The 7 Metrics Gaslighting Your Team
- 16 hours ago
- 5 min read
Jared Blaine, Feb 17 2026
Note to Readers: A successful social enterprise that solves social problems and is financially viable requires tracking its performance with actionable metrics.
NB The following article was lightly edited for length
“We live in an era obsessed with data. We measure everything, from our steps to our sleep to our server response times. But in the rush to quantify success, we’ve fallen into a trap. We’ve started confusing the map with the territory.
The Science of Cheating (Or: Why We Can’t Have Nice Things)
Before we drag your current metrics into the interrogation room, we need to talk about two British guys from the 1970s who predicted exactly why your team is stressed out right now.
First, meet Goodhart’s Law. Named after economist Charles Goodhart, it states: “When a measure becomes a target, it ceases to be a good measure.”
Translation? The moment you tell a support agent that their bonus depends on keeping call times under two minutes, they aren’t going to solve problems faster. They’re going to hang up on grandmas.
Then there’s Campbell’s Law, which is Goodhart’s darker, edgier cousin. Sociologist Donald Campbell argued that the more a quantitative metric is used for decision-making, the more likely it is to be corrupted. It’s not just that the data gets fuzzy; it’s that the pressure distorts the very process you’re trying to improve.
1. The “Success Theater” Metric (aka Vanity Metrics)
In The Lean Startup, Eric Ries coined a phrase that should haunt every dashboard designer’s nightmares: Success Theater.
This is the metric that makes you feel like a rockstar while your business slowly bleeds out. It’s the 100,000 page views on a blog post that generated zero leads.
It’s the massive spike in app downloads after you spent $50k on ads, but nobody opened the app a second time.
The Lie: “Look how popular we are! We’re growing!”
The Sabotage: Vanity metrics consume resources without offering guidance. They are ego-food, empty calories that bloat your confidence but starve your strategy.
The Fix: Switch to Actionable Metrics. As Ries suggests, look for data that proves cause and effect. Instead of “total registered users” (vanity), track “active users who performed a key action in the last 7 days” (actionable). If you can’t make a decision based on the number, delete it from the slide deck.
2. The Cobra Effect (The Perverse Incentive)
This is Goodhart’s Law on steroids. The name comes from a legendary (and possibly apocryphal) story from British colonial rule in India. The government wanted fewer cobras, so they offered a bounty for every dead cobra.
The result? People started farming cobras to kill them and collect the cash. When the government caught on and canceled the bounty, the breeders released the snakes. The net result: More cobras than before.
The Fix: Audit your incentives. Are you rewarding the outcome (a happy customer) or the activity (opening an account)? If your metric can be gamed, assume it is being gamed.
3. The “Cheat Code” Metric (Gaming the System)
Sometimes, the sabotage isn’t about creating fake accounts; it’s about technically following the rules while destroying the intent.
Enter Volkswagen. In 2015, the “Dieselgate” scandal revealed that 11 million cars were fitted with software that could detect when they were being tested for emissions. When the car sensed a test, it ran cleanly.
On the road? It spewed nitrogen oxide up to 40 times the legal limit.
They hit the KPI (pass the test). They missed the point (don’t poison the planet).
The Fix: Pair your quantitative metrics with qualitative checks.
If efficiency goes up, check quality.
If sales go up, check customer satisfaction.
Never let a metric stand-alone without a “counter-metric” to keep it honest.
4. The Rearview Mirror (Lagging Indicators)
Driving a car while only looking in the rearview mirror is a great way to hit a tree. Yet this is how most businesses operate. They obsess over revenue, churn rate, and quarterly profit.
These are Lagging Indicators. They tell you what happened three months ago. By the time a lagging indicator turns red, the damage is already done.
The Fix: Identify Leading Indicators. These are the canaries in the coal mine.
Lagging: Churn rate.
Leading: A drop in weekly active usage or a spike in support tickets.
Find the behaviors that predict success or failure and obsess over those.
5. The Activity Trap (Busyness vs. Impact)
The Activity Trap is the silent killer of high-performing teams. It prioritizes output over outcome. It’s measuring lines of code written instead of features shipped. It’s measuring the number of sales calls made instead of deals closed.
The Fix: Stop measuring effort. Start measuring value delivery. If you send 1,000 emails and get 0 replies, your KPI shouldn’t say “1,000 emails sent.” It should say “0% effectiveness.”
6. The “Silo” Metric (My Win is Your Loss)
This is the Civil War metric. It happens when one department’s KPI directly conflicts with another’s.
Marketing is measured on the number of leads generated. So, they throw a net over the entire internet and bring in 5,000 leads. They hit their goal! Champagne for everyone!
Sales is measured on conversion rate. They look at the 5,000 leads, realize 4,900 of them are terrible, and miss their targets because they’re drowning in junk.
Engineering is measured on uptime, so they refuse to let Product launch new features because changes cause downtime.
The Fix: Shared metrics. Align the incentives so that nobody wins unless everybody wins.
7. The Zombie Metric
These are the metrics you track because… well, you’ve always tracked them. Maybe a VP who left three years ago asked for a specific report, and nobody ever told the data analyst to stop running it.
The Fix: The Marie Kondo approach. Look at every metric on your report and ask, “Does this spark action?” If a metric turned red today, and you wouldn’t change what you’re doing, delete it.
The “KPI Red Flag” Checklist
Ready to exorcise your dashboard? Screenshot this list. If your metrics hit any of these tripwires, you have a problem.
The Goodhart Test: If employees knew exactly how this metric was calculated, could they cheat it without actually doing the work? (If yes -> Red Flag)
The Ego Check: If this number goes up, does it actually put money in the bank or help the customer? (If no -> Vanity Metric)
The Lag Check: Does this metric tell me what happened, or what is going to happen? (If it’s only history -> Red Flag)
The Friction Test: Does hitting this goal make life harder for another department? (If yes -> Silo Metric)
The “So What?” Test: If this metric changed by 10% tomorrow, would we do anything different? (If no -> Zombie Metric)
TIP: Consult Module 8 in the Practitioner’s Guide for an overview of metrics as part of a Business Model.
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