When science, art and language collide
As researchers, we often report our findings in the form of a story. Our analysis and insights may be used for various outcomes: to convince investors to invest funds, to persuade boards to increase budgets or even to mobilise society to take action. An impactful way to achieve any or all of these results is to tell a compelling story that is also credible.
I have a strong research interest in how stories are told. My PhD thesis was a story about storytelling — I analysed how some corporations use scientific data to spin their own stories in ways that are ambiguous and even misleading, and the extent to which this has contributed to an ineffective global environmental governance system. The stories that individuals and organisations tell become the stories (or discourse) of society. As the collectors, analysers and publishers of data, we have a duty to mitigate and disclose biases, and to convey responsible and honest messages.
The need for effective storytelling has become critical in the field of data science where decision makers often find themselves floundering in a quagmire of statistics. Even more painful, are the gaudy graphs and colourful charts, niftily (and perhaps too easily) produced by some or other software package and then copy-pasted onto slides ready to be administered as a potent sleeping pill to the captive audience at a pitch or meeting.
As both a producer and user of data analysis and insights, I have identified the following key guidelines that might be useful for data scientists and business analysts to consider when preparing reports or presentations for organisations:
- Include pertinent information about the data: It is usually useful to indicate how you collected data, why it is relevant, and anything else that needs to be disclosed, e.g. if there are gaps in the data sets or the information is dated. Highlight if there is some competitive advantage to the data you used, e.g. industry or sector-specific information.
- Choose relevant visualisation tools: Only use graphs or charts that are relevant to the analysis and that add value to the message. Do not include too much information in a graph or chart — focus the reader’s attention on one or two comparisons or patterns. Avoid excessive use of colours and exclude graphs that are unrelated to the narrative.
- The analysis should provide insights: The outcome of the data analysis should be insights about how to solve the problem or exploit the opportunity that is the subject of the report. An analyst adds value by pointing out insights that were not obvious at the start of the process.
- Translate insights into actions: Many project reports omit this step. It may be useful if decision makers are presented with two or three scenarios, and a comparison of the different outcomes. Practical actions are preferable to philosophical musings.
- Do not lie to or mislead your reader or audience: A compelling and credible story requires a measure of trust and connection between the narrator and the reader / audience. Many corporations lose the trust of their stakeholders because of inconsistent, misleading or blatantly untrue assertions in their reports. Analysis and insights should always be supported by evidence (i.e. the data).
- Foreground or highlight a common theme or thread that runs throughout the report: The word ‘narrative’ refers to a story that is told about connected events. The research, analysis, findings and conclusions should merge into a cohesive story. Common threads or themes can be the organisation’s values, goals or contribution to stakeholders.
- Keep the report or presentation concise and focused: An impactful story should excite its audience, not bore them because it is narrated in the form of a 500-page report or a 100-slide presentation.
- Communicate how the proposed action will result in impact or change for the better: Will the decision add value to shareholders’ investment in the organisation? Or help the CEO to achieve his goals for the year? Or demonstrate to the organisation’s stakeholders that it is committed to its espoused values? Or change the world and make it a better place?
The bottom line is that data analysis has to be augmented with succinct and well-articulated narrative in order to mobilise action that leads to change.
The idea is to create an impactful presentation with a persuasive narrative that generates insights into a particular problem or opportunity. The presenter must also communicate how to translate these insights into actions that add value, all the while engaging the audience or readers so that they can anticipate and visualise a happy ending.
And isn’t that what storytelling is all about?