Data Storytelling: Do it properly or don’t do it at all!
Most evenings I will read a chapter of a book to my daughter, and the pages will convey images of the characters, and the words will convey the story that unfolds over time. However, it is my expression and ability to bring the story to life through my voice, that really gets my daughter to listen and understand the narrative. Often along the way she will ask me questions about why something happened, or the meaning of a word, or the depth of the characters. Sometimes, I will put on different accents so that she can really immerse herself into the time, location and culture. We are currently reading a book which dates back to life in the 1800s, so everything is peculiar.
So, what is storytelling? My definition: storytelling is the ability to invoke from words or images – new ideas, thoughts, meaning, and take some action to understand the context / situation.
In the same vein, companies have a story to tell, through the information they gather from the various systems they implement. These systems come by many names such as: CRM, ERP, marketing, sales, product, social etc. The data that is generated individually in these systems tells a story about a transaction, or a person, or a product and so on. The stories individually don’t mean much until they are blended together to create a more powerful story, such as blending information for customers, transactions and marketing campaigns. This provides companies with the narrative of how marketing campaigns have changed over time, where there has been more success and why. Decisions that need to be taken where perhaps the campaign isn’t doing to so well, and what needs to change. Data storytelling isn’t about a data point, it’s about bringing the customers or products to life that matter to the business.
Data visualisations engage people by telling them the story that is key to their roles. It delivers targeted insights into their world, engages them to explore the information, ask questions that embrace the narrative, and then get them to make a decision that can be tested through generating further insights.
Just as the stories I may read to my daughter, data stories that companies should be generating explore changes in the data that have occurred over time, providing the narrative that piques the interest and leads to action. Most companies still struggle with the telling of data stories mainly down to the fact that their data stories only explore data at one point in time.
The objectives of any good story are to engage the reader, ask them to explore the situation, ask questions, and lead them to a decision based on critical thinking.
So, if you are struggling, how do you start to create data stories in your business? Here are some tips from the data visualisation team at datazuum. Here goes:
- Uncover the narrative: Yes, we all want facts from the data that will allow us to make the right decision. Data visualisations need to find the hook that can pique the interest of the viewer. Remember as a developer / designer you are telling a story based on a set of numbers to a person that has competing viewing priorities. So, your job is to find that hook, for example: if it’s the head of marketing they may want to visualise their marketing funnel and your job is to pinpoint where the funnel looks weak, why that is, and what it has led to. On the converse, your gift to the head of marketing is to tell them how to improve it by the next possible best action. The data should support the head of marketing asking different questions, being able to pinpoint the insights that will help them fulfil their marketing strategy.
- Know which visualisation will support the story: It’s time to keep it simple. Intricate pie charts with too much data splayed across them in minute detail won’t help. Key numbers indicating variance over time with good use of colours will instantly strike a chord with the viewer. Moving from a headline figure, to a bar chart with comparative numbers over time will support the hierarchy of questions that might emerge from the viewer. It lays out a logical path that creates that story, instead of being inundated with graphs, charts, heat maps etc. Always create comparisons where you can and draw these out, as this will catch the eye of the viewer as something that needs to be looked at. For example, a school’s trust benchmarked their schools against the national average, doing so helped them to understand underperforming schools. Being able to drill down into the under performing schools to see which areas were dragging them down i.e. maths, literacy, science etc. It told the story very quickly for the CEO, and corrective action could easily be taken with the school, setting out a strategy to improve the teaching and performance etc.
- Who is the audience: Generally, when putting visualisations together you have to understand who is looking at the story. Executives for example want to see high level numbers with the story displaying deviation from the norm and in the area that it happened. This way the executive can have crucial conversations with their managers to determine the next best action to take to correct the issue. Or if the executive wants to explore the data in more detail, she can drill into it and understand the narrative to better explain what needs to be done. Analysts for example need more data as they want to explore the story in greater detail and want to get to the root cause, possibly through adding more data to the mix. So, understand who they are, how they look at data and crucially how much time they will spend with the data.
- Don’t give your opinion: The data will speak for itself, never attempt to give your slant on the story as the person viewing it will see through it and be able to uncover the fact that there is bias. Always maintain objectivity and keep the message simple, if you see something you think is strange, don’t make it 5 times bigger than it ought to be, keep it in the same style as everything else and the viewer will get the gist as long as the visual cues are there.
- Not everyone can be a storyteller: one of you might be the visualisation expert and the other is the storyteller – each have their place and the important thing that you need to think about is how to convey the meaning in the data. I have met very good visualisation developers who can translate the data simply into meaningful charts and graphs, but need someone to break out the story and narrative in a different way so as to weave the story that sets the scene for more exploration. Being able to discuss the narrative with another individual will help breaking the story down to manageable chunks, and conveying a message that makes sense to the business. Don’t do it in isolation.
Making sure that most people in the company can view meaningful data is absolutely necessary today. Some call it “data democracy” and is something that should be paramount in all departments, and not left to IT to determine. If data isn’t properly portrayed within your company, then a valuable resource won’t be sufficiently tapped into. Data isn’t the new oil, it can never be, as data doesn’t have an expiry date unlike oil. It’s up to you how you choose to craft stories from this valuable resource, that will be the essence of your success. Good luck!