What are the best practices for creating data stories that inspire action and change?

I have see that many a times the solution is simple and that is "to know what excites your stakeholder?". Now the answer to this Q would be different for each stakeholder so make sure your presentation contains enough material to "engage" each of them.

One of the biggest drivers of impactful data stories is knowing exactly who you're speaking to. Understanding their pain points, motivations, and also how they consume information really helps create a story that resonates.

In order to save time and effort, it’s crucial to be crystal clear on the goal. Is the purpose of the data story to inform, persuade, or drive a decision? Defining this upfront keeps the narrative focused and ensures that the data not only tells a story but leads to actionable outcomes. When you know exactly what you want your audience to do, it’s easier to guide them there.

he next crucial step is finding the right data—and this is where I often see projects struggle. In my experience, selecting data that directly addresses the audience’s concerns or highlights their opportunities is what helps create a story that drives real change. It’s not just about accuracy; it’s about relevance and resonance.

Keep in mind that each story has 1 or several heroes. Set yourself above most of the data professionals and share data stories with actual heroes (abstract concepts or human being). Without heroes your story will be flat and won't convey emotions.

Think of the data story like a Hero’s Journey. Start by framing the challenge, introducing the insights as the guide that helps overcome the obstacles, and finally, leading to a resolution with clear, actionable steps. This storytelling arc not only keeps the audience engaged but also makes the data more relatable and memorable.

In my opinion, the best way to make a visual is having a clear and strong message, preferably mentioning some values. Then you need a good visual that shows those numbers so you can highlight them to attract the viewers eye. For example: We see the sales go down from 168K last month to 153K this month (-9%) due to a specific promotion of one of our main competitor. Now you can make a visual with some context and also the values 168K, 153K and -9% as a difference in red. That difference in red helps you to tell that this is a unwanted situation. Next you can highlight these 3 values in the chart so everybody can connect the strong message with the visual. The main take-away is that the chart supports the strong message. Not otherwise!

Data visualization isn't just about making numbers look pretty—it’s about simplifying complexity. The best visualizations turn complex insights into clear, digestible visuals that your audience can immediately understand and act upon. It should feel intuitive and enhance the narrative.

Always express how you feel about the data. Lets say you are presenting about the performance of a particular team or a project and it has superseded everyone's expectations or reached the target - Speak to them about the numbers, express and share their joy and speak about the numbers with pride; acknowledge their humongous effort in reaching it. Conversely, when delivering unfavorable news about declining performance, ensure your tone doesn't instill fear of impending consequences. Instead, focus on the insights gleaned from the numbers. Identify alternative areas of opportunity and offer guidance on how improvements can be made to help the business thrive.

Humanizing data is crucial for inspiring action and ensuring that your information remains memorable. When dealing with "people-based" data (data on consumers, students, employees, users, etc), readers or listeners can overlook the fact that each figure in the dataset represents an individual with a unique story and experience. To remedy this, consider using examples or case studies to breathe life into the data. Share the journey and challenges of a specific person within the dataset, or construct a persona that represents the average person in the dataset and discuss the average experience. Humanizing numbers--especially large numbers--helps listeners connect, retain information, and feel inspired to take action.

The goal of the visual presenter does not end at the dashboard delivery; the goal extends further to coerce actions from the audience. In my experience, providing a 'what-if' scenario analysis tool helps users to take relevant actions. For example, It is insufficient to showcase that the forecasted profit will decrease in the next quarter. The user wants to know what they can do to prevent it. One way to help the user is by providing a granular view of the variables used to predict this outcome, e.g., COGS is rising due to inflationary pressure, or the finance cost is rising due to higher interest rates. Users can use a 'what-if' tool to play around with these numbers in an attempt to reduce the impact of these variables in final profit