Organizations wanting their decision-makers to base actions on numbers, rather than hunches, better paint them pictures.
Data visualizations – visual renderings of data sets - have changed the way information is communicated in corporate contexts for good. The products of necessity in a time-poor, information-rich age, visualizations take the hard work out of interpreting dense data. They’re picking out the critical information and putting it in front of the audience’s eyes.
Visualizations are often very striking to look at, but this style needs to come with substance. Let’s face it: Poor presentation can ruin the best data. Because audiences may actually miss the vital insights, regardless of how much an organization has spent on analytics solutions to get to the bottom of the data.
Data visualization can fix that: Helping turn big data into clear insights.
The rise of the data visualization follows what businesses have labeled the consumerization of IT. Employees expect to have the same technology experience at work that they get at (their digital) home – which is a much more intuitive way of consuming the services that are enabled by technology. There are countless examples of this, from applications that give an at-a-glance view of your sleeping patterns, or let people order and watch their taxicab’s approach in real time on their smartphone. Little wonder executives are increasingly asking why they can’t get a similar experience at work.
Visualizations are great for communicating large amounts of data. Almost always, they offer a much more efficient way to tell a story about numbers, rather than talking about the numbers themselves.
But the benefits go further than clear and compelling communication. Visualizations can also help in getting to decisions faster and more efficiently, just as road signs pass along critical information to drivers in an instant.
One practical example comes from a British water utility company, which is using visualization to bring operational data to life – from data involving metering and water flows, to pump efficiency and leaks. This information was previously shared as long, data-heavy tables, but it is now visualized through a Google Earth-like environment. Now, engineers can easily see where a problem is emerging, and plan the best strategy and equipment in advance to best cope with the particularities of the leak.
The word on what visualization can do for a business has gotten around. Firms of all kinds, from real estate companies to banks, to retailers, are now using visualization to better identify and display operational trends. Many of these enterprises have followed some basic principles to guide their first steps towards becoming more visual. I’ve summed them up into the following five quick ideas.
Get agile: Select one area of data to focus on, build a prototype to get business buy-in and prove the technical solution. Then adapt the solution to reflect user feedback and scaling to more areas of data. If you’re in IT, a good place to start is your own department: Visualization is a powerful way to improve communication between IT and the rest of the business.
Put yourself in the user’s shoes: The UX (user experience) is critical. As we know from the consumer arena, the look and feel and navigability of any application is fundamental to user adoption: If people can’t get a tool to do what they need straight off they will throw it away. By involving graphic designers and UX experts at the start of a visualization project you can vastly increase your chances of getting this critical aspect right.
Know your data: Visualization is about getting optimal benefit from the data an organization already has available; it’s not necessary to seek out new data. A successful project will also need to blend together functional understanding of the data area (how best to link cause and effect in the data) and technical expertise (how to source and integrate multiple datasets).
DIY or buy: Today, most organizations are choosing to buy visualization technologies because solutions vendors have on offer have matured and ongoing support is an important consideration.
Plan for talent: Looking ahead, consider how growing analytics adoption is putting data visualization talent at a premium. To make sure you’ve got the right talent on tap, explore your options – Do you have the right talent today? Will it support tomorrow’s need? Should you build an internal capability?