Data Storytelling: How to Tell a Story with Data

Data Storytelling

Organizations must do more than just analyze data to be truly data-driven enterprises. IT leaders and business professionals must make relevant data into compelling stories that key stakeholders can readily comprehend. This will allow them to make better business decisions.

This skill is called data storytelling and is essential for any organization looking to extract actionable information from their data without getting lost in the ocean of charts and numbers typical of traditional data reporting.

Here’s a look at data storytelling and how IT and analyst leaders can use it to maximize data’s potential for decision-making.

What is data storytelling?

Data storytelling is a method for conveying data-driven insights through narratives and visualizations. It engages audiences and helps them understand key conclusions and trends.

This is often easier said than done.

Kathy Rudy, says that telling stories with data can be challenging. Chief Data and Analytics Officer at global technology advisory, and research firm ISG

Rudy believes data storytelling starts with understanding your audience.

Remember to identify your main characters or the audience for your data story. What information is most important for them? You can organize your data story to anticipate the audience’s next question by thinking like a reader. Rudy says that she learned how to tell a clear and concise story with data to support ISG recommendations. In her 20-year career as a data analyst and benchmarking professional,

She says that acceptance of the validity and reliability of the data presented is the first obstacle for data storytellers. To overcome this hurdle, To do, it is best to hold data validation and understanding sessions to get the question of data validity out of the way.

Rudy says that the goal of the Data Storyteller is to answer all questions about the source and age of the data so that subsequent views of data don’t make it seem like the storyteller is constantly defending the data.

She advises that you don’t go too technical, or you might lose your audience. They don’t need to know everything about IT benchmarking. All they want is for that data to be relevant, secure, and current.

Also read: How Data Analytics Can Help You Generate More Leads

Elements of data storytelling

Data storytelling is data visualization and narrative. It also includes context, according to Peter Krensky (director and analyst, Gartner’s business analytics and data science group).

He says, “With visualization, a picture can be worth a thousand words.” How do you make the story visually compelling? Is your story using iconography or a graphic? It doesn’t have to be a table or even very basic information. But it’s important to include a visual component.

The narrative is the story, the who, what, and whereabouts. Krensky states that it’s the emotional arc. “If it’s sales forecasting for quarters, are we doing well, or are people going out of work?”

The context is what people who hear this story should know. Why one sales representative is always outperforming all other sales representatives is an example of the context for a data story. Krensky says,

Grace Lee, a chief data-analytics officer at The Bank of Nova Scotia (known under Scotiabank), said that blending context with narrative requires an in-depth understanding of what makes a story compelling.

“The way we think about stories. If we take out the data term, it requires a plot you care about and characters you root for. It requires a destination or an end result that you believe in, and that you aspire towards,” she said.

Lee says that being able to use narratives to place data in context allows people to feel more involved and understand the consequences. Lee’s team is working to develop more storytellers throughout the company, in addition to their focus on storytelling as a discipline.

She said, “The way that we educate people about storytelling involves action orientation. Helping them create those stories and providing more context. This allows people to see the clear line between data, insight, and the action to follow.”

Because of the importance of data and analytics, Scotiabank’s role as the storyteller of the enterprise is what Lee considers it to be because only through data can some insights about customers’ needs and wants to emerge.

Key steps in data storytelling

Lars Sudmann is the owner of Sudmann & Co. a Belgium, based consulting and management training network, that provides insight into the steps involved in data storytelling.

  • Identify the “aha” insights: One of the greatest pitfalls of data-based presentations is the “data dump.”Instead of overwhelming the audience with visualizations and data, CIOs/data analytics officers should focus on identifying one to three key insights from the data. These are some of the most surprising facts. The most important things you need to know Sudmann suggests that you identify them and create your presentation around them.
  • Share the genesis story of the data: A good starting point for telling a story with data is the genesis. This is the source of the data. It is important to know where it came from. This is particularly important for storytellers who present data sets for the first time.
  • Turn surprising turning points into exciting transitions: When storytellers present data and facts, they should share where the data/graphs/trendlines make “surprising” moves. Is there a leap? Is there a turning moment? This can lead to compelling transitions to deeper analyses, such as: “Normally, we would believe that the data does X. But here, we see that it has declined.” Let’s find out why.
  • Develop your data: Presenting presentations is difficult today because people often throw a lot of data onto the screen, then “catch up” with words such as “This is a crowded slide, but let me explain.” This might seem difficult but …” Storytellers should instead develop their data step by step. Sudmann states, “I don’t like fancy animations but in PowerPoint, there’s one animation I recommend: the appear’ animation.” It allows one to harmonize what one sees with what one says, and can then be used to build a data story step-by-step.
  • Highlight and emphasize your story to make it come to life: Once storytellers have identified the flow and key aspects of their data stories, It is important for people to highlight and emphasize key points using their bodies and voices. Show the data, point at it on the screen, walk towards it, circle it, and it will come to life. Sudmann says,
  • You can have a hero’ or a villain’: To make stories more engaging, Data storytellers need to consider creating a hero (e.g. the “good tickets”) and a villain e.g. “The bad tickets that were raised by not reading the FAQs,” Eventually, they will show development over time, in various departments, as well as the “hero’s journey” to success, Sudmann advises.

Also read: Customer Data Management: Definition of CDM, Benefits and Best Practice

Data storytelling tips for success

Rudy believes in letting data unfold through telling stories so that the storyteller can get to the punch line or “so what, does what” and there is complete alignment on the message.

Storytellers should always start from the top and start with the “what” (e.g., IT benchmark) and then go on to say that IT spending is $X million annually.

Storytellers must start from the top and then set the scene with the “what”. Take, for example: In the case of an IT benchmark the storyteller might say that $X million is spent on IT annually (remember that the data has already been validated so everyone is nodding).

The storyteller then explains that, based on current usage volume, the unit cost for each technology area is $X. She also explains that compares to other companies of similar size or complexity the storyteller’s organization spends more on certain areas, such as security (now everyone is paying attention). Rudy says.

She says, “You have so led your audience towards these how’ parts of the story. Specifically, that there are areas to improve.” “The next question that your audience will ask is most likely to be ‘Why?’ and finally,?So what are we doing about it? ‘”

Rudy says that the rest of the story relies on a shared understanding of data validity to make recommendations for changes and take the necessary actions to implement those changes. This story provided the data necessary to create credibility and a call for arms, a reason to change that is indisputable.

Consider the old saying, “If a tree falls into a forest and nobody is around to hear it,” does it make a sound?” into consideration, It is crucial that data storytellers consider the various media people use to consume information. what times they access this information.

Kim Herrington is a senior analyst at Forrester Research for data leadership, organizational culture, and culture. “The pandemic certainly helped in the shift towards allowing thought workers to work from home,” Kim Herrington said. “A lot of times, you communicate with thought workers who are all over the world. It’s important that you think about the communication software you use and the communication rules you have with your team.

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