We’ve all had projects we were excited to start. I remember an assignment to do a profile analysis on our millennial customers with the goal of comparing sales and churn to our overall base. My gears were clicking on all cylinders! I would compare sales by geographical markets, household income, and the number of phone lines on their account. I had my tableau worksheet all fired up with line graphs and scatter plots and felt I was ready to provide an update to the Marketing team. As I began showing off all of my different data cuts, I could tell I was losing my audience. It was the usual symptoms: long periods of silence, glazed over eyes, and then, “This looks great! Can we just get one slide with a graph that is showing the overall sales trend for the past two years?” Of course, I nodded and sighed inwardly thinking, “Why didn’t you just ask for that in the first place?”
I recently started assisting storytelling with data class in the hope to impart this lesson and many more to my students. Balancing data analysis, high-level value proposition and a good story is an invaluable skill. An effective narrative should link findings and visuals to solve business problems while maintaining the audience’s interest. Data story curation is an art and even after putting together countless PowerPoint decks, creating dashboards, and delivering presentations, there are always lessons to learn.
The three lessons that I’ve come to learn when telling a concise story is:
1. Know your audience – Will you be discussing an analysis with your analytics team or presenting a business read out to your senior management? The matter of who you’re speaking to will influence every detail of how you choose to craft your story. Also, think about the relationship you have with your audience. Is this the first encounter you’ve had with your audience or is there an established relationship? The more specific you can be about who your audience is, the better position you will be in for successful communication.
2. Know your goals – In business, we’re usually given a problem to solve for or a benchmark to compare and measure the performance of an initiative. The problem may not be easy to solve and can be compared to looking for a needle in a haystack. Sometimes you’re looking for multiple needles! Before you begin diving into the haystack, understand that there is a difference between exploratory and explanatory analysis.
i. Exploratory analysis is what you do to understand the data and figure out what might be noteworthy or interesting to highlight to others. So you may spend days or weeks going through stacks of hay to find two needles.
ii. Explanatory analysis is when we’re at the point of communicating our analysis to our audience. This is where we are talking about the needles we were able to extract from the hay!
When presenting your work, your audience should be led through an explanatory analysis. This is where you’re using your findings to answer the business problem and support your reasoning and approach to the solution. It can be very tempting to want to show and tell the audience all of the heavy lifting diving into the haystack was and the splinters you had to pull out while searching for needles but time is better served for everyone focusing on the findings and how it answers the problem at hand.
3. Know your analysis – Typically, findings and results are communicated through a presentation that may include PowerPoint, a dashboard, or a memo. When presenting, it is unnecessary to bring your audience through the haystack; however, exploratory analysis is the bedrock (and/or “foundation”) and should be rigorously documented. You can (and will) be asked multiple times about your findings after the initial presentation. Having your notes to refer to prepares you for the various downstream communications to come.
Putting it all together
When preparing your presentation the goal is to have a clear and concise story. A good story has a beginning, middle, and end. You have anticipated the information the audience is seeking and gauged the knowledge level they are coming in with. The presentation should address the business problem and walk the audience through the key findings. Here is a high-level framework that will help in telling your story:
1. Use an introduction to recall your objectives and clearly state them for your audience.
2. Provide a high-level summary of your results and key findings.
3. Take your analysis into small bits by breaking your questions into sub-parts.
4. Drive the point home in the conclusion.
Going from business objective to analysis to presentation is not always a clear path. Balancing the discussion of deep data analysis and high-level value propositions is a skill that is honed over time. Adding to the complexity is the audience, invariably a diverse crowd of colleagues with varied backgrounds and expertise. In an optimal execution and delivery, your crafted messaging will resonate at all levels and will be understood and well-received. Your presentation should foster conversation and ultimately, result in business improvement.