The Key to Good Decisions

Neville Chamberlain, the British Prime Minister leading up to World War II, has been ridiculed like few other leaders. He is an easy target because his negotiations with Adolf Hitler resulted in the Munich Agreement, what some have called appeasement, which failed to stop Germany from invading Eastern Europe. It is easy to conclude Chamberlain erred if the Munich Agreement is viewed through the lens of Hitler’s subsequent invasion of Czechoslovakia instead of trying to understand the information Chamberlain had available to make his decision at the time. When the full picture is considered, it is safe to conclude that most leaders who ridicule Chamberlain would likely have made the same decision as him if they had the same information that he had. Chamberlain had bad data.

WWI hangover, the Great Depression, and strong public sentiment against going back into war with Germany were among the pressures Chamberlain was feeling at the time of the Munich Agreement, but they weren’t his biggest concern. British intelligence told him that Germany’s Luftwaffe was much larger than it actually was. In addition, when global hero Charles Lindbergh was invited to Germany three separate times to view Germany’s aviation developments, he was fooled by Hitler into believing the Luftwaffe was much more advanced, in both technology and aircraft, than it was. British intelligence, with Lindbergh’s corroboration, had convinced Chamberlain that England, which had minimal aircraft and no air defense, would quickly be turned to rubble by the Germans if a war started. Chamberlain had to buy time to build the British military and made the decision that people mock today, but those folks don’t realize that Chamberlain believed that he was in a very bad negotiating position, because he had bad data.

A similar situation happened in the United States during 2002 to 2003. The U.S. President, George Bush, had data conclusively showing that Iraq possessed weapons of mass destruction (WMDs). Many still remember Secretary of State Colin Powell presenting the U.S. evidence to the United Nations indicating the exact places where the weapons were stored. However, the U.S. data was horribly bad, resulting in the U.S. invading Iraq and, by some estimates, nearly a million people losing their lives. President Bush had bad data.

In other cases, the necessary data is available but is filtered before it gets to the decision maker, losing its impact. The O-rings on the space shuttle Challenger are a good example of this; NASA had the data needed to delay the takeoff, but did not get it to the right people.

The business world is full of examples of bad or inadequate data leading to bad decisions. The 2008 financial crisis and resultant recession was largely driven by bad data about borrowers of sub-prime loans. The New Coke fiasco occurred because while Coke had good data on taste tests they had bad data on emotional attachment. Finally, in the recreational boating industry, where our company operates, I have seen numerous acquisitions fail because the acquirer did not have good data regarding the acquired company.

At the company I lead as CEO, Correct Craft, we work hard to make data-driven decisions. In a recent board meeting one of our directors even complimented our team stating that we have used data as a competitive advantage, helping us grow our company 25X over the past sixteen years. We are far from perfect in this area, but ensuring decisions are data-driven is a top priority for us. We want to have a data culture.

So, what should a leader do to ensure that they are making data-driven decisions?

• Create a data-driven culture. If a leader does not make data important it won’t be. Leaders must create clarity about the importance of data and then, most importantly, personally model data-driven decision making.
• Create a system to ensure reliable data. This will require developing or acquiring a data system with dashboards and analytics tools. For data that is regularly considered, agree on the metrics, so everyone is measuring and analyzing data the same way. Finally, encourage sharing data across departments.
• Develop your team. At our company we have an in-house data expert that works with all our companies to develop their tools and reports. Make sure the users of your data also understand the tools well and know how to interpret them. This will require training.
• Ensure that the data is considered when making decisions. This may seem obvious if you have taken the other steps, but it isn’t always. When making decisions always ask to look at the relevant data.
• Be prepared to create data for one-off decisions. You can create systems for recurring decisions, but you need to make data important for non-recurring decisions too. Always make sure you understand the data related to your decision.
• Fully understand how much of the decision you plan to make is based on emotion. Most people think their decisions are based primarily on logic, but behavioral research tells us that 80-90% of decisions are made emotionally or with heuristics. Emotional decisions can hijack our thinking and feel very right when they are actually very wrong. Because emotional decisions feel so right in the moment, it is hard to think logically when considering them. Force yourself to consider this when making decisions.

Great data can be a huge tailwind for your business. The department store Target has developed excellent predictive analytics; there are stories of Target using their analytics to send couples ads for prenatal vitamins before they even realized that they were expecting a new baby. Amazon uses real-time data in its algorithms to review customer buying patterns and competitive pressures to optimize both pricing and customer satisfaction. Starbucks uses its artificial intelligence models to select optimal store locations after considering demographics, traffic patterns, and competitor proximity. These companies have created billions of dollars in value by using data well.

Data does not eliminate the need for good judgment and intuition. However, history teaches us that relying solely on judgment and intuition is dangerous. That lesson doesn’t just apply to others; it applies to you too.

Leaders who make data important, invest in systems and employee development to create and interpret data, recognize the risk of emotionally discarding data, and consider data in their decisions will reap huge rewards from their data driven organizations.

Written by Bill Yeargin.