A number of years ago, I had the distinct privilege of working with a professional sports team. This ingenious team was eager to try what no other team had -- to use data and analytics to improve its performance, both on the field and at the box office. The stakes were high: Winning or losing any one game in this league was an eight-figure swing in revenues. As an engineer, I had an unlikely front-row seat to the quiet birth of analytics in professional sports, before the idea exploded onto movie screens across the country in 2011.
Industry can learn many lessons from the failures and successes of analytics in professional sports.
It was a fascinating and inspiring time. The old guard of the league held on dearly to the entrenched rules of how to win, which clashed with the young, naïve, nerdy data scientists who sought to influence the game in nonstop late-night sessions in front of their computer screens. In the end, the "this is how we have always done it" mentality gave way to analytics as a permanent fixture in professional sports around the world. Today, every sport from badminton to horse racing has a cadre of data jockeys (pardon the pun) pouring over game statistics and game receipts.
It is now just as interesting to see how this parallels with the adoption of data analytics for business -- to make our organizations stronger, more resilient, more valuable and financially proficient. Today, I call this point in history "the start of the automation era." Industry can learn many lessons from the failures and successes of analytics in professional sports. Every day I see examples of how more forward-thinking companies are creatively incorporating methods first used in professional sports into their own practices. For example, I saw a software company use the same techniques that Major League Baseball uses to evaluate players to determine the efficiency of each and every salesperson among the 4,000 professionals in its nationwide group. I have seen companies "wire up" workers in industrial plants to analyze the ergonomics of their movements just like teams "wire up" players in the NFL Combine to assess their physiological statistics as they run drills.
Like traveling to a new country, we need to learn a whole new language to describe the elements of the automation era. Terms like "digital twin," "feedback loops," "recommendation engine," "gamification" and "IFTTT" will be key terms in the lexicon of our conversations. In my writings, I will include the meanings behind each of these concepts so they can be understood and applied.
This is by far the most exciting time to be alive in the world of business and industry. The transformative power of data, analytics, technology and automation will unfold right before our eyes over the next decade. We will see brand new, unimagined business models, unprecedented automation and a few legacy companies falling by the wayside. Seemingly insurmountable challenges will be an everyday feature of corporate life. It will be terrifying and exhilarating, all in one movement.
In the next few issues of BIC Magazine, I will be expounding on this trend by reporting our progress through the lens of actual case studies on the use of analytics in industry. I will seek to draw lessons from many of these stories -- lessons that can be applied by you, the reader, in practical ways at your own company, regardless of industry, location or size. Join me on this incredible journey into the automation era at our doorstep. Bring with you your courage and intellect, and let us see what we can make of the "art of the possible" that we have in our grasp today. Here we go.
George E. Danner is president of Business Laboratory LLC, a specialty firm that builds simulation and analytical models to solve complex problems for businesses worldwide. He is the author of two books, "Profit From Science" and "The Executive's How-to Guide to Automation."
For more information, visit www.georgedanner.com.