How to Learn to Solve Problems with a Large Number of Unknowns

The causal foundation laid in us from childhood often fails when we face complex problems with many unknowns. Our upbringing is steeped in a culture of clues and cues, which offer us a sense of comfort and direction. However, this reliance can leave us ill-equipped to navigate situations where such guidance is absent.

From a young age, we are accustomed to living with clues. The more clues we have, the more comfortable we feel. Our lives are often dictated by these cues—we go to school on the advice of our parents, choose our colleges based on their recommendations, and even select our professions following their counsel. This patterned existence provides us with a maximum comfort zone but deprives us of the opportunity to make independent decisions. Decision-making, at its core, is about solving problems with the highest success rate. When the cues disappear, we often find ourselves at a loss, desperately seeking guidance from courses, books, and social media, hoping to find a clue on what to do next.

Consider the typical journey of a high school student. This path is often laden with external advice and guidance, much like the broader path of life. When the structured environment of school ends, many find themselves adrift, struggling to make decisions without a preset roadmap.

One key to solving problems with a large number of unknowns is to reverse our approach. Instead of moving from cause to effect, we should start with the desired outcome. By clearly defining what we want to achieve, we can work backward to identify the steps needed to get there. This approach shifts the focus from finding clues to understanding the end goal, enabling us to navigate complex problems more effectively.

In essence, solving problems with many unknowns requires a fundamental shift in perspective. We need to move beyond our comfort zones, embrace the uncertainty, and focus on the desired outcome. By doing so, we can develop the skills and confidence to tackle even the most complex challenges, independent of the clues and cues that have guided us for so long.

When I first encountered a problem with many unknowns, I was overwhelmed. My initial instinct was to look for clues, but they were nowhere to be found. I decided to try a different approach. I asked myself, "What is the ultimate goal here?" By focusing on the desired outcome, I was able to work backward, breaking down the steps needed to achieve that goal. This method transformed my way of thinking and helped me tackle the problem effectively.

For instance, when I was working on a project with a team, we faced numerous unknowns about market conditions, customer preferences, and technological capabilities. Instead of getting bogged down by these uncertainties, we defined our goal: to create a product that met a specific market need. We then mapped out the steps required to reach that goal, identifying and addressing each unknown as it arose. This outcome-focused approach allowed us to make informed decisions and navigate the complexities successfully.

Another practical solution is to embrace the process of elimination. When faced with multiple unknowns, systematically ruling out possibilities can help narrow down the options. During a startup launch, we encountered several potential customer segments but had limited resources to target all of them. By testing and eliminating less promising segments, we were able to focus on the most viable market, optimizing our efforts and resources.

One of the most specific (but useful) approach is to develop an irrational outcome. Operate mostly on assumptions. Consider the early days of Bitcoin and Tesla. Neither of these projects were initially assessed by analysts as promising ventures. Bitcoin, the pioneering cryptocurrency, was seen as a niche interest for tech enthusiasts rather than a viable financial asset. Similarly, Tesla's ambitious vision of mass-producing electric vehicles was met with skepticism, with many experts doubting its feasibility and market demand.

Great discoveries were where there was a lot of logical criticism and scepticism.

References and Sources:

1. Dweck, Carol S. "Mindset: The New Psychology of Success." Random House, 2006.

2. Kahneman, Daniel. "Thinking, Fast and Slow." Farrar, Straus and Giroux, 2011.

3. Adams, Scott. "How to Fail at Almost Everything and Still Win Big: Kind of the Story of My Life." Portfolio, 2013.

4. Eisenhardt, Kathleen M., and Jeffrey A. Martin. "Dynamic Capabilities: What Are They?" Strategic Management Journal, vol. 21, no. 10-11, 2000, pp. 1105-1121.

5. Brown, Tim. "Change by Design: How Design Thinking Transforms Organizations and Inspires Innovation." Harper Business, 2009.