Measuring the ROI of your data team is vital, as it allows you to:
- Decide between hiring more people or investing in new tools.
- Convince management to increase investments in data projects/ data tools.
In some cases, the data team has an impact that can be directly measured. For example, if the company sells data as its product, the data team has a clearer connection to value creation.
But for most teams, the impact is created indirectly: they are partners, acting in support of functions like Marketing, Finance, or Engineering to impact performance. For this reason, it isn’t 100% clear yet which KPIs should be tracked to evaluate the performance of data teams.
Different frameworks have emerged for evaluating the performance of data teams, taking into account their very unique way of working. The aim of this discussion is to review these frameworks and identify which one(s) work best in practice.