Most analytics investments are approved on qualitative benefits that are never quantified after the fact. The teams that secure continued investment in their data capability are the ones that can demonstrate what it has produced - in decision quality, time recovered, and errors avoided.
This guide covers how to build a business case for analytics investment and track whether it is delivering: a framework for quantifying decision quality improvement, time recovered from manual reporting, and error reduction across the reporting estate.
Qualitative benefits that are never measured become assumptions that are never challenged.
Why analytics ROI is hard to measure - and what to do about it
Analytics benefits are diffuse, indirect, and often absorbed into business-as-usual rather than recorded as savings. The challenge is not that they are not real - it is that they need a measurement framework designed to capture them before the engagement begins, not reconstructed afterwards.
Three categories that capture most of the return
Decision quality improvement, time recovered from manual reporting, and error reduction account for most of the measurable value analytics investments produce. The guide covers how to define and track each in a way that is credible to a finance audience.
What the guide covers
- A framework for quantifying the return on analytics investment
- How to measure decision quality improvement, time recovered, and error reduction
- How to build a business case that holds up to scrutiny from a finance audience
- What to track before an engagement begins to make ROI measurement credible afterwards
- How to use return measurement to secure continued investment in the data capability
Who this is for
Data leaders, analytics heads, and CFOs in mid-market organisations who need to justify continued investment in data and analytics - or who want to evaluate whether a previous investment has produced the return expected.