Data Literacy for the Data Phobic: 7 Ways to Boost Data Literacy Across Your Team

Author's avatar Analytics UPDATED May 5, 2022 PUBLISHED May 11, 2022 17 minutes read

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    Peter Caputa

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    Data gives you a competitive edge. It also helps you make better business decisions.

    Not to mention, it helps you better understand your target audience, which, in turn, boosts business growth.

    So you’ve heard. But how useful all this data is to your business depends on one key thing: your team’s data literacy. Why? Because that is what ensures your team correctly understands what the data is revealing.

    So in this post, let’s talk about data literacy. We’ve also got data literacy examples, a free data literacy course to share, and insights from 65 respondents who reveal proven tactics for growing data literacy skills that have worked for them.

    54.90% of these folks are from the B2C services/products industry. 23.53% are from agencies (marketing, digital, or media) and the remaining 21.57% are from the B2B services/products field.

    Here’s everything that we’ll cover:


    What Is Data Literacy?

    Data literacy is the ability to read, analyze, and use data for business decisions.

    It’s pretty much like literacy in general except, as its name suggests, data literacy focuses on having the knowledge and understanding of reading and interpreting data.

    Why Is Data Literacy Important?

    Not all business decisions and strategic planning can be based on guesswork.

    Instead, you need to make decisions on the back of data indicating what’s worked in the past and how well it has worked. But here’s the thing: taking such data-backed decisions is only possible if your team has the required data literacy skills.

    Without data literacy, you can’t interpret data meaningfully. This leads to poor decision-making and strategic planning.

    In contrast, data literacy reaps the following benefits:

    • Gives you a strong competitive edge as you plan data-backed campaigns and strategies that are far more likely to succeed than plans made based on assumptions.
    • Improves employee skills and confidence by empowering your team to ask the right questions, make better decisions, and build knowledge.
    • Increases customer satisfaction. As data helps you learn more about your customers, you offer them more value based on it — for example by building needed features. In turn, this improves their experience with you.

    Data Literacy Levels Across Business Departments

    So what do the current data literacy levels look like? We asked our respondents the same and found out that more than half of them, 56.86% to be exact, say their organization is overall very data literate.

    The remaining, 43.14% share that some people in their organization have strong data literacy skills while others understand its importance — having only basic knowledge.

    Data Literacy Levels

    In terms of which specific departments are the most literate, we learned that management, marketing, and sales take the lead.

    Data Literacy Levels Across Business Departments

    Both departments show the most in-depth understanding of data. Folks in these two departments are also competent in designing, developing, and applying data and analytics cases.

    We also learned that customer service is the department that has the least data literacy skills. It’s also the department where the complete lack of data literacy is the highest.

    Data Literacy Examples

    Now for areas to grow your data literacy skills in:

    • Data comprehension. This involves basic understanding of data such as understanding common terms and interpreting information from data visualizations such as bar graphs and pie charts.
    • Cause and effect. Knowledge of how data values impact one another while also understanding that not all correlated data pointers have a causation effect.
    • Fallacies and biases. Full awareness of common biases and fallacies in collecting data and interpreting it. For example, cognitive biases like letting personal experiences come in between your study of data, make your analysis subjective rather than objective.
    • Critical thinking. Critical thinking is the unbiased examination and analysis of data to make usable judgments. Put simply, it’s the ability to question information such as sample size, sample composition, and so on to make better decisions.
    • Scientific method. This covers knowledge of the methods used to collect, interpret, and analyze data. It’s based on a handful of moving pieces such as asking the right questions, forming your hypothesis, experimenting, drawing conclusions, and more.
    • Nuance. The ability to detect nuances in collecting and studying data. For example, studying questions sent to survey respondents for nuances.
    • Data Analysis. The process of systematically applying logical and other techniques (as needed) to study and evaluate data.
    • Statistical analysis. A data analysis tool that assists in collecting and analyzing data to identify common trends and patterns. Its aim? To give you meaningful information from a large volume of data.
    • Data visualization. Data visualization is the visual representation of data that helps communicate data in an easy to understand and digestible manner. For example, in the form of graphs, charts, and maps.
    • Context. Context is understanding the connecting points in data. For instance, if you’re looking at an increase in sales in the last quarter of the year, you should also look at the context for its growth (shopping season) — not just the campaign you’re running.
    • Data communication. This involves clearly communicating data without misleading the results or letting bias guide your communication.
    • Data tools. The ability to use tools that help with data collection and analysis such as business intelligence and data visualization tools, for instance.

    7 Proven Ways to Improve Data Literacy Skills Across Your Team and Company

    Briefly, the consensus is that the majority of the companies, 74% of our contributors, include data literacy in employee training. What’s more, over 68% say they use dashboards regularly to improve data literacy.

    Other ways to improve data literacy skills include decentralizing access to data and letting each team member create their own dashboard.

    Ways to Improve Data Literacy Skills Across Your Team and Company

    Now for data literacy examples that reveal how others like you have improved data literacy across departments. Here’s a rundown of all the proven ways:

    1. Bring data specialists on board
    2. Provide role-specific training
    3. Offer data assimilation training when hiring new employees
    4. Create a data literacy curriculum
    5. Offer sufficient access to data to encourage learning
    6. Use dashboards for effective data literacy
    7. Open a line of questioning

    On to the details next:

    1. Bring data specialists on board

    The best way to assess how good you’re at something and to determine which specific areas need work is to seek help from specialists.

    That’s what the team at Entire Looks did. Ansar Hammad recalls: “Boosting data literacy in our organization has been a long and winding road, but it’s been more than worth it.”

    To begin with, Hammad writes, “The first thing we did was hire a team of data specialists to help us unpack what exactly ‘data literacy’ meant for our business, and then set goals to achieve it.”

    Note that the specialists help very specifically — not generally — by highlighting how data literacy would be valuable for their team in particular.

    From there, Hammad comments: “At first, we only focused on training our members who are responsible for managing the data that trickles down through our system — the people who take raw information, validate it, and put it into our systems — but soon realized that everyone in the company needed to be able to use their data-literacy skills when dealing with clients.”

    “So, we rolled out a two-pronged approach,” points out Hammad. This approach included:

    • “Teaching the people who work with data how to manage it better from start to finish
    • Teaching everyone else how to read that data better so they can make informed decisions about how to best approach customers.”

    “The benefits of this approach were exponential. Not only did we see an increase in productivity overall, but we were able to offer a better customer experience because every member of our team had the insights they needed from each client’s data set,” Hammad concludes.

    2. Provide team-specific training

    “The best way to make data literacy the default standard in your organization is by training every one of your employees in data and tech literacy,” opines Tim White from Milepro. “There’s simply no other solution to the problem.”

    “People forget that millions of people across America and the entire world don’t have access to basic broadband services whatsoever, which means that there’s great inequality in data and tech literacy in the country/world,” White observes.

    “The only way to bridge this gap is by paying your employees to take comprehensive training in these topics. This is what we did and it worked wonders. Everyone is on the same page when it comes to technology and data literacy, and I don’t have to explain why the emphasis on the two is so important.”

    But if you tell an employee they’ve to learn everything related to data collection and analysis, you’ll end up making them feel overwhelmed.

    However, if you tell them the specific chapters they should learn and how that’ll benefit them, you’ll have employees interested in taking a data literacy course.

    Bran DeChesare of Breaking Into Wall Street echoes the same. “We boosted data literacy in our organization by building role-specific data content for my teams.”

    “Data literacy is essential throughout a company, but it is a mistake to think that your entire team needs to understand the full picture to any level of detail,” DeChesare says. Not only is it a mistake but it’s a surefire recipe for demotivating employees.  

    “I think employees get easily intimidated by the idea that they have to understand data analysis from 10,000 feet up,” DeChesare adds.

    “What your employees need is access to the information that is directly applicable to their jobs — that’s the only in-depth knowledge most of them will have the space for anyway,” observes DeChesare.

    So the take-home message? “Tailor your data analysis to each team or department, and when stress levels go down, the ability to actually focus, learn and integrate will go up.”

    3. Offer data assimilation training when hiring new employees

    “We introduced a two-week training for each hiring where they are familiarized with our specific data terms and datasets,” shares Tony Maldonado of 10 Beasts.

    “This is the first step to position our employees to efficiently interpret and assimilate data. Secondly, we switched from using numbers in our reports to visual data like graphs.”

    “Technically, this helps employees interpret data in a better way and also understand the trends.”

    Consequently, “Each employee can now analyze their performance on their own and make necessary amends without the need for a detailed performance report produced by a data analyst.”

    4. Create a data literacy curriculum

    Similar to the educational tactics above, Finance Jar’s Elena Jones suggests creating a complete curriculum — not a one-off training session. Instead, plan a data literacy course, complete with how you’ll evaluate results.

    “To be data literate, one must be rhetorically, quantitatively, and aesthetically savvy,” Jones advises.

    “This was a difficult skillset for our business to develop since it demanded personnel to exceed expectations and understand several core competencies that were not commonly taught simultaneously.

    Since there is no particular approach to determining digital literacy, we began by generating an evaluation, subsequently developed the curriculum, negotiated on reasonable levels, and then implemented a plan of action.”

    Jones continues: “We also:

    • Made it a point to create data comprehension standards
    • Evaluate personnel’s present performance level and
    • Set out appropriate instructional programs so that staff members could better comprehend what data literacy entailed.”

    As a result, the team has become more data literate. “It assisted our staff in making sense of the figures and gaining resourceful business awareness,” Jones says.  

    “Employees with business acumen were able to act on advanced analytics to yield results. Furthermore, once our company was data-educated, it was able to depend on evidence while consumers were able to explore the statistics to unearth new areas of opportunity. As a result, putting the data to use showed extremely advantageous results for the company.”

    5. Offer sufficient access to data to encourage learning

    Data silos are the enemy of data literacy. In fact, The Finances Hub’s Mike Ward notes, “Data literacy is only possible when the employees have sufficient access to data.”

    “Creating data silos will keep the employees from curating meaningful insights from raw information.” It’s why Ward’s team takes a decentralized approach to data sharing.

    “Almost all our data is accessible to the relevant departments. Employees can also access cross-departmental information if it is relevant to their analysis.”

    Explains Ward: “Restricted data increases the chance of poor and misinformed decisions affecting organizational performance. Moreover, if it is difficult to gather business metrics, data literacy won’t happen.”

    “Therefore, we make sure that our data is widely and easily available within our organization. The more eyeballs it receives, the more value it will create,” Ward concludes.

    At GrammarHow too, Martin Lassen shares that giving access to data has been the key to improved data literacy. “I increase data literacy within my firm by assisting my employees in gaining access to and locating information across various data sources.”

    “My employees should be aware of the sources available and the information included within them,” Lassen goes on. “They should also be able to evaluate the reliability and utility of data sources. As a result, it is critical to properly map out and solve data access and automation challenges throughout the planning stages of any data literacy program.”

    6. Use dashboards for effective data literacy

    Data literacy hinges on not just collecting the right data but also reading it correctly so you can understand data better and identify patterns too. Thankfully, dashboards help with this.

    Essentially, dashboards bring all the important data together on one screen. Not only does this help with curating data accurately but it also makes reading and analyzing data easy. How? By presenting data in a visually engaging manner. This makes it easy to understand and interpret.

    Related: What’s the Best Chart Type for Your Dashboard Metrics?

    Become’s Ryan Montgomery applauds dashboard as their top proven way to grow employees’ data literacy skills.

    “We want our employees to go beyond just reading the data. They need to develop skills to read, query, and explain data. We ask our employees to regularly use dashboards so that they get familiar with them. They are encouraged to experiment with their projects, determine the valuable information and metrics to track.”

    “Understanding the dashboards helps the employees make sense of raw data and bring it to productive use,” explains Montgomery.

    “They also take on data requests where other team members ask them to extract certain statistics or data about a project. This tests their understanding of the dashboards and how data is stored in them. The goal is to make them feel comfortable around data and enhance their data literacy skills.”

    Related: Data Insights: Best Practices for Extracting Insights from Data

    7. Open a line of questioning

    Essentially, this opens up meaningful conversations around data, which helps employees get a better grip on analyzing it.

    Lottie’s William Donnelly shares taking this strategy has helped improve their team’s data literacy skills.  “I improved data literacy in my organization by creating an open line of questioning.”

    “Data is flawed and highly subjective to an individual’s perspective,” Donnelly outlines. “Hence, to combat this issue, we assign multiple experts to handle our datasets; the more, the merrier. When individuals have questions, they can directly seek my expertise without any kind of repercussions. This promotes a culture of learning, which ensures our company’s sustainability.”

    To further grow a culture of learning, provide the needed data learning tools and incentivize employees as well — both hat tips to Donnelly.

    “We provide different departments with different learning tools, such as Gapminder. This allows them to gain knowledge and broaden their perspective regarding data literacy. It enables us to create a culture reliant upon continuous learning.”

    Speaking of the benefits of this approach, Donnelly goes on to say: “The benefit of this method would be that it helps foster a sense of achievement. For example, when my employee is aware that a reward is waiting for them as soon as they complete their learning task. Employees with increased data literacy can fast-track their careers to be C-level executives.”

    Related: 7 Data Analysis Questions to Improve Your Business Reporting Process

    Lee Wilson from Vertical Leap shares they also promote a culture of learning and provide the necessary tools. According to Wilson, “We have our own proprietary technology (Apollo Insights) which enables us to remove a lot of the data literacy barriers. Areas such as learning many distinct tools, platforms, and technology become a lot easier when most systems data is accessed in a single central and intuitive marketing platform.”

    “Added to this we have an evidence (data) based culture, where everything we do stems from the meaningful application of data,” Wilson writes. “And we put in place tried and tested training programs, support roles, and team structures whereby training is layered, ongoing, and an always active element of our working approach.”


    Improve Data Literacy in Your Company with Our Free Business Analytics Course

    Now that you know these expert tactics and the importance of data literacy, there’s no reason to delay working on building your team’s data literacy skills.

    Want to get started today? We created this short but thorough data literacy course for you. In less than 90 minutes, your team will learn all the essentials related to gathering and analyzing data including how to identify metrics to track, how to use data to inform your strategy, and building their own dashboards.

    The best part? It’s free! So what are you waiting for? Enroll today.

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    Masooma Memon

    Masooma is a freelance writer for SaaS and a lover to-do lists. When she's not writing, she usually has her head buried in a business book or fantasy novel.

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