All businesses must make good decisions, or they won’t be in business for very long. Making good decisions requires sound data upon which to act, and to analyze for the insights that can be gained. Communicating that information to the decision-makers is ultra-important because they’re the ones who have to buy in and use the data as a foundation for their business decisions. Using data stories helps to communicate this data to those in power in a much more compelling fashion, motivating them to act on it and render sound decisions.
Data stories can be an essential component of communicating important data, so that the recipients are persuaded and motivated to use it to advantage. Having a firm grasp of data analytics is a good place to start, so those in your company charged with developing data stories should first understand the basics. A company like Learn Data Analytics can offer a comprehensive course in the subject to provide a solid foundation in data analytics. Then your employees will be ready to develop their own data stories and improve communication throughout your company.
What exactly are data stories?
Data stories are narrative-style descriptions of how data is modified over a period of time, and why those modifications occur. It often makes use of accompanying visuals to make things clear to listeners, and it helps recipients to draw keen insights from the data. In general, there are three consistent components to any good data story – data, visuals, and the narrative. The function of the data story is to put data into its proper context, and emphasize the key elements of the data so decision-makers can make best use of it.
Why data stories are so important
The bottom line on data stories is that they help listeners understand the context of the data, and that inspires and motivates them to take appropriate action. When a data analyst uses a data story, it is for the purpose of clarifying some complex data and presenting it in a digestible manner, so it is most useful for those listening. For ages now, narratives have been used by man to simplify and make sense of a very complicated world, and that is still true today. Narratives provide context, insights, and interpretation, all of which make data more meaningful and useful. Data stories make sure that data comes to life and becomes much more memorable than dry statistics that don’t really mean anything at all.
How to tell your data story
The first step is to identify the kind of story you want to tell with this data. Start by asking relevant questions and then dig into the data itself to find the answers. For instance, you should ask yourself exactly what it is you’re attempting to explain. Then consider what your goals are in preparing this data story. Approach your data with the intent of discovering a story within that accurately reflects what the data has to say. You’ll need to identify an over-arching theme for your story and develop a structure. You can do this by:
- seeking correlations – look for connections among various data points, especially for any surprising or compelling ones.
- notice any trends – trends indicate changes of direction, for example a particular product that is suddenly becoming popular. Identifying such trends can be crucial to making future business decisions.
- draw comparisons – comparisons help you to discover relationships between data.
Another key element in data storytelling is to be aware of your audience. Make sure your data story will be interesting to them, or you’ll have wasted your time. Keep in mind that your audience will be affected by their ages, demographics, positions in the company, and their areas of expertise. Customize your story for the particular audience you’re pitching to.
Now it’s time to build your narrative, and make liberal use of visuals to emphasize important points. Visuals are always more easily absorbed than dry text or speech. When building your narrative, look for some kind of hook that helps to engage your audience, keep the overall problem in mind, and offer some potential solutions to that problem.
You should always save your findings until last, rather than mentioning them right at the outset. Relating your findings should be the most exciting and compelling part of your story, so it should come at the climax. Avoid cherry-picking data or manipulating the scale of the data – all your conclusions should be drawn directly from the data, so as to provide the most accurate picture to decision-makers. Want to learn how tell a story with Data? Talk to Admissions (1-800-400-5321) or visit our website: https://learndataanalytics.ca