15.2 The Role of Dashboards in Decision Support

A dashboard is not just a collection of charts — it is a decision support tool. Its purpose is to move information through a pipeline that ends with action: data is collected, cleaned, modeled, and visualized, but the dashboard is where a manager actually uses it to make a decision. Understanding this pipeline clarifies what makes a dashboard effective.

Dashboards support decisions at three levels (Few 2006; Eckerson 2010):

  • Informational — “What happened?” The dashboard displays current and historical metrics so the user can assess the state of operations. Example: total absence hours this month compared to the same month last year.
  • Diagnostic — “Why did it happen?” The dashboard provides drill-down or filtering capabilities so the user can investigate causes. Example: clicking on a spike in March absences to see which departments and absence reasons drove the increase.
  • Prescriptive — “What should we do?” The dashboard surfaces model outputs or recommendations that guide action. Example: a ranked list of employees flagged as high-risk for chronic absenteeism, generated by the predictive model from Chapter 9.

The most effective dashboards support all three levels through progressive disclosure — showing the “what” at the top level and allowing users to drill into the “why” and “what next.”

15.2.1 Key Performance Indicators

The metrics displayed on a dashboard are typically Key Performance Indicators (KPIs) — measurable values that demonstrate how effectively an organization is achieving its objectives. Not every metric is a KPI. A good KPI meets the SMART criteria: it is Specific (clearly defined), Measurable (quantifiable), Actionable (the audience can influence it), Relevant (aligned with business goals), and Time-bound (measured over a defined period). The traditional SMART framework uses “Achievable” for the A; we substitute “Actionable” here because for KPIs specifically, the critical question is whether the audience can act on the metric — a KPI that no one can influence is not useful on a dashboard, regardless of whether it is achievable.

A useful framework for organizing KPIs is the Balanced Scorecard (Kaplan and Norton 1996), which groups metrics across four perspectives: financial (costs, ROI), customer (satisfaction, retention), internal process (efficiency, quality), and learning and growth (employee development, innovation). The four perspectives may require adaptation depending on the context — for an internal HR dashboard, “customer” might map to “employee” or “department,” reflecting the internal stakeholders whose outcomes the dashboard tracks. For an absenteeism dashboard, the financial perspective might track the cost of lost productivity, the internal process perspective might track average resolution time for absence requests, and the learning and growth perspective might track wellness program participation rates.

Example: KPIs for an Absenteeism Dashboard

Using the Absenteeism at Work dataset from this book, an HR dashboard might track these KPIs:

  1. Average monthly absence hours (Specific, Measurable, Time-bound) — the primary metric, displayed prominently as a value box with month-over-month trend.
  2. Chronic absence rate — percentage of employees exceeding 40 hours of absence per quarter. Actionable: HR can target interventions to this group.
  3. Top 3 absence reasons — the most frequent ICD-coded reasons, updated monthly. Relevant: guides wellness program design.
  4. Absence cost estimate — total absence hours multiplied by average hourly labor cost. Financial perspective: translates a behavioral metric into dollars.
  5. Seasonal absence index — current month’s absence rate relative to the 12-month average. Time-bound: reveals whether the current period is unusually high or low.

Each KPI answers a specific question, can be acted upon by the dashboard’s audience (HR managers), and is tied to a defined time period. A metric like “total number of employees” would not qualify — it is informational but not actionable in the context of absenteeism management.