Data everywhere, alignment nowhere: What dashboards are getting wrong, and why you need a data product manager

In recent years, organizations have poured vast sums into developing data infrastructure, including petabyte-scale warehouses and real-time data pipelines. However, when faced with questions about increased churn or performance metrics, teams often respond with conflicting data from multiple dashboards. This chaotic scenario highlights a crucial issue: it’s not the data itself that poses a problem, but rather the approach to product management within data teams. Historically, these teams functioned like internal consultancies—reactive and driven by individual requests. While this 'data-as-a-service' model sufficed when data demands were minimal, it has since faltered under the pressure of a burgeoning data-driven culture. Take Airbnb as an example. Prior to the establishment of its metrics platform, various departments generated their own metrics, leading to inconsistencies and disputes over which numbers were correct during leadership reviews. The root cause of these discrepancies is not a failure of technology but rather a failure in product management. Many data leaders mistakenly attribute these issues to data quality, yet the real problem lies in a lack of trust in the outputs. The systems may function effectively, but they were not designed with usability or decision-making in mind. To address this, a new role has emerged: the data product manager (DPM). DPMs differ from traditional product managers in that they navigate complex, often invisible interdepartmental challenges. Their main focus is not merely on delivering dashboards but on ensuring that stakeholders receive the insights they need to make informed decisions. The most effective DPMs go beyond basic data handling; they critically assess whether the insights derived genuinely enhance workflows and decision-making quality. Their success is measured by outcomes rather than outputs, asking questions like, "Did this lead to a tangible improvement?" As these managers reshape how internal data systems are developed and utilized, they are not just cleaning data; they are rebuilding organizational trust in it. For far too long, the industry equated activity with progress—engineers built pipelines, scientists created models, and analysts produced dashboards, but no one focused on whether these insights influenced business decisions. In modern enterprises, nearly every significant decision—from budget alterations to new initiatives—begins with data. Yet, without designated ownership of these data layers, decision-making can become paralyzed. DPMs play a critical role in ensuring that metrics are understandable, assumptions are clear, and tools align with actual workflows. As artificial intelligence continues to evolve, the role of DPMs will become even more vital, transforming them from mere coordinators into architects of trust and responsible data management. For leaders in technology and data, the key question remains: If clarity is lacking, it’s not more dashboards that are needed, but rather a skilled data product manager to bridge the gap.