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Any great story means great details and strategic use of visuals.
Besides, it’s a proven fact people don’t like numbers. They are interested in insights. So how can you represent insights in a simple and compelling way?
You guessed it right. The solution is incorporating easy-to-read charts into your data story. Sankey Chart for Excel version is one of the easiest charts to understand in the world of data visualization.
Definition: Sankey Chart visualizes “a flow” from one set of values to the next. The two items being connected are referred to as “nodes.” The connections are labeled as “links.”
Besides, it’s named after an Irishman, Capt. Matthew Sankey, who first used them in a publication on the energy efficiency of a steam engine in 1898. Sankey diagrams were initially used to visualize and analyze energy flows, but they’re a great tool to depict the flow of money, time, and resources.
Directional arrows between the nodes show the flows in:
Let’s head to the next section where you’ll learn the building blocks of the Sankey diagram.
A Sankey is a minimalist diagram that consists of the following:
This brings us to the meaty part of the blog: the best tool to use to create a Sankey Chart in Excel that complements your data story.
Please pay attention because this is one of the essential parts of the blog.
Creating a Sankey diagram in Excel is very easy if you have ChartExpo add-in installed. You just need to select the Sankey diagram, check the sample data provided with this chart, replace the data with your own data and in one click your visualization will be ready.
Storytelling with data is the best way to present your data in a meaningful way. Sankey is one of the best visualizations which gives colors and life to your data story. Let’s have one practical application of the Sankey diagram.
Energy Management Application
Imagine you’ve been tasked by the Energy Commission of a hypothetical country to analyze their gigantic data. They want to know various details about domestic energy consumption, namely:
The Energy Commission wants a data story to use for the forthcoming launch of their 10-year Plan. The table below has the sample data we’ll use for the scenario above.
Note: the table below is pretty long to show you that Sankey can visualize gigantic data sets without obscuring key insights.
Apologies in advance if you find the table below weirdly long.
| Energy Type | Main Source | Source type | Energy Source | Usage | End-User | MegaWatt |
| Agricultural waste | Bio-conversion | Solid | Thermal generation | Losses in process | Lost | 5 |
| Agricultural waste | Bio-conversion | Solid | Thermal generation | Electricity grid | Industry | 7.3 |
| Agricultural waste | Bio-conversion | Solid | Thermal generation | Electricity grid | Heating and cooling – commercial | 5.1 |
| Agricultural waste | Bio-conversion | Solid | Thermal generation | Electricity grid | Heating and cooling – homes | 3.7 |
| Agricultural waste | Bio-conversion | Solid | Thermal generation | Electricity grid | Lighting & appliances – commercial | 4.9 |
| Agricultural waste | Bio-conversion | Solid | Thermal generation | Electricity grid | Lighting & appliances – homes | 2 |
| Other waste | Bio-conversion | Solid | Thermal generation | Losses in process | Lost | 7.2 |
| Other waste | Bio-conversion | Solid | Thermal generation | Electricity grid | Industry | 5.4 |
| Other waste | Bio-conversion | Solid | Thermal generation | Electricity grid | Heating and cooling – commercial | 6.7 |
| Other waste | Bio-conversion | Solid | Thermal generation | Electricity grid | Heating and cooling – homes | 4.8 |
| Other waste | Bio-conversion | Solid | Thermal generation | Electricity grid | Lighting & appliances – commercial | 7.4 |
| Other waste | Bio-conversion | Solid | Thermal generation | Electricity grid | Lighting & appliances – homes | 2.5 |
| Marina algae | Bio-conversion | Solid | Thermal generation | Losses in process | Lost | 0.7 |
| Marina algae | Bio-conversion | Solid | Thermal generation | Electricity grid | Industry | 0.5 |
| Marina algae | Bio-conversion | Solid | Thermal generation | Electricity grid | Heating and cooling – commercial | 0.9 |
| Marina algae | Bio-conversion | Solid | Thermal generation | Electricity grid | Heating and cooling – homes | 0.5 |
| Marina algae | Bio-conversion | Solid | Thermal generation | Electricity grid | Lighting & appliances – commercial | 0.8 |
| Marina algae | Bio-conversion | Solid | Thermal generation | Electricity grid | Lighting & appliances – homes | 0.6 |
| Land-based bioenergy | Bio-conversion | Solid | Thermal generation | Losses in process | Lost | 1.3 |
| Land-based bioenergy | Bio-conversion | Solid | Thermal generation | Electricity grid | Industry | 2.5 |
| Land-based bioenergy | Bio-conversion | Solid | Thermal generation | Electricity grid | Heating and cooling – commercial | 3.2 |
| Land-based bioenergy | Bio-conversion | Solid | Thermal generation | Electricity grid | Heating and cooling – homes | 0.7 |
| Land-based bioenergy | Bio-conversion | Solid | Thermal generation | Electricity grid | Lighting & appliances – commercial | 1.4 |
| Land-based bioenergy | Bio-conversion | Solid | Thermal generation | Electricity grid | Lighting & appliances – homes | 0.9 |
| Biomass import | Bio-conversion | Solid | Thermal generation | Losses in process | Lost | 0.4 |
| Biomass import | Bio-conversion | Solid | Thermal generation | Electricity grid | Industry | 0.7 |
| Biomass import | Bio-conversion | Solid | Thermal generation | Electricity grid | Heating and cooling – commercial | 0.8 |
| Biomass import | Bio-conversion | Solid | Thermal generation | Electricity grid | Heating and cooling – homes | 0.3 |
| Biomass import | Bio-conversion | Solid | Thermal generation | Electricity grid | Lighting & appliances – commercial | 0.6 |
| Biomass import | Bio-conversion | Solid | Thermal generation | Electricity grid | Lighting & appliances – homes | 0.2 |
| Nuclear reserves | Nuclear Plant | Solid | Thermal generation | Losses in process | Lost | 50 |
| Nuclear reserves | Nuclear Plant | Solid | Thermal generation | Electricity grid | Industry | 13 |
| Nuclear reserves | Nuclear Plant | Solid | Thermal generation | Electricity grid | Heating and cooling – commercial | 8 |
| Nuclear reserves | Nuclear Plant | Solid | Thermal generation | Electricity grid | Heating and cooling – homes | 6 |
| Nuclear reserves | Nuclear Plant | Solid | Thermal generation | Electricity grid | Lighting & appliances – commercial | 11 |
| Nuclear reserves | Nuclear Plant | Solid | Thermal generation | Electricity grid | Lighting & appliances – homes | 4 |
| Coal reserves | Coal | Solid | Thermal generation | Losses in process | Lost | 4.7 |
| Coal reserves | Coal | Solid | Thermal generation | Electricity grid | Industry | 3.1 |
| Coal reserves | Coal | Solid | Thermal generation | Electricity grid | Heating and cooling – commercial | 4.2 |
| Coal reserves | Coal | Solid | Thermal generation | Electricity grid | Heating and cooling – homes | 0.7 |
| Coal reserves | Coal | Solid | Thermal generation | Electricity grid | Lighting & appliances – commercial | 4.8 |
| Coal reserves | Coal | Solid | Thermal generation | Electricity grid | Lighting & appliances – homes | 0.5 |
| Gas reserves | Natural Gas | Gas | Thermal generation | Losses in process | Lost | 5.1 |
| Gas reserves | Natural Gas | Gas | Thermal generation | Electricity grid | Industry | 8.4 |
| Gas reserves | Natural Gas | Gas | Thermal generation | Electricity grid | Heating and cooling – commercial | 7.9 |
| Gas reserves | Natural Gas | Gas | Thermal generation | Electricity grid | Heating and cooling – homes | 4.8 |
| Gas reserves | Natural Gas | Gas | Thermal generation | Electricity grid | Lighting & appliances – commercial | 7.3 |
| Gas reserves | Natural Gas | Gas | Thermal generation | Electricity grid | Lighting & appliances – homes | 3.5 |
Let’s unleash ChartExpo Add-in on this data.
Follow the incredibly simple and easy steps below to visualize your data using Sankey Charts.
Let’s check out our resulting chart.
Check our resulting chart after editing.
As you’ve seen above in the Energy Flow Diagram generated using Sankey Chart, I’ve cherry-picked the insights that are relevant to the data story. Congratulations if you’ve reached this point. The long but insightful journey is coming to a conclusion.
If you have not installed ChartExpo yet or having any kind of difficulty installing it you can watch out guide to install ChartExpo for Excel next in the blog.
Besides, audiences can get a high-level view, see specific details, or generate interactive views.
Let’s assume you have data from different but interlinked segments. You’ve noticed that there’s a leakage point. And you want to bring this to the attention of your company management.
How would you go about it?
You guessed it absolutely right. A data story is a very powerful tool you can use to persuade the management to act on your recommendations.
But then, how would you make this story irresistible?
You need to use simple and easy-to-interpret visualizations. You don’t want your audience to drown in confusion trying to decode insights from a chart. This is a morale killer.
A Sankey is strategically positioned to visualize the data scenario above. And this is because it can help paint a vivid picture of the leakage in the audience’s minds (in our case, company management). Yes, you heard that right.
This chart will show the exact points where the leakage is occurring. Like we said earlier, leakages, also known as drop-off zones, are flows without a target node.
Choosing relevant and easy-to-interpret charts makes it easy for your audience to understand and engage with the data.
Before we delve right into the tools you can use, we’ll answer the question that’s lingering in your mind.
Where can you apply Sankey Charts for Excel?
Like we said earlier, these charts are strategically positioned to visualize data with flow characteristics, namely:
We’ll later cover energy management use in detail in the coming section. Keep reading to avoid missing this highly insightful part of the blog.
Let’s talk about Excel because it is one of the most used tools for visualizing data besides Google Sheets. This spreadsheet app is incredibly popular because it’s easy to use. Besides, it has been there for decades, making it familiar to almost anyone who works with data.
So how can you use Excel to create Sankey Charts that are easy to read and interpret?
Remember, for a data story to be compelling to your target audience, it should have charts that lend clarity. You don’t want any critical insight to be obscured by unnecessary stuff, such as heavy colors.
We’re sorry to disappoint you, but Excel does not have Sankey templates.
Yes, you heard that right. Even Microsoft Office 365, which is the most updated version, doesn’t have Sankey templates.
The solution is not to ditch your beloved Excel. No, we’re not advocating you to do away with the spreadsheet tool you’ve probably known since childhood.
You need to supercharge it with an add-in to make it a reliable partner for data visualization.
Microsoft knew very well it’s impossible to cater to all the data visualization needs you may have. And that’s why they came up with an app store where you can access third-party add-ins to get various specialized tasks done with ease.
Well, there’s a reliable and incredibly easy-to-use add-in called ChartExpo. And it comes jam-packed with Sankey templates and other 80-plus charts.
ChartExpo is a cloud-hosted add-in that transforms your Excel spreadsheet app into a highly responsive data visualization tool.
Wait! That’s not all.
This highly affordable data visualization tool comes with over 80 chart templates to grant you a broader choice of visuals to select. With ChartExpo, you don’t need to know programming or coding. Yes, it’s that easy peasy to use.
When you’re curating a data story, feel confident you have a reliable data visualization buddy on your side. ChartExpo provides you unlimited freedom to customize your Sankey Chart.
Remember, you can highlight the key insights you want your audience to take in with ease. You just need a few mouse clicks to access a Sankey Chart for Excel that fits seamlessly within your data narrative.
Let’s head to the meaty part of the blog: the section where you get to practice what you’ve learned. Follow the simple steps below in preparation for the next section.
To Get Started with ChartExpo for Excel add-In, follow the Simple and Easy Steps Below.
Now you have a clue about why data stories matter to you, let’s delve into its core building blocks.
Selecting the best visualization possible to highlight key insights in a narrative depends on your goals. Yes, it depends on the key takeaway you want to communicate to your audiences.
If you’ve ever been a victim of boring, long, and disorganized presentations and meetings, raise your hand.
We’re kidding, just give us a slight nod.
Well, one of the biggest fails in storytelling with data is the use of charts haphazardly. Different charts come with different uses. So your choice of data is influenced by multiple factors, such as the target audience type, nature of the data, and most importantly, the main goal.
Data storytelling needs context. Yes, it requires an understanding of the circumstances that surround each metric (variable). These circumstances (usually in the form of related data sets or events) shed light on information that would otherwise be nothing more than rows of numbers in a spreadsheet.
Essentially, context turns facts into actionable information and – in the end – decisions that have a positive impact on your business or company.
Simply put, the context of your data environment is the situation that created the data.
Let’s say you’re in the education sector. If you’re drawing enrollment data from multiple universities, each campus is its own data environment. If one university increases funding for scholarships while others don’t, that school might see increased student enrollment and retention.
When comparing that particular school with others, it’s important to take those environmental factors into consideration to gain a better understanding of your data and its implications.
So creating contextual labels provides guidance for your audience.
Creating context, therefore, is your responsibility, as a data storyteller. There are many methods to create context (labeling, chart choice, color, etc.). Remember, a line graph and a scatter chart can hold the same data but communicate different ideas.
The key is to understand what you need to communicate and then find the right visual elements to convey it.
Ask these questions: what is the message, and what base information does my audience need to understand that message? If, for example, you need your audience to understand why website traffic suddenly increased, consider a month-over-month graph and an area chart to help them understand. By illuminating different angles of the same information, you give your data context and – most importantly – help your audience see the context.
We’re sure you get motivated to tell your story more and more if people are listening. Yes, the listening factor matters a lot to the progress of any story.
Just imagine trying to communicate a story to people who aren’t paying attention.
It hurts, right?
In data storytelling, you can refocus your audience’s attention to particular insights with strategic use of colors and the size of the chart.
Take a look at the screenshot below: Can you spot the two-digit number repeating in the cluster of numbers shown below?
Now, answer the question above using the screenshot below. Which two digit repeating numbers are there in our data?
Of course, it’s easier to spot the answers. And this is because of strategic highlighting of the details we want you to see. Similarly, you should deploy this strategy of highlighting the insights you want your listeners to take home when storytelling with data.
Rather than let your audience do all the work, make the findings easier to cherry-pick with strategic use of colors.
And this brings us to the other crucial element that can make or break your data story.
The key takeaway is the theme of your presentation. Essentially, this is the part that answers the ‘So what?’ question.
For instance, you’ve just discovered that sales in March and April have declined. What would be the key takeaway for the scenario above?
“In March and April, our sales declined 25%, thereby erasing all the gains we made in the third quarter because:
We should investigate further into the product development process to know the cause of the money-draining problem”.
For you to create a compelling big idea, you’ve got to know your presentation very well. And I mean inside-out. The section can boil down into a sentence or a paragraph.
And this brings us to the critical part of your data story: the action you want your audience to take.
Insights have little value if you don’t recommend action, such as whether to invest or divest.
Providing actionable information is, after all, the goal of good data visualization and storytelling. And it’s thinking through the layers and making sure there’s continuity between where your story starts and its ending.
After doing all this, how do you make your story compelling?
This other section provides you with the fundamental building blocks of a story.
So how can you tell a story with your data?
Use the steps below to get started.
The first step to telling a good data story is to uncover a story worth telling. And you can start by asking a question or forming a hypothesis, then compiling and digging into relevant data to find answers.
As you consider your data story, ask:
There are several ways to approach data to uncover a story—and the story you set out to tell may not end up being the story you find. As you analyze your data, consider using the following approaches to help you identify a theme and develop a structure for your story:
What connections do you see between data? And are there interesting or surprising correlations?
These relationships can provide a compelling foundation for a story.
Let’s talk about trends.
For starters, trends indicate the direction of change.
It can go either upwards or downwards. For example, is there growth in a particular product or service your business offers? Or maybe you want to know your website traffic patterns over time—you may discover that certain days or times tend to be higher or lower volume.
Identifying new or evolving trends in your data is crucial.
Outliers are one-off occurrences you may spot in your data. And data that doesn’t fit in with the rest of your data settings can be just as valuable for you. Look for outliers and ask questions. Besides, pay attention to any data that is counterintuitive or surprises you.
Always be aware of your audience when developing and sharing your data narratives. And if the story you want to tell isn’t relevant or interesting to your intended audience, it won’t have the impact you want.
As you build your data narrative, ask yourself:
Your audience’s age, demographics, job, and subject matter expertise influence how they understand and respond to your stories. Besides, it should inform how you tell your narrative.
So if you’re speaking to a room full of engineers, you may want to provide more technical details and dig into the data sets more thoroughly as you tell a story. However, an audience of executives will likely be looking for simplified data with clear insights.
Develop a habit of customizing your story and approaching it from different angles depending on your audience.
Lastly, a good data story needs visuals. Charts, such as Sankey Charts for Excel are a powerful way to engage your audience and improve retention—especially when communicating with non-technical audiences.
Visualizing your data story enhances understanding at every level by simplifying the information, highlighting the most important data, and most importantly, communicating critical insights quickly.
There are many ways to visualize your data, including:
So how can you tell a data story with Sankey?
This section is full of golden tips and strategies that can take your data storytelling skills to the next level. Yes, the level where you move audiences without struggle or breaking a sweat.
So why is data storytelling important?
Data without a story lacks impact for two reasons, namely:
The data seldom comes distilled. And this means you don’t necessarily need more data to solve your problems or uncover opportunities. But you do need to identify and communicate value from the data you already have.
Secondly, data on its own cannot support your key takeaway. And this makes it difficult for our audience to grasp the actionable “news” it brings quickly.
We live in a world characterized by information overload, ads, and trend news. So it takes strategic use of emotional triggers, such as captivating narratives, to capture their full attention of the target audience.
So if you have numbers and want to explain their changes to any form of the audience (including engineers): use stories. And you’ll find your audience taking action you desire at the end of it all.
Like we said earlier, numbers without stories are pretty much noise. So if you want your audience to tune their ears to you, you need to arouse their emotions. Stories have been tested and proven to do so.
Use stories to transform your data into actionable insights to empower data-driven decision-making in your organization.
So let’s agree that numbers without captivating narratives are pretty dry and less attractive to audiences. And this brings us to the other crucial benefit.
One of the core ingredients of a compelling story is simplicity in details. You might have stumbled upon a fascinating insight in your data that either communicates opportunity or impending risks.
But your problem is to share these insights with the decision-makers for action-taking. Use data narrative for a change. There’s no doubt that stories can lead your audiences in the direction you want.
This implies that if you use this visualization strategically to support your data story, you’ll move audiences in the direction you want. As Aristotle put it thousands of years ago, the building blocks of a persuasive narrative are logos (appeal to logic), ethos (appeal to emotions), and pathos (personality). Charts, which transform abstract numbers into insightful diagrams that appeal to the logic part of our brains.
For you to nail your data story, you have to get the chart part right.
You see, the human brain processes visual content over 60,000 times faster than texts and numbers. And this creates a strong case for incorporating relevant visuals into your data story.
Storytelling with data can be intimidating, especially if you’re not an expert in data visualization. To create a compelling data story, you need a strategy, a plan, a thesis statement, and most importantly, an easy-to-use visualization tool.
In this blog post, we’ve rounded up thought-provoking tips, how-to strategies, and other ingredients to help you craft compelling data stories using Sankey Chart for Excel.
These tips are tested and proven.
We use them to create compelling and actionable narratives for our clients, presentations, and meetings. And every time we use them, we get an overwhelming response.
We hope you’ll gain immense value from the blog.
Excel spreadsheet does NOT have Sankey templates. To create a Sankey chart in Excel, start by installing an external ChartExpo Add-in. And then, browse to find the Sankey chart. It’s the first chart in ChartExpo’s ultra-friendly user interface. Use this chart to visualize flows and processes in business settings.
Now it’s possible to create a Sankey chart using ChartExpo Add-in for Excel. No matter how complex your data is, you can trust Sankey to get the job done.
ChartExpo provides you with unlimited freedom to customize your charts to highlight key insights supporting your data story.
Yes. You can achieve this by downloading and installing ChartExpo Add-on in your Google Sheets. And this is because Google Sheets lacks chart templates for Sankey. This version of ChartExpo (Google Sheets Add-on) is the same as the one for Excel with regard to the user interface. You can also refer to our guide on Sankey Diagram Google Sheets to create Sankey Chart.
If your data represents some processes, transfer flows, and relationships: then Sankey is the best option to use for your data story. You can use this chart for visualizing the following classes of data:
First, you need to identify the Sankey categories. These categories can be read from either of the sides: left to right or right to left.
Typically, we read everything including books and charts from the left side. We suggest you read charts including Sankey from the left.
Sankey diagram was named after Irish captain Captain Matthew Henry who first used this diagram in 1898 to visualize the energy efficiency and losses of a steam engine. Initially, these charts were confined to engineering fields. But now you can use them to visualize various aspects of the business.
Sankey Charts for Excel is among the best charts you can use to make your data narrative irresistible to your audiences. This chart is amazingly easy to read and interpret. You can bet on it to highlight the key insights supporting the thesis statement of your data story. You can draw this chart with very easy steps by using ChartExpo library in Excel.
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