15 Dashboards and Reporting

Every week, a vice president at a mid-sized manufacturing firm receives a 40-page PDF report on employee absenteeism. It contains dozens of tables, charts broken across multiple pages, and paragraphs of narrative analysis. The report is thorough, accurate, and almost never read past the first page. Meanwhile, the HR director at a competitor opens a browser tab each morning and sees a single screen: four numbers at the top (average absence hours this month, number of employees flagged as high-risk, year-over-year trend, cost estimate), a line chart showing the seasonal pattern, and a bar chart comparing departments. She clicks on the Operations bar and sees a drill-down to individual team data. The entire interaction takes thirty seconds.

Both organizations have the same data, the same analytical capabilities, and the same business questions. The difference is the delivery mechanism. This chapter covers the principles and tools for building that delivery mechanism — the dashboard — and explains when a static report is actually the better choice.

Chapter Goals

Upon concluding this chapter, readers will be able to:

1. Explain the role of dashboards and reports as decision support tools in Business Intelligence.
2. Distinguish between operational, analytical, and strategic dashboards and select the appropriate type for a given business context.
3. Apply dashboard design principles — including information hierarchy, progressive disclosure, and Few’s guidelines — to create effective layouts.
4. Build a basic dashboard in R using flexdashboard, incorporating value boxes, gauges, and interactive visualizations.
5. Describe how AI tools can assist with dashboard design, layout generation, and code production.