Treat government programs as experiments. Define success metrics upfront and set a firm deadline. If the program fails to achieve its stated goals by that date, it should be automatically disbanded rather than being given more funding. This enforces accountability.
For leaders overwhelmed by AI, a practical first step is to apply a lean startup methodology. Mobilize a bright, cross-functional team, encourage rapid, messy iteration without fear, and systematically document failures to enhance what works. This approach prioritizes learning and adaptability over a perfect initial plan.
When launching a new strategy, define the specific go/no-go decision criteria on paper from day one. This prevents "revisionist history" where success metrics are redefined later based on new fact patterns or biases. This practice forces discipline and creates clear accountability for future reviews.
Foster a culture of experimentation by reframing failure. A test where the hypothesis is disproven is just as valuable as a 'win' because it provides crucial user insights. The program's success should be measured by the quantity of quality tests run, not the percentage of successful hypotheses.
The most effective government role in innovation is to act as a catalyst for high-risk, foundational R&D (like DARPA creating the internet). Once a technology is viable, the government should step aside to allow private sector competition (like SpaceX) to drive down costs and accelerate progress.
Unlike most countries that fund legislation upon passing it, the U.S. Congress passes laws first and separately debates funding later. This fundamental disconnect between approving work and approving payment is a structural flaw that repeatedly manufactures fiscal crises and government shutdowns.
When handed a specific solution to build, don't just execute. Reverse-engineer the intended customer behavior and outcome. This creates an opportunity to define better success metrics, pressure-test the underlying problem, and potentially propose more effective solutions in the future.
Chess.com's goal of 1,000 experiments isn't about the number. It’s a forcing function to expose systemic blockers and drive conversations about what's truly needed to increase velocity, like no-code tools and empowering non-product teams to test ideas.
In siloed government environments, pushing for change fails. The effective strategy is to involve agency leaders directly in the process. By presenting data, establishing a common goal (serving the citizen), and giving them a voice in what gets built, they transition from roadblocks to champions.
To ensure continuous experimentation, Coastline's marketing head allocates a specific "failure budget" for high-risk initiatives. The philosophy is that most experiments won't work, but the few that do will generate enough value to cover all losses and open up crucial new marketing channels.
In government, digital services are often viewed as IT projects delivered by contractors. A CPO's primary challenge is instilling a culture of product thinking: focusing on customer value, business outcomes, user research, and KPIs, often starting from a point of zero.