Misaligned Incentives

What This Looks Like

Performance reviews ask about features delivered. OKRs are written as “ship X, Y, and Z by end of quarter.” Bonuses are tied to project completions. The team is recognized in all-hands meetings for delivering the annual release on time. Nobody is ever recognized for reducing the mean time to repair an incident. Nobody has a goal that says “increase deployment frequency from monthly to weekly.” Nobody’s review mentions the change fail rate.

The metrics that predict delivery health over time - lead time, deployment frequency, change fail rate, mean time to repair - are invisible to the incentive system. The metrics that the incentive system rewards - features shipped, deadlines met, projects completed - measure activity, not outcomes. A team can hit every OKR and still be delivering slowly, with high failure rates, into a fragile system.

The mismatch is often not intentional. The people who designed the OKRs were focused on the product roadmap. They know what features the business needs and wrote goals to get those features built. The idea of measuring how features get built - the flow, the reliability, the delivery system itself - was not part of the frame.

Common variations:

• The ops-dev split. Development is rewarded for shipping features. Operations is rewarded for system stability. These goals conflict: every feature deployment is a stability risk from operations’ perspective. The result is that operations resists deployments and development resists operational feedback. Neither team has an incentive to collaborate on making deployment safer.
• The quantity over quality trap. Velocity is tracked. Story points per sprint are reported to leadership as a productivity metric. The team maximizes story points by cutting quality. A 2-point story completed quickly beats a 5-point story done right, from a velocity standpoint. Defects show up later, in someone else’s sprint.
• The project success illusion. A project “shipped on time and on budget” is labeled a success even when the system it built is slow to change, prone to incidents, and unpopular with users. The project metrics rewarded are decoupled from the product outcomes that matter.
• The hero recognition pattern. The engineer who stays late to fix the production incident is recognized. The engineer who spent three weeks preventing the class of defects that caused the incident gets no recognition. Heroic recovery is visible and rewarded. Prevention is invisible.

The telltale sign: when asked about delivery speed or deployment frequency, the team lead says “I don’t know, that’s not one of our goals.”

Why This Is a Problem

Incentive systems define what people optimize for. When the incentive system rewards feature volume, people optimize for feature volume. When delivery health metrics are absent from the incentive system, nobody optimizes for delivery health. The organization’s actual delivery capability slowly degrades, invisibly, because no one has a reason to maintain or improve it.

It reduces quality

A developer cuts a corner on test coverage to hit the sprint deadline. The defect ships. It shows up in a different reporting period, gets attributed to operations or to a different team, and costs twice as much to fix. The developer who made the decision never sees the cost. The incentive system severs the connection between the decision to cut quality and the consequence.

Teams whose incentives include quality metrics - defect escape rate, change fail rate, production incident count - make different decisions. When a bug you introduced costs you something in your own OKR, you have a reason to write the test that prevents it. When it is invisible to your incentive system, you have no such reason.

It increases rework

A team spends four hours on manual regression testing every release. Nobody has a goal to automate it. After twelve months, that is fifty hours of repeated manual work that an automated suite would have eliminated after week two. The compounded cost dwarfs any single defect repair - but the automation investment never appears in feature-count OKRs, so it never gets prioritized.

Cutting quality to hit feature goals also produces defects fixed later at higher cost. When no one is rewarded for improving the delivery system, automation is not built, tests are not written, pipelines are not maintained. The team continuously re-does the same manual work instead of investing in automation that would eliminate it.

It makes delivery timelines unpredictable

A project closes. The team disperses to new work. Six months later, the next project starts with a codebase that has accumulated unaddressed debt and a pipeline nobody maintained. The first sprint is slower than expected. The delivery timeline slips. Nobody is surprised - but nobody is accountable either, because the gap between projects was invisible to the incentive system.

Each project delivery becomes a heroic effort because the delivery system was not kept healthy between projects. Timelines are unpredictable because the team’s actual current capability is unknown - they know what they delivered on the last project under heroic conditions, not what they can deliver routinely. Teams with continuous delivery incentives keep their systems healthy continuously and have much more reliable throughput.

Impact on continuous delivery

CD is fundamentally about optimizing the delivery system, not just the products the system produces. The four key metrics - deployment frequency, lead time, change fail rate, mean time to repair - are measurements of the delivery system’s health. If none of these metrics appear in anyone’s performance review, OKR, or team goal, there is no organizational will to improve them.

A CD adoption initiative that does not address the incentive system is building against the gradient. Engineers are being asked to invest time improving the deployment pipeline, writing better tests, and reducing batch sizes - investments that do not produce features. If those engineers are measured on features, every hour spent on pipeline work is an hour they are failing their OKR. The adoption effort will stall because the incentive system is working against it.

How to Fix It

Step 1: Audit current metrics and OKRs against delivery health (Week 1)

List all current team-level metrics, OKRs, and performance criteria. Mark each one: does it measure features/output, or does it measure delivery system health? In most organizations, the list will be almost entirely output measures. Making this visible is the first step - it is hard to argue for change when people do not see the gap.

Step 2: Propose adding one delivery health metric per team (Weeks 2-3)

Do not attempt to overhaul the entire incentive system at once. Propose adding one delivery health metric to each team’s OKRs. Good starting options:

• Deployment frequency: how often does the team deploy to production?
• Lead time: how long from code committed to running in production?
• Change fail rate: what percentage of deployments require a rollback or hotfix?

Even one metric creates a reason to discuss delivery system health in planning and review conversations. It legitimizes the investment of time in CD improvement work.

Step 3: Make prevention visible alongside recovery (Weeks 2-4)

Change recognition patterns. When the on-call engineer’s fix is recognized in a team meeting, also recognize the engineer who spent time the previous week improving test coverage in the area that failed. When a deployment goes smoothly because a developer took care to add deployment verification, note it explicitly. Visible recognition of prevention behavior - not just heroic recovery - changes the cost-benefit calculation for investing in quality.

Step 4: Align operations and development incentives (Weeks 4-8)

If development and operations are separate teams with separate OKRs, introduce a shared metric that both teams own. Change fail rate is a good candidate: development owns the change quality, operations owns the deployment process, both affect the outcome. A shared metric creates a reason to collaborate rather than negotiate.

Step 5: Include delivery system health in planning conversations (Ongoing)

Every planning cycle, include a review of delivery health metrics alongside product metrics. “Our deployment frequency is monthly; we want it to be weekly” should have the same status in a planning conversation as “we want to ship Feature X by Q2.” This frames delivery system improvement as legitimate work, not as optional infrastructure overhead.

Measuring Progress

Related Content

• Deadline-Driven Development - Deadline incentives are a specific form of misaligned incentives
• Velocity as Individual Metric - Using velocity as a performance metric creates its own misalignment
• Metrics-Driven Improvement - Building the case for delivery health metrics
• Baseline Metrics - Establishing current delivery health as a foundation for improvement goals
• Retrospectives - The forum for surfacing incentive misalignment and proposing change