Search

❌ When One Chart Confuses More Than It Clarifies

Michael Lee, MBA
Jun 29
3 min read

✔️ Why Small Multiples Are the Quiet Superpower of Data Visualization

🤯 The Problem: When One Chart Tries to Do Too Much

Your team just wrapped up Q2 sales.

You want to share how your four regional teams performed across three product categories. So you open Excel, fire up a line chart, and... here comes a rainbow spaghetti mess.

One chart. Four regions. Three products. Multiple months. Lines crisscross. Legends stretch across the screen. You zoom in. You squint. You give up.

Here’s the problem: When one chart tries to show everything, it often shows nothing clearly.

These charts:

Obscure individual trends
Make comparison painful
Add cognitive load and frustration

In short: good data, poor communication.

💡 The Solution: Small Multiples, Big Clarity

Enter Small Multiples—a set of mini-charts arranged in a grid, one for each item or category, all using the same scale and design.

Instead of overlapping lines and dropdown filters, you get clean panels. Each shows a single story. Together, they tell the whole truth.

Within seconds, you spot:

Which region consistently outperforms others
Who's volatile and who’s improving steadily
Where performance dropped (and when)

This is what we mean by clarity multiplied.

🔍 Real-World Examples of Small Multiples in Action

1. Singapore MRT Ridership Recovery

After the pandemic, the Land Transport Authority wanted to study line-by-line recovery. Instead of using one tangled chart for all five MRT lines, they plotted five mini area charts, broken further by age group (Adult, Student, Senior).

2. Dengue Trends Across Town Councils

A health analytics team replaced a bulky heatmap with 9 mini bar charts—one per district, showing monthly case counts.

The shift helped non-technical stakeholders see:

Which districts had seasonal peaks
When interventions made a difference
Which districts were consistently high-risk

3. Campaign Performance in Digital Marketing

Instead of using filters in a dashboard, a marketing team used small multiple line charts to compare CTR and conversion rate across 6 campaigns.

It revealed:

Campaign C had high CTR but poor conversion
Campaign F had a slow start but ramped up
Campaign A needed a full redesign

📊 What Types of Charts Work Well as Small Multiples?

Small multiples aren’t just about line and bar charts. You can use any visual structure that benefits from repetition with consistency.

Here are popular chart types that work beautifully in small multiple layouts:

Chart Type	Best Used When...	Why It Works Well
Line Chart	Showing trends over time	Clear comparison of slopes and shapes
Column/Bar	Comparing values across discrete categories	Works well in grids, easy to interpret
Area Chart	Showing magnitude and cumulative trends	Emphasizes volume change over time
Dot Plot	Comparing specific data points across dimensions	Clean and minimalist
Clustered Column	Comparing subgroups within time or category (e.g., age)	Makes intra- and inter-group comparison possible
Bullet Chart	Showing performance vs targets or benchmarks	Great for executive summaries
Heatmap	Comparing intensities across two dimensions	Excellent for showing density or frequency

These formats reduce scrolling, remove filtering bias, and make pattern recognition fast and intuitive.

🧠 Why Small Multiples Work So Well

They remove the need for legends, filters, and guesswork
The uniform design trains the eye to spot meaningful variations
They make comparisons feel natural, not forced
They scale beautifully in dashboards, print, and slides

🎓 Learn These Skills in Our Data Visualization Course

If you want to move from default dashboards to data storytelling that works, we’ve designed a course for you.

At FYT Consulting, our Data Visualisation Workshop helps you:

Understand how visuals shape interpretation
Choose the right chart for your message
Master techniques like small multiples, slope charts, and annotation layering
Build charts with hands-on messy datasets (not clean textbook examples)