Organizations engage in data sharing to enhance data analytics and artificial intelligence efforts, to innovate, to create competitive advantage or to collaborate for economic or social benefit.
More and more, organizations are using their own data to power use cases like hackathons, vendor evaluation, commercialization of data-driven products and customer record matching; joining data with partner data for smarter marketing programs or more personalized customer experiences. But often it is difficult to estimate the return on investment (ROI) of these data sharing initiatives.
Before an enterprise organization decides to engage in data sharing, they need to figure out why they’re doing it and what success looks like. That is, what value are they expecting from their investment.
The value derived for organizations can be both quantitative or qualitative and organizations should consider all use case outcomes as potential sources of value and combine them to estimate the total ‘return’. To calculate the associated investment, enterprises typically look at people, technology infrastructure and time costs. These days enterprises often leverage purpose-built data sharing software to make the sharing of data safer and simpler. These software solutions are powerful, but the value is realised in how they are used.
There are many approaches to calculate return on investment, let’s explore some common ways organizations determine ROI.
Quantitative benefits are returns that can be measured, including:
- Increase in revenue
- Cost savings
- Efficiency savings
Whereas, qualitative benefits include variables that are often observed rather than measured, including:
- Brand reputation
- Risk mitigation
- Customer experience