Data is an important tool for decision-making, yet it is often overcomplicated and fails to deliver the value it should. This is especially common with data practitioners whose expertise in data can be a weakness, shifting the role of data from driving decisions to making or managing complexity. Reflecting on my own experiences at the start of my career, I have seen this challenge arise when there is a lack of strategic guidance, limited understanding of common data analysis pitfalls, and a failure to recognize that data is just one factor in influencing decisions and actions.
Analysis Paralysis
For many, especially those in a junior or professional data role, the challenge of building a persuasive story begins with the data itself. Faced with a sea of information, they fall into analysis paralysis, overcomplicating the process, hesitating on direction, and losing sight of the objective. Without a clear framework guiding their work, they veer off track in the exploratory phase, resulting in unfinished analyses or insights too vague to drive action. This happens when there is a lack of structure or consideration for the end user, the person who made the request, whose priorities should guide the exploration, and how the findings are communicated to influence their decisions.
The Story Is More Important Than How You Got There
Another common challenge when using data is telling a compelling story. Stories are one of the powerful tools for persuasion, and the primary reason for using data is to drive decisions. Yet, too often, the instinct is to start by showing the work: the process, the analysis, the steps, and the considerations made. Everything except the story itself. However, this leads to oversharing, forcing the audience to sift through the details to find the key insights.
The best stories are simple and focused. As you refine your narrative, ask yourself: How can I make this simpler and the message clearer? Through iteration on both the data and story, you will eventually find the core message that will resonate with the parties involved. This often means simplifying your visuals, turning your takeaway into a headline, and expressing your insight in just a few words. In data storytelling, practicing minimalism is your ally. It makes the data feel accessible to all audiences and delivers a confident story that leads to action.
Improving Your (or Your Team's) Data Storytelling
From my experience in data, I’ve found a few key principles to help improve your storytelling, whether you are crafting it or coaching others to do it more effectively.
1. Start with a structured framework for analysis
Avoiding analysis paralysis begins with a solid exploratory data analysis framework that provides you with clarity. It helps answer questions efficiently and templatizes the common data storytelling process. Finding the framework that works best takes some trial and error, but providing examples of strong analyses or a codified framework can significantly accelerate the learning curve and help individuals produce impactful, actionable insights.
2. Understand the context behind the question
Once you have a solid data analysis framework in place, shift the focus to the context that led to the analysis. Use the classic, narrative-creating 5 W’s and H framework (Who, What, When, Where, Why, and How) to shape the story from the insights you have and speak directly to the people who matter. This simple but powerful framework has guided effective storytelling for generations and remains just as relevant in data today. It helps ensure you address the essential questions needed to drive action. Here’s how to apply this framework effectively in the context of persuasive data storytelling.
- Who is the audience for this data and story?
- What is their level of understanding?
- Are they the decision-maker, or what is their level of influence in the decisions you are looking to make with your recommendation?
- Why do they care about this data?
- What biases, assumptions, or preconceptions might they bring to this data?
- How does their role or function shape the way they interpret data?
- What is the most relevant content to them?
- Where do you need to explain more or less?
- How detailed do you need to get to make sure you are understood?
- What prior knowledge or context can you assume they already have?
- What potential objections or counterpoints might they raise, and how can you address them proactively?
- Where will this story have the most impact?
- What format or medium will be most effective for delivering this data (e.g., visualization, narrative, etc.)?
- Where does this story fit within the decision-making process?
- Where does this tie into potential implications or actions within the business?
- Why does this data matter to them?
- How do you connect this to their goals, priorities, and challenges?
- What problem does this solve?
- Are there risks associated with ignoring or misinterpreting it?
- How does this empower them?
- How can they use this data for positive change?
- What are the possible actions that can be taken from this data, and what is your recommendation?
- Does this change the way they are thinking about the problem or opportunity?
- Are there potential barriers to acting on this data?
- What does success look like when acted upon?
3. Always lead to action
A great story is about more than just sharing insights; it drives change and meaningful outcomes. One that builds toward a clear recommendation, action, or next step. Without it, your audience will be informed but left no closer to a decision or resolution. To ensure action, ask yourself:
- How is my story leading the audience closer to a decision?
- What are the next steps that you recommend?
- What are the pros and cons of your recommendation?
Additionally, make sure you apply the right call to action to your audience. Are they an executive who only needs in of the takeaway and decision point, or a collaborator needing more detail and support to arrive at a decision? Depending on who they are will dictate the action being delivered.
Data and Persuasion
Don’t let expertise or overcomplication of data become a blocker to the value data has in telling a compelling story. Data is only as powerful as the story you tell with it. The impactful ones are those that persuade your audience to take action. Before your next analysis, revisit the principles shared in this article and shape your story with your audience, message, and action in mind.