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Iliinsky’s 4 pillars of effective “data visualization”—for risk, claims and safety managers

effective_data_visualization_for_risk,_claims_and_safety_managersLast month, I led a webinar for Aon eSolutions clients on the topic of “Effective Reporting and Visualization.” The webinar was part of the Third Thursday Client Webinar Series, which is an informational, education-oriented monthly virtual presentation focusing on a topic of importance to our clients in the fields of risk management, claims administration and safety management. 

In recent months, I’ve spent a lot of time researching the theory and practice of effective data visualization, which was a big part of last month’s webinar. In this blog post, I’d like to give an overview of what effective data visualization can mean for risk, claims and safety managers. 

A buzzworthy buzzword?

Data visualization is a buzzword you may have come across already, or it may be entirely new to you. It’s an area of study that’s really taking off. Colleges and universities are granting degrees in visualization. There are people whose whole job revolves just around visualization. 

It’s a very exciting topic, because when you think about the number of data points we have coming at us, whether it’s on our phones or tablet devices or laptops, we’re all inundated with information demanding our attention.

Visualization is a tool to help make that data more meaningful and to help take advantage of the fact that, as consumers of information, we are often absorbing information without even being aware of it. The practice of effective visualization can help us better grasp that information we process at a subconscious level. 

To visualize effectively, first follow the story

So what, exactly, does effective data visualization have to offer risk, claims and safety managers? It all comes back to reporting, which is, of course, a central, vital responsibility for anyone in those roles. By understanding and practicing effective visualization, anyone who reports up, down or across an organization can become better at reporting. Risk Mapping in Action

Before going any further, we need to consider another concept that’s integral to effective, visualization-based reporting: that is, the concept of storytelling. 

For our purposes, a story and a report are practically synonymous.

With a report, you’re trying to influence your audience to take a certain action or actions, adopt a new perspective on something, and/or consider the facts at issue in a different way. Effective visualization is founded on the principle that we comprehend ideas and information better when they’re presented to us as stories.

Now, by story, I don’t mean a novel, a short story or a children’s book; however, each of those forms are instructive in the sense that they rely on certain structures and conventions that resonate with us as readers. 

Just as an author of fiction thinks constantly of the reader and how to engage her or him, we as creators of reports should always be thinking about how to engage the people we’re trying to reach, whether inside or outside our organizations. Fortunately, it’s much easier to become an effective practitioner of data visualization in your routine reporting than it is to become an accomplished novelist or writer. 

Noah Iliinsky’s four pillars of visualization

A great place to start on the road to effective visualization is by considering the following four pillars of effective visualization. IBM's Noah Iliinsky, one of the leading figures in the visualization movement, has developed these pillars, which I find to be of great use in conceiving and executing on reports of all kinds. 

It can be challenging to rethink existing reports or initiate new ones. By following Iliinsky’s pillars as a sort of sequential, process-oriented approach to visualization, it can be much easier to produce the kinds of reports that truly motivate your audience to take the action you want them to or begin seeing the facts in a new light. 

  1. Purpose: According to Iliinsky, you have to know what you’re trying to communicate before you can select the right data points to support your proposition. 

    In my experience working with clients, I know that it’s often not easy to figure out what it is that they want to convey. To take a risk management example, a client may be used to sending out the same metrics month after month, simply because that’s what’s always been done or because that’s the risk management “standard.” 

    This is where it can help to take a step back and realign the data points in your reports with your team’s overall goals. To continue the risk management example, if one of your team’s goals is to drive down the number of incidents, then you should select data points that illustrate the causes and rates of incidents. 

    Bottom line: You must be able to articulate your purpose in order to have successful, visualization-oriented reporting. 

  2. Content: Once you know what you’re trying to communicate, it becomes easier to select the data points—or content—that support your purpose. Select only the content that supports the message you’re trying to deliver; exclude the rest. The more information your audience has to go through to grasp your message, the less likely it is that your message will be received. 

  3. StructureOnce you can articulate your purpose and you know what content supports that articulation, then the structure of that data becomes easier to conceive.

    According to Iliinsky, structure is the physical layout of your visualization. Elements of the structure can include a line graph, scatterplot, map or entity-relationship diagram.

  4. FormattingAccording to Iliinsky, formatting is akin to the paint the covers a house, whereas the purpose is like the foundation. Format refers to things like labels, fonts, highlighting and colors, but it goes beyond the vague concept of look and feel. By making what is most important most visible, you can improve the effectiveness of your reporting. 
In this blog post, I’ve only scratched the surface of the exciting, exploding practice of data visualization. For more information on this topic, I encourage you to check out these resources from Noah Iliinsky here, here and here

 

 

RMIS Guide

Dec 5, 2013

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