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Definitive Guide to Decision Intelligence
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For decades, data analytics has relied on numbers, charts, and graphs -data visualization- to convey business performance, which can be challenging to interpret for non-technical employees. Fortunately, a transformative shift is occurring, offering a deeper understanding of data through a technique called data storytelling. Data storytelling marks the evolution of data analytics from complex charts to plain text narratives that make data more accessible and meaningful to everyone. In this article, we will explore the art of storytelling with data, key components, examples, and the benefits it brings to organizations of all sizes.
Data storytelling is an analytical technique for communicating specific insights to a target audience using narrative and visual representations. Unlike data visualization, which only focuses on what is happening with data, data storytelling goes deeper to explain the "Why". It includes a plain text written explanation of data that adds more context and meaning.
Imagine working as a retail sales manager, and you have to deliver an end-of-year sales report.
Using the data visualization method, you collect, clean, and analyze data, and then display the insight using visual elements such as a bar chart, heat map, or pie chart. The data visualization report will show the monthly sales numbers, making it easy for you to spot trends. You might be able to see that sales dipped during the summer months but rose sharply during the holiday season.
In contrast, using the data storytelling approach, your report dives deeper and explains why sales dipped. A report that leverages a data storytelling approach will have the visual elements plus some explanation. In this case of retail sales, you could have a summary like
"This year, our retail store has generated over $50,000 in revenue. In the summer, sales took a dip by 5% as people went on vacations, but went up to 7% in autumn as consumers get ready to swap out their warm weather wardrobes for cold weather clothes. During the holiday season, sales skyrocketed up to 50%, surpassing expectations. Despite the summer slump, the end-of-year figures show an overall increase, demonstrating the ability to adapt to changing seasons and customer behaviors."
Compared to a graph showing numbers, the data storytelling approach explains every aspect of the numbers on the chart.
Storytelling with data needs three significant elements to deliver effective results. These components are data, visuals, and narrative.
Data involves an organization's numbers in raw format collected from different touchpoints. The data offers the basis for the insight and other relevant information you can extract.
After data is collected, cleaned, and analyzed, it can then be presented visually with elements like graphs, charts, and images. These elements also utilize colors to differentiate different results.
The narrative provides the explanation that showcases the “why” behind the business performance. A narrative will offer context and direction on what’s next given the root cause behind trends in the data.
Combining the data, visuals and the description enables you to explain complex aspects of performance to your audience.
Storytelling with data offers many benefits: increased accessibility, better communication of complex insights, collaboration, and improved decision-making.
Data storytelling offers a concise and engaging analysis of business performance using a combination of visual elements and plain English explanation. Unlike raw numbers, this storytelling data enables all stakeholders to access, digest and understand the information. It ultimately eliminates the reliance on technical analysis and the deadlock it creates in the decision-making process.
Although data analysts or statisticians understand data without further interpretation, it's challenging for others. With data stories, you can communicate complex insights concisely and efficiently share across teams. The combination of data analysis and a narrative gives more insight into the "why" and “so what” behind the number, supporting more accessible communication and planning.
Considering that market trends are often changing fast, its imperative for leaders to have access to data insight in formats they understand and with context. Decision-makers can generate these explanatory insights with data storytelling. You don't have to wait on an analyst or stare at a dashboard for hours, simply ask questions and get responses in plain English. Furthermore, you can dive as deep as you want to identify root causes and other data performance metrics. The speed and simplicity enables you to make decisions faster and take advantage of opportunities.
Imagine the marketing team being able to extract insights about why sales dropped in plain English. They can immediately share their findings with the product development or sales departments and get their insight on ways to improve the performance. Also, considering that the technical barrier is eliminated, it's easier to loop other departments in on ongoing projects analytics without having to go through the IT and analytics team. Consequently, teams collaborate better as they can all see the analytics, extract relevant insights that affect their department and adjust accordingly, therefore fostering smooth running of the project deliverables.
Here are some examples of how organizations across industries use data storytelling approaches.
Although there was a lot of information on the impact of Britain's exit from the European Union, none of these painted a clear picture. Sky News presented a detailed and engaging piece titled Brexit in Numbers using data storytelling techniques. The publication used visualization and clear narratives to explain the impact, drawing insights from historical data and more.
In the healthcare industry, The United Nations Office of Drugs and Crime UNODC Synthetic Drug Strategy 2021-2025 is an excellent example of storytelling with data. The strategy highlights essential topics and arguments around the use of synthetic drugs. It captures its global impact, helps you understand beyond the numbers and improves the public's awareness.
In the entertainment industry, Spotify has been an excellent storytelling practitioner with data with their Spotify-wrapped report. In 2022, they delivered a Spotify 2022 fan study for artists to help musicians understand how their listeners' behavior affects their results. Unlike raw analytics, the report helps musicians understand how users react and suggests ways to reach a wider audience with their music.
Here's a three-step approach to help you create compelling data stories
Different audiences will be interested in specific data insights. For example, some executives are focused on high-level insights, while others require a deeper dive into particular performance. Understanding who your target audience is will help you tailor your narrative and visualization to their interest.
Crafting a compelling narrative involves considering the best approach to your report and the flow. You should include the introduction, conflict or challenge, development, resolution, and call to action.
When the narrative is set, you should select the visual elements that help you convey this message at a glance. Do you want to use bar charts, heat maps, or images? Which visual elements will come first, middle, and last? Carefully arranging the visualization helps to support the storytelling flow for better impact.
Numbers and charts give surface-level insights into business performance. And while this might be good, it creates a gap between data accessibility and decision-making. However, including a third element -a narrative-you can achieve better results with your data. That's where the Kyligence Copilot tool comes in handy to enable you to do more with your data using AI-powered data analytics features. You can analyze reports beyond what happens to find out why and how you can solve the issue. Start building compelling data stories today with Kyligence. Sign up now for a free trial.
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