Choose the right metrics for a PMO portfolio dashboard
A focused set of portfolio and delivery metrics with definitions, data sources, thresholds, and the decisions each supports.
The prompt
Help me choose the metrics for our PMO portfolio dashboard.
Who will use the dashboard: [e.g. executive team monthly, project managers weekly]
Decisions it should support: [e.g. "which projects to fund, pause, or help", "where capacity is overloaded"]
Number of projects in the portfolio: [COUNT and typical size]
Data we have: [tools - e.g. Jira, MS Project, finance system, timesheets - and how reliable each is]
Metrics we track today: [LIST, if any]
Consider metrics across these areas, and recommend no more than 10-12 in total:
- Delivery: milestone hit rate, schedule variance, forecast accuracy, cycle time.
- Cost: budget vs. actual vs. forecast, CPI where earned value is used.
- Health: share of projects red/amber/green and how long they have been that color.
- Risk: open high risks, overdue mitigations, escalations.
- Capacity: resource utilization and over-allocation.
- Value: benefits forecast vs. realized, strategic alignment coverage.
For each recommended metric, give: definition and formula, data source, update frequency, thresholds for red/amber/green, owner, and the decision it informs. Drop any metric that does not change a decision.
Also warn me about: watermelon reporting (green outside, red inside), metrics that teams can game, and status colors that reflect opinion rather than defined criteria.
Return a metric table, a suggested dashboard layout (top-to-bottom), and a definition of red/amber/green that is objective enough to apply consistently.
Highlighted [brackets] are blanks to replace with your own details.
Fill in the blanks and use this promptMore Data & Analysis prompts
What to fill in
- e.g. executive team monthly, project managers weekly
- COUNT and typical size
- LIST, if any
How this prompt is built
This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.
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