If data is the new oil, then content is the refined product.
Just as oil needs processing and refining to be useful, data needs to be turned into content that humans can consume and understand.
This is the valuable result of data analysis and interpretation, providing insights and knowledge, and can take many forms, such as articles, infographics, podcasts, social media, video.
Delivering the data properly requires the careful crafting of raw numbers and facts into a compelling story enough to engage, inform and resonate with an audience.
This is even more relevant today as the Internet has had a dramatic impact on how content is produced, accessed, consumed, persuades, and is memorable.
Particularly as we are in an age where information on a page is skimmed and there are tools today that enable the better presentation of data as opposed to the traditional PowerPoint, an Excel spreadsheet, or numbers on a page.
Data storytelling means creating content that is informative, engaging, emotional, inspiring to drive action and change both for external and internal audiences.
According to Gartner research, decision-makers only currently use 22% of the data-driven insights they receive. Sixty percent of investments in analytics capabilities go to waste because people don't use the insights properly.
Creating effective stories with data helps ensure organisations are making informed decisions and surfacing valuable insights from the data they collect.
Artificial intelligence, machine learning, and predictive analytics can analyse large quantities of data quickly, identify trends or patterns and produce visualisations.
Data Storytelling and Visualisation
At its core, data storytelling is about telling stories with data and conveying the narrative through visualisations, interactive elements, or simply telling the story through words.
Data storytelling allows organisations to tell powerful stories about themselves using hard facts and figures rather than relying on opinion alone.
By providing evidence-based insights into what the company has achieved or where its potential lies helps build trust with stakeholders and customers alike–something that is invaluable for any business.
Tips for Data Storytelling
Here are some tips for getting your message across:
- Use simple language and short sentences—don’t get too technical or overly complex
- Break up long sections of text with relevant images or graphs that illustrate your point
- Focus on the importance of the data and what it means in the real world rather than just presenting facts
Data Storytelling Examples
The movie ‘Moneyball’ showed how the Oakland Athletics baseball team used data to find undervalued players and buy them. This strategy worked as the team went on a 20-game winning streak.
The Big Short is a movie about people betting against the housing market based on data analysis. Data storytelling brings this dry subject to life in a compelling and engaging way by the stellar casting.
These are ‘big’ examples of data storytelling, yet each example communicates insights from data, presenting complex information by making it easier for people to understand and remember.
As data continues to increase, the need for data storytelling will become even more important. Investing in better analytics capabilities and data visualisation tools will help enterprises take full advantage of the data they collect and improve their decision making process.
By focusing on these areas, businesses can ensure they are making the most out of their data and staying ahead of the competition.