Every complex system, whether an organization, a product, or a culture, tends toward entropy. Left alone, it drifts from excellence to mediocrity. Most leaders respond by adding reviews, reports, and dashboards, trying to inspect their way to quality. That does not scale.
Fitness Functions help teams become excellent and stay excellent. Fitness functions are measurable signals that reveal whether things are getting better on their own.
The idea comes from evolutionary computing, where algorithms “evolve” by measuring how fit each candidate solution is against a goal. Amazon adapted the concept to assess whether a system, technical, operational, or organizational, is improving over time without direct supervision.
A fitness function is a measure of system health and learning capacity. It does not replace goals or OKRs; it complements them. OKRs tell you what to achieve. Fitness functions tell you whether your system is getting better at achieving anything at all.
You can define fitness functions across any dimension of your organization using the CBTO lens: Customer, Business, Technology, and Organization.
Customer: Are we delighting customers more over time?
- Amazon Retail Page Load Time → Revenue
Amazon teams discovered that page load speed directly affected conversion. Tracking median page load time (weighted by revenue) became a fitness function for customer experience. If pages got faster and conversion improved, the system was fitter. - Delta Airlines “Net Promoter Recovery”
Delta measures how many detractors, or low NPS scorers, they successfully convert to promoters after a bad experience. The upward trend shows whether their service recovery system is improving.
Customer fitness functions measure how effectively customer delight compounds over time.
Business: Are we improving the long-term engine, not just quarterly results?
- Amazon Innovation Velocity
Amazon tracks the percentage of revenue from products or services launched in the past three years. It is a proxy for how quickly the business model refreshes itself. A rising number signals a company that continually invents on behalf of customers; Think Big in measurable form. - Google “Budget-to-Learning Ratio”
Google has tracked how much R&D spending results in new validated learnings such as experiments run, patents filed, or new models deployed. A healthy ratio signals a business that is investing wisely in future value, not just executing the current plan. - SpaceX Launch Reliability
SpaceX measures anomaly closure rate and recurrence. When issues close faster and repeat less often, the business system of design, supply chain, and quality is learning faster than it breaks.
Business fitness functions measure whether your engines for innovation and investment are compounding, not stagnating.
Technology: Is our system getting stronger on its own?
At Amazon we used COEs (Correction of Error reports) to measure how fast systems learned from failure. Each COE documented what happened, why, and what correction was engineered to prevent recurrence. A key fitness function was latency: how long it took from error detection to permanent fix. When that latency trended down, the system was getting fitter.
Later, at Control4, my team built a similar process called EECs (Engineering of Error Corrections), pronounced “Eek!” (like Bill the Cat). It had the same purpose: capture each failure, identify the root cause, and design a fix that made recurrence unlikely. Faster EEC closure meant a more resilient product and organization.
Meta (Facebook) uses a comparable approach through its SEV review process. Every production incident is assigned a severity (SEV1 for major outages, SEV2 for partial impact, and so on) and triggers a structured review. Meta tracks SEV-to-fix latency, the time between detection, mitigation, and full resolution. When that latency shrinks while incident volume stays flat or declines, Meta knows its infrastructure is learning faster than it fails.
Other leading tech orgs show the same pattern:
- Google’s Site Reliability Engineering (SRE) teams monitor Mean Time to Detection (MTTD), Mitigation (MTTM), and Recovery (MTTR) to balance reliability with speed.
- Netflix deliberately injects failure through Chaos Monkey, using MTTR as its core fitness signal.
Different names, same logic. A healthy system detects, corrects, and recovers without heroics.
Technology fitness functions measure execution and operational excellence; the system’s immune response.
Organization: Are our people and culture getting stronger without heroics?
Most leaders rely on engagement surveys or turnover stats, but those are outcomes, not signals of organizational health. A fit organization learns, adapts, and sustains performance without managerial firefighting.
- Spotify Squad Health Check
Spotify teams score themselves on autonomy, purpose, and learning. Leadership tracks trends, not snapshots. When those scores rise without intervention, the culture is scaling effectively. - Microsoft Employee Thriving Index
Microsoft measures the percentage of employees who say they are learning, energized, and empowered. When that number rises alongside productivity and retention, the organization is fitter. I used a similar metric called Employee Engagement to great effect at SnapOne. - Regretted vs. Unregretted Attrition
The ratio of regretted to unregretted departures is a direct cultural fitness measure. When high performers stay and low performers move on, leadership systems are working. A spike in regretted attrition means the Ghost of Mediocrity is creeping in. - Persistent Vacancies
Roles open more than 90 days are a sign that hiring, onboarding, or development pipelines are lagging behind business needs. As time-to-fill declines, it shows the system is learning how to attract and integrate talent faster.
When these signals move in the right direction, it means the organization’s leadership and culture are evolving faster than complexity is increasing.
Organizational fitness functions measure the rate of cultural learning and leadership maturity.
Leading by Fitness Function
Fitness functions are not vanity metrics or inspection rituals. They are how teams know their systems are improving their ability to produce results, consistently, and without constant intervention.
OKRs tell you what to achieve. Fitness functions tell you whether your organization is becoming more capable of achieving anything.
Define them across your CBTO stack: Customer, Business, Technology, and Organization. Review them regularly. When your fitness functions are trending in the right direction, excellence becomes self-reinforcing.
This is how great organizations deliver outsized results. They do not rely on inspection. They build systems that learn.
How do you know your system is getting fitter?
If you would like help designing fitness functions for your team or company, my office hours are open.
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