About the project
This descriptive operations dashboard is based upon a on a real Tableau dashboard I created for my role as a healthcare data analyst.
The top section of dashboard features the following information: counts of open requests/issues, resolved requests, total requests received, two Service Level Agreement's (First Response Time and On Schedule to Resolution), and the almighty utilization rate. The middle contains comparisons of requests by issue type, the client/company who created the requests, and the agent who solved that request. The bottom shows time-series data, the average requests for that time period, and the mean time to resolution, total resolution rate, and open ticket to current agent ratio.
I created this dashboard by wrangling the data from our various service portals within Jira using an API. That API was then used to pull the data into Tableau Desktop, where I created the data visualizations. Adobe XD was used to create the UI/UX elements. This dashboard is used in our weekly metrics reporting and team-syncs.
In the interactive Tableau workbook version, selecting an agent acts an action that filters the rest of the dashboard to rank results to that agent. A similar filtering happens if you select a client, it will show only relevant statistics for that client, and updates all the data visuals accordingly. In this manner, any widget, bar, line, or number can be used to drive your exploration and investigation into your data. By interacting with the data in this way, you may discover insights hidden within your data.
Project results
The internal monitoring of our IT team's performance has created many valuable insights. Since this dashboard has been deployed, our organization has been able to:
- Spot seasonal trends using time-series analysis.
- Make hiring (or firing) decisions based upon team's utilization rates.
- Identify our top 'noise' creator, or client that creates the most tickets.
- Understand which agents are being most efficient, and which are the slowest.
- Increase the percentages on both SLA KPI's, to be in compliance with our contract.
- Determine our busiest day and even hour of the work week. This is helpful for planning purposes.
- Identify the most common problems within our company and work towards preventing repeatable tickets.
- Forecast how many requests our IT team serves on an annual basis across many ticket portals, clients, and physical locations.
