Why Leaders and Teams Need This Essential Skill

The Duarte Guide to Data Storytelling

Data storytelling is a communication skillset that transforms complex data analysis into a compelling story that drives audiences to understand and act on a clear recommendation. By using a simple beginning, middle, and end story structure combined with succinct visuals, data storytellers aim to quickly reveal why the data is important and articulating what’s at stake for decision makers.

Illustration by Aisling Doyle

It seems every news cycle announces how the world of work is changing. But as thought leaders weathervane to track each emerging claim, macro trends continue to crystallize. Where the rise of Big Data enabled savvy teams to parse signals through the noise, communicating your findings with a clear message requires the right skillset.

At Duarte, we believe telling stories with data is the best way to unpack its significance and help organizations make better decisions faster. It’s about presenting recommendations backed by data that audiences can understand at first glance. Learning how to tell effective stories with data was once a nice skill to have; But data’s growing ubiquity in everyday life is making data storytelling a necessary strength.

And guess what?

The data backs this up.  

The U.S. Bureau of Labor Statistics predict that by 2033 the demand for operations research analysts, information security analysts, and data scientists will increase by 23-36%. The picture is clear: We’re experiencing an upward trend in data-centric employment. From tracking the health of an industry to navigating buyer sentiments, data-related roles are indispensable for success across b2b and direct to consumer markets. And over the next decade, communicating with data and articulating key takeaways will be an increasingly essential skill.

But here’s the takeaway: With data-derived jobs and insight on the rise, data storytelling is more important than ever.

This shift suggests a greater reliance on data literacy across a range of industries, and with it, leaders who can name emerging trends, communicate actionable recommendations, and make confident data-backed decisions. For anyone looking to take center stage or drive change at their organization, data storytelling should be considered a prerequisite.

Easy right?

The good news is any skill is achievable with proper training.

And learning how to tell compelling stories with data is no exception.

DataStory: Explain Data and Inspire Action Through Story by Nancy Duarte is the book that started it all, and the perfect spot to begin an analog journey toward telling your first data story.

Otherwise, buckle up for an extensive deep dive into the multiverse of data storytelling as told by Duarte. This article will follow the table of contents below, but feel free to jump ahead to any topic by clicking the link.

Ready?

Onward.

Table of Contents

What is a Data Story?

What is Data Storytelling?

What is a DataPOV™?

Effective Data Storytelling

Visual Data Storytelling

Data Storytelling Examples

Data Storytelling Techniques

Data Analysis vs. Data Storytelling

Persuading with Data Storytelling

Making Data-Driven Decisions

Who Benefits from Data Storytelling Training?

Data Storytelling for Leaders

Data Storytelling for Teams

Data Storytelling Training

How to Find a Data Storytelling Course

How to Find Agency Data Storytelling Services

What is a Data Story?

Put succinctly, a data story is a story told with data. Where traditional narrative storytelling emphasizes character development and plot, data stories find a data point or trend and communicate clear recommendations to influence the trajectory of that trend.

Data stories can derive from analytics related to:

• Sales, expenses, and revenue
• Market sentiment
• Share of voice/influence
• Customer satisfaction, social media engagement, and churn rate
• Hiring, HR, and employee retention
• Click-through/open rates, site health, and web traffic.

Any metric your organization is tracking can be explained with data storytelling. In other words, a data story uses familiar narrative techniques to turn data-backed observations into digestible, data-backed recommendations for actionable, informed decision-making.

Data stories use clear, concise language to:

• Identify and explain emerging data trends,
• Reveal opportunities or risks based on informed analysis of data,
• Propose actionable recommendations to mitigate or enhance the effects revealed in the data.

To carry out this sequence, data stories rely on three-act structures with a beginning, middle, and end to make a clear, data-backed recommendation. This is called data storytelling.

What is Data Storytelling?

Grammar heads will be shocked to learn that data storytelling is the act of telling a data story. More specifically, data storytelling applies narrative elements to explain what data means and inspire people to take a prescribed action. Once you’ve clocked an emerging trend or crunched enough numbers to reveal a potential action, data storytelling sets the stage and provides your audience with the evidence to move forward confidently based on your findings.

By using a classic three-act storytelling structure, data stories:

1. Establish the stakes in the beginning, or first act; 
2. Introduce a problem or potential opportunity in the middle, or second act; 
3. Propose a clear course of action in the resolution, or third act.

This progression is the life cycle of a data story.

Another key part of data storytelling is identifying who (or what) should be telling the story. Depending on the data trend you’re analyzing and the needs of your target audience, this element can vary. A story told with data can center around a particular department, customer segment, industry, or individual depending on its focus.

Watch → An Introduction to Telling Data Stories

Thoughtful perspectives give data stories a point of view (POV) that uses data to illustrate the stakes of taking or not taking a particular action. When framed purposefully, audiences are more inclined to see themselves in the data trends and outcomes. By establishing a clear DataPOV™ from the jump, effective data storytellers set the stage with context to reinforce their recommendation.

As a refresher, let’s revisit how POVs are used in storytelling, and explore how a DataPOV™ serves as the throughline of an effective data story.

What is a DataPOV™?

Along with the narrative structure outlined above, a DataPOV™ is the backbone of a data story. When chosen wisely, a DataPOV™ can help communicate actionable recommendations to executives, department heads, and leadership teams by framing the problem from their perspective.

Illustration by Aisling Doyle

At a basic level, every story is told from someone’s (or some-thing’s if we’re getting experimental) POV. Whether a story is told via a first-, second-, or third-person perspective, every narrative structure has a direction in which the story unfolds. Here’s how they breakdown:

First-person

• First-person stories are told from the “I” perspective of a particular character, either in the story or recounting the tale in hindsight.
• A notable example is the iconic opening line of Moby Dick, “Call me Ishmael,” which immediately sets up who’s telling the story.
• In business, a first-person POV can help build trust and authority by projecting confidence and connecting with customers directly on a human level.

Second-person

• This approach addresses the reader as “You,” placing them inside the story.
• It serves as an immersive technique in fiction, most notably in “Choose your own adventure” stories, but can also be a potent tool in persuading the reader or audience toward a specific action.
• In marketing and sales, a second-person POV speaks directly to the customer or buyer. This can be an ideal framing for unique pain points and reveal potential opportunities in choosing your product, service, or solution.

Third-person

• Third-person narration addresses characters as “he,” “she,” or “they,” and never in first or second person pronouns. However, the mode in which this style is applied can vary as follows:
  • Omniscient: This refers to an over-reaching perspective that knows everything about the characters’ thoughts, feelings, and time in which the story is set. This is most common in classical literature.
  • Limited: While still “all-knowing,” this approach is confined to the thoughts and feelings of one character, also known as close third-person.
  • Subjective: Like limited, this technique expands its circle to describe the thoughts and feelings of one or more characters in a story with the same depth and detail, but not the world in its totality.
  • Objective: While still “all-knowing” in terms of its view on the actions in a story, objective third-person does not reveal the thoughts and feelings of the characters involved, and presents an unbiased, judgement-free account of the story’s movements.
• Third-person storytelling is ideal for creating hypothetical situations to show how your product or solution can apply to a wide range of situations.

In the case of a data story, the task falls on the data storyteller (you, your sales team, your leaders, etc.) to give shape, contour, and direction to some subset of data points. Likewise, a data story combines a compelling POV with real-world stakes to reveal opportunities behind the numbers. By combining these two elements, a DataPOV™ shows how the world reflected in the data could change course if certain trends were acted upon or ignored.

Free Resource → Branch Out Your Data Decision-Making With Duarte’s Recommendation Tree

For example, imagine your app that allows homeowners to hire bespoke yard work services from community members is underperforming with younger demographics. To help explore potential solutions, you could frame a data story from a first-time homeowner’s perspective to highlight their preferences and learn how they’re most likely to encounter (and trust) your brand.

Alternatively, a data story told from the company’s perspective could highlight the opportunities or risks involved in mending or further damaging customer relationships. In this case, should your app prioritize older users to drill down on current success, or pivot to secure broader generational appeal? With clear language and ample evidence, either approach could yield an effective data story.

Depending on what you’ve parsed from the data, taking decisive data-backed action can affect the success of a product launch, reinvigorate user engagement, boost revenue, and even pivot entire industries toward a new trajectory. Finding and acting on the right opportunity in a data set even has the potential to domino toward monumental change.

In short, the power of an airtight DataPOV™ delivered over three acts provides an opening to define the stakes of your data story and guide the audience toward a desired takeaway. For those familiar with the broader Duarte universe, this is the Big Idea of your data story.

Put another way, consider the following:

Once you’ve set up a clear DataPOV™ and backed it up with defined stakes to highlight your data story, it’s time to spin the yarn. Let’s examine some examples of data storytelling and what makes it effective.

Effective Data Storytelling

As with any skill, there’s a gulf between doing something and doing something well. Learning how to tell effective data stories is no different. Effective data storytelling uses a variety of approaches to nudge a target audience toward taking a recommended action.

There are countless ways to tell a story with data. But the task of an effective data storyteller is to decide what your audience needs to hear to understand and act on your data observation. Once you’re confident in the action needed following careful analysis, it’s time to consider the audience for your data story.

Watch → How Effective Data Storytelling is Reshaping a $1.5T Industry

Everyone learns differently. Across departments, engineers and data analysts thrive on hard numbers. Meanwhile, leaders and decision-makers prefer information presented alongside clear stakes and solutions. Whether presented live or shared via a well-designed takeaway or leave-behind, an effective data storyteller assesses who their audience is and how they’ll engage with the information before plotting their data story.

To help guide your data storytelling, consider the following questions:

• Who is the target audience for my data story?
• What are their motivations?
• What is their relationship to the data being presented?
• What biases or preconceived notions may my audience have about the information or data trend?
• What’s at risk for them personally/professionally in hearing and/or reacting to the information?
• What do they stand to gain by taking decisive action?

By applying bespoke considerations to your data story that address audience concerns and preferences, the more effective your data story will be in delivering its message. To this end, another key element is design.

Visual Data Storytelling

Helping your audience visualize data is another cornerstone of effective data storytelling. This includes everything from how data is represented—whether by charts, graphs, or infographics—along with the look and feel of your overall presentation.

Using visual components in data storytelling can help:

• Illustrate risks and opportunities from data trends
• Highlight key takeaways that inform your recommendation
• Orient your audience toward actionable decision-making
• Bring potential outcomes into focus

Illustration by Aisling Doyle

Bar graphs, pie charts, line charts, and a variety of images can all be tailored to communicate the urgency of taking data-backed action. To help streamline data visualization, here are three steps to consider:

Select what chart type to use

Choose the type of chart that makes your point most effective and clear. To compare static values side-by-side, a bar graph might be the best bet; for tracking a trend over time, a line chart might be appropriate. Or to compare resource allocation from a budget, a pie graph or infographic could help drive your point home.

Read → 5 Secrets to Displaying Data in Presentations

AI-enabled tools like Microsoft BI or Tableau can help recommend a chart type and even propose an observation to make. Keynote or Microsoft PowerPoint even allow you to import your data to create an array of charts and graphs, and toggle between them to choose the best one. However, it’s essential to always double check the accuracy of any AI-generated or optimized work before passing it along as your own.

Emphasize the most important part of the chart

Whether using the observation recommended by an AI tool or your own critical thinking (*gasp*), next you’ll want to visually emphasize the most important part of the chart. You can do this by applying a contrasting color to a bar or data point to make it stand out. This visual emphasis will pull the reader’s focus to that data point without losing sight of its framing and context.

Write a data observation as the title

Craft a short, concise insight gleaned from the chart and use it as the title of your slide. Some consulting firms put the key insight at the bottom of the slide as well. The objective here is to make your point visually clear and prominent. In other words, audience members should be able to grasp your key takeaway after a quick glance.

Free Resource → Do Your Data Slides Pass The Glance Test™?

When presenting data analysis to an audience, you might only need one chart to create a compelling recommendation. However, most “hairy” business problems involve a collection of charts from multiple data sources to determine a clear path forward.

For example, consider the bar graph below and how design best practices dovetail with the above framework to elevate the data’s reception. This approach showcases how data visualization can emphasize a key point for prompt audience clarity:

By ensuring the title of the slide clearly articulates your data observation, the audience will know the problem or opportunity you’ve discovered. This is further refined by the chart title, which can reinforce or sharpen your scope. Then, the color gradient helps guide the audience’s understanding of the data. Notice how the highlighted bar stands out among the other greyed metrics without losing the overall context they provide. This will ensure the audience is properly informed to act confidently based on your data-backed recommendation.

Implementing data storytelling standards can ensure proper data visualization and branding are applied every time. By providing brand guidelines outlining approved colors, logos, and fonts, organizations can align their data storytelling for internal and client-facing purposes. Below, Ken Holsinger, Senior Vice President of Strategy at Freeman, unpacks why data storytelling standards are essential for uniform messaging and brand success.

Watch → Why Brand Guidelines Should Include Data Storytelling Standards

With this foundation of the verbal and visual elements of data storytelling, let’s explore how all this can come together to spark real change. The following examples of data storytelling help illustrate how design and proper framing can urge audiences to act.

Data Storytelling Examples

Effective data storytelling aims to inform an audience and move them to act. Whether in-person, onstage, or connecting via an online platform, there’s no limit to how stories can be told with data. Examples of data storytelling include corporate keynote addresses, informative lectures, and even snappy memes shared on social media. Put another way, telling stories with data is only limited by the creativity and innovative spirit of the storyteller.

Watch → Overcoming the Odds: Why Data Needs a Storyteller

To better conceptualize data storytelling in action, here’s an example of an effective marketing data story:

Or for those in product development, here’s a three-act data story exploring customer UI:

This simple structure is the perfect jumping off point for building a polished pitch deck that reinforces the Big Idea of your data story. Below are just some of the ways Duarte has helped enterprising data storytellers amplify their message with a clear, concise, visually enhanced approach:

Al Gore’s An Inconvenient Truth

• The former Vice President contacted Duarte to sharpen troves of climate data and a pressing urgency into a focused pitch for why saving the planet is essential for humanity’s survival. By highlighting uncomfortable statistics with striking metaphors and interactive visuals, Gore’s data presentation invited the audience to understand the stakes from a vantage point of dire personal investment. An Inconvenient Truth won Best Documentary Feature Film at the 79th Academy Awards. Read the full case study.

Freeman’s XLNC Quarterly Event Attendee Trends Report

• Creating moments that matter at events and tradeshows is Freeman’s bread and butter. But when it came to urging a reluctant industry to adjust its posture for a post-COVID world, Freeman knew they needed to get the messaging just right. Duarte collaborates quarterly with Freeman to tell compelling data stories centered on the experience of conference attendees. With rich, textured visuals that illustrated the report’s data-backed insights, Freeman found a data storytelling agency partner to articulate a bold vision for fine-tuning the future of live events. Read the full case study.

Cisco’s RSA Conference Documentary Brought Their Connected World Technology Report to Life

• Using a classic person-on-the-street format, Duarte reimagined eye-popping statistics from Cisco’s 2011 World Technology Report to serve as a visual during their RSA event. The video tells a compelling data story by juxtaposing real human behavior alongside the report’s findings. As each person admits to cutting a corner around their workplace’s IT policy, data points superimpose over their silhouettes accompanied by a tonal shift in the music. The end result drives home how seemingly innocuous behavior can make users and companies vulnerable to a battery of security breaches. Read the full case study.

After showing the hallmarks of effective data storytelling, let’s explore some of the techniques that data storytellers use to inspire action.

Data Storytelling Techniques

There are plenty of reasons why companies collect and synthesize data. Perhaps you’re tasked with surveying the landscape before a product launch or testing the winds for direction on a new strategy. The amount of available data can feel overwhelming. Thankfully, a few helpful data storytelling techniques can provide critical tools to overcome “analysis paralysis” and arrive at a clear course of action. That’s why telling an effective data story starts with organizing your data.

Read → 3 Strategies Brands Use to Communicate Data

Nancy Duarte’s book DataStory outlines the best data storytelling techniques to achieve a laser focus. Here’s what to keep in mind to craft and communicate your data story:

Identify the focus of your data story

• Whether you’re tracking website traffic, click-through rates, sales metrics, customer retention, or user sentiment, narrowing the scope of your inquiry can reveal the “hero” in the data, and any obstacles they might be facing. For instance, the hero of a data story can be the action or group generating the data or whomever has the decision-making power to influence the way it’s trending.

Talk to the people behind the data

• We know talking to people can be scary. But facing a fear in service of better data storytelling will make the end result all the more deserved. Just conducting a few quick interviews with or sending a brief survey to the folks generating the data can help understand their motivations, challenges, and goals. This could require contacting customers or those in other departments depending on the data you’re investigating. This will help you craft a message that speaks to their unique needs with empathy grounded in first-hand knowledge.

Illustration by Aisling Doyle

Identify and address the conflict

• This data storytelling technique is all about finding an opportunity in the data. For Nancy, this is the tension of what is vs. what could be. By describing the world as it is, data storytellers provide foundational context that helps reveal the opportunity or risk in their observation. Meanwhile, the what could be portion demonstrates how your recommendation can help decision makers close the gap. In short, it’s about making the what could be a reality.

Share context

• This is the so what? of your data story. As a data storyteller, you’re the subject matter expert on why this action must be taken. It’s your job to provide background information that helps your audience understand and care about the data. Use comparisons, analogies, metaphors, visual aids, or any other rhetorical devices to make the data accessible, clear, and memorable.

Present the data as a recommendation

• Don’t just show the data; guide your audience toward arriving at your conclusion. This will educate decision-makers about the issue and lend urgency to your course of action. Structure your recommendation using clear and concise language based on evidence gleaned from your data analysis, stakeholder interviews, etc. This will ensure your data story is airtight.

Read → 4 Storytelling Techniques to Bring Your Data to Life

By taking the time to apply the best data storytelling techniques, your analysis will recommend a clear course of action. However, pure analysis can quickly spiral into inaction without a catalyzing call to action. Here’s the difference between data analysis and data storytelling, and why the latter is recommended for driving change.

Data Analysis vs. Data Storytelling

What are you more inclined to remember: a set of facts or a well-crafted story? This study has been replicated in many ways, but the results bear repeating.

According to a working paper by the Harvard Business School, “[t]he average impact of stories on beliefs fades by 33% over the course of a day, but by 73% for statistics.” This is a perfect example of a what is vs. what could be scenario: more data storytelling could close this gap. At this point, the question becomes how to communicate information in a straightforward yet engaging way.

For the statistics above, imagine a pair of images broken into a hundred different sections like a paint-by-number and arranged side-by-side. Let’s say it’s two pictures of a brain with a lightbulb popping overhead. The image on the left has 33 sections filled in while the one on the right has 73. The caption reads: Which approach paints a clearer picture? Rather than simply stating the fact, the audience would see the impact good storytelling has by how much clearer the brain is on the right than the left.

Or maybe you’re presenting the information in front of a live audience and want to emphasize how 73% is more than double 33%. Taking a page from The Wheel of Fortune, you could reveal 33% tiles alongside 73% of tiles in the style of Vanna White to put the illuminative benefits of data storytelling into sharp contrast for the audience. Again, the visual difference is striking while putting the different values into direct conversation.

Read → 3 Ways to Help People Understand Data

These are just two of countless examples of how stories prioritize showing over telling to gain audience consensus. When stories linger longer than just data alone, it’s important to weave both elements together into one efficient process to ensure the facts stay top of mind. In that regard, think of story as a floatation device for your data that contextualizes its importance.

Too often, data is shared as if it occurred in a vacuum. But numbers or figures devoid of context make it difficult for audiences to connect their meanings. Without thoughtful framing, decision-makers will have a tough time arriving at a compelling and actionable “so what?” from your analysis. This is one of the key differences between data analysis and data storytelling. Another boils down to action.

Where data analysis is a critical step in identifying a problem, data storytelling articulates a solution. Remember, an effective data story relies on the three-act structure to guide audiences toward understanding your data recommendation. This should articulate a projected outcome based on the action outlined in your recommendation. This ensures your audience can quickly understand the role they play in addressing the problem, and what they stand to gain by acting decisively.

Persuading with Data Storytelling

When used thoughtfully, data storytelling can be a powerful persuasive tool. Ultimately, guiding decision makers toward making data-informed decisions is the goal of a data story. As companies rely on ever-growing tech stacks to enhance their understanding of customer and industry trends, identifying and proposing strategic actions based on sound data analysis has never been more important. Packaging your analysis as a data story can persuade decision-makers to act by nurturing their understanding of what’s at stake before seizing on or missing an opportunity.

Watch → How to Gain Traction with Data Storytelling

High-stakes decisions are made from data every day. Knowledge gleaned from a single chart, synthesized from a dashboard, or gathered from a commissioned report by a trusted agency partner can all inform decision making. For data storytellers, finding a compelling throughline that articulates and solves a problem is key to connecting with their audience. However, the scope and depth of any story you tell with data will be determined by the problem it aims to tackle.

Below are some examples of different data-driven decisions that are achievable with targeted data storytelling.

Making Data-Driven Decisions

When aiming to persuade decision-makers with data storytelling, it helps to determine what type of decision should be made. Like choosing the right DataPov™, delivering your recommendation via a decision-making framework can help leaders better grasp your intent. Typically, decisions made from data fit into three buckets: tactical, operational, or strategic.

Another way to think of these different decision types is the level at which your data-backed recommendation would drive impact. Tactical decisions can help redirect a specific data trend in a desired direction, such as increasing user engagement or driving down costs. Operational decisions often track results over time and adjust the approach as needed. Strategic decisions are high-level pivot points that require careful analysis and calibration across multiple sources to drive organizational change.

Read → 3 Types of Decisions Made From Data

Once you’ve identified the type of decision required by your data analysis, that’s when the data storytelling begins. Since stories are the best way to communicate change and possible futures, human connection plays a critical role in meeting audiences with empathy. To this end, it helps to explore how data storytelling can help teams, departments, and companies create impact through smart, approachable messaging.

Who Benefits from Data Storytelling Training?

Whether you’re communicating data to funders, board members, co-executives, or direct reports, rallying audiences to your vision takes a synthesis of analysis and story to drive results. To this end, honing the art of data storytelling is increasingly relevant for leaders in any sector. No matter how close you are to the decision-making levers in your organization, knowing how to find and articulate potential opportunities and risks can inspire measurable outcomes.

Proficiency in data storytelling is increasingly essential for those who work in:

• L&D – “Training the trainer” in data storytelling can make implementing new skills (including data storytelling) at scale throughout your organization a lighter lift.
• Sales – Address customer pain points with straightforward evidence that centers their buyer journey.
• Design – Make hard numbers easy to read and visually enticing for internal- and client-facing work.
• Human Resources – Learn how to track and communicate the health of your employees and company culture to key decision-makers.
• Executive roles or C-Suite – Cut through the noise to reveal the big picture, capitalize on emerging trends, and craft bold vision for your organization’s future.

With data-centric roles on the rise, the ability to “speak your geek” is increasingly valuable to achieve team alignment and unify purpose.

Data Storytelling for Leaders

Business leaders and executives are pulled in a thousand different directions, which presents unique challenges for communicators. When communicating in time-strapped environments with fellow decision-makers, arriving quickly at a crisp, clear assessment is essential to having your DataPOV™ acknowledged and implemented. Once your data storytelling skills are proven valuable, such moments can inspire greater organizational success and increased trust among key players.

Free Resource → Diagnose Your Data Leadership Skills in Seconds

This is just as true for those at the helm of teams or departments. By respecting the critical thinking skills of knowledge workers, leaders can gain crucial buy-in and additional insights from reports. Leaders have an opportunity to set expectations and get everyone on the same page about telling effective data stories.

Illustration by Aisling Doyle

And what about when it’s time to act? Data analysis has never been more critical to taking decisive action. But for leaders, this can encapsulate a whole spectrum of challenges. From redirecting ad spending to making macro-level strategic changes, communicating why an action should be taken is essential to aligning on an organizational level. To this end, learning how to turn data analysis into digestible data stories can help leaders project confidence by articulating the thinking behind their decision making.

Free Resource → Skills Roadmap for Data Storytelling

While it’s common to rely on a convergence of data streams to track the health of your business, it’s important to recognize how storytelling principles can fill crucial gaps. Sometimes datasets are unavailable or incomplete. Other times datasets are available but too vague to provide a clear response. In these instances, business leaders can rely on storytelling to draw conclusions and make inferences based on their observations. Like a detective, practiced data storytellers can sift through clues to make the most practical decision from the information available.

When coupled with experience and deep industry knowledge, data storytelling can be the missing piece leaders need to play 4D chess in today’s economy. And like any skill, committing to regular upkeep ensures it stays sharp and adaptive to an evolving set of circumstances. This can include regularly engaging with course work and exercises that test your mettle. For example, Nancy’s recent contribution to LinkedIn Learning is a great jumping off point or refresher for making data-informed decisions.

LinkedIn Learning Course → Data Decision-Making and Communication for Leaders with Nancy Duarte

But skills that accumulate at the top and fail to trickle down create structural weak points in organizations. Rather, ensuring everyone in your orbit is up to speed on current industry trends and confident in their ability to make actionable recommendations with data is essential to staying competitive.

Data Storytelling for Teams

Investing in data storytelling training for teams or company-wide can reinvigorate how information is shared and applied across your organization. Teams that tell effective stories with data align quicker. They share goals and make actionable recommendations to ensure projects and outcomes remain on track.

Illustration by Aisling Doyle

Effective data storytelling works to improve interpersonal communication by uniting teams and organizations through a shared language. When everyone is equipped to interrogate metrics and empowered to make data-informed decisions, seizing opportunities and avoiding emerging risks becomes second nature.

Watch → Transforming Teams Into Data Storytelling Leaders

Data storytelling training can give teams across corporate and non-profit sectors a clear advantage in data-rich environments. With people, systems, and devices always growing closer together, learning how to understand and navigate these dynamics is essential to keeping pace.

Data Storytelling Training

Duarte offers online and in-person data storytelling training workshops for teams to accommodate onsite and remote-first workplaces. Both formats offer extensive course materials to upskill your data storytelling abilities alongside a live Duarte facilitator.

Topics and exercises covered in the training include:

• A comprehensive data storytelling workbook
• Case studies to practice data storytelling fundamentals
• Storyboards and writing templates to encourage clear, crisp language
• An introduction to Slidedocs® for concise pre-reads, leave- behinds, and internal memos
• The chance to tell your own story with data and receive collaborative feedback
• How data-informed decision-making can help your organization get ahead in a competitive market
• Explorations on how data storytelling can help diverse entities make smart decisions fast.
• A digital credential to share your accomplishment in data storytelling with your professional network.

How to Find a Data Storytelling Course

Duarte offers virtual and in-person data storytelling courses year-round. Navigate to Training in the menu above and select Duarte DataStory® for upcoming course dates and details.

Free Resource → Duarte DataStory Training Workshop: Course Overview

Stay tuned for more data storytelling courses near you. Or enroll in a live online training workshop to begin telling better stories with data.

For more information on Duarte DataStory, visit the training page.

How to Find Agency Data Storytelling Services

At Duarte, we’re firm believers in the power of education to empower a DIY drive. But sometimes it pays to call in data storytelling experts. Complex data storytelling can require bespoke services that get it right the first time.

No iterations.

No repeat attempts.

It all starts with gathering the necessary information. We know how to ask the right questions upfront to create exceptional content that meets unique audience and project expectations. Then, our designers, story architects, and seasoned speech writers harness the proper framing and execution to help your data story soar.

So you can catch up on your to-do list.

Read → How Duarte’s Agency Data Storytelling Services Drive Change

Looking to spotlight context, stakes, risks, and opportunities your organization can’t afford to miss? Duarte’s agency data storytelling services are ready to craft memorable, motivating data stories that spark action.

You can always pursue data storytelling training down the road. But high stakes data storytelling moments are worth seizing when they strike.

Just complete this form to speak with a Duarte concierge.

We’ll take it from there.