Successful analytics, to me, is that analytic projects get built, used and have an impact on decisions within an organization. This definition does not require that a group is doing the most advanced analytics possible, but rather that it is doing the most impactful analytics possible. With this definition in mind, Warren Berger’s 2010 post at the Harvard Business Review Blog that lays out the four principles of design thinking–Question, Care, Connect and Commit–changes from a piece centered around design thinking to a vital tool for all analysts. While this is a very introductory piece to design thinking, I was struck by how important these principles are in order to build a successful analytics group within an organization.
The idea that part of the role of analytics is to answer tough questions is not novel. Part of the struggle for analysts though is to determine what those tough questions are. From a design perspective, the way to get at the tough questions is to ask the stupid ones first. It is often difficult for analysts to ask what may appear to be fundamentally basic questions about their industry, but it is vital in order to gain insight. In sports, this has meant sitting down with coaches and asking questions that clearly demonstrate my lack of deep knowledge about their sport (“What does it mean for a player to be a ‘glue guy’?”).
The risk with these types of questions is obvious; the analyst is in danger of losing the respect of the decision makers because they are not knowledgeable about their sport. What analysts need to understand is that these decision makers are already sure you know nothing about their sport. I once sent a student on an interview at a pro team. I called the day after the interview to see how he had done and was told “He did great. Knows absolutely nothing about football, but that’s fine, that isn’t why we are hiring him anyway.” It is much better to ask questions to educate yourself and hopefully, through a series of “stupid” questions you get to an interesting and useful answer.
Analysts often struggle getting new metrics and tools used in an organization because they are thinking about what they see as valuable about the new idea. Instead analysts need to care about how decision makers would see and use the tool. How would a busy head coach, who has become very successful without this tool, use it and more importantly, why would they use it? Asking these questions forces the analyst to shift focus from their interests and goals to that of the users of their work.
Dean Oliver’s insistence, for example, that ESPN’s QBR (a new metric that measures the impact a quarterback has on an NFL game) be on 0 to 100 scale, was to make the interpretation of the metric more accessible to any fan who was interested. Understanding how the consumer of your work will actually use it makes it much more likely that the work will be used, and that you will design tools that decision makers actually need.
Connecting in design thinking is about bringing two previously unrelated products or tools together to create a new experience for the consumer. In analytics, this may be connecting advanced metrics that were used in player evaluation together with new data from sport science to map out player development plans. The idea is that we often do not need new ideas to have a new impact, but rather combine ideas and tools that we are already using in novel ways that increase the use of the tools and the value they bring to an organization.
Committing to a new project (or even an idea before it actually becomes a project) means moving from good ideas to innovation (actually implementing something). There are a variety of steps to take in order to get to a fully implemented tool that is used throughout an organization. Along the way from idea to implementation, the analyst has to show pieces of the tools whether they are mocked up interfaces or specific decisions the metric could have influenced. The analyst has to constantly push the concept forward and build it more and more into the decision making process. If the analyst is not committed to the tool, then why would anyone else be? The analyst needs to constantly think creativity about how to demonstrate their commitment to a project, so that others can get committed as well.
The key takeaway from the design world for the analyst, is that they have be focused not on building the next coolest new analytic model or tool, but rather on how to have an impact on their organization. This requires knowing how processes work and why they work that way, understanding the perspective of their “consumers,” leveraging previously disconnected ideas to create new value, and committing to a long term strategy of getting new tools used.
Thinking along these lines will help analysts find success and satisfaction not with creating fancy analytics but with impacting how an organization makes decisions and helping them make better ones. Whether that leads to more wins or more profit, the idea is to design analytics and not just do them.
Benjamin Alamar is a sports analytics consultant, researcher, speaker, and author of “Sports Analytics: A Guide for Coaches, Managers, and Other Decision Makers” (Columbia University Press, March 2013).