Excutio ergo sum: “I analyze, therefore I am." This is what René Descartes might have said if he’d been a 21st century data scientist.
At a recent West Coast conference for leaders of analytic functions, the cocktail party conversations revealed an interesting pattern. “What are you working on?” “Well, we’re building predictive models for personalization.” Or, “We’re implementing text analytics.” The common denominator in these conversations more than 80 percent of the time was a focus on the work--the analysis, the tool.
Missing from most of the interactions was a sense of context. By this I mean a clear statement of the why behind the work, references to factors aiding or inhibiting progress, and a sense of pace. In many cases, the topics being discussed were expressed as projects to be executed, rather than inquiries to be explored and experimented on. I’d hear, “We’ve got our machine learning platform up now, and we’re training it,” rather than, “We really needed to improve our conversion rate, so we’ve been exploring better ways to target offers to customers who visit us.”
These omissions highlight a typical gap. On the one side, senior executives expect their analytics teams to be active navigators who will scan external factors and the firm’s performance and suggest and pursue high-stakes, high-uncertainty issues to explore further. On the other, frequently passive analysts are often, in reality, looking for direction on problems to tackle. They are often criticized as being order-takers.
Good analysis requires intense focus, and good analysts often are introverts who can marshal the necessary concentration. The disadvantage of this personality is an inability to “open the aperture” for inquiry and to actively engage line managers and executives in a back-and-forth about what issues need to be explored, to what degree, in what order. This isn’t just the case for newer analysts or specialists. Don’t assume because the analyst group is well-managed operationally--the trains run on time, on budget--that it’s led by a navigator.
In the research for my recent book, “Marketing and Sales Analytics,” conversations with senior executives at 15 leading brands suggested a higher bar and a different orientation. Most of these leaders were C-level, and the few who were not were senior analytic function leaders, and they had observed or experienced a failure of the “if you build it, they will come” approach to getting value from analytics. It was when they began to pay attention to several ecosystemic conditions for analytic success that their returns began to roll in. What were these conditions, and how did these leaders work them in their favor?
The synthesis of our discussions suggested four factors:
1. Strategic alignment: This is the degree to which senior teams--C-level--could work together effectively to agree on what questions were worth asking. This is often hindered by exposure to different data, different world views executives may have, and the lack of adherence to unifying frameworks and processes for their analytic cannons.
2. Access to data: In many cases, data platform architectures and implementations were disconnected from the specific questions and opportunities they were intended to serve. This was especially the case when organizational lines--analysts in the business, data architecture in IT--came between them. This meant, effectively, that it often took a long time to provide the wrong data.
3. Operational flexibility: Good analysis is tightly integrated with--in fact, defined by--experiments to test and validate insights. But when analysts are in one pool and operators are in another, or when operating platforms evolve at a different pace than the analytical output that informs them, this crucial link can break.
4. Shared perspective: In the organizations that had made the most progress, the line between analysts and operators was a blurry one. In fact, in the domains I examined, “analytic marketer” would be a better description.
Many leaders of analytic functions have come up the ranks as career analysts who understand their craft deeply, and of course have become competent managers as well. But they don’t typically have the experience or the organizational clout to advance the improvement of these conditions. So it falls to senior C-level functional leaders of each major domain where analytics are to be leveraged.
Here are some techniques applied by executives to successfully manage their organization’s analytic efforts:
• Adopt common denominator strategic frameworks: First, to drive strategic alignment and shared perspective, adopt simple common denominator strategic frameworks to organize performance scanning and to facilitate communications and discussions about where opportunities might lie and how far they should be pursued to support decisions. For example, Rob Schmults, vice president of ecommerce at the women’s fashion retailer Talbots, notes that digital channel executives frequently emphasize features and infrastructure development as the focus for progress, while store channel leaders are more focused on optimizing ongoing operations. Identifying and bridging these perspectives greatly improves the speed and execution of mutually relevant opportunities.
• Take an iterative approach to data platforms: Second, to address data access and operational flexibility, evolve an iterative approach to specifying and implementing operating and data platforms that emphasizes regular usage and results to define and pay for subsequent phases. At Lenovo, as director of corporate strategy Mo Chaara describes, analytic teams engage directly with available data in the early stages of tackling opportunities and experiment with actions based on their insights before committing to major platform investments.
• Uncover inhibiting organizational boundaries: Third--and in that order--look hard at where organizational boundaries are inhibiting the development of these conditions and either re-draw the lines or work across them.
Rotations with co-location offer one approach. David Norton, former CMO at Harrah’s, kept the centralized analytic capability he developed honest through six-month field assignments for new analysts, with shared reporting to him and managers of local properties.
Analytics and the analysts who pursue them are a powerful resource for any firm. Harnessed properly, with the right engagement and attention to conditions for success, this potential can be harvested for its maximum value. In the best shops, the saying thus might be Equidem ergo sum: “I achieve, therefore I am."