Today, businesses rely on data more than ever before, and presenting raw numbers is not enough to drive actions. The power of data lies in storytelling and combining data visuals, and narratives is important to create actionable insights. This approach helps in transforming complex data sets into meaningful stories and simplifies making informed decisions and connecting with the audience.
What is data storytelling?
Data storytelling is a combination of the 3 main aspects: data, visuals and narratives.
- Data: It consists of the raw data that is required to generate insights and it’s the foundation.
- Visuals: It’s about the representation, charts and graphs that convert complex data into a clear picture.
- Narrative: This is the connection between the data and real world meaning, and it includes the context and explanation.
Why data storytelling matters?
Data brings the facts to the table and storytelling connects emotionally and intellectually. When a story is weaved into the data, that narrative becomes more relatable and actionable. This helps in:
- Simplifying complexity: It simplifies data and it breaks down complex huge amounts of data into understandable insights.
- Engaging Audiences: This requires visuals and relatable narratives to capture audience attention.
- Drive Action: Based on the data storytelling, it inspires the decision makers to make informed decisions.
Choosing the right chart for your story
It is crucial to choose the right chart as each type of chart serves a unique purpose in data storytelling. But picking the right chart can get a little overwhelming, so here’s how to pick the right one based on your goals:
- Line Charts – These charts are best for showing trends over time like stock prices or website traffic etc. They are used to show growth, decline or patterns in a timeline.
- Bar Charts – These charts are best for comparing different categories like different regional sales or product performance. It gives a comparative study and shows the best and worst performers.
- Pie Charts – A pie chart is more likely to represent proportions or percentages and is useful for instance, for budget allocation or to show the market share of businesses. Pie charts depict how different contributors are contributing on the whole.
- Scatter Plots – Scatter plots is a useful tool that shows the relationship between two quantitative variables such as incomes and educational levels or incomes and cities. They are useful for spotting outliers in the data.
- Histograms – Histograms are charts for understanding distribution in the data set for age groups, test scores and in the medical research field, among others. This highlights whether these data points are common or uncommon.
- Area Charts – Area charts are suitable for showing cumulative trends over time and the total revenue or usage. This will focus on the individual elements and the overall growth.
- Bubble Charts – Bubble charts allow comparisons in size and position of various statistics such as sales, market shares, and prices. They provide a simple, user-friendly visual of what can lend themselves to quite complex relationships.
- Heat Maps – Heat maps depict intensities or frequencies like rises or decreases in website clicks or customer density. This highlights areas of activity that require further attention.
- Waterfall Charts – Waterfall charts work for the step-wise change in the data such as in-profit analysis or budget adjustment. This shows how the individual components add to the total.
- Radar Charts – Radar charts allow comparison of more than two variables broken into various categories such as performance metrics, indicating which are the strongest and weakest aspects of anything.
How to craft a data story?
Here are a few basic steps to get an interesting and compelling data story:
- Know your audience: Identify what they care about and align your story to address their concerns.
- Define your key message: Identify the most important insight from your data and make it clear.
- Choose the right visuals: Use charts that fit well in your storytelling and simplify the understanding of data.
- Provide context: Answer the most important question “Why the data is important,” and make sure that it applies to real-life situations.
- Emotional engage: Use stories for relevance and make it memorable.
Real-life examples of data storytelling
- Marketing: Businesses use heat maps to identify where customers are most engaged on the company’s website, thus improving their websites for increased visits.
- Finance: The CFO can utilize waterfall charts to communicate how expenses affect profits and also track them, thus enabling implementation of insights.
- Healthcare: Hospitals use histograms to visualize patient age for specific diseases, enabling them to allocate resources.
- Human Resources: HR teams can use radar charts to compare skills for each employee and note where training would be required; hence it gives an overview of the requirement for training and employee analysis.
Creating impact from data
Data storytelling is not just about showing charts, it is about revealing insights that would help you take decisions and inspire action. By understanding when and how to use various types of charts, you can convert complex data into stories that appeal to your audience.
CRG Solutions is a Business Performance Improvement Company helping organizations traverse their Data to Insights journey and beyond.
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