It can be challenging when stakeholders cannot translate business questions into technical requirements or do not provide enough context for data teams to do so. From there, the data team is often left to maintain the status of a series of ad hoc projects rather than connect these business questions to a larger more defined data strategy.
Thinking through specific, high-level challenges in collaboration can help generate a list of viable project opportunities where natural synergies align using the what-why-why-why framework below. A typical business team requirement is expressed below as a data need and correlating solution. Neither group presented here is exhaustive but provides a sense of the sentiments expressed by each team and the to-do’s that can correlate.
🎯BUSINESS STAKEHOLDER GOAL(S)🎯
Increase the customer's lifetime value.
👉WHAT? Steward data by cataloging high-priority metrics (customer, renewal, adoption).
(because)
👉WHY? Need to implement a new loyalty program for customers based on tenure, usage, etc.
(because)
👉WHY? This year, our goals include improving retention and renewals.
(because)
👉WHY? The strategic plan states that we must increase the customer's lifetime value; this requires an ongoing investment in a centralized data strategy.
🎯DATA TEAM GOAL(S)🎯
Update customer database
👉WHAT? Need to modify the database to track a common, unique identifier for all customers.
(because)
👉WHY? It allows the customer record to be referenced in the central index without confusion or unintentional overwriting from other records.
(because)
👉WHY? Support business stakeholder’s goals for improving retention and renewals.
(because)
👉WHY? To enable the business to increase the customer's lifetime value, we must overcome internal data challenges (incompleteness, accuracy, redundancy, latency) by investing in typical data architecture and shared efficiency processes.
🌟What is on your shortlist? How do you translate business requirements into multi year goals ?