Any number of articles and books about “data science” (side note: the term’s a bit oxymoronic, I think) emphasize the importance of asking the right question. “If I had an hour to solve a problem, I’d spend 55 minutes thinking about the problem and five minutes thinking about solutions,” said Albert Einstein famously.1 Personally, while I’d want to get a peek at the data I had to work with a little before the 55th minute of the hour to see how close it might get me to answering the questions I’d really like to pursue, his point is well-taken. In the context of marketing and sales analytics, as elsewhere, the ultimate questions are where to shift scarce resources like dollars and people.
Most books on analytics start with a list of common questions and techniques for how to solve them. This book starts differently, by trying to understand the decision-makers who must absorb and act on your analysis. One important realization our real-world questions suggest is that the ultimate resource-related questions we describe above are rarely asked and answered by a single individual alone.
People have different ways of defining possible challenges to focus on, ways of evaluating performance, and means for assessing tradeoffs among possible solutions to challenges. So, for any decision-making process with more than one participant, Einstein’s advice should be extended to weaving these three elements into a deliberation structure that each person with a hand in the decision can connect to, even as you try to select an analytic structure most suited to the business challenge or opportunity at hand. If you can’t get senior executives who will use the fruits of the analytic labor to agree on what they want, or even how to ask for it, you are doomed.
In this chapter, we’ll explore how different executives think about these needs and suggest a synthesis that might serve as a point of departure for you. We’ll also highlight some common organizational “fault lines” that you’ll have to navigate and offer some ideas for how to recognize and address them. Then, in Part II, “Practical Analytics: Proven Techniques and Heuristics,” we’ll present analytic frameworks and techniques that can serve as candidate “common currencies” for facilitating strategic alignment across the divides we identify in this chapter.
Framing Your Focus Beyond the Answer Itself
So, first, there’s the question of where to focus your analytic attention. My former boss George Bennett, who co-founded Bain & Company and then successfully built and sold several services firms after that, used to say, “Come prepared to talk; be prepared to listen.” Consistent with his advice, the first challenge is to develop your own perspectives on possible questions and answers from multiple angles, not only for a richer set of options, but also to help you identify and compensate for your own biases. At the same time, you need to understand what questions others are asking and what solution options they might be lobbying for, as well as what logic and fact set led them to their conclusions. Then, while you can’t satisfy everyone all the time, you can provide discipline as to how priorities get set that goes beyond the individual analyses you’ve done. If people feel that the processes for deciding where and how to spend scarce resources are rigorous and fair, they’ll be better able to accept the answers. In our conversations for this book, Judah Phillips (who has built and run the digital analytics functions at Monster.com and elsewhere, and has written an excellent book on the subject called Building The Digital Analytics Organization) memorably suggested, “If information is power, then analytics is inevitably a political act,” and you have to think several moves ahead about how to influence direction and progress in the best interests of the business. (We’ll tackle this third issue more extensively in Part III, “Making Progress.”)