Prediction Error and Small Bets

Prediction error, simply put, is the difference between what we expect to happen and what actually unfolds. It drives learning, adaptation, and sometimes, costly surprises. We’ve all encountered it in our lives, but how can we harness prediction error to learn and grow without risking serious or lasting mistakes?

The sliding scale of prediction errors

Prediction errors, like all errors, aren't bad in and of themselves. They simply reflect a mismatch between expectations and reality. Whether an error is perceived as "good" or "bad" depends on its context, impact, and how its used. When approached constructively, even highly impactful errors can be valuable learning opportunities that drive growth and improvement.

In experience design, a significant amount of attention is devoted to a concept known as "error recovery," which refers to a person’s ability to complete their task after making a mistake. For example, if a user accidentally adds two items to their Amazon shopping cart, error recovery involves how quickly and easily they can access their cart and adjust the quantity back to one. This concept is also relevant to prediction error; in fact, I often use error recovery as a key factor when prioritizing situations where I seek expert advice, with the goal of mitigating prediction error.

Consider the following scenarios:

• Missing the goal: A soccer player shoots, thinks it'll go in, and he misses the goal. Was the shot worth taking? What was the risk? Was the error easily recovered from?
• Missing the pitch: A colleague prepares a pitch that she believes will wow the team but it falls flat. Is this an error that can be recovered from easily? Could it have been mitigated?
• Business flop: We start a business and invest two years of our lives and millions of dollars but the market isn't there and we close. How easy is this to recover from? Could we have avoided this?
• Investment crash: I invest all my money into a stock I think will soar but it cashes. This might be tough to recover from. I probably should have tried harder to avoid this outcome.

When error recovery is easy, the implications of prediction error are less severe, turning these “small bets” into valuable learning experiences. However, when error recovery is difficult, prediction error can lead to unrecoverable consequences. While such situations may also offer valuable lessons, the cost of learning may far outweigh the benefit.

Mitigating Prediction Error through Small Bets

Prediction error is a double-edged sword: it can fuel transformative learning but also lead to severe setbacks. By embracing small bets, we create a cycle of continuous, low-cost learning, mitigating the impact of prediction error and gaining valuable insights along the way. Conversely, when big bets are necessary, careful planning and proactive mitigation of prediction errors can help protect us from disproportionately high costs. Balancing these approaches allows us to learn, adapt, and grow wisely.

Helping Organizations Mitigate Prediction Error

At The Moment we help organizations mitigate prediction error though a dual approach focused on both immediate and long-term impact. For big bets, we deploy diagnostics, studies, and tailored solutions to identify gaps, reduce uncertainty, and provide a clear path forward. We then empower teams with the tools and knowledge to break future big bets into smaller, manageable steps through incremental change management, agility, measurement, and continuous improvement. By embedding feedback loops and adaptive strategies, we turn complex challenges into opportunities for growth and resilience, minimizing risk while maximizing organizational learning and adaptability.

Learn more about how we use our Insight to Impact Lifecycle to help mitigate prediction error: https://www.themoment.is/insight-to-impact-jj/