15/4/2025 ☼ public sector ☼ strategy ☼ uncertainty ☼ innovation
Public sector organisations now face unprecedented uncertainty (which is not the same thing as risk). This uncertainty comes from extreme and unpredictable weather and climate change, demographic transitions, economic dislocation, geopolitical upheaval, and new technologies that change everything from how things get made to how work is done — to name only a few.
The traditional slow-moving, risk-management and planning oriented policymaking approaches which are unintentionally baked into every single government by default are no longer adequate for making good policy in the face of uncertainty.
What if the key that unlocks truly transformative policy work lies in understanding how to work better in uncertainties that aren’t risky and in rethinking what strategy looks like? (And not just, as every government seems to think, in ever more elaborate forms of risk management and planning.)
This is on my mind because I’ve just wrapped up several months designing a four-day strategic innovation programme for a central strategy team in a federal government. My objective was to build an application-focused and experience-based programme that will be useful in context — much like the short adaptive management training workshops I’ve designed for the UNDP.
During the year-long research for this strategic innovation programme, I discovered that the single greatest obstacle to policy innovation in this government wasn’t lack of creativity or even lack of resources. Instead, it was confusion about the fundamental difference between risk and uncertainty, and an obsession with planning as a replacement for actual strategy.
The root cause here is that the public sector has a risk mindset when it should have an uncertainty mindset instead.
Unknowns are only risky if they can be accurately quantified. You have to know the probability of an action leading to a particular outcome, so you can plan around that risk and take action to optimise around it.
Uncertainty is a fundamentally different type of unknown. These unknowns aren’t well-understood enough to be quantified accurately, or even at all. In an uncertain situation, you don’t know enough to calculate probabilities.
Risk is when you’re trying to figure out how much to bet on what numbers will show up when you throw a pair of dice. Uncertainty, on the other hand, covers all the genuinely difficult problems public sector organisations face: How much of our limited budget should we invest in education when there’s a regional security crisis demanding investment in the military? What kinds of investments in research should we encourage to best support our national economy? Where should we set aside land for housing that will be built a decade or more from now? What kinds of government services should be delivered over the internet? The list of difficult and uncertain public sector questions is quite literally infinite.
Yet most public sector organisations treat this important uncertainty as merely “more risk,” and they assume it can be accurately and precisely quantified for optimal decisionmaking. So they end up applying inappropriate risk-management methods that don’t really work and, worse, stifle policy innovation precisely where it’s most needed.
Why’s this important? Because planning around inaccurately quantified unknowns leads to outcomes like buildings that collapse when exposed to unexpectedly strong winds, investment funds that fail when markets don’t perform as expected, or economies falling into recession because key trade agreements are unexpectedly invalidated by the actions of unpredictable political leaders.
Failing to clearly separate uncertainty from risk leads to these kinds of bad outcomes — but it also gets in the way of innovation.
Consider the development of mRNA vaccine technology. Early in their research, well before Covid-19, the key researchers involved weren’t facing calculable risks about whether this way of using mRNA would work — these were true uncertainties that couldn’t be quantified. In fact, one of the foundational research papers for the technology was desk-rejected (i.e., rejected by a decision of the receiving editor without the benefit of reviews by peers) by a prominent scientific journal because it was only an “incremental contribution.”1
The journals, universities, and pharmaceutical companies that passed on this emerging technology early in its development were often assessing it using traditional frameworks that assume detailed knowledge of unknowns (a risk mindset) and the associated ROI and expected value calculations. By inappropriately applying a risk mindset to evaluating this emerging technology, those organisations missed out on supporting one of the most transformative medical innovations of our time.
The conceptual confusion between uncertainty and risk creates a relationship problem that also gets in the way of transformative policy work: Counterproductive relationship dynamics between central government units and line agencies.
These relationships are counterproductive when they grow hierarchical and adversarial over time. Such dynamics make interactions high-stakes, infrequent, and focused on “finished” or “polished” work products. This creates precisely the wrong conditions for innovation, which requires calibrated explorations of unknowns, early and frequent feedback, and rapid-cycle experimentation.
The programme I built is designed to introduce an uncertainty mindset, gently erode these conceptual and relationship problems, and build some replacement tools that unlock transformative policy work at the whole-of-government level.
The first day of the programme introduces the powerful practical distinction between uncertainty and risk, demonstrating how shifting from a risk mindset to an uncertainty mindset can transform policy approaches.
Most organisations see uncertainty as a threat to be minimized. But what if uncertainty is viewed as a strategic resource? Organisations that excel at innovation don’t try, fruitlessly, to eliminate uncertainty through better planning. Instead, they learn how to embrace it and incorporate it through multiple parallel experiments, well-calibrated exposure to failure, investment in building learning cultures, and rapid iteration.
This approach is counterintuitive and uncomfortable for many public sector leaders, who are usually rewarded for mistake-free execution. The mistake they make is a subtle but profound one: Assuming that being rewarded for reliability means that they should invest in rigorous planning — even if it doesn’t work when facing unknowns that can’t be planned for.
Day 1 highlights how public sector work inherently involves both uncertainty and risk simultaneously. Acknowledging this reality, and learning how to respond appropriately and differently to risk compared to uncertainty isn’t admitting incompetence. It’s the first step toward more effective and transformative policy work.
The second day addresses a difficult truth: Innovation becomes much less likely when the relationships between central government and line agencies focus only on “finished” and polished work.
When government entities think only in terms of polished, complete work products that are “ready” for senior civil servants or political office holders to sign off on, they unintentionally suppress the frequent, small, low-stakes experiments which innovation requires.
The surprising insight here is that lower-stakes interventions often have more transformative potential than grand initiatives — simply because the lower stakes mean you can do more of them, and do them more quickly. When frequency and quantity go up, learning inevitably goes up too.
The workshop structure of Day 2 is oriented around finding context-relevant ways to change relationships to be more accommodating of uncertainty: Finding smaller first interactions to emphasise, lowering the stakes of those interactions, and also increasing their frequency.
What strategies and tactics work for transforming these embedded institutional practices that hold public sector teams back from innovation? Day 3 is a workshop that focuses on identifying specific high-potential, high-leverage entry points for introducing more well-designed experimentation into policy work.
Simply reframing early work as “pilots” vs experiments can create implicit permission for early work to fail in order to generate useful learnings. This approach can also create implicit permission for more ambitious experiments later.
I often find that the highest-leverage intervention points are located in trivial and boring-looking processes and SOPs, not in substantive areas — and some of the most powerfully transformative opportunities exist in gaps that entities themselves have already identified.
The Day 3 workship focuses on surfacing these high-leverage entry points and developing immediately testable ways of experimenting on those entry points for change.
The final day tackles a practical challenge: Creating a context-specific strategy toolkit that supports more transformative policy work.
Toolkits of any sort succeed only when they’re based on deep, contextual understanding of how policy professionals actually work, not how they officially say they work. And focusing on the realities of the context usually reveal that the biggest obstacles to adopting new tools are usually boringly mundane: Things like misaligned timelines, awkward reporting structures, and overly frictional approval processes. Though they’re mundane, these obstacles must nonetheless be identified and systematically dealt with.
Making a useful toolkit shouldn’t be about inventing brand new tools. Instead it should be about selecting from existing tools, making sure they address the problems identified in the local context, and then translating them for the local context.
Building effective strategic tools requires deep understanding of the context in which those tools will be used.
Good tool translation must always go beyond translating literal words from one language to another. The kind of translation I’m talking about is understanding the functional mechanisms underlying the tool, and then finding ways to implement those mechanisms in the local context. A translated tool can look different from the original and be implemented in a very different way; what matters is that the functional mechanism is robustly ported over.
That’s what Day 4 focuses on doing.
This 4-day programme is a progressive journey toward transformation. Participants begin by learning how to distinguish uncertainty from risk, then identifying areas in which relationships can be transformed to be more open to uncertainty. The programme ends with structured workshops designed to find practical and context-relevant entry points for rigorous experimentation, and to build contextualised tools that support better experiments in transformational policy work.
As they move through the programme, participants gain conceptual clarity and develop immediately usable interventions for transforming counterpart relationships, map high-leverage opportunity areas, and build specifications for context-appropriate tools.
The result? Strategy and innovation teams that are equipped to move beyond the limitations of traditional planning-oriented, risk-framed approaches and help their organisations achieve truly transformative policy outcomes in an increasingly uncertain world that demands real strategy.
Public sector innovation doesn’t demand radical restructuring or massive new resources. Most often, it simply requires a different way of thinking about uncertainty, a better understanding of strategy, and a practical, context-specific toolkit for transforming institutional relationships.
If your organisation is ready to move beyond traditional approaches to uncertainty and unlock more transformative policy work, this might be the catalyst you’ve been looking for. Get in touch to chat about whether the programme can be customised for your local context.
I’ve been working on turning discomfort into something productive. idk is the first of these tools for productive discomfort.
And I’ve spent the last 15 years investigating how organisations can succeed in uncertain times. The Uncertainty Mindset is my book about how to design organisations that thrive in uncertainty and can clearly distinguish it from risk.
Karikó, Katalin, et al. “Suppression of RNA recognition by Toll-like receptors: the impact of nucleoside modification and the evolutionary origin of RNA.” Immunity 23.2 (2005): 165-175.↩︎