Analytics

Analytics go deeper than the dashboard. Where the dashboard shows you what’s happening now, analytics show you patterns over time.

What you can track

Project metrics — How long do projects take? How many are on schedule vs. delayed? What’s the completion rate?

Team performance — Utilization trends, task completion rates, how long tasks actually take vs. estimates.

Document and AI usage — How many documents are being uploaded and processed? How much is AI being used?

Finding insights

The numbers themselves aren’t the point—the patterns are.

If projects consistently take longer than planned, your estimates need work. If one team is always overutilized while another has capacity, something’s off with allocation. If AI usage is low, people might need training or the documents might not be there yet.

Look for trends, not just snapshots. One bad week happens. Three bad months is a pattern.

Using the data

Planning. Use historical data to set realistic timelines. If similar projects took 6 weeks, don’t promise 3.

Resource decisions. If utilization is consistently high, you might need more people. If it’s consistently low, you might need fewer—or need to capture more work in the system.

Process improvement. When you see bottlenecks, you can address them. When you see what’s working, you can do more of it.

Sharing reports

Export data for presentations, stakeholder updates, or further analysis. Most reports can be exported to PDF, Excel, or CSV.

The point isn’t to generate reports—it’s to make better decisions because you have the data to back them up.

---

Related: Dashboard for the real-time overview. Utilization Tracking for team capacity details.