How can the lessons exposed in Moneyball relate to hotels? Through analytics of course!
As a quick recap, Moneyball relates the tale of the Oakland Athletics, who in the early 2000s, used innovative analysis of baseball statistics to make strategic decisions regarding the team. The strategy proved fruitful as the A’s won more games with less money than anyone thought possible. In my opinion, the story in Moneyball bears truth across a myriad of other industry vertical, including the hospitality industry. Here we discuss what hotel executives should do to harness the power of analytics.
Recently, revenue managers have used predictive analytics to maximize profits from room rates by using forecasting and optimization techniques. However, like the baseball scouts in Moneyball that were still evaluating players solely by antiquated stats such as batting average, a new way of thinking needs to occur for hotels to fully realize the potential of analytics. For example, hospitality executives need to understand that optimization is not solely for revenue management. Take the well known hotel chain Marriott for instance.
Marriott International became a recent analytical competitor because of its new strategy, “total hotel optimization.” They realized how predictive analytics could help marketing departments optimize the best way to communicate with potential guests to not only adhere to potential customer preferences but also minimize the number of guests turned away due to a lack of vacancy. The finance department and operations managers could finally balance the labor schedule to maximize customer satisfaction while minimizing labor costs. Similar to the Oakland Athletics’ use of predictive analytics, human resource leaders could optimize their human assets. Marriotteven identified their most profitable customers by applying analytics to their Marriott Rewards program. Naturally, these strategies transcend hospitality to any relevant departments in other industries. However, it does take more than the introduction of analytics to local departments to achieve sustained success.
Although predictive analytics can redeem organizations, it can only help a business when all executives and departments commit themselves to this strategy. Davenport and Harris discuss this mantra by encouraging senior management to commit to endorsing an enterprise-wide analytical strategy. For example, in Moneyball the coach would not initially commit to implementing the analytical strategy dictated by Billy Beane. This led to a succession of losses and a lack of faith in Beane’s approach. However, when the coach finally had to no choice but to fall in line with Beane’s view, the Athletics proved his strategy with continued success.
As discussed above, if an industry, such as the hospitality industry, only implements analytics in a localized, or minimal, fashion, the full redemption of the organization would not blossom. A business needs to achieve analytical maturity by getting in front of trends, setting data-driven strategies, and achieving goals to gain that competitive advantage. Only then would predictive analytics illuminate its pure truth leading to redemption.
The SaberSmart Team
Davenport, T. H., & Harris, J. G. (2007). Competing on Analytics: The New Science of Winning. Boston, MA: Harvard Business School Press