In the context of organizing data domains and focusing on data product teams, how should ongoing maintenance of existing data assets be handled? Is it realistic to expect teams to fully drop those responsibilities in pursuit of new products? Should this work fall to the central data team, or how can it be managed without burdening others with less desirable tasks?
It’s important to acknowledge that not all existing data work should be maintained. Teams should periodically review their portfolio and consider ceasing efforts that deliver only marginal value. By doing so, resources can be reallocated more strategically.
In data management, there’s a distinction between proactive and reactive tasks. Proactive efforts drive innovation and strategic change. Reactive work, such as maintaining compliance or supporting legacy dashboards, remains essential but should be minimized. While some reactive work is unavoidable, it should not dominate the agenda.
A helpful analogy can be drawn from analytics: cross-functional KPIs that steer company decisions should be prioritized and governed tightly. Local or departmental metrics, while still important, do not warrant the same level of investment and can be managed with lighter oversight.
Ultimately, many data teams are overly operational. To unlock greater value, it’s necessary to rebalance efforts toward strategic opportunities, even if that means letting go of less impactful legacy tasks.