Little Bets: Fail Fast, Learn Quickly
The ability to adapt and innovate is paramount for survival and success. Problem-solving has a natural tendency to create innovations, largely because of the need to generate new ideas to solve current problems. However, people often misunderstand some of the best practices for generating innovative ideas and solutions. They incorrectly assume that the approaches center around extensive planning, prediction, forecasting, large investments, and high risks. In reality however Problem-Solving best practices reveal a more agile and efficient way to tackle challenges, foster innovation, and generate creative solutions. Enter the concept of "Little Bets."
What is a Little Bet?
Making little bets revolves around taking small, calculated risks to test hypotheses and gather feedback iteratively. Rather than committing large resources upfront, little bets allow businesses to experiment, learn, and adjust course as needed. This approach is rooted in the notion that innovation thrives on exploration, experimentation, and embracing failure as part of the learning process.
Fail Fast to Learn Quickly
At the heart of making little bets lies the principle of "Fail fast to learn quickly." Instead of fearing failure, little bets encourage businesses to embrace it as a stepping stone towards success. By failing fast, organizations can quickly identify what works and what doesn't, allowing them to pivot and refine their strategies accordingly. Many organizations’ successes have been the direct result of previous failures and privative iterations of their products. Consider:
Amazon did not start off as the #1 online retailer. They focused only on books until they understood more about their business and the needs of their customers.
AirBnB did not start off as the #1 place to rent another person’s house for your vacation. They started selling air-mattresses! (Hence, “Air” BnB)
Uber was originally a private chauffer service before it broke out into the ride-sharing powerhouse it is today.
Executing Little Bets: The PDCA Framework
That’s all well-and-good theoretically. But how can a person start making little bets today? A powerful framework for implementing little bets is the Plan-Do-Check-Act (PDCA) cycle, also known as the Deming Cycle. This structured approach to experimentation emphasizes iterative innovation and problem solving in four-steps:
Plan: In this initial stage, businesses identify the problem or opportunity and develop a hypothesis or plan to address it. This involves setting clear goals, defining metrics for success, and outlining the actions to be taken, including the proposed solution that will be tried.
Do: With the plan in place, the next step is to simply enact it by implementing the proposed solution on a small scale. This could involve launching a pilot project, releasing a minimum viable product (MVP), or conducting a small-scale experiment.
Check: Once the solution has been implemented, it's essential to evaluate its effectiveness by gathering data and feedback. This involves measuring key performance indicators (KPIs), soliciting user feedback, and analyzing the results to determine whether the hypothesis was validated, that is whether or not the plan had the impact that was expected. If the impact differs from the expectation, the check phase is also the appropriate phase to investigate why. By doing this, you’ll not only learn what works and what doesn’t, but also more about the problem itself and what assumptions may have been incorrect.
Act: Based on the findings from the check stage, take decisive action to either pivot, persevere, or abandon the current approach. If the hypothesis was validated and the solution proved successful, the next step is to scale it up. If not, adjustments are made, and the cycle begins again.
Example: PDCA in Action
Let's consider a hypothetical example of a software company experiencing high customer churn rates. The company predicts that improving the customer onboarding process will lead to higher customer retention. Here's how they could apply the PDCA framework to test this hypothesis:
Plan: The company sets a goal to reduce customer churn by 20% within three months. They develop a plan to revamp the onboarding process by streamlining account setup, providing personalized tutorials, and offering proactive customer support.
Do: The company implements the new onboarding process for a small segment of customers, such as new sign-ups from a specific geographic region or demographic group.
Check: After two weeks, the company analyzes data on customer engagement, satisfaction surveys, and retention rates for the test group. They find that while engagement has increased, retention rates remain unchanged.
Act: Based on the findings, the company decides to pivot their approach. They hypothesize that offering a dedicated account manager for new customers could address common pain points and improve retention. They update the onboarding process accordingly and repeat the PDCA cycle.
By iterating through the PDCA cycle, the company can continuously refine their approach, gradually improving customer retention without committing extensive resources upfront.
Conclusion
The ability to innovate and adapt is critical for long-term success. “Little bets” offer a flexible and pragmatic approach to problem-solving, allowing businesses to experiment, learn, and evolve over time. By embracing the PDCA framework and adopting a mindset of "fail fast to learn quickly," organizations can navigate uncertainty with confidence and drive meaningful change in the pursuit of innovation.
