Bad Graphs Are Everywhere
No one intentionally creates a bad graph—yet we see them everywhere. Across industries, organizations, and even major media outlets, poorly designed charts make their way into presentations and reports. Most of these come from well-meaning individuals who simply haven’t been taught how to visualize data effectively.
But why is this so common?
We’re Not Naturally Equipped for Data Storytelling
In school, we develop two main skill sets: language and mathematics. We learn to craft cohesive stories and analyze numerical problems. Yet these two skills—storytelling and data analysis—rarely meet.
In today’s data-driven world, the ability to tell meaningful stories with numbers has become essential. But most of us were never taught how to turn raw data into a compelling narrative, nor how to design visuals that communicate clearly.
As technology enables us to collect enormous amounts of data, making sense of it has become both a challenge and a necessity. Data visualization bridges this gap, transforming numbers into insights that support better decisions.
However, without proper training, many people rely heavily on tools like Excel or PowerPoint. While these tools make graph creation accessible, they also produce visuals overloaded with unnecessary 3D effects, excessive colors, and confusing pie charts.
The result?
Missed opportunities to inform, persuade, and inspire.
The Journey of Storytelling with Data
Effective data storytelling is a transformative skill—it allows you to communicate complex insights clearly and persuasively. This series of articles will explore the core principles from Storytelling with Data, breaking each concept down into actionable techniques you can apply immediately.
Part 1: The Importance of Context
Before creating a single chart, start with one critical question: What is the context?
Ask yourself:
- Who is my audience?
- What do I want them to know or do?
Your answers determine the structure, tone, and level of detail in your narrative. Executives may need a high-level summary, while technical teams may want deeper analysis.
Understanding context from the beginning reduces rework and ensures your visuals support your objectives.
Our next article will explore practical ways to uncover audience needs and define your narrative purpose.
Part 2: Choosing the Right Visual
Selecting the right visual form is essential for clarity. Common and effective visuals include:
- Bar charts – for comparisons
- Line graphs – for trends over time
- Heatmaps – for patterns and correlations
- Slopegraphs – for showing changes between two points
Equally important is knowing what not to use. Pie charts and 3D graphs often distort information and confuse audiences.
In an upcoming article, we’ll explore how to match the visual to your message—ensuring clarity, accuracy, and impact.
Part 3: Clutter Is Your Enemy
Clutter is the silent killer of good data visualization. Every extra line, color, or label makes it harder for your audience to understand your message.
To avoid this:
- Apply Gestalt principles to organize visual elements
- Use white space, alignment, and contrast to guide the eye
When you remove unnecessary elements, your insight becomes the center of attention. We’ll share concrete decluttering techniques in a future article.
Part 4: Focus Your Audience’s Attention
Great storytelling directs attention where it matters most.
Use techniques like:
- Preattentive attributes (color, size, position)
- Visual hierarchy to emphasize key points
These tools ensure your audience immediately sees what you want them to notice. Our article on this topic will include practical examples of guiding attention through design.
Part 5: Think Like a Designer
Good design is not decoration—it's functionality. In data visualization, form follows function.
Key design concepts include:
- Accessibility – making visuals usable for everyone
- Affordances – making important elements stand out
- Aesthetics – balancing beauty with clarity
We will explore how design thinking helps create visuals that are both clear and appealing.
Part 6: Dissecting Model Visuals
What makes a visualization great? In this section, we’ll analyze exemplary charts, examining:
- How graph types are selected
- How data is ordered
- How color and alignment strengthen the message
By breaking down strong examples, you’ll learn how thoughtful design improves understanding and decision-making.
Part 7: Lessons in Storytelling
Numbers rarely stick with people—but stories do.
This chapter introduces storytelling frameworks with clear beginnings, middles, and ends, applying them specifically to data communication. You'll learn how to use:
- Narrative flow
- Repetition for emphasis
- Smooth transitions
These tools help transform your analysis into a compelling message that people remember.
Part 8: Pulling It All Together
The final chapter brings the entire process to life through a complete example:
- Defining the context
- Choosing appropriate visuals
- Removing clutter
- Designing for clarity and impact
The result is a coherent and persuasive data story that informs, convinces, and inspires action.
The Journey Begins
Storytelling with data is more than presenting numbers—it’s about crafting narratives that influence decisions. This series will guide you through each step of the process, helping you build the skills necessary to communicate insights powerfully and effectively.
Let’s begin this journey together—one part at a time.
Note: This article is inspired by Storytelling with Data by Cole Nussbaumer Knaflic, a highly recommended resource for mastering the principles of effective data visualization.
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