“I see dumb people, walking around like regular people. They don’t even know that they’re dumb, and they all work here.”
Have you ever felt this exasperation in the office? If so, you are not alone. As a ZS consultant often working to give research and analytics a seat at the table, I’ve heard this grievance from my clients many times—particularly from research and analytics leaders, some with Ph.Ds, who say that their insights are not being acted on. In the quote above, one of my clients, in particular, has taken a few liberties with a quote from the movie The Sixth Sense to capture his vexation.
For analytics professionals who wish to make an impact, the feeling that their hard work is going to waste can be incredibly frustrating, but don’t throw in the towel just yet. Just like in the scientific method, the first step is to perform the correct research to construct a reasonable hypothesis on why you aren’t making an impact, and to identify all of the variables—both controllable and uncontrollable—that may be precluding positive change. In this case, there are four variables that likely are impeding companies’ ability to make the insights from their analytics efforts actionable:
1. The company’s purpose and where you fit in: Many scientists and engineers go into the business world because they want to have an impact through their products and services. This means working in an organization—a pooling of talent and resources to create something that cannot be achieved individually. It includes not just engineers, but executives and functional leaders in areas like strategy, marketing, sales and finance.
Within this organizational structure, you should assess where you stand, as well as your knowledge of how your work aligns to broader business objectives. To start with, what has your company promised its shareholders, both short-term and long-term? What about its customers? Do you know what the market is saying about your company this quarter? How should the executives balance long-term and short-term gains to meet those promises? This will give you a starting point for understanding the company’s priorities.
Now where do you fit in? More often than not, analytics and research are not the queen, but the “humble handmaiden.” The goal is not to provide analysis for analysis’ sake, but to inform decisions before the question becomes moot. Or even better, to frame the question before it’s even asked—for example, providing actionable insights to the executives before a major milestone in the product development process. This involves understanding what parameters will go into the decisions, tying your findings to those parameters and resisting the temptation to give extraneous information. If your analysis isn’t serving these business needs, then there’s a good chance that people aren’t taking you seriously, no matter how high your R-squared.
2. Correct sequencing: Given what you are asked to do, are you being looped in at the right time to make impactful recommendations? A mismatch is very possible. For instance, I have seen companies ask their research departments for quality testing on a product that was already announced to the shareholders and, thus, they were unreceptive to anything but good news. If there is a mismatch of this kind, you are the person best positioned to identify it, explain the situation and ask to be brought in earlier.
3. Your stakeholders’ biases: Unfortunately, a handful of lazy analyses have given analytics a bad rep in the business world. It’s a sad fact of life. From books like How to Lie With Statistics to the rating models’ contribution to the 2008 financial crisis, decision makers are constantly reminded to never trust numbers alone.
Researchers’ reputations aren’t much better. Since researchers, who often come from academia, rarely analyze their role in the organization, they are often perceived as the “crazy Ph.D.s” who always push for additional complexity with no thought given to cost, product schedule or value add for customers. Analysts can be just as guilty of this, pushing for precision when speed may be more important. Having 80% confidence is often enough in sales and marketing, for instance. Anything more and the value from the additional accuracy is trumped by the opportunity lost in the time performing the extra analysis.
Ask around: How do internal customers perceive your department and analytics in general? Do they view it as unintelligible because no one explains it to them in terms that they can understand? Do they feel useless because they never get answers in time to make decisions? Uncovering these biases and your company’s former “nightmare analytics experiences” will let you know what you’re up against in convincing stakeholders to adopt a certain action.
4. Your communication effectiveness: For your message to sink in, you need to be persuasive. Most engineers believe that the analysis—the logic alone—is enough, but as Aristotle teaches, persuasion needs to happen not only through logos (facts), but also ethos (the persuader’s authority) and pathos (appealing to what the audience cares about).
Ask people you have a good relationship with, both inside your department and outside of it, for candid feedback on how you come across. First of all, do they understand your reasoning? Many people won’t have your technical background, so you might need to frame your findings in different terms. Second, do you have the “street cred” to make these recommendations—tenure, experience, loyalty, or however else your company defines credibility—and do people view you as a reliable source? Lastly, do your findings have a “So what?” component that your stakeholders care about? Is it something that will impact their personal performance to such an extent that they have no choice but to adopt your recommendations?
This four-dimensional analysis will help you identify the possible variables—both controllable and uncontrollable—for why you aren’t being heard. This is your starting point towards a plan to remedy the situation.
What should you do next? Stay tuned for my next post.
Ekaterina Mamyshev is a consultant in ZS’s Boston office. She has advised companies on improving their sales and marketing processes by applying both an analytical and business lens to find solutions. Ekaterina earned her MBA at Harvard Business School and holds a bachelor’s degree in operations research and financial engineering from Princeton University.