Metrics That Drive Behavior (Not Vanity Dashboards)

I used to think “more metrics” meant “more control.”

If we could just track enough things—tickets, turnaround times, completions, backlogs, hours, status updates—then we’d be on top of it.

What I learned is that while a dashboard can make you feel informed, your team may still be stuck.

The Problem Isn’t Data. It’s Signal.

In leading multiple support organizations, it’s easy to drown in numbers. You can track open service requests, inventory accuracy, cycle times, training completion, recruiting pipeline, invoice aging, close timelines, and contract actions in-work.

All of it matters—until it doesn’t.

Because if you try to manage everything, you end up managing nothing. The real job is to find the few measures that tell you the story and drive behavior change in the right direction.

The “Vanity Metric” Trap

A vanity metric is anything that looks impressive or looks busy, but doesn’t reliably connect to outcomes. You’ve seen them:

• “We closed 300 tickets” (but the same issue keeps coming back)
• “Training compliance is 92%” (but the people who matter most are the 8%)
• “We have 40 candidates in the pipeline” (but offers accepted are down)
• “We processed 200 purchase requests” (but cycle time is creeping up)

Vanity metrics create a false sense of progress. Strategic leaders don’t collect metrics to feel better—they use metrics to make decisions.

The Leadership Shift: Measure Outcomes, Not Activity

Here’s the simplest filter I use now:

If the number goes up, does the mission get better?

If the answer is “maybe” or “it depends,” it might be activity. If the answer is “yes,” you’re closer to an outcome.

That doesn’t mean activity metrics are useless—it means they’re secondary. Outcomes tell you if you’re winning. Leading indicators tell you if you’re about to lose. You need both—but not a hundred of them.

What Good Looks Like

When your metrics are right, you’ll notice:

• Your dashboard fits on one page
• Every metric has a single owner
• Thresholds are clear (RYG is consistent, not emotional)
• The team knows what “good” looks like without asking
• Reviews create actions, not explanations
• Bad news shows up early, not at the deadline
• People stop debating the data and start improving the system

That’s when metrics become a leadership tool—not a reporting obligation.

My 5-Metric Rule (Per Function)

This is a guideline, not a law, but it’s helped me cut out the noise: no more than 5 core metrics per function at the director level.

If you need more than 5, you probably have one of two issues: you haven’t agreed on priorities, or you’re trying to manage at the wrong altitude.

Those 5 should usually include:

• 1–2 outcome metrics: what success looks like
• 2–3 leading indicators: what predicts success or failure
• 1 capacity/health metric: so you don’t burn the team down

The Difference Between Metrics That Help and Metrics That Hurt

Metrics that help:

• Have a clear definition (no interpretation games)
• Are reviewed on a cadence that matches reality
• Tie directly to decisions or corrective action
• Are hard to “game” without improving the outcome
• Drive the right behavior even when nobody’s watching

Metrics that hurt:

• Are tracked “because we always have”
• Have no owner
• Are reviewed, but nothing changes
• Create fear, hiding, or blame
• Encourage speed at the expense of quality (or vice versa)

If a metric creates defensive behavior, it’s not a performance tool anymore. It’s a morale killer.

Practical Framework: Outcome + Leading Indicator + Corrective Action

Channeling our inner Stephen Covey—let’s start with the end in mind.

Step 1: Pick the Outcome

• Reduce DSO
• Improve inventory accuracy
• Improve system uptime
• Improve offer acceptance rate
• Reduce training delinquency for critical roles

Step 2: Identify What Predicts the Outcome

• For DSO: aging buckets, dispute cycle time, billing accuracy rate
• For inventory accuracy: cycle count completion rate, adjustment reasons trend
• For uptime: repeat incidents, change failure rate, patch compliance
• For recruiting: time-to-submit, interview-to-offer conversion, offer acceptance rate
• For training: scheduling adherence, access constraints, manager completion cadence

Step 3: Decide What You’ll Do When It Turns Yellow/Red

This is the part most teams skip. If yellow doesn’t trigger action, yellow is meaningless.

Instead, define the response: who owns it, what the first move is, when it’s due, and what “back to green” requires.

Quick Vignette: “Busy Recruiting” With No Results

I’ve seen recruiting teams working hard—lots of candidates, lots of screens, lots of activity. But hiring still stalls.

When you dig in, the constraint often isn’t effort. It’s conversion and cycle time: candidates are dropping because the process takes too long, hiring managers aren’t available for interviews, onboarding timing doesn’t match reality.

If you only measure “pipeline size,” you’ll miss the real issue. When you measure time in stage, conversion rates, and offer acceptance—you can actually fix the system.

That’s the difference between a dashboard and a decision tool.

The Part I Had to Learn (And Still Work On)

As a detail-oriented leader, I can over-index on measurement. It feels responsible. But if I’m not careful, metrics can become a way to stay in the weeds while convincing myself I’m being strategic.

The better discipline is this: pick fewer metrics, review them consistently, and act on them every time.

That’s leadership.

Your One Commitment for This Week

Pick one dashboard you use today and run this quick test:

1. Circle the metrics you actually make decisions from
2. Cross out anything that never changes behavior
3. Reduce what’s left to the top 5
4. Add thresholds (RYG) and define what action yellow/red triggers
5. Assign one owner per metric

Then watch what happens. Less noise. More clarity. Better execution.

Reflection Questions

• Which metric do we track but never act on?
• Are we measuring outcomes—or just activity?
• What leading indicator would have warned us last month?
• Which metric might be driving the wrong behavior?
• If I cut this dashboard in half, what would I keep?