Businesses that are good at decision-making are more likely to be successful. However, current events like supply chain disruption, rising inflation and Trumponomics have dialled up the uncertainty quotient across the globe; significantly impacting businesses’ ability to make suitably informed decisions in a timely way, and outdating their strategies faster than the time taken to formulate them. 

At the time of writing, stock market volatility is high, making it harder to interpret trends or forecast with confidence, directly impacting decision making. As John Kay and Mervyn King note, “We do not know what the future will hold, particularly in the midst of a crisis, but we must make decisions anyway.”¹ Businesses typically respond to instability in three different ways: managing the immediate; looking through the noise; and capitalising on disruption. The first involves responding to clear, near-term needs: adjusting recruitment, supply chains or cash flow based on current data. The second means holding course, assuming that the fundamentals remain unchanged. The third, taking advantage of volatility, demands a deeper level of insight and evidence, which can be difficult to gather amid market unpredictability. This route demands bold thinking and breakthrough ideas that challenge conventional thinking and embraces malleable, not static, strategy.  

Experimentation is a fundamental part of such a strategy. Structured in the right way, experimentation enables decision makers to couple opinions and new ideas with insight – supplying the confidence that turns a ‘brave’ decision into a serious contender. At Yonder, we call this ‘creating confidence in possibility’, and we regard it as one of our superpowers; bringing our strategic skills together with market-leading insights capabilities to address difficult decisions for clients. 

Creating confidence in possibility is both an art and a science. It requires blending logic and intuition, reason and imagination, along with a client’s tolerance for risk – no small task. Adding to the complexity, aligning strategy with insight isn’t always seamless. Carefully constructed assumptions, often grounded in historical data, must be re-evaluated against a more volatile and evolving reality. At times, strategy’s inherent drive for innovation can appear to dismiss hard-earned institutional knowledge, even when that knowledge still holds value. 

Yet, a decision must still be made. With resolve, we move forward, embracing uncertainty not as a threat, but as a catalyst for exploration; driving our curiosity to uncover what lies beyond the limits of what we currently know. 

Inevitably, this process is tailored to a client’s circumstances and requirements, but there are some common themes: 

1. Identify the uncertainty in the context of what is at stake for the business. It’s important to unpack the problem and be clear about the project scope. Goals, conflicts, assumptions and biases need to be identified, to ensure stakeholder alignment and buy-in. 

2. Develop a decision framework that allows scenarios to be stress-tested, reframing risk into the elasticity of opportunity. The framework provides a clear articulation of the hypotheses to be tested, the experiments that will be run and the success metrics. For example, whether customers can sustain a higher price for a product, or if a new segment of customers would be more receptive to a product proposition. 

3. Experiment, record, adjust and repeat. This iterative approach, which we call “adaptive strategy”, helps build resilience in the face of uncertainty, as decision-makers grow more comfortable operating without complete information. Each result feeds into a broader decision-making framework, informing new experiments and guiding future choices. Sometimes, the original decision must be reframed, but even then, its potential consequences can be evaluated through the lens of probability and impact – the elasticity of opportunity. This process also anticipates alternate outcomes, including those that arise if the decision ultimately proves to be incorrect. 

We see similar processes in multinational tech companies like Amazon and Netflix, that run continuous experiments in areas such as logistics, programming and messaging. But you don’t necessarily need huge data sets and tech-driven return paths when you can speak to consumers directly. Use intelligently designed questions, technology, and decision science to uncover valuable insights. 

Uncertainty is no longer a barrier to innovation; it’s a driver of progress. Rather than something to fear, it’s a force to be embraced. It was previously thought that big data would eliminate uncertainty, but the events of the past five years – the COVID-19 pandemic, disruptive technologies, geopolitical conflict and economic upheaval – have dispelled that illusion. In reality, the pursuit of certainty often leads to conventional thinking. Those who lean into uncertainty are better positioned to seize the opportunities hidden within volatility. In a world where the ground is always shifting, adaptability isn’t just an advantage, it’s a superpower. 

1. John Kay and Mervyn King, Radical Uncertainty, 2020 ↩︎