Power BI vs Tableau vs QlikView
June 19th, 2019
Has this ever happened to you? You’ve spent a great amount of time and effort on a detailed data analysis, and are asked to present to the C-suite, marketing team, or other non-tech group at your company. The findings, you’re convinced, are quite interesting, and should be self-evident, you think. You launch into the numbers and graphs, only to look up and see blank or confused expressions on the faces before you. How could this happen?
Stereotypes would tell us that data-oriented people can’t communicate with non-IT literate people, and that those who don’t work with data every day can’t understand its impact. We don’t believe either of these to be true, of course. But we do believe there are ways to facilitate understanding between the two groups. Essentially, it’s a matter of framing your findings into a narrative – in other words, you have to tell a story.
To give an example, I recently sat in on a meeting in which a data analyst was presenting the result of a 3-month project. He had identified a whole host of valuable data, such as characteristics of the most profitable customer segments, and had built a lapsing customer model to help customer services intervene and retain customers at risk of leaving. He walked the MD and Marketing Director through a 38-page PowerPoint that contained some powerful data insights, but as he moved through graph after graph, explaining methodologies and testing procedures, I could see he’d lost his audience. His focus on numbers and process simply weren’t relevant to the group he was addressing. He had no story.
In order to establish a framework for a narrative, you’ll need to answer the following questions before preparing your presentation:
WHO: Who is your audience? What are their objectives?
Knowing who you’re talking to, and what their goals are, is a critical step toward targeting your message. The Marketing Director has different worldview and set of goals than, for instance, an IT project implementation manager.
WHY: What prompted your data analysis?
In the above story, the company was in jeopardy of losing valuable clients, but limited resources demanded identifying which customer group to focus on. There was a specific study of a business problem in that example, but perhaps your study is a planning-oriented one that uses predictive analytics to anticipate and avoid an issue that hasn’t happened yet. Whatever the reason, it’s important to establish why you’re presenting the data.
HOW: How is the audience meant to react to the findings? What action or outcome is desired as a result?
Marketers have a term in their presentations: ‘call to action.’ It’s all well and good to present information, but you have to know what it is you want people to do with that information. While maybe it’s not in your remit to provide a specific solution, the results of your data can act as the catalyst for further action from others.
Thinking of it in terms of a narrative, remember that every good story has a beginning, a middle and an end. Really spend some time thinking about what message you want your listeners to take away, rather than getting overly involved in describing methodologies. This isn’t to say that rigorous testing and ensuring your data is robust isn’t critical – of course it is. But this is information that is perhaps better found in the appendix to the presentation, rather than as the lead story. So many data presentations, reports, or executive dashboards fail to have an impact because – as odd as this may sound – they are too much about the data. When you’ve expended so much on the collection, reporting and analysis of data insights it’s natural to want to make that the focus, but the reality is, analysis must be put to a strategic purpose – and the clearer you can make your point to the strategic teams, the better.
Visualising information can be enormously helpful to an audience of non-IT people. Presenting data in a clear, readable, eye-catching format is going to go a long way toward getting your point across. Pick one primary point to make per slide or dashboard. Keep graphs simple and clear, avoid cluttering with extraneous information, and don’t overlook the impact of graphic elements such as fonts and colours, strong headlines, or the use of icons.
After you’ve invested so much time in conducting the analysis, it’s worth spending a bit longer optimising your presentation. Remember: the purpose of your efforts is to provoke discussion and, ultimately action – so think about the story you want to tell, and how to make that story come across loud and clear.
It’s your turn. What are your best methods for taking complicated data and simplifying it? Is there an ideal visualisation strategy for shifting the focus from the data to the next action step? What steps can analysts and non-IT teams take to improve communications? Please share your thoughts below.