Tuesday, March 25, 2014


scip.insight March 2014
Introducing SCIP's New Website

By Karen Rothwell
Outward Insights

As competitive intelligence analysts, we strive to report the intelligence we gather in meaningful yet creative ways that will garner the attention of senior executives who can act on it. One of the challenges with reporting on complex or substantial amounts of data is how to portray it in a way that is manageable, interesting, and easy for the consumer to digest. Data visualization is becoming an increasingly popular tool for portraying and distributing complicated information in creative ways. We should consider employing data visualization techniques in the production of our intelligence findings and deliverables.

What Is Data Visualization?

Data visualization represents information with the goal of providing the reader with a clear understanding of the information contents. This information can be data, numbers, processes, concepts, relations, etc. Typically the quantity of information to be presented is dense and substantial, or the nature of the data is complex. This information can often be overwhelming if just viewed in its raw form.

Data visualization uses maps, charts, graphs, animation, and other means to represent information in a way that is easy for the reader to digest and understand. With today’s technology, data can be viewed in multiple ways and enhanced via interactive techniques, resulting in a more effective way of distributing data findings and ideally creating an engaged viewer.

Data journalist David McCandless has made a career turning complex data sets (like worldwide military spending, media buzz, Facebook status updates) into beautiful, simple diagrams that tease out previously unseen patterns and connections. Good design, he suggests, is the best way to navigate the information glut facing us all today.

According to McCandless, “The good news is there might be an easy solution to that, and that’s using our eyes more. Visualizing information, so that we can see the patterns and connections that matter and then designing that information so it makes more sense, or it tells a story, or allows us to focus only on the information that’s important. Failing that, visualized information can just look really cool”. A key takeaway for intelligence analysts is that we can use visualization tools not only to communicate complex findings in captivating ways but to help focus our internal customer on what is most important – the “so what” in our intelligence reporting.

Opportunity for Analysts

The ability to focus senior management becomes incredibly important as the intelligence community continues to seek ways to engage their internal customers. Not only is data visualization an effective medium, but by creating a distinct deliverable through visualization, it builds an inroad to hold the attention of your senior executives in a world of information overload.

In many ways, competitive intelligence teams compete with top newspapers and industry journals for the attention of senior executives. So whatever you can do to make your intelligence deliverable standout will be critical to obtain their notice and time.

Another benefit of data visualization tools is its effectiveness in developing trend analysis. The ability to use visuals to spot or “see” trends can be much more effective than a long written report explaining the same thing.

For example, the website Gapminder uses an animated data visualization capability to report on the world’s most important trends. It’s a fascinating tool that reports on global trends in a way that static graphs or statistics cannot. In their Wealth & Health of Nations graph, Gapminder shows a country-by-country comparison of how long people live and how much money they earn spread by year across a 200 year period. Click on this link to see how the worlds’ countries have developed since 1800. One just clicks the play button and the animated graphs illustrate the wealth and health of nations over that period using multiple variables in yearly snapshots.

Data Visualization Tools

Numerous data visualization tools are in the marketplace, too many to report on in this article. My intent is only to highlight these tools as a possible option for analysts seeking new and creative ways to report on data. Many tools today like Gapminder are focused on dissecting world trends in a way that makes sense for consumers of news. One does not need to be a data or research expert to interpret the findings, which makes the software that much more compelling to use.

While trend analysis might not be your sole responsibility, data visualization has potential application across other intelligence deliverables. You may want to consider investigating some of these data visualization tools that I identified on the web.


In summary, data visualization tools are another type of arsenal to keep in your analytical toolbox when you have the need to portray complex or vast quantities of data. This type of tool, which relies on animated or interactive maps, charts, and graphs represents information in a way that is easy to digest and interpret.

Particularly effective for doing trend analysis, data visualization excels in telling a story in a way that other tools cannot. Most importantly, data visualization creatively gets the attention of your internal customer and has the potential to engage them and draw them in to your analysis, an increasingly important asset in today’s world of information overload. Our work is only as good as the people that choose to act on our intelligence so you should consider any tools that help accomplish this goal.

About the Author:

Karen Rothwell is a director at Outward Insights where she works with companies to design world-class competitive intelligence programs. She previously was vice president of consulting at Fuld and Company, and project manager at Accenture. Karen holds an MBA from Suffolk University and received her BA in Marketing from the University of Massachusetts, Amherst. She can be reached at krothwell@outwardinsights.com.

This article originally appeared in Competitive Intelligence Magazine, Vol. 14, No. 3,
July-September 2011.

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