the data improves, and estimate the value of better decisions, fewer errors, new revenue or saved cost. Specificity beats generic claims.

Estimating cost

Include all three components, underlying data, sourcing commission, services, plus integration and operations. Total cost of ownership, not headline price, is the right basis.

Proving return

After deployment, measure realised value against the case, and track usage. Evidence of return justifies expansion and protects the budget.

Sourcing considerations

Transparent, itemised pricing makes the case credible, and a trial or PoC can de-risk the investment before committing.

In a managed model

A managed partner can provide transparent costs and support measurement of value, strengthening the case.

Link data to outcomes

A credible business case starts from the decision or process the data improves and estimates the value of better decisions, fewer errors, new revenue or saved cost, then sets it against total cost of ownership, not headline price. Specificity beats generic claims about “data-driven” value.

Prove the return

After deployment, measure realised value against the case and track usage; evidence of return justifies expansion and protects the budget. Transparent, itemised pricing makes the case credible, and a trial or PoC can de-risk the investment before committing.

Sources & further reading

• OECD: measuring the value of data.
• Industry data-ROI frameworks.
• DAMA-DMBOK: data value.
• Internal practice: DataSupplier cost transparency.