Justifying investments in enterprise data management capability requires that they add value to your organization. But how to ensure this happens?
One way is to focus on how enhanced data management capability will be used by the business. This requires engaging with stakeholders to discover and document data use cases. Consider the following two use case examples:
"As an Asset Manager, I want a predictive model that identifies which assets are likely to fail within the next 90 days, so that I can perform preventative maintenance and improve system reliability."
"As a Customer Service Representative, I want quick access to tailored energy saving tips, so that I can proactively help customers reduce their energy costs and improve overall satisfaction.”
Note that theses use cases follow a structure:
- [The Stakeholder] As a…
- [Desired Output] I want…
- [Value Created] So that…
A few points on the above:
- Putting use cases into this structure takes some work, but it makes the business identify exactly what they want and why.
- This is just a starting point. Operationalization requires further detailed requirements gathering.
- It is the responsibility of the business (not the IT team) to propose and prioritize use cases.
- Notwithstanding the above, it can help to provide examples of what is possible, from other utilities (and other industries).
- Data pain points often provide a starting point for use case identification (e.g., the effort involved in the current manual reporting process…).
- Once an inventory of use cases is developed, it needs to be prioritized (more on how in a future post).
- Use cases don’t need to be a new report or model. Fixing existing reporting can often deliver the greatest value.
- The use case inventory is a living document and will change as business needs change. It’s important to have a mechanism in place to capture new use cases as they arise.
- Once use cases have been identified, don't forget to keep the business updated on when they will be deployed.
- Use case discovery process is tied to data culture. As literacy improves, the process will become easier and produce better results.
Finally, don’t assume that this is the first-time that stakeholders have gone through this process. Given the frequency with which data programs fail to deliver, it's possible that stakeholders have invested time in previous efforts and been let down.
Don’t let that deter you. Acknowledge and leverage this prior work.
Advancing a data management capability is difficult, but a strong focus on delivering business outcomes via use case discovery is a positive first step.
The views reflected in this article are the views of the author and do not necessarily reflect the views of the global EY organization or its member firms.