Skip to main content

Analytics and Reporting

Summary​

Analytics and reporting have been an important part of how I’ve supported documentation work at scale.

This part of my work sits at the intersection of documentation, visibility, process improvement, and decision support. The goal is not to produce dashboards for their own sake. The goal is to make the work easier to understand, easier to manage, and easier to improve.

The problem​

Documentation teams often know when something feels off before they can describe it clearly.

Common problems include:

  • low visibility into work in progress
  • uneven workload across products or teams
  • too much manual tracking
  • weak reporting on documentation effort
  • difficulty identifying patterns or bottlenecks
  • not enough information to support process decisions

Without better reporting, those problems stay vague longer than they should.

What this work included​

Across roles, this work has included:

  • implementing documentation metrics in Tableau
  • building automated documentation analytics with Tableau and SharePoint
  • using Excel to streamline processes and manage large data sets
  • improving visibility into documentation work across many products
  • supporting planning and prioritization with better reporting
  • identifying opportunities for process improvement through data

How this showed up in my work​

At Meta, this work included a Tableau dashboard set used to measure a large-scale wiki migration effort spanning 421 products, including completion rates by team and team group.

It also included setting up a SharePoint-based work progress tracker and using Tableau to display the data in a more usable way for monthly reporting and documentation visibility.

At Jack Henry, this work included streamlining data collection, analysis, and reporting for a department of 45 by implementing an automated documentation analytics system using Tableau and SharePoint.

Across these environments, the pattern was similar: use reporting and structured analysis to make documentation work easier to see and easier to improve.

What I pay attention to​

When I work on analytics and reporting, I usually care about questions like:

  • What is changing?
  • What is taking too long?
  • Where is the friction?
  • What patterns are visible across the work?
  • What would help a team make better decisions?
  • What should be simplified, standardized, or tracked more clearly?

That keeps the work tied to action instead of turning it into passive reporting.

Why this matters​

Documentation work gets stronger when teams can see reality more clearly.

Reporting helps with that by making it easier to:

  • understand workload
  • identify bottlenecks
  • support prioritization
  • improve process visibility
  • make decisions based on patterns instead of guesswork

That is why I see analytics as part of documentation operations, not something separate from it.

What this shows about my work​

This is a good example of how I work beyond page-level writing:

  • I use data practically
  • I care about operational visibility
  • I like making systems easier to understand
  • I connect reporting to documentation decisions
  • I treat process improvement as part of good documentation work