Being a data narrator
In the simplest form, a data story is a narrative that contextualises and frames the broader implications of data. Data storytelling – and being a data narrator – is the skill to craft this narrative within the optimum context for the audience being presented to.
Avinash Tripathi, Vice President of Analytics at the University of Phoenix, spoke at the DataIQ 100 Summit and stated that the secret behind effective data storytelling and being a data narrator is about absorbing complexity and delivering simplicity. At the beginning of the year, DataIQ produced a piece on how to utilise storytelling to get decision makers to follow the data which echoes Tripathi’s points.
Tripathi noted during his talk that is it likely every organisation will claim to be data driven, a recent McKinsey report showed that only 8% are able to draw value from their data investments, and a separate IDC report on data culture found that only 30% of decisions are driven by data.
To improve data narration skills, Tripathi proposed a three-pronged approach:
- Align your analytics resources with an overarching strategy.
- Close the widening skills gap.
- Change the way your organisation communicates with data.
As for the data story itself, the solution should not be more complex than the problem, Tripathi stressed. “Start with a clear understanding of the problem itself, identify the success criteria for the use case, focus on two data metrics at most, and identify and analyse your stakeholders – this part is critical as it’s all about collaboration.”
Innovation does not have to use completely new or unique ideas; it is the way the idea is implemented and the value it adds that matters most. Tripathi noted that one thing to avoid is going in reverse – for example, trying to force an existing solution fit the latest problem is not the answer as this will not drive innovation forward.
Why is it needed?
Data professionals must be able to readily and succinctly tell numerous data stories to stakeholders and decision makers to further the funding and reach of the data office. It has been repeatedly shown that teams which utilise data learnings perform better than those that do not, so it is in the best interests of the data leader to demonstrate why data-led decisions are so essential.
This can be achieved through data storytelling, and successful data stories require focus on three key elements:
- Audience
- Narrative
- Visuals
Know your audience
Data leaders need to understand who makes up their audience – and this will change – so that the emphasis on details for the storytelling are tailored for the optimal impact. For example, when demonstrating the success stories of data to the sales team, it is not necessary to dive into the technological integration details to become data driven that the IT team would appreciate.
If a data leader creates a data story without considering the audience, it will become non-targeted and fail to inspire action. It is important to consider what the audience knows, what they need to know, and how the data relates to them.
Data story narratives
The narrative of the story should be based on what we know about the audience. When presenting to a sceptical audience, for example, more data-based evidence may be needed to help sway people to follow the conclusions of the story. An audience that is already on side with a data-driven approach to business will not need their stories to convince them about the value of data, but it will require the story to demonstrate why investment in the data team or a new data direction is needed.
A good story needs to lay out the information in a suitable order with a final call to action so that the audience in compelled to take action to further the data-driven success of the business. Failing to provide a clear conclusion that contains actionable insight risks a story where the audience is unsure of the significance, particularly regarding their involvement in data. Additionally, data leaders do not want to develop a reputation for wasting the time of other department leaders.
Visualisation of the data story
Data visualisation is the skill of being able to utilise tools such as charts, graphs, maps, and other visual aides to represent information in a clear and digestible manner. This is an important part of being a successful data narrator as it is another avenue to ensure engagement with a target audience for them to understand the story being presented.
Data visualisation is particularly important for those who have not been trained to read data. By using visual tools and examples, complex data can become accessible to a wider audience. This is important as it allows more people with thought diversity to get involved and potentially spot outliers, patterns, and trends.
It is imperative that data leaders develop the data visualisation skills of their team and across the organisation. Data visualisation can easily be ingrained into any business with a maturing data literacy and culture and can simply be done by implementing the correct tools for the job followed with appropriate training.
The above learnings came from keynote presentations and discussions at the 2024 DataIQ 100 Summit. DataIQ events provide incredible insights into how leading data professionals have approached a multitude of topics. The DataIQ 100 Summit is the premier face-to-face opportunity for attendees to learn from, connect with, and develop lasting relationships with some of the most prominent minds in the industry.
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