In honor of Malcolm Gladwell, author and keynote speaker that this year’s Microsoft Business Application Summit, Corey and I have decided to write a series of blog posts tying Mr. Gladwell’s books to familiar concepts from our day-to-day work. This post is based on The Tipping Point, a book that explores the reasons why some ideas and trends spread epidemically and have massive influences on our daily lives. Given the growing demand for data visualization platforms and employees with data presentation skills, it is clear that there has been a Tipping Point in the corporate world with regards to how companies consume their data. But what about your company? My guess is that if you’re reading this post, you don’t need to be convinced to consume your data in visual, interactive dashboards instead of static, bloated spreadsheets, but you might need help convincing your business users to use these new tools.
Getting business users to adopt data visualization tools like Power BI can be extremely challenging. Oftentimes, these users don’t have a technical background. They are used to seeing spreadsheets and talking points in their inboxes on a regular schedule. This familiarity is the biggest obstacle to adoption. Luckily, you can use The Three Rules of Epidemics described in The Tipping Point – The Stickiness Factor, The Law of the Few (Salesmen, Mavens, & Connectors), and The Power of Context – to overcome this familiarity and drive more users to your dashboards. This post focuses on The Stickiness Factor and describes tips you can use to design memorable dashboards for your audience
The Stickiness Factor states that there are small changes that you can make to the structure and presentation of your message that will make it more memorable. Two of the best opportunities to make your dashboard stickier are 1) properly identifying your audience so that you can cater to their specific data needs and 2) choosing the right visualizations for your analysis.
Whenever you start developing a dashboard, the first and arguably most important step is to identify your primary audience. Who are you designing the dashboard for? Executives? Managers? Analysts? Field sellers? Each of these groups focus on different aspects of the business and need to see results at different levels of granularity. A dashboard showcasing transaction level data might be of huge help to a field seller or analyst, but it probably won’t be of much use for an executive. Properly identifying your audience helps you determine the granularity of data that you need to query.
Once you have identified your audience, you need to know what questions they typically ask about this data. Though the original requestor usually has a pretty good idea of what the audience is looking for, I’ve found that the best way to identify these questions is to ask some of the audience members directly. What metrics are they interested in? What breakdowns would they like to see? What fields would they like to filter their results by? Are they looking for results by day, week, month, or year? You’ll probably get some different responses from each of these users, but pay attention to any recurring questions. If you can adjust your approach to account for these recurring questions, then your dashboard will likely be much more successful. Providing too much or too little detail can be enough to turn users off, so make sure that your understanding of what these users are looking for is as complete as possible.
Just having the data to answer your audience’s questions isn’t enough to make a dashboard sticky. You could dump the data into a crosstab, but that would defeat the purpose of making a dashboard in the first place. That data needs to be displayed so that it answers your audience’s questions as quickly and effectively as possible, and that means choosing the right visualizations for your analysis.
Selecting appropriate data visualizations can be tricky (especially since Power BI and Tableau offer so many default options), but this is where knowing your audience can come in handy. Though most users are used to consuming data in spreadsheets, they are probably familiar with bar graphs, line graphs, maps, scatterplots, and pie charts. These chart types also allow you to display most typically requested business information (Ex. Sales by Category, Sales by Month, Sales by State, Sales vs. Profit by Item, etc.), and knowing that your audience is familiar with these charts makes them great choices for visualizing your data. The more familiar the audience is with a chart type, the less you have to explain it, and vice versa. You might find another chart type that answers the audience’s questions more effectively, such as a waterfall chart or a Gantt chart, but if it requires too much explanation, you’re probably better off sticking with the familiar chart types. I’d recommend sticking with bar graphs, line graphs, maps, scatterplots, pie charts, and tables for your initial dashboards and then maybe adding more advanced visualizations as your audience gets more comfortable with dashboards in general.
Properly identifying your audience, catering to their data concerns, and choosing appropriate visualizations are crucial to making your dashboards stick. Users are looking to get their data questions answered as soon as possible, and you can get them those answers if you do your due diligence with gathering requirements and dashboard design. Your dashboards may have the information that they’re looking for, but if they get distracted by a new chart or have to work too hard to find their answers, they’ll lose interest and start clamoring for the old spreadsheets. Use that knowledge to your advantage. Give them the answers they’re looking for in a new yet familiar picture that pops off the screen. And sticks in their brains.
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