"The No. 1 Predictor Of Career Success and How to Measure Product/Market Fit"

"The No. 1 Predictor Of Career Success and How to Measure Product/Market Fit"

In the world of career success and product development, there are key factors that can make or break your journey. Network science has revealed that being in an open network, as opposed to a closed one, is the number one predictor of career success. This makes sense as an open network allows for new perspectives and the generation of fresh ideas. It provides individuals with a more accurate view of the world by allowing them to pull information from diverse clusters, canceling out errors. In fact, research by Philip Tetlock shows that people with open networks are better forecasters than those with closed networks.

But what exactly does it mean to be in an open network? It means having the ability to serve as a translator or connector between different groups. By doing so, you can create value by connecting two people or organizations that can help each other, even if they wouldn't normally cross paths. The top performers in various fields have references that are 90% conventional and 10% atypical, meaning they pull from other fields. This ability to create atypical combinations is a key aspect of success.

Creativity is often described as connecting things. When you ask creative people how they come up with their ideas, they often feel a sense of guilt because they didn't actually "do" anything, they simply saw connections that others may have missed. Steve Jobs famously said, "You can't connect the dots looking forward; you can only connect them looking backward." This highlights the importance of trusting that the dots will somehow connect in your future.

Moving on to the realm of product development, measuring product/market fit (PMF) is crucial. Rahul Vohra, the CEO of Superhuman, shares a framework that has proven effective in determining PMF. One leading indicator is asking users how they would feel if they could no longer use the product. The magic number, according to Vohra, is 40%. If 40% or more of users would be very disappointed, then you have likely achieved PMF.

Vohra recommends focusing on users who have recently experienced the core of the product, specifically those who have used it at least twice in the last two weeks. By emailing these users a survey with specific questions, such as the main benefit they receive from the product and how it can be improved, you can gain valuable insights. Segmenting the data further by looking at the very disappointed group, which represents users who love the product most, can provide even deeper insights.

Julie Supan's high-expectation customer framework is a useful tool in this process. By identifying the most discerning person within your target demographic, you can better understand what truly resonates with your users. It's important to focus on building something that a small number of people want a large amount, rather than trying to cater to a large number of people with a mediocre product.