Geometrx big data“Everyone in our business knows they need to visualize data, but it’s easy to do poorly.  We invest in it.  We’re excited if we can use it right while they use it wrong.”  – Daryl Morey, GM, Houston Rockets

In the 1990s, charting tools became cheap enough to acquire that it was accessible in mainstream business. The tools to make a pie chart were so easy to use that anybody could do it.  We forget today but back then, it was something new to be able to create a bar chart, make it 3D, change colors, etc.   The visual output was quick, but there wasn’t a lot of thought about what that chart meant.

Today, we have powerful tools to store data, manipulate the data in real-time, and create useful output. You can create hundreds of charts in seconds.  However, just because you can create a chart, doesn’t mean you should or that it will be useful.

A good graph communicates information effectively and efficiently in the context it is presented, so people don’t have to work to see and understand exactly what you are trying to portray, nor are they confused.

A TreeMap on a dashboard contains all the data collected but isn’t easy to quickly digest.  Ultimately, most people just want to know “where is my score” and “how am I doing against other people?”  Mapping the data in a useful way more effectively communicates the answers at a glance.  Think through what you want someone to take away from the map and then try to present that visually.

When companies start to invest in data visualization, they think all the tools are available on the market, it’s easy to do, we can just hire some people, and they can begin creating.  Unfortunately, not all employees can think through the challenges needed to present good data visualization for effective communication.

Big data has been talked about in all industries for several years.  Companies have the data, invested in software, and hired data scientists but the results still seem elusive and out of range.  The dashboard is nice, but executives struggle to have a clear understanding what’s happening within the business.

Executives are looking for a design thinking, data wrangling, subject expert who not only knows how to manipulate (i.e. clean and analyze) big data but also understands the software, then takes meaning from the data and present it in a meaningful way.   That’s a lot to ask of any one person.

The data scientist has all this information to show, but it’s hard to get meaning out of too much data poorly displayed.   The missing piece is the presentation layer, which is effective communication instead of what data will show.

To figure out a company’s data visualization challenges, develop a team that consists of a design thinker, a data scientist, and a subject matter expert.  Your team should be agile and sit together.

One of the first things data scientists do is set up dashboards for the bosses, so they can see all this data coming in, in real-time.  It’s pretty, has lots of information on the screen, and is changing all the time.  However, Executives are not getting the value out of the dashboards that they had hoped.  Can everything on the dashboard be edited to show only the information needed to help them make a better decision?  How can it be more usable?

Which is better: Complex or Simpler Charts?

If an audience is fluent in the subject we are talking about and fluent in the chart type we are using, then there is a little more leeway for the chart to be complex.  However, if the viewers are looking at a treemap for the first time and don’t know what it is, then a simpler design is necessary.

Storytelling with Data Visuals

Storytelling is not necessarily a narrative. Storytelling can be broken down into three steps.

  • Setup –  here is some reality
  • Conflict (doesn’t have to be negative) –  here are changes to that idea
  • Resolution –  here are the results from those changes

Almost any chart you can think of can be broken down into this storytelling structure.  In fact, multiple charts and big data sets can be broken down into this structure.  Even with simple charts, how can you set it up; what would you introduce in the visual as conflict; and then how will you show the resolution?

Look for opportunities with your charts to make them even simpler.  Maybe you have a chart that you think is simple, but can that be broken down even more into two or three more straightforward charts?  Set up a storytelling methodology where you start with the simplest thing possible and then add layers on top of it – step by step.  This progression helps with the audience’s understanding of what you are trying to convey.

You might be surprised that a somewhat simple chart can have up to 25 entry points where people might choose to focus first, and if the chart hasn’t been executed well, then you are going to have five or six individuals in the audience looking at five or six things. If you can control that flow and force them to look at one thing at a time, it helps with their understanding of what you are explaining.

Storytelling is reducing the data into a narrative flow where you are carrying the audience through the conflict and resolution in a visual way.

To learn how GeoMetrx can help your organization tell better stories with your data, request a demo today.