0.8 Analytics Supports the Main Effort
As you go along, always keep in mind that analytics is a tool. Analytics helps businesses to answer questions, and to solve problems, but in nearly all cases, analytics is not a solution in and of itself. 5
To illustrate this point, let’s start with Lobster Land. Lobster Land succeeds because families love to visit the park, whether for the rides, the food, the games, the fun atmosphere, or some combination of these features. Lobster Land existed, and succeeded, before its owners had ever heard of the term “analytics,” let alone incorporated it into their decision-making processes.
This is not to say that analytics is not important. Analytics matters! As we will see throughout this book’s pages, analytics can help inform managers about which products to offer, how to approach specific types of consumers, how much to charge for specific items, and much, much more.
Analytics is not, however, a magical solution, or a silver bullet. It will not fix things that are fundamentally broken, nor will it substitute for the things that make a product or service great in the minds of consumers.
The same is true for nearly any business. Think about a restaurant that you love, located on a busy street corner just a few blocks away from where you live. Why do you like to go there? What makes it popular with other patrons, too? Chances are, you answered that question with things like the food, the service, the atmosphere, etc.
Certainly, analytics can help this business. A dedicated analytics professional on staff might be able to identify patterns regarding the customers – maybe, for instance, there are more orders of specific types of expensive seafood dishes on Fridays and Saturdays than on other days. That could be very valuable to the manager who buys from a wholesaler twice a week, as she can adjust her purchases to maximize the freshness of the dishes when served.
Analysis of customer wait times could yield insights about staffing – perhaps the restaurant is understaffed on Wednesdays, but winds up with too many idle employees on the clock early on Thursday evenings. Carefully applied analytics could help to identify issues such as these.
Similar examples could be applied in other realms. In sports, analytics might yield insights that suggest that a basketball team should attempt more three-point shots, or that a football team should avoid punting on fourth down near the middle of the field.
In sports, just as in the restaurant example or the theme park example, analytics has the potential to help offer the winning “edge” that can make an operation, or a team, even stronger or more efficient. It will not deliver miracles, though – an outmatched basketball team that cannot shoot accurately is not likely to beat its opponents, regardless of analytics. Similarly, a restaurant with subpar service and food cannot be saved by even the sharpest analytics insights.
5 One possible exception here would be a company that provides marketing analytics services.