The true value of data can only be realised if it is summarised into a compelling narrative
Most companies in 2020 recognise the importance of data. According to Forbes, in 2012 just 12% of Fortune 1000 companies had a chief data officer (CDO); by 2018 that number had increased to 68%, and is still rising.
But even now, are companies realising the potential value of their data offers?
A 2019 survey of 64 C-level technology and business executives from large corporations such as American Express, Ford and General Electric found that over half of respondents stated they were not yet treating data as an asset. Similarly, from Zone’s report, ‘Bridging the customer experience gap’, we found only 56% of the respondents described their data capability as ‘excellent’ or ‘good’ and are ‘able to access the data they need across organisational silos to derive actionable insights’.
The above suggests a clear need for many organisations to properly invest time in turning their data into a valuable and actionable asset. I believe that true value can only be garnered from data when results of the data collection and analysis are succinctly summarised to form a narrative that can be understood and acted upon by any relevant stakeholder.
Sainsbury’s CDO, Helen Hunter, is a big advocate for effective storytelling, saying in a 2018 interview with Marketing Week: “We can only really change the way the organisation views information if we’re able to explain it in a compelling way.”
Process to make a compelling data report
Creating a strong data narrative can be difficult, with factors such as data quality, data type, audience and reporting format all having an effect. However, I have outlined three key questions that should be answered in order to make a compelling report.
Is the narrative easy to understand?
The foundations of the data world are based on statistical methods and the scientific process of analysis which, as data professionals, it is our job to understand and apply.
However, the outputs may not be clear or accessible to a wider audience. This is sometimes forgotten by data analysts (including me), who show complex graphs and visuals without thinking of how someone may interpret them.
Before employing these analytical approaches, make sure you have a clear vision of your audience so you can produce concise insights for them. This example from a featured Tableau dashboard, which aims to highlight the top-level nutritional elements when making a coffee, shows a lot of information succinctly. By being simple, but also providing an interactive element, it creates an engaging way to personalise specific metrics for each viewer.
Does the narrative start a conversation?
The sign of a poor report is one where the intended audience remain silent. A strong data narrative poses questions to engage the audience and get them thinking. The findings may show a wildly different narrative to what the audience expects, and it is important to encourage them to find out why.
This is particularly challenging when creating a real-time dashboard as it is not always presented with someone talking it through. One way to solve this would be to create an option to capture feedback so that a conversation can be started.
Can the narrative answer the ‘so what’ question?
Showing visuals, graphs and data points is interesting, but unless there is a key action or insight for the audience to take away, what is the point? Data becomes effective when it can be acted upon and used to drive change, performance or direction.
I think this is the most overlooked area of reporting in general, where showing impressive sounding numbers (eg vanity metrics) often wins out over actual value or use. The key to answering the ‘so what’ is by making the report focused on the end audience. A report in which an audience comes away knowing what the next steps are gains a higher level of confidence in the campaign or tool being measured.
Taking the coffee dashboard as a reporting example, to an extent it is able to stand up to the 'so what' test. Its informative nature allows the audience to make decisions based on the metrics shown (eg deciding to use almond milk rather than whole milk). However, it does require some effort from the audience to get those useful conclusions, which can be problematic.
A clear and simple narrative is optimal for ensuring the information presented can be acted upon by the audience. Perhaps using relative metrics vs a baseline or adding labels could make it clearer what the action is, eg to reduce your daily sugar intake, choose almond milk over whole milk as it has two-thirds less sugar.
These are just a few of the methods that can help provide a strong data narrative, ensuring your audience can understand the situation, ask questions based on their experience and see a clear next step.
James Tyson, data strategist at Zone.