Government technology (govtech) is a space filled with constraints – regulations, privacy laws, compliance requirements, and bureaucratic oversight that often slow down modernization efforts. We find in our research that upwards of 76% of a developer’s time isn’t even spent on writing code at this point (as cited by the CUBE Research). At Prodacity, Alistair Croll explored how metrics shape outcomes, sometimes in unintended ways, and why innovation within government requires not just technical solutions but creative problem-solving.
The Problem with One Metric That Matters
Croll highlights Goodhart’s Law: When a measure becomes a target, it ceases to be a good measure. In other words, optimizing toward a specific metric often leads to unintended consequences. The classic example: If you measure a factory’s success by the number of nails produced, workers may make thousands of tiny nails. If you measure by total nail weight, they’ll make just a few oversized ones.
In the govtech world, similar optimization pitfalls emerge. Governments set rigid targets – whether for efficiency, fraud prevention, or regulatory compliance – that end up undermining the very outcomes they were meant to achieve. A simple goal, like reducing paperwork for citizens, turns into a tangled web of new requirements: regional compliance rules, privacy constraints, fraud checks, RFP processes that exclude small vendors, and an increasing need for data reporting. Instead of streamlining processes, the system builds complexity and shifts accountability from outcomes to process adherence.
Finding the Loopholes to Innovate Within Constraints
Croll illustrates how constraints force workarounds – sometimes called loopholes, but often the only viable path to innovation. The Australian Open, for example, faced licensing issues when trying to display player likenesses in broadcasts. Instead of removing the broadcasts, they used software to replace real athletes with animated stick figures, sidestepping legal barriers while still delivering a viewer experience.
Another case: When sesame seeds were added to the list of allergens in food regulations, some companies found it easier to add sesame to their products and label it rather than go through the extensive process of proving sesame wasn’t present. It’s a perfect example of how rigid regulations sometimes create counterproductive behaviors.
In government, innovation often requires these types of creative workarounds. It’s not about breaking the rules – it’s about working within the red tape to achieve the real mission.
What Makes a Good Metric?
Croll emphasizes the importance of metrics that drive growth. With 76% of organizations struggling to align their metrics with business goals, identifying the right metric can be the key to unlocking success. To avoid the pitfalls of metric-driven bureaucracy, Croll lays out principles for effective measurement:
- Explainable – The metric should be easy to understand and justify.
- Comparable – It should allow benchmarking over time or against peers.
- Ratio- or Rate-Based – Absolute numbers often lack context; ratios provide deeper insights.
- Behavior-Changing – It should encourage the right actions rather than blind adherence to a process.
- Defined by Those It Serves – The best metrics are outward-facing, judged by the people impacted by them.
- Mission-Focused – It should capture the why behind a goal, not just the task itself.
For developers working in govtech, understanding how metrics shape outcomes is critical. When accountability is tied to process instead of results, it limits innovation. The challenge isn’t just about writing better software – it’s about designing systems that measure success in ways that drive meaningful change.
Final Thought
Modernization in government isn’t just about deploying new technology but about navigating the complexities of regulation, compliance, and legacy processes. It is also about bridging the gap between the heritage systems and new, modern applications. The best developers don’t just write code; they find creative ways to work within constraints to drive real outcomes. Metrics matter, but only if they measure the right things.
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