ADVICE FROM THE SI-SUITE
Research Narrative’s SI-SUITE™ offers researchers & analysts advice on how to be heard and add value to organizational leadership.
A spreadsheet with no context. A 200-slide PowerPoint deck of tables and graphs. A digital dashboard featuring droves of unlabeled metrics that may or may not align with business objectives.
You’ve perhaps witnessed these things firsthand. We have, too. We affectionately refer to these types of deliverables as “data dumping.”
To an executive looking for answers to their questions, data dump deliverables are at best annoying – and at worst, cause research to get ignored altogether. Think of it this way: if you asked a friend a question, would you want them to hand you an encyclopedia and suggest you look up the answer? Probably not. So why would you give an executive a detailed interactive dashboard with no annotations, context, or organizational recommendations in response to their questions? It’s akin to handing them a digital encyclopedia.
COMBATING THE DATA DUMPING TREND
The data-dumping trend seems to be escalating, as more data becomes available and more time does not. And it leaves senior executives saddled with the unwelcome onus of sifting through countless data points to discover what the information actually means for the organization. Simply put, it leaves them frustrated.
As researchers, analysts, and data specialists, it’s our job to remedy that frustration. The key to great data analysis is not merely possessing and organizing large volumes of data, but rather, gleaning understanding of what that data means. Analysts aren’t just data architects, we’re storytellers who craft insights that have implications for business and society at large. And as we deal with larger and larger volumes of data, we need to be mindful of that end game: we don’t collect data for sport, we collect it to derive meaning and impact.
So how can we each be impactful storytellers who think and speak the language of executives? Or as we phrase it—how can we continuously “think executive” and “speak leadership” more effectively, in order to give meaning to data? We find the following five key practices to be instrumental.
THE FIVE COMMANDMENTS OF LEADERSHIP IN DATA STORYTELLING
Recently, a streaming video client shared the good news that one of their new original series was a breakout hit. As we embarked on an analysis of what was driving that success, we also binged watched the first season and discovered that their free preview offering extended through the 4th episode – after which audiences hit a paywall. Without knowing that context, we might have thought that the series was immediately driving subscriptions…or that episode 5 was a bust. And in both cases, we would have been wrong.
As analysts, it’s precisely our job is to understand the context around our data, so that we can derive the right conclusions. Get to know your business (or your client’s business) and the competitive context, so you can analyze your data in a way that is meaningful and impactful – and accurate. Likewise, take time to learn what questions your executives (or your client’s executives) are asking about their business and the competitive context. It sounds pretty basic, but if you don’t know what questions they’re asking, you’re certainly not in a strong position to answer those questions.
One of the first things we teach in our SI-SuiteTM curriculum is that a finding is not an insight. A finding is the result, the data point. An insight is what it means for the organization. Think of it in this structure:
A common complaint that we hear from executives is that their analysts show them all the results they’ve collected, without assessing what’s important for their organization.
As you review findings, ask yourself: what does this data really mean to this organization? How can this information be helpful? What impact could it have? Executives want to know how to fix the problems or leverage the opportunities that you may have unearthed during research. Don’t just present data, present answers to the questions they’re asking.
As students, we are often taught to show our work in analytical classes; “partial credit” is the mantra of math classes across the U.S. Those of us who came to the workplace through advanced education in math, engineering, or statistics had that behavior further reinforced – we were conditioned precisely not to edit ourselves.
And then we got to the workplace and received a startling reality check: very few people want to see all our awesome work anymore. Maybe we analyzed and reviewed 100 findings to get to 5 key insights. It’s tempting to show all 100 findings – look at how many findings support our insights! If you’ve ever tried to present everything you’ve learned to a time-pressed room, you know the reaction that ensues halfway through: the entire room is looking down at their cell phones, not listening.
The professional world isn’t math class, and speaking leadership requires breaking the “show our work” habit and learning to show just enough of our work to gain trust without losing the attention of our audience. Even when a senior-level audience is interested in the mechanics under the hood, they generally don’t have time to listen to it all.
A key leadership skill in data storytelling is learning to edit yourself and convey what is important to the audience and tempering the instinct to show everything that is interesting to you. You’re not there to prove your intelligence, but rather, to convey organizational insight.
A useful tactic in this endeavor is to test-run your insights on someone from a different team. Learn what they think is boring or too “in the weeds.” If a finding isn’t meaningful or doesn’t help answer any pertinent business questions, it shouldn’t make the final edit in your data story. Or as we like to say, “put it in the appendix.”
Be careful not to confuse editing with oversimplifying. We can’t tell you how often we’ve heard an analyst say, “I had to dumb it down” for an executive. We cringe every time. There’s a reason that an executive made it to the top, and generally speaking, it’s not because they’re stupid or ignorant. It’s important to edit yourself because their time is valuable, not because they’re too dumb to understand the underlying details.
Being condescending is a great way to communicate that your ego gets in the way of offering insight. And that can give the impression that you’re not adding value – even when you are. So stay humble, fellow analysts. The goal isn’t to water down your insights, it’s to communicate them succinctly.
It’s wonderful to always be right. It’s also a bit impractical.
When it comes to conveying data-driven insights, develop a point of view and share your insights with confidence. And then remain open to further discussion about those insights. Insights don’t just come from analyzing and sharing; they also come from listening.
We want to emphasize the word “sharing.” One of the core challenges of the above-mentioned “data dump” deliverables is that they are often fundamentally delivered as one-way communication. A digital dashboard, for example, is typically built to be read. It doesn’t inherently invite dialogue to discuss and enhance insights.
That two-way dialogue is critical; it offers executives an opportunity to share new information that helps evolve and advance the final insights. And that’s not only ok, that’s ideal. Collaboration is how great business insights are often built.
READY FOR LEADERSHIP
So put those encyclopedic dashboards and epic PowerPoint decks aside, and think about what does this data mean, and how can I best communicate that? Without a proper understanding of the business context and leadership perspective, recommendations run the risk of being meaningless, and even costly to executives. Get to know their (or your) business, so you can help senior management come to a resolution that is meaningful and impactful. Delivering insights and meaning is, after all, our entire purpose.
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