Descriptive Analytics typically deliver reports and dashboards that provide operational insight into the business and ad hoc queries and analytics provide deeper answers to questions about it. The technologies supporting these needs are called Business Intelligence or BI and they focus on what has happened in the business. Descriptive Analytics provide value by identifying problems needing attention, but only after they have occurred.

The most important technical aspect of descriptive analytics is the identification of Key Performance Indicators (KPIs) and metrics used to evaluate business performance. Organizations often confuse metrics and KPIs – a metric is simply a measure while a KPI like profitability is fundamentally critical to a business – because they address them in a local context rather than an enterprise-wide one.

Effective Descriptive Analytics require:

  • A KPI/metrics architecture linking KPIs and the metrics that affect them;
  • Aligning KPIs and metrics with Data Delivery and Data Use Scenarios;
  • A Technical Architecture that supports the capture and delivery of KPIs and metrics;
  • Monitoring KPIs and metrics to ensure they continue to represent effective business measures.