They say a picture’s worth a thousand words, and it can certainly be nice to present data in visual form. But on the IT and analytical side, we are sometimes skeptical of pretty pictures. We worry they can oversimplify data, mislead viewers, or prevent the kind of manipulation (i.e. sorting, filtering, and pivoting) we need to garner real business insights.
So, when should you use your data to create a visual representation of your business intelligence? I thinks it depends on two main factors:
- Who is your audience? Are you talking to other analysts, your marketing team, or executives? How much time will you have? What are their priorities? As with any presentation, this should guide how detailed your visualization is.
- Will the visualization make your data substantially clearer? Can you find a visual format that is easily comprehensible? You want the visualization to illuminate your data, rather than obscuring it. If your charts distract viewers from the important insights, causing them to fixate on red herrings, reconsider your visualization.
Because we have more data, faster processing, and more complex data sources, Business Intelligence now has access to a quantity (and quality) of data that was previously only accessible to enormous research firms—or NASA. Making sense of this data is harder than ever, and design can be a vital part of digesting and presenting data effectively. (A recent TED talk did a great job of showing just how helpful it can be.)
IT’s cultural hesitation about “just” pretty pictures is justified: how many times have we had someone draw up an elegant UI on a wireframe, but neglect to involve the technical team in discussions about feasibility and long term flexibility and support? We know that starting with the picture can run the risk of creating unrealistic expectations or ignoring technical realities. We prefer to start with data and the ability to sort, filter, pivot and manipulate it in whatever ways we need to make our analysis.
On the other hand, if I’m a Chief Marketing Officer and I can quickly illustrate—with hard data—my claim that this year’s campaigns have been more effective than last year’s, my CEO is much more likely to sign off on the budget I’m seeking for next year. A dramatically sloped line, intriguingly weighted pie chart, or clear spatial correlation can be stunningly persuasive. What if I could look at multiple campaigns and channels and overlay the impact one has when used in conjunction with another one? For instance, email and a quick follow up phone call vs. a newsletter sent out after a trade show?
If I’m a business owner, good data visualization can give me a snapshot of how my business is performing as well as helping me spot trends and trouble spots more quickly. For the techie in IT, visualization provides validation for my business intelligence initiatives by increasing understanding of them among those who operate more at the business level.
Recently I attended a Seattle Technical Start Up meeting, where Tableau Software presented their method for visualization of data about FAA accidents with various types of birds. The type of bird was represented by a colored circle which grew in size relative to the total cost of the collision with the airplane. At a glance, you could tell which type of bird caused the greatest damage and filter by time of day or type of aircraft, drilling down to the underlying source and raw data to appease their need to see the numbers.
If we can more quickly and clearly understand the vast amounts of data we all are confronted with on a daily basis and use this information to make changes in our business processes earlier on, we’re one step closer to the promised land of analytical enlightenment.
Contact me at brianh@projectlineinc.com if you would like to learn more.
