All businesses have the “cup runneth over” problem with data. That’s been one of the major problems in convincing the business side of the house the value of data analytics in decision-making.
As Marik Brockman and Jamie Yoder of Diamond Management & Technology Consultants wrote in a recent post, IT executives can produce spreadsheets, graphs presentations until they turn blue in the face. It appears that the amount, type and even data structure don’t matter to the business suite. It really goes back to visually presenting “immediately relevant and actionable” data.
Brockman and Yoder point out that most organizations are unable to cure this problem because they don’t have the tools and skills to present data the way the business side of the house needs to see it.
In their article, they point out some key ways the insurance and financial industry can leverage new data sources, data visualization tools and data models to create market intelligence that will make data visualization for financial services a powerful tool in market intelligence. This is encouraging for not only financial services, but also for other industries. Let’s look at some of their strategies and how data visualization can transcend the “too much data” problem.
Use natural representations to present complex data in a simple format.
Using visual formats for presenting data analytics that are “natural” to the decision makers is an easy way to begin making the move toward data-driven decisions. Brockman and Yoder use the example of maps – nearly everyone uses them so they are simple to comprehend. In their article, they use the example of how a property/casualty insurer used a map overlay data of markets and agency performance. The result was getting sales, underwriting and finance on the same page by seeing whether the challenge was the agency or the market.
Mapping sales and market performance is not a new technique, but data analytics can make the map richer and more accurate. That’s the key to the value of data analytics – relevance on the deepest level possible in the simplest presentation possible.
Tell the story of time, trends and change with visuals.
Telling the story of what happens over time is a key piece of data analytics. Seeing the change in pricing, sales closed and other historic data is good, but what’s even better is using this data to create “what if” scenarios, as Brockman and Yoder point out.
One of the easiest ways to do this is to chart the trends in a visually stimulating format. Yes, graphs are good, but putting some thought into what people “see” naturally is even better at winning buy-in to predictive analytics. Try storyboarding or using data graphics to enhance the insights you gain from analytics.
Make your analytics presentations to senior executives interactive.
Even if you have a pretty presentation packed with details for how to make a future decision, someone must tell the story. That person must be able to comprehend the data and present – a rare skill, but as Brockman and Yoder say, it can be taught through repetition.
Developing a team with the right mix of analytics acumen, data visualization and presentation skills is achievable and as predictive analytics progress, we predict you’ll see more of this team in action. See our recent post on this topic.
