Storytelling with Your Business Data


We are in the era that data experts are calling Age of Big Data. In fact, we have been for several years now. The data craze has driven us to a widespread state of what we like to call “Analysis Paralysis.” It’s that point where you collect every piece of information that is, will be, or may become important. And for most business owners, that means you’re now sitting on an enormous pile of data without any real insight.

That is not business intelligence.

As a business leader, you’re challenged with interpreting what your data is really saying. Crafting that message and molding it to be useful to the business decision-making process is key. But getting there can be frustrating and overwhelming.

To simplify, we’re breaking down the basics of data storytelling. Or, the art of crafting an impactful narrative for you, your team, and your entire organization.

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An analytic data story is an ever-evolving narrative that’s actively explored and questions to drive decisions. We use data stories to communicate what the data is trying to say. Because, well – data by itself can’t always get the job done.

As Gartner explains:

Data Story = Visualization + Narrative + Context

To build a compelling data story, you need a strong narrative told through useful visuals that operates within the context of your business goals and objectives. This is how to find value in your data.

The visual graphics are what most think of when they think of data analytics. But it’s only one chapter of the story. Without a narrative – or a “plot” – and context that frames it within the scope of your business goals and audience, your visuals are just pretty graphics.

  • Context addresses who you are speaking to, what do they need to know about the data set you are exploring, and why does it matter to them.
  • Narrative creates the journey your audience will embark with all the twists and turns along the way.

Explanatory or Exploratory Data Analytics

First, you can’t just jump right to picking the visualization type. Stop and think about what you’re trying to say, solve, or explore. Ask yourself:

  • Is this data explaining an idea or topic?
  • Or is this data exploring an idea or topic?

Cole Nussbaumer Knaflic differentiates between explanatory and exploratory analytics by understanding what you want to do with the information.

  • Explanatory analytic addresses a specific, defined topic. For example, sales by region.
  • Exploratory analytics allows for learning or discovery. For example, examining why sales in a particular region are declining.

When you have defined your goal, you can then dive into the context of your data story.

  • Who is your audience? Is it the first time they’ve seen this data? How much detail do they need?
  • What do you want them to know or do? Is there an action step?
  • What is the environment? Is this a small team dashboard, or is this a boardroom presentation?

Your response to these questions will define the narrative you need to write. This is where the data comes in to build your story.

Giving Meaning to Your Data

What are you really trying to say?

Your narrative is what makes your data story captivating. Without it, your analytics lack meaning. It is your “so what?” factor. And while this may sound simple enough, it can actually take a few tries to get it down. Try running through your data story with a colleague or friend who is unfamiliar with the topic. Your goal is to have them fully understand your “so what?” in 3 minutes or less.

Bring it all Together

When you have your story-line firmed, you can move on to the creative side. Now the visualization comes into play. What type of graphic will best tell your story? How can you clearly communicate your “so what?” message?

A valuable data story is the combination of a strong narrative, visuals, and context woven together into something meaningful for your audience. You create the plot, the data may give you a few twists in the process, but you ultimately craft a compelling story with your business’s data.

❯❯❯Ready to kick-start your data analytics journey? This five-step worksheet will help you get on track.


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