“If history were taught in the form of stories, it would never be forgotten.” – Rudyard Kipling The same applies to data too. Companies, clients and even individual enthusiasts will remember data only if it is represented in the right way. Let us understand why it’s imperative for data to be explained in a narrative.
- Have you ever wondered why you might not remember a movie, scene by scene but can easily summarize its story? Human mind, despite its pictorial affinity, comprehends and stores a story better than any graphical representation.
- Imagine if while reading a movie review we were only presented with how cinematography was or how the screenplay went, would you be able to gain a proper feedback? Similarly, data charts by themselves aren’t sufficient to gain a complete insight of the relevant parameters in the bigger context. However, when data analysts and data scientists present us a narrative, a finished product is given to the client like a summarized movie review, making it easy for the end user to understand data efficiently. A captivating data narrative would not only present facts but also build connections between them; thereby being impartial and offering some uniformity to the end user. Data when explained in narrative even if taken out of context will be comprehensible as the reader would still understand what a chart is trying to explain as visualization has now turned into a story.
- Data charts and dashboards are not only meticulous to analyze each and every constituent in order to derive at a conclusion but also take up a lot of time and resources. Veteran analysts have often stated that it takes half their time thinking about how to narrate a good story with data. But what if there were software, which could collate, analyze and store reports only to present them, in moments, in simple narratives, customized to a specific audience, based on the effective analysis (work that would otherwise take valuable long human hours)? You would not only save time but also deliver better analytical outcomes while containing the rising costs and resources.
- A data narrative can be drafted keeping the target audience in mind and hence can be tailor made to suit the end user’s requirements. Data presented in a narrative has optimum technical details sans overwhelming buzz words for any kind of reader, facilitating easy interpretation and understanding. For e.g., a novice analyst does not necessarily require oversimplification while the managerial clientele would seek thorough, exhaustive and actionable understanding of the narrative. As data is extremely precious to an organization and not just the fellow analysts and scientists, it is important to communicate business value of data that helps viewer gain accurate and deep understanding.
- Generally, readers rely on ideology than actual facts hence a data narrative would not only establish end viewer involvement but also give rise to considerable interest and loyalty.
- Content marketing through data analysis using story telling is the upcoming big trend i.e. data narratives are used for efficient reviews and comparisons of organizations for the end viewers.
In brief, Tom Davenport, the distinguished professor, author and co-founder of the International Institute of Analytics, succinctly explains the effectiveness of data-driven storytelling: “Stories have always been effective tools to transmit human experience; those that involve data and analysis are just relatively recent versions of them. Automated narratives is the way we simplify and make sense of a complex world. It supplies context, insight, interpretation—all the things that make data meaningful and analytics more relevant and interesting”. We can now be reaffirmed that data-driven storytelling along with augmented BI is the next inevitable form of understanding data. In conclusion, dashboard and infographics will tell you the ‘what’ in your data, while narratives can tell you the ‘why, as they give you a story rather than just dropping a lot of data and expecting you to just sail through it!
Romil Shah is an AI enthusiast with considerable experience across varied technology domains, primarily Natural Language Generation (NLG), and Blockchain technology. He is passionate about technological innovation and more importantly its real-world applications. His work within the field has brought about constructive conversations and explorations around AI and its extended use in businesses.