Hard numbers are the basis of most good business decisions, but it’s not always easy to draw insights just by looking at a spreadsheet or table. Data storytelling takes raw data and turns it into a narrative that any manager or executive can understand and act on.

Data analysts play an important role in storytelling by providing context that turns data into more than dashboards, spreadsheets, numbers and charts. Here’s how your company can use data storytelling to improve business results.

What Is Data Storytelling?

Data storytelling is the art of turning data into insights. It requires three things: data that is both complete and up-to-date, a tool that makes it easy to combine data and produce compelling visuals and the ability to add a narrative. Modern ERP, accounting and other business systems can provide relevant data, while visualization tools that plug into many of these systems help with dashboard creation. Often, it’s the narrative that trips companies up.

For example, talent analytics is growing in popularity. A company may have the right data, such as employee net promoter scores, effectiveness of various recruitment methods, turnover rate for all workers and high performers, revenue per employee and training costs. It may also have the right software to enable employees to pull this data into a customized dashboard. But unless an HR specialist with data analysis skills adds a narrative that transforms the data threads into a cohesive story, decision-makers may miss out on critical insights.

Data science typically involves working with large databases and spreadsheets to find meaningful trends and opportunities for improvement. But data scientists, often focused on math and programming, may not bridge the narrative gap to fully meet the needs of marketers, sales managers and executives.

Businesses that combine data science, visualizations and data storytelling are in the best position to grow revenue and pull ahead of competitors.

Key Takeaways

  • Data storytelling is the process of turning raw data into a narrative that business owners and managers can use to make informed decisions.
  • Data science requires math and analysis skills, but datasets may still be difficult to interpret by non-experts.
  • Combining data, visualizations and narrative leads to the best business decisions and results.

Data Storytelling Explained

To further our HR example, say a company is running into problems recruiting talent for important midlevel positions. Executives want to know how current employees view the company, which affects whether they will recommend it as a good place to work. They also have questions about what actions HR is taking to find viable candidates.

HR is able to access accurate, real-time recruitment metrics and construct dashboards within the company’s human resources management system. But it takes a skilled subject-matter expert to add narrative context to help executives understand that the answer may be more emphasis on training and promoting from within, which increases productivity and retention.

infographic internal recruiting

How Does Data Storytelling Work?

Data storytelling relies on the three-legged stool of data, visualizations and narrative to fully explain a trend or concept and back up conclusions with metrics or KPIs. Success may require bringing together feeds from multiple software systems and external sources as well as members of various teams. When implemented well, data storytelling can yield excellent business results. For example, a compelling data story can motivate people to take an action they may consider counterintuitive because they perceive it as being backed by metrics.

Now, let’s dig into the three must-have elements of a data story that drives better decision-making.

Three Components of Data Stories

A successful data story relies on three main components. The combination of these elements animates data in new and exciting ways.

  1. Data: Today’s companies run on data. When cataloging data sources, look to core business applications, including ERP, financial and HR management systems. Query relevant departments about the KPIs they track, and see what data sources contribute; as an example, recruiters likely track sourcing channel cost, which measures the cost of posting and advertising open positions on various channels compared with the number and quality of applicants, broken down by channel. For our hiring conundrum, you might find that the cost of recruiting viable candidates isn’t too far off the cost of putting a solid internal prospect through some training courses that would provide the skills needed to take on the new role.

    And remember, stories needn’t be limited to internal data. Our HR team might turn to salary sites and the U.S. Bureau of Labor Statistics to supplement what they can learn from their HR systems.

  2. Visualizations: Once you’ve identified the data to be included, it’s time to create tables, charts, graphs and other visualizations; these may include advanced views and pivot tables to summarize and aggregate source data. Don’t skimp on visualizations — as they say, a picture is worth a thousand words. You can often tell much of your data story with visuals before reaching for the keyboard to create a narrative.

  3. Narrative: Here, subject matter expertise trumps writing skills, at least on the first draft. A best practice is to pull in an employee skilled in written communications but not familiar with the question being answered. This served dual purposes: To check that the SME made a clear case and by suggested edits to make the story simple, concise and straightforward.

    Remember: The goal of a data story is to deliver information clearly and persuasively.

Where to Get Data Stories?

Unlike big newspapers and magazines, no assigning editor is handing out data story assignments with useful insights for success. Many data scientists, marketers, analysts, accountants, salespeople and operations managers use their own creativity and a combination of sources to create data stories.

Internal data story

sources include your core business systems, like ERP, HR, CRM and financials, where you can find useful dashboards and drill down to larger datasets. But look also to marketing and sales tools. You can examine a variety of data types, including analytics, finances, customer databases, inventory and supply chain, operating results and more.

External data

can come from large, public databases and paid private sources. Common public data sets include publications from the Bureau of Labor Statistics, Census Bureau and academic sources. Paid databases may offer industry-specific, competitive analysis and cutting-edge data not available elsewhere.

Be creative — nowadays, there is generally a source for pretty much any information companies may want.

Why Is Data Storytelling Important?

Not every report needs this treatment, but data storytelling can be invaluable in situations where you want to issue a persuasive call to action, build empathy, connect to a specific audience or facilitate high-level decision-making. In these cases, telling a customized story that an audience can relate to may be much more effective than simply handing over another spreadsheet or dashboard.

As any sales professional will attest, when decision-makers understand and empathize with the subject, they are more likely to respond favorably. Whether you are presenting to a new client, a department head or a potential funder, data stories are among the most effective ways of delivering a meaningful, data-backed message.

Data Storytelling vs. Data Visualization

Data storytelling isn’t the same thing as data visualization. However, the two often go hand-in-hand.

Data visualization is the process of converting data into a graphical form. Graphs, charts and other pictures that tell you something about the data at hand are considered data visualizations.

Manufacturing Employment: Slow Growth, Skills Shortage

This chart is an example of a visualization comparing GDP and employment in the manufacturing sector. While it does have some valuable information, there is little context.

Data storytelling weaves written or spoken narrative with data visualization.

How Can Companies Use Data Storytelling?

Businesses can use data storytelling in a variety of ways. Here are a few examples:

  1. Sales: When analyzing sales order data to see how often customers buy two products at the same time — an increased frequency could help you tell the story of why you should bundle products and run a promotion.

  2. Management reporting: When creating internal reports, data storytelling can help executives and non-technical colleagues understand nuanced industry or technical data.

  3. Investor reports: When fundraising or telling your story to a private equity house, VC firm or even your local bank, reports that combine data, graphics and storytelling can make you stand out. Many CEOs lean on data when writing their annual letters to shareholders, yet another form of data storytelling.

Benefits of Data Storytelling

Data storytelling is most useful when trying to persuade someone or when you need to reach a broad audience. Many companies regularly use stories in their social media and blogs to engage potential customers and community stakeholders. Adding in data gives those stories more credence than words alone.

When you craft a high-quality and compelling story, your ideas and concepts may begin to sell themselves.

Industries That Use Data Storytelling

In the 2020s, it may be easier to point out industries that don’t use data storytelling than industries that do. Data storytelling can be used in virtually every corner of the economy.

Some fun uses of data storytelling engage readers and tell them something novel and informative. Education and entertainment combine to make stories more memorable and impactful.

One of the best known types of data storytelling comes from data journalism, stories that rely on big data or incorporate interactive features. In many industries, data storytelling reports are private and confidential, so there’s not too many you can look at around the web.

However, examples could include data maps that help oil and gas companies decide where to explore and drill, manufacturing reports that explain production and shipping times to identify areas for improvement, or a telecommunications company mapping out office buildings with a large number of workers close to its existing network.

How to Tell a Great Data Story

Manufacturing Employment: Slow Growth, Skills Shortage

If you are looking to tell a data story, follow these steps to get started:

Determine what question you want answered:

Make sure that the problem the company needs to solve is clearly articulated. Asking, “Why are we having trouble hiring good people?” will yield a less useful story than, “How can we best fill these specific midlevel positions?”

You may find that you need to split the problem into a few separate but related data stories.

Determine what data is needed to answer the question:

In our example, HR might gather referral and turnover rates, experience of applicants versus existing staff, training costs and a grid of required skills for the open positions. If your company employs data scientists or analysts, take advantage of their expertise and knowledge of business data.

Identify your data sources:

As discussed, stories needn’t be limited to internal data. Our HR team might turn to salary sites and the U.S. Bureau of Labor Statistics to supplement what they can learn from their HR systems.

Determine your visualization options:

Companies may have embedded reporting tools that pull business intelligence (BI) capabilities into core applications, like ERP, financials and HR, and present data in customizable charts. Or, they may need to do some manual construction of charts. The key is to work with the person who will be writing the narrative so the visuals support the story.

Construct the narrative:

Once you’ve collected your data and put together some useful charts, adding a creative written or spoken narrative is the final step in creating your data story. The narrative can be text, but also consider a video if your company has that capability.

Are you looking to tell a story with business data? It may be just a few clicks away. If you use a robust, cloud-based enterprise resource planning (ERP) system like Oracle NetSuite, you and your team can securely access your company’s data and resources with built-in data warehousing and storytelling capabilities, from anywhere in the world, with an internet connection.

Whether you’re sitting at your desk, jetting across the world with your laptop, or need to pull something together with a teammate before a big meeting, data storytelling may be your best solution. When you have the best tools and systems, data storytelling is an easy way to improve your business.

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Data Storytelling FAQs

What is a data story?

A: A data story is a narrative supported by graphics and backed by data.

Are dashboards data storytelling?

A: Dashboards are a useful form of visualization, but they are not data storytelling. Data storytelling includes a written or spoken story that accompanies numbers and charts seen on dashboards.

What are the 4 P's of storytelling?

A: The four Ps of storytelling are people, place, plot and purpose. These are common elements of a successful story and can be incorporated in a data story.

How do you create a data story?

A: To create a data story, find a data source that includes a compelling, interesting or important trend or datapoint. Write or tell a story to explain what that data means and how it works. That is the essence of a data story.

How can data tell a story?

A: Data may not tell a story on its own. When transformed into a combination of visualization and narrative, however, data can tell the story of a business’s revenue, profits, cash flow, sales and much more.