by Jesse Wolfersberger | January 12, 2018
In October, the Houston Astros won the World Series, beating the Los Angeles Dodgers in an incredibly entertaining seven-game series. To the baseball stats community, this was felt as a shared victory. The parade happened in downtown Houston, but the victory lap was felt across blogs, message boards, websites, and social media where stats nerds such as myself spend our time. 

The stats-oriented front offices have had plenty of regular season success, dating back to the "Moneyball" Oakland A's, but none have won a World Series without significant monetary help. To clarify, every MLB team has data analysts now, and several stats-heavy front offices have won the World Series recently, the Boston Red Sox and Chicago Cubs, for example. However, those rosters also boasted huge payrolls, so their victories had just as much to do with paychecks as spreadsheets. The Astros were different. They have been living the data-first philosophy for years, had to rebuild through multiple 100-loss seasons, and yet climbed to baseball's highest peak with a bottom-half payroll. That is what makes the Astros' story inspiring to the rest of us -- the business managers who drive results without being able to just throw money at the problem. 

The Astros laid out a path to victory that those of us in the incentive industry can follow. 

Move your data people to the very top
In the Astros' case, the road to the 2017 World Series began with the hiring of Jeff Luhnow as General Manager in 2011. Luhnow filled his inner circle with analysts and analytics-savvy staff. This changed the paradigm in the organization. No longer was it executives who had an analytics team, the executives were the analytics team. 

 As a diagnostic for your company or your incentive program's management team, ask yourself how many degrees of separation there are between the principal decision maker and the analytics team. If that number isn't one or zero, you might need to rectify that.

Be patient and trust the process 
Luhnow's tenure with Houston started with two straight 100-loss seasons. The third was a 92-loss season before finally recording a winning season in year four (2015). This is easy to sweep under the rug in hindsight, with the knowledge of 2017's championship. However, these early seasons are the most critical aspect of the Astros' story. Most business owners, in sports or otherwise, expect quick results. Losing this long and this badly would typically lead to another change in management. But, in Houston's case, this was part of the plan. Luhnow and the team were exercising incredible patience, developing prospects, building knowledge, and saving money for the right time to cash in their chips and make a run. This is only possible if there is organizational buy-in at every level. If Luhnow was expected to win a title within two years, he would have made more short-term decisions, gotten fired within a few years, and the cycle would have started all over again.

For the sake of your programs and mine, let's hope we never concoct a plan that will require three years of losing. However, the tradeoff between short term and long term are common decisions we make every day. Maybe it's the decision to invest in a new technology, to hire more staff, or build a new program site. These are all things that require up-front cost for the promise of long-term gains. Even A-B tests fall into this category -- running a test next quarter won't maximize sales immediately, it's an investment to gain insight. One client my team is currently working with is planning on making the entirety of 2018 a "test year," with the only goal being to learn as much as possible before a major program relaunch in 2019. 

We should all strive to make the decisions that create the best long-term business health. In order for that to do that, we need communication to and buy-in from management that a short-term investment won't be held against us.

Experiment and don't be afraid to fail
We know the Astros' journey to success took years. It also was not a straight line -- they made some mistakes along the way. Some were small, such as the "tandem pitching" experiment in the minor leagues, where they essentially had two starting pitchers for each game, each throwing roughly half the game. This was abandoned shortly after it began.

A more high-stakes mistake was the contract of Jon Singleton, a first baseman who they signed to a $10 million contract before he even played a Major League game. This was an unconventional move that was viewed with a raised eyebrow across the league. Singleton never developed into the power hitter they hoped, and he was not even on the 40-man roster last season. 

Both examples are failures of results, not failures of process. These were bold risks, the type no other teams dared to make. When the results did not materialize, the organization could have gotten spooked and adopted a more risk-averse strategy. Instead, they learned from the failure and moved on to the next bold risk. In businesses without this test-and-learn culture, you can imagine how the process typically works -- someone takes a big swing and misses… they are too defensive to admit they missed… a year later the mistake is compounding… no one is willing to take another big swing again because of how badly the last one went. 

Calculated risks should be applauded, even ones that fail
Last quarter, we helped a client design four different rule structure changes, and tested them with different audiences. At the conclusion of the test, none of tests worked well enough to implement across the board. Was that a failure? Maybe, but because we approached the situation with a test-first, data-driven approach, the client was not distressed about the results, and we're ready to explore other options together.

Analytics isn't a strategy, it's core to every strategy. This Astros story is just another page in the growing body of evidence that data-driven decisions are more effective than pure human judgement. I think this is fairly well understood across the incentive industry, although there are still days that I'm surprised. Those days are becoming more and more rare. I recently had a chance to give a talk to an auditorium full of account managers. I asked for a show of hands for how many had a new principal client in the past 12 months. Then I asked to keep their hands up if the incoming person was more data-driven than the outgoing one. Not a single hand went down. This pressure to measure, analyze, and predict will continue to rise every year.

Jesse Wolfersberger leads the Decision Sciences team for Maritz Motivation Solutions, and specializes in merging the fields of behavioral science and artificial intelligence. Contact him to discuss if you are using data in your programs to make them smarter at [email protected]