In the process of finding product-market fit with a new product or feature, it’s challenging to know exactly when to pivot and when to persevere. Making a pivot decision too early, or without enough evidence, can lead you away from a valuable opportunity. Making a pivot decision too slowly, on the other hand, can lead you to spend time and resources on a product that doesn’t deliver customer value.

Pivot decisions are challenging because they are not a perfect science. Even when you’re operating with a rigorous, data-driven process, the choice of when, how, and where to pivot requires measured intuition and risk. 

In this article, I’d like to explore three pivot decision anti-patterns. These are scenarios where it might feel right to avoid a pivot or to make a pivot, but doing so can lead to bad outcomes. 

#1 You’re avoiding a pivot decision due to sunk costs

It’s never fun to abandon work that you and your team have already started, but not completed. However, in some cases – due to new user insights, bad business results, or new business priorities. It’s necessary to stop a project mid-flight. When we avoid making a pivot decision because the work on something has already started, it can lead to even worse results than pivoting away early. It means that your team continues working on something that could drive mediocre results. 

It is much better to end a mediocre or failing project early and switch to higher-leverage work than to finish a project that might not add value when completed. And your team, while potentially disappointed to abandon their work, will also be happier, in the long run, working on a project that adds value to your business and its customers. 

#2 You’re avoiding a pivot decision because you’re avoiding a decision

Another reason you might be avoiding a pivot is that you’ve tabled a decision that is complex, or tough, to confront. If you are waiting for data to come in from test results, then it makes sense to delay a decision until tests are called. But, if you find yourself chronically punting on a decision, it might be time to make a decision with the best data you have. So that the product can move forward. Delaying decisions can slow down momentum and lead to missed learning. 

We tend to avoid decisions when we fear making the wrong move. However, in some cases, it’s best to make a call even though you could be wrong. Rather than make no decision at all. Some decisions will be the right ones; however, it’s better to make decisions and learn from mistakes than to avoid decisions entirely. 

It’s also useful to consider the level of consequence that follows each decision. Is this a small implementation detail that can easily be reversed? If so, the decision can be made with less scrutiny. Is it a high-stakes decision that cannot be easily reversed? This decision involves a higher level of scrutiny. (See Bezos’ famous Type 1 and Type 2 decision concepts.) 

#3 You’re pivoting too soon because the outcome of a test, or feature, is not guaranteed

Related to the last point, I have seen teams pivot because they cannot prove that a new test or feature will lead to a clear win for the product. The team gets stuck in a pattern of doing nothing because the outcome is not certain. 

While it is important to avoid the build trap – when teams focus on output and ignore outcomes. It’s also important to avoid the product perfection trap. This is where we raise the bar so high that we fail to ship experiments because there is some level of risk that the experiments might fail. 

There are no risk-free product decisions. However, many big wins involve exploring untested areas and solving new problems. As long as we test unknowns properly, and are mindful of the resources we’re spending to run these experiments. We shouldn’t feel the need to pivot away from ideas that involve risk or uncertainty. 

Wrapping it all up – TL/DR

While there are never easy ways to make pivot decisions, it is useful to categorize some scenarios where you should, or should not be, make pivots. Here are three pivot anti-patterns that you can watch out for as you manage your product area:

  1. Don’t refuse to pivot due to sunk costs. It’s better to stop a flawed project mid-flight than to see it to the finish line. 
  2. Don’t avoid a pivot because you’re delaying a decision. Sometimes, you need to commit to making the best decision possible – even if you don’t have perfect data, and even if you might be wrong. 
  3. Don’t pivot from an idea too soon because the outcome isn’t 100% guaranteed. To grow our products, we have to experiment in areas of risk. Reducing risk experiments leads to missed learnings, and missed opportunities. 

If you found this article helpful, check out David Prentice‘s other article on product pivots.

About the speaker
David Prentice CollegeVine, Product Manager Contributor

David Prentice is a Product Manager who is happiest when actualizing ambitious visions, fine-tuning high-quality user experiences, streamlining complex interfaces into simple interfaces, learning by talking with customers, binge-building dashboards, collaborating with cross-functional teams, and shipping products that make a meaningful improvement in the lives of their users. He currently works at CollegeVine, an education startup dedicated to bringing high-quality college guidance to every family, and has led the creation of a new app to help students optimize their college choices. Prior to CollegeVine, he managed brand, platform, and research teams at two of the world’s largest online travel companies. PM-life aside, David is a music, art, and history nerd, who lives in Boston with his girlfriend and three cats.

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