Gather round, gather round! We hear an eerie sound… I remember the old times around the holiday campfire when smooth talking uncle Alfred with his grand imagination and picturesque speech would tell spooky ghost stories that would make the children huddle closer and closer together, and well, ensure they don’t wander off exploring in the night. Even in business today, storytelling plays an important role when conveying the messages that are unearthed from the deep dark vaults of our data. Besides, we have to keep our business users focused and not wandering off down a side road as a result of poor data narratives.
This post follows on from a previous post on ‘Storytelling in Data Science’. In simple terms, storytelling helps business people make better sense of the data by articulating in business terms what insights have been discovered by applying analytics to the data. The insights can be further illustrated through commentary, visualisation and the use of complimentary and meaningful images.
However, as any author of children’s stories will tell you, telling a compelling story isn’t all that simple. You have to plan a plot that is exciting enough to capture and hold their attention, but the complexity and length must be appropriate for the target age group. It can’t be too scary so that they can’t read it at night. The younger the group, the more applicable and bigger pictures you need to illustrate what is happening in the story. Interesting, this analogy to all the various levels of business users…
In my experience, the following steps should be followed when using storytelling to transform the insights derived from data into easier to understand and more meaningful messages for the business.
Source the right data
Unlike fictional stories, your data-related stories need to be based on proven facts. It is therefore very important to ensure it is compiled from pertinent, accurate and up-to-date data.
As most businesses are inundated with data every day, it’s important to focus on the data that is most significant to the organisation and that would have the biggest impact on the business. But having said that, you have to make sure that you are continually able to see and use new data and ‘not just the same old collection of data views you are used to compiling.
Your biggest impact will be when you discover new data or reveal new insights from existing data that will change some of the concepts that the whole business is built on. Therefore, just as the story author needs to think of a new and riveting plot, you need to analyse old and new data in forever new and original ways in order to arrive at that all important new and revealing insights. But above all, the underlying data needs to be factually correct and relevant. Even kids know that ghosts don’t fly around in daytime.
Use tools to systematise the data
I have noticed over the years that the hardest part of working with data is getting it organised in such a way that it is in a useful format for data visualisation tools, statistical analysis packages and advanced analytical modelling tools.
If your data is very complicated it may be necessary to contract the IT department or a few technical “data jockeys” to massage it into a more useable format. They may use data integration tools, like ETL tools, or other data manipulation and data scripting languages to get the job done.
It is a talent to discover the story in the data
Once you have correlated and structured all the data, you can start the search for those little nuggets of wisdom in the data that would be of value to the organisation. The “story” that you unearth may be something beneficial to the organisation, or it may be a “do this or else” message of potential doom and gloom. Not all the messages contained in an organisation’s data are feel-good stories.
Data discovery and data science are fun activities, as it allows you to search for and hopefully find the interesting nuggets of “story” in the data. Sometimes you may work off a hunch, while other times you just have to explore the data looking for outliers, unexplained correlations or unexpected trends. Sometimes not finding an insight is a result in itself, especially if a result was expected. An empty grave may mean a zombie needs to be found!
However, it is very important that you should verify and double-check or test the validity of any such newly found insights. This may require further analysis, hypothesis testing or validation against industry or competitor data.
Use tools to visualise your data
When you have identified the relevant data and a plausible and interesting insight, you can start compiling your story by making use of visuals to illustrate the point and to make it more convincing. This can be done by using graphs, graphical images or even infographics that will present your data in a way that will accentuate the story that you need to tell.
There are a number of tools that can be used to make the visuals more engaging for the target user group. Data visualisation tools are a very important category of tools – especially if they allow you to interactively illustrate the plot of the story and its potential impact. Some visualisation tools have “what-if” scenario modelling and forecasting capabilities, which is very useful to illustrate the impacts of some proposed action.
It is vitally important to remember that the credibility of your story will be influenced by the credibility and careful use of visuals. Follow the work of visualisation experts like Stephen Few who specialise in highlighting the messages contained in the data without cluttering it with unnecessary ink and imagery.
Focus on the story you are there to tell
I’m sure many of you have drifted off in presentations, even in movies… not because the facts conveyed or the story told was irrelevant, but because it was presented badly. You don’t want critiques such as:
- Boring.
- Death by PowerPoint.
- Monotonous.
- Unfocused
- Maybe even too long and detailed.
Make sure you’re a vibrant and engaging uncle Alfred!
Tell the story – verbally – and only use the visuals and graphics as supporting evidence. Do not get trapped into reading off the slides or reciting a bad script. Speak about it from your heart. And if it’s a doom and gloom story, get behind it too – after all, it may even affect your future if they don’t react appropriately.
Your data is only the main character of the story and as such it is up to you to explain the significance of the data and its potential implications to present the storyline and plot. Moreover, you need to explain the impact of the derived insight – and suggest what should be done about it. And you need to tell it in an exciting and interesting way. You need to be enthusiastic and interested in the topic yourself in order to tell a good story. Become part of the story. I mean, uncle Alfred himself was there that dark stormy night outside the castle. Really!
Question time
One of the more interesting times around the campfire was to watch smooth uncle Alfred take a sip of his campfire coffee on completion of the story and wing his way through question time. “Why did the princess leave the castle in the night?” “Why wasn’t the wolf scared?” “Why didn’t he run away?” Why, why, why? Just like he couldn’t squash the children’s curiosity, you have to field questions and encourage debate around the data and insights presented. You have to be prepared that you may have to prove a point or two, justify your insight or re-motivate your recommendations. A combination of an interactive visualisation tool and the ability to think on your feet works well.
In some cases, the story will not be told face-to-face – it may be published on an internal website or a company blog, even as an infographic. In this case you need to facilitate dialogue through collaboration facilities. Business users must get the opportunity to ask those questions and comment on the insights and applicability of the proposed actions to the business through easy-to-use collaborative facilities.
Concluding thoughts
Given that our world is often cluttered with data, business and data analysts need to consider the importance of using storytelling together with data visualization to get the insights and the messages across. However, it is also important not to make use of the visuals to compensate for a poor delivery of the story. The visuals, supported by the underlying data, should only be an aid to help you tell a more compelling story, and to motivate for the required actions to be taken. Storytelling is not a forgotten art – with the growth of data-driven decision-making its role has become even more important in the business workplace.
