Business Intelligence

How To Set Up a Data Literacy Framework to Prepare Your Business for the Future

Dec 19, 2022

Every organization should be motivated to improve their data literacy. But motivation without a plan will get you nowhere. We’ll help you get there in this article.

AvatarImg
Andrew ConradSr Content Writer
How To Set Up a Data Literacy Framework to Prepare Your Business for the Future

As a small business data and analytics leader who is trying to improve your organization’s data literacy, you need a data literacy program that is accessible enough for non-analytics professionals and can also be scaled as your business grows and data literacy improves.

For a data literacy program to stick, organizations must follow a detailed, well-organized framework to ensure ongoing improvement. We’ll show you how to build such a framework below with the help of insights from research firm Gartner [1].

What is a data literacy framework?

A data literacy framework, also referred to as a data literacy program, is a carefully planned and structured system for educating people about data and analytics. The purpose of a data literacy framework is to improve organizational data literacy and help individuals make more informed, data-driven decisions.

What are Data and Data Literacy? (Source) [2]

If you’d like to learn more about the concept of data literacy as a whole, check out our article about the importance of data literacy here.

To underscore the importance of data literacy: Gartner predicts that by 2023 data literacy will become essential in driving business value, as evidenced by its formal inclusion in over 80% of data and analytics strategies and change management programs [1].

But there is still a disconnect: While 68% of chief data officers report that data literacy and analytics training are primary responsibilities, only 21% report that they are either effective or very effective at fostering data literacy [3]—which leads us into the meat of this article.

How to set up a data literacy framework

Now that you know what a data literacy framework is and why you need one, let’s look at how you can go about implementing a data literacy framework at your business. The steps in this section are inspired by Gartner’s Data Literacy Playbook for Chief Data and Analytics Officers [3].

Step 1: Plan with end-users in mind

According to our recent Data Visualization in Marketing survey (methodology below), 75% of respondents said their entire company benefits from data tools their business uses. This means your data literacy framework should be built around the people—from all parts of the company—and not the other way around. Here are some tips to help you reach that objective.

  • Cater the content and format of your data literacy framework to the different needs of the users. You shouldn’t launch a data literacy program without establishing a data literacy baseline first. Some organizations are naturally more advanced than others when it comes to data literacy, so your framework should be a reflection of that in order to save time and prevent any confusion. Use our data literacy assessment tool to figure out where your organization stands.

  • Engage with other leaders based on their data and analytics maturity. As a data and analytics leader, you’ll need to foster buy-in from all of the other team leads in your organization. Some of the leaders may need more convincing and assistance than others, and it’s important to determine this early on so that you can target your resources accordingly.

  • Market analytics as a skill for the entire organization and not just select individuals. One of the biggest roadblocks to improving organizational data literacy is teams and individuals who think that they don’t need data or analytics to reach their objectives. This can fragment your efforts to improve overall data literacy. Provide examples that show where data insights have already helped the business grow, then explain how those analytics can continue to make the entire business thrive.

In this stage, you gauged the general data literacy level of your organization, and this will inform what your actual data literacy training looks like. For example, if your teams have very little experience with data and analytics, a mandatory data literacy 101 training course using LMS software would be a good place to start. On the other hand, if your teams are already fairly data literate, you might be able to skip ahead to data workshops where your citizen data scientists [4] can work directly with your data professionals.

Step 2: Empower employees to think critically about data

Once you’ve designed your data literacy framework around the end-users, the next steps should enable them to spread their wings and start becoming self-sufficient in their data skills.

Here’s how:

  • Offer guidance to help users arrive at the right information and perform the right analysis. If you give someone a data insight, they have a single data insight. If you teach someone to find their own data insights, they have data insights for a lifetime. This is much easier said than done, but can be achieved through workshops, educational sessions, data ambassadors, and more. Check out our general tips for improving data literacy here for more details.

  • Help business partners understand what machine learning is capable of so they can ask data scientists for the right solution. The goal of improving organizational data literacy isn’t necessarily to empower previously data illiterate employees to become fully self-sufficient. It’s to enable them to work more effectively with the data professionals in your organization. Teach your employees what’s possible through advanced technology like automated analytics, so they know what type of data solutions are reasonable to ask for.

  • Teach business partners the data requirements of machine learning algorithms. To truly understand what data and analytics are capable of, it’s important to first establish the limits of data and analytics. For example, the most advanced analytics tools in the world can’t pull data out of thin air. Educate teams on what types of data are most useful for building algorithms so they can identify useful data sources that they may be sitting on.

Step 3: Set up your data literacy framework for growth

A data literacy framework isn’t a one-time course or even a series of courses; it’s meant to be a permanent system for continuous improvement throughout your organization. Follow these next steps to foster ongoing growth:

  • Gather stakeholder priorities to ensure that their dashboards are relevant and actionable. Just like you wouldn’t launch a new project without discussing and documenting goals and deliverables, you shouldn’t set out to improve data literacy without some objectives in mind. In the context of data literacy, these goals will likely come in the form of dashboards that can consistently deliver useful data insights to different teams.

  • Set up actionable dashboards that direct users’ attention to areas where their time and effort will be best spent. Set your newly data literate employees and teams up for success by meeting them halfway. Rather than releasing them into the data wilds and asking them to fend for themselves, make sure their dashboards are set up to deliver the data that is most useful for their team’s needs.

Want more information on dashboards? Check out our guide to interactive dashboards here.

  • Hold workshops to brainstorm new data-based value propositions that generate business value. Once your employees are gaining confidence with their data literacy and showing an ability to recognize and contextualize data insights, it’s time to give them opportunities to think more critically about data. Data workshops, led by experienced data analysts, are a great forum for brainstorming these ideas.

That’s a lot of information to absorb, so here is a summarized graphic that you can refer back to as needed:

How to set up a data literacy framework

Tools for implementing a data literacy framework

As a technological medium, you’ll want to take advantage of technology when establishing your data literacy framework. Here are a few important software tools that you can use to support your data literacy framework:

Business intelligence software: BI software will be the hub for almost all of your data and analytics activities, hosting important features like data preparation, custom dashboards, and data visualizations.

A custom dashboard showing various financial data in Northspyre business intelligence software

A custom dashboard showing various financial data in Northspyre business intelligence software (Source)

Tech tip: Secure as many seats as possible for all of your employees to have access to your BI software, and encourage them to use it and take advantage of any tutorials offered.

Learning management system: LMS software is used to educate employees on various topics, but it can be an especially valuable tool for rolling out a data literacy program through features like the course library, online quizzes and exams, and course tracking.

A customized course library in Tovuti learning management software

A customized course library in Tovuti learning management software (Source)

Tech tip: Consider curating a brief series of data literacy courses that can be used as mandatory training for all new employees during onboarding.

Collaboration software: Especially in a remote work environment, collaboration software is critical for ensuring open lines of communication among and between teams. This holds true for improving organizational data literacy as well.

A company wiki page with various resources in Notion collaboration software

A company wiki page with various resources in Notion collaboration software (Source)

Tech tip: Create a data insights channel to give users a forum to ask questions about data and analytics, share success stories about especially helpful data insights, and brainstorm ways that data and analytics could solve business problems.

Next steps: Track the effectiveness of your data literacy framework

Once your data literacy framework is in place and organizational data literacy is on the upswing, it’s important to remember to monitor the effectiveness of your data literacy framework and make adjustments as needed. Here are some final tips from Gartner on how to track the effectiveness of your data literacy program:

  1. Regularly audit your data and analytics software solutions to make sure they’re meeting your business needs.

  2. Give your data and analytics leaders time during company-wide presentations to promote data success stories and encourage ongoing data engagement throughout your business.

  3. Encourage teams to continue proposing new data and analytics projects to stimulate an appetite for data demand and consumption.

  4. Prioritize new software solutions that make the best use of data and analytics. For example, marketing automation software that includes advanced data reports.

  5. Identify data and analytics power users in each department so that they can act as ambassadors and help identify data opportunities and problems within their teams.

Another way to bolster your data literacy framework is to follow our business intelligence blog where we cover all things data, from advanced analytics to visualization techniques.

You can also share our brief video on the basics of analytics and business intelligence as a first step to improving data literacy :

Sources

  1. Chief Data Officer Agenda Survey for 2022, Gartner

  2. What are Data and Data Literacy? (YouTube), Arizona State University

  3. Data Literacy Playbook, Gartner

  4. How to Use Citizen Data Scientists to Maximize Your D&A Strategy, Gartner

Note: The applications mentioned in this article are examples to show a feature in context and are not intended as endorsements or recommendations. They have been obtained from sources believed to be reliable at the time of publication.

Methodology

GetApp's 2022 Data Visualization in Marketing Survey was conducted in October 2022 among 294 U.S. marketing professionals to learn about how data visualization tools or software impacts stakeholder decision making. Respondents were screened to have marketing, advertising, communications, or public relations job functions or have some level of involvement in marketing-related activities. All respondents use or produce marketing data to inform decisions.

avatar
About the author

Andrew Conrad

Sr Content Writer
Andrew Conrad is a senior content writer at GetApp, covering business intelligence, retail, and construction, among other markets.

As a seven-time award winner in the Maryland, Delaware, D.C. and Suburban Newspapers of America editorial contests, Andrew’s work has been featured in the Baltimore Sun and PSFK. He lives in Austin with his wife, son, and their rescue dog, Piper.
Visit author's page