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Project Management Metrics: Types and Practical Examples
Project Management · Chapter 9: Project Monitoring, Control, and Performance ManagementSection 9.2 · lesson 56 of 7312 min · free with a free account
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In this lesson
Choosing a small set of metrics that drive real project decisions.
- Define a project metric and distinguish leading from lagging measures
- Calculate milestone hit rate and burn rate as a series over time
- Set targets and tolerances that separate three statuses before data arrive
- Recognize vanity measures and gaming, and apply defenses against them
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Transcript
Everything said in the video, section by section (1,750 words). Read along, or search it.
Opening Case
Twelve Metrics and Few Decisions
Priya is running a second Willowbrook project: rebuilding the clinics' patient portal. As before, the figures are made up. At the start, the steering group asked for full visibility. So every Friday, she reports twelve metrics, and collecting them eats much of the day. As far as she can tell, nobody acts on most of them. She can't simply stop sending numbers. So which should she keep, and how can she show the others aren't needed?
Definition
Defined, Repeatable and Tied to a Decision
Start with what a metric is: a defined, repeatable measurement of some part of a project, that supports a decision. Defined means a written rule says exactly what's counted, so two people reach the same value. Repeatable means it's taken again on a regular rhythm, by the same rule. Supports a decision means someone can say in advance what they'd do differently if the value moved. Compare a one-time observation. Priya walks past the portal's test room on a Tuesday, and sees it empty. That's worth a follow-up, but it can't show direction. There's no rule behind it, and no earlier value. As a metric, it becomes: test sessions held, divided by sessions planned, calculated every week.
Leading and Lagging
Results Already Happened Versus Signals Ahead
Helen, the sponsor, asks about lagging and leading measures. A lagging measure reports a result that has already happened: milestones met on time, cost spent to date, defects found in a delivered build. A leading measure signals a result that hasn't happened yet, because it tracks a condition that tends to come first. Change requests waiting for a decision tend to bring rework and slippage. So do high-rated risks with no named owner. And a falling client rating often comes before a dispute. That word, tends, matters. A leading measure is a prediction, so check it against experience: did rises really come before trouble on this project? Lagging measures are hard to dispute, but arrive too late to change the result. Steering by them alone is steering by the rear-view mirror. Leading ones alone can never be confirmed. And the label depends on the result. Open defects lag the quality of past work, yet lead next week's fixing effort. So name the result you mean.
Coverage Check
Six Dimensions of Performance
To spot blind spots, check six dimensions of performance, each one measured separately. Schedule, by milestone hit rate. Cost, by burn rate: the cost spent per unit of time. Quality, by open defects: problems logged and not yet fixed. Scope, by open change requests. Risk, by high-rated risks with no named response owner. And satisfaction, by the client's average rating on a short survey. The dimensions interact. A project can hit every date by cutting testing, so schedule looks fine while quality quietly suffers. But coverage is a check, not a target. If no decision depends on a dimension, it can go unmeasured.
Selection Test
What Would Someone Do Differently
To choose, ask one question of every metric: if this value moved from acceptable to unacceptable, what would someone do differently, and who? A specific answer, like holding an extra meeting to decide change requests, earns a place. No answer makes the metric a candidate for removal, however easy it is to collect. Keep the set small. Each metric costs time to collect, check and explain, and a long list lets a reader pick whichever numbers look best. Add a measure only when a named decision needs it. Mix leading with lagging, and give each one a written definition, an owner, and a rhythm.
Targets and Tolerances
Three Statuses Set Before the Data
Each metric also needs a target and a tolerance. The target is the value you aim for. The tolerance is the deviation agreed in advance, before the matter is escalated. A measure can miss its target without crossing its tolerance. In that middle zone, the project manager acts on their own authority, and monitors closely. That gives three statuses: on target; target missed, but within tolerance; and outside tolerance, which means escalate. Write them down before the data arrive, by the people who'll use them. Lines drawn afterward can be placed to flatter the colors.
Trends and Dashboards
How a Dashboard Can Mislead
One value isn't enough. A trend is the direction and rate of change across readings. Eighty percent could follow a fall from a hundred, or a recovery from sixty. A dashboard is a one-page display of a few metrics, each with its current value, target and trend, so a reader takes in the position at a glance. It can mislead without one false number. A color hides how near a value sits to its limit. An axis starting well above zero makes small moves look large. Averages and running totals smooth out recent change. One overall color hides which tile drives it. And without a status date and definitions, readers guess.
Worked Example
Milestone Hit Rate Week by Week
Marcus, the developer, brings the portal's numbers. Milestone hit rate is milestones met on time, divided by milestones due. One finished a day late stays a miss. Counting from the start, two milestones were due by week one, and four by week two. All were met on time: one hundred percent. Week three: four of five, eighty percent. Week four: five of six, eighty-three. Week five: six of eight, seventy-five. Week six: eight of ten, eighty percent. The target is eighty-five, and the limit seventy-five. So it misses the target, but stays above the limit. The rate can't show how late a miss was: one day and three weeks count the same. And it weighs every milestone equally, and ignores the ones not yet due.
Worked Example
Reading the Portal's Burn Rate
Burn rate is the cost spent, divided by the time in which it was spent. The portal spent six, six, seven, seven, eight and eight cost units in weeks one to six. That's forty-two over six weeks: an average of seven a week. The last four weeks give thirty over four: seven and a half. The latest week is eight, which is the planned rate once the full team arrived in week five. A rising rate may be a planned build-up of staff, or unplanned overtime, extra people, added work, or higher prices. Here, the build-up was planned. A falling rate may mean cheap progress, or people moved off, work blocked, or invoices not yet recorded. And burn rate can't tell whether the money bought the planned work.
Series Measures
Open Change Requests and Open Defects
Some measures say little as one number, and a lot as a series. Open change requests equal last week's open count, plus requests raised, minus requests decided. On the portal, the open count went two, three, three, five, six, seven. Thirteen were raised in six weeks, and only six decided. Arrivals are steady, one to three a week. The backlog grows because decisions lag. Seven sits right at the limit of seven, and a typical week would make it eight. Open defects follow the same rule: five, eight, twelve, ten, nine, eight. They peaked when testing began in earnest, then fell as fixes outpaced finds. Eight meets the target of ten or fewer. So single values mislead both ways. And even falling defect finds need care: fewer finds can mean fewer defects, or less testing.
Quick Check
Ten of Twelve Milestones on Time
Quick check, on the Riverside clinic's fit-out. Twelve milestones are due, and ten were met on time. The target is eighty-five percent, and the limit seventy-five. What happens? Pause, and decide. Priya handles it herself. Ten over twelve is about eighty-three percent: below the target, but above the limit. That's the middle zone: she acts within her own authority and watches the trend. Escalating would be for a value below seventy-five.
Common Pitfalls
Vanity, Gaming and Measuring the Easy
Three pitfalls spoil a metric set. A vanity measure looks impressive but drives no decision: tasks completed, lines of code, meetings held, pages written, hours logged. The test is the same question as before. If nobody can name an action that changes when the number changes, it's vanity. Gaming is changing behavior to improve the number, without improving the result it stands for. It needs no bad faith: it's a natural response to being judged by a figure. A hit rate can be gamed with easy milestones, moved dates, or trivial splits. Defects can be relabeled as enhancements, and invoices entered late to lower a burn rate. The third pitfall is measuring what's easy, like items closed, instead of what matters, like the client's confidence, or the state of the risks. Four defenses against gaming: define each measure so the rule can't bend; pair measures that pull against each other; steer with them, rather than judge people; and check against the ground.
Quick Check
Agents Cutting Calls Short
Quick check. Willowbrook's call center is scored on average call length. Agents start ending calls fast, and asking patients to call back. What's going on? Pause, and decide. Gaming the measure. The number improves, while the result it stands for, patients' problems solved, gets worse. It isn't vanity: managers do act on call length, which is exactly why agents bend it. A paired measure, like repeat calls, would expose it.
Two Views
Numeric Targets or Judged Trends
Should metrics carry numeric targets at all? One side says targets focus effort, make expectations explicit, and allow early escalation. Without one, a number can't be judged. The other side says a target turns the number into the goal, inviting gaming and neglect of whatever isn't measured. Trends, discussed with judgment, are safer. How often targets help or distort is an empirical question, with no general answer here. Whether to steer by preset numbers or by discussion is about values. No side is taken.
Case Resolved
Six Metrics Kept, Six Dropped
Back to Priya's twelve metrics. She asks Helen, Marcus and the finance contact one question about each: in the last eight weeks, what did you do differently because of this number? Six draw a specific answer: milestone hit rate, burn rate, open change requests, open defects, unowned high risks, and the client rating. Six draw none: lines of code, meetings held, tickets closed, hours logged, test cases written, and documentation pages. Of the six that survive, three lag and three lead. She keeps all three leading ones, because Helen's questions were about what might go wrong next. The trade-off: Marcus liked tickets closed, since it showed his team's effort. Priya keeps the raw data in the tracking tool, and accepts that a dropped measure might have caught something. The steering group agrees, and will review the set after eight weeks.
Key Takeaways
Small, Mixed and Decision-Driven
To recap: a metric is defined, repeatable, and tied to a decision someone would make. A good set is small, and mixes leading and lagging measures. Each needs a target, a tolerance agreed in advance, and a trend, not just one value. Milestone hit rate and burn rate are simple divisions, best read as a series. And drop vanity measures, and design against gaming.
About Project Management at UPI Study
Project Management (Business 230) is a self-paced online course of 73 video lessons in 12 chapters, from starting and defining a project to planning, budgets, scheduling tools, proposals, contracts, execution, monitoring, closure, teams and certification. It carries a NCCRS credit recommendation for 3 semester credits.
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