Are BI dashboards good at showing what happened but not why it happened?

Summary

BI dashboards are effective in displaying data but often fail to explain the underlying reasons behind it.

Lack of Insight into Causes

Many organizations have robust BI infrastructures featuring dashboards for key metrics like revenue, spending, and forecasts. Despite the visual clarity of these dashboards, teams encounter challenges when follow-up questions arise, such as "why did this metric change?" This often results in a convoluted workflow where users must jump between multiple dashboards and datasets.

Relevance for BI Professionals

This issue is significant for BI professionals as the trend in data analysis shifts from merely presenting what has happened to understanding underlying causes. Competitors that can provide deeper analyses and explanations have an edge. This raises important questions about how technologies and tools should be leveraged not just to present figures, but also to provide context and reasoning.

Concrete Action for BI Professionals

A key takeaway for BI professionals is the need to assess tools and processes aimed at enhancing cause-and-effect analyses behind metrics. Developing flexible dashboards that can offer this deeper insight, alongside investing in team training to effectively use existing datasets, can be crucial for successful BI initiatives.