If you’re here, reading our articles about data literacy, it’s likely you already know the importance of data to a thriving business. After all, both stakeholders and employees say that data skills are crucial for the success of any business. 82% of stakeholders expect basic data literacy skills from employees at all levels, yet only 47% of employees say they’ve been offered data training by their company. It takes more than just encouraging employees to attend workshops because different functions have different needs. The significance of a data literacy curriculum is knowing where it needs to be applied first, and by whom.
To build a data culture it’s important to analyze issues, structure thinking, and communicate recommendations through a common framework. Frameworks help us articulate goals with succinct language. They can help us develop an outline for a successful strategy.
In this article, we’ll cover:
What is data literacy?
Gartner defines data literacy as the ability to read, write and communicate data in context, including understanding data sources and constructs, analytical methods and techniques applied, and the ability to describe the use case, application, and resulting value. Increasing data literacy helps businesses with benefits like employee engagement, increased productivity, innovation, and better overall customer experience.
What is a data literacy framework?
A data literacy framework is an end-to-end plan for how you’re going to encourage data literacy from the top down and the bottom up at your company. At the most basic level, the framework is a tool to help you structure and break down complex problems into manageable components. You can think of it as a place to organize brainstormed ideas into different categories.
Do you need a data literacy framework?
Despite the fact that the world produced 79 Zettabytes of data in 2021, and we’re projected to more than double that figure by 2025, Gartner predicts that through 2022, around 80% of analytic initiatives will not deliver business outcomes. It’s more important than ever before that businesses streamline their data processes and work to build data literacy.
But, let’s get more specific and talk through a hypothetical example: Acme Co. is a large manufacturer and retailer of food products. They are looking to grow and are developing a data literacy program as part of their digital transformation project. Should they create a data literacy program?
Important questions:
In order to determine whether Acme Co. should develop a data literacy program, we need answers to a series of questions.
- Does Acme Co. know how to produce and resource data literacy content for training?
- How would Acme Co. deliver its training?
- How much would it cost to develop Data Literacy content?
- Will Acme Co. enjoy increased employee engagement by providing Data Literacy training?
- What are the risks of creating (and not creating) a Data Literacy program?
- Are there other more effective programs Acme Co. could prioritize to increase employee engagement and drive revenue?
- How would Acme Co. outcompete competitors in people measures (eg., employee recruitment, engagement, retention) and business measures (e.g., productivity, efficiency, etc.?)
- What is the size of the employee population in the United States? Globally?
- Can Acme Co. prioritize continued learning for its employees as the data space continues to grow and expand?
The answers to these questions will determine whether or not Acme Co. is capable of creating an effective data literacy program. If they can’t create an effective one, then it would be a waste of effort and possibly deliver worse outcomes in the long run.
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How to develop a data literacy framework from scratch
So, now, you’ve asked yourself the important question of should you create a data literacy program. Now, you’re probably wondering how do you create the data literacy program?
There are several steps to consider, of course. You need to gauge appetite for data literacy. Is there a hunger for it and how can you harness that? Or, do you need to create an appetite, and how might you frame the value? From there, ensure you have the correct resources, align all your key stakeholders, assess what your business truly needs, and create your initial framework. Then, you have to actually do the work of educating your employees and ensuring they understand and can continue to learn as the data landscape changes.
We’ve broken these down into key steps below, to make each step more manageable.
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Ask the important questions
Before anything else, you need to make sure you have answers to some key questions. We talked about the questions above of whether or not you should create a data literacy program so it can be effective. But there are four additional questions that you need to ask and answer before taking any further steps.
All four of these questions must have the answer “yes” in order for you to proceed:
- What data literacy efforts exist, and do they align to the organization's primary pain points?
- Will creating this training program make the company more competitive?
- Do we have the capability to produce outstanding training content for data literacy?
- Are we expanding our data literacy efforts (or program) with intention (ie. not just doing "more")?
If the answers to any of those questions are no, you may need to re-evaluate your approach. Or work until the answer is “yes.”
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Align stakeholders
The next key to success is to make sure all your key stakeholders are informed and on board with your data literacy initiative. You won’t be able to make such a major push without their support and help.
You’ll need to present the clear benefits of your plan, then ensure that stakeholders know that buy-in also means being present for training and participating in them. If you have an idea of how that training will happen, you can present that as well.
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Create an employee journey map
One of the best ways to ensure that your data literacy program actually addresses the needs of your business and your employees is to make sure you understand your employees’ journey.
Start by listening to your employees. Schedule listening sessions throughout the organization–at key pinch points where data is collected, managed, stored, analyzed, reported, and used to drive business decisions. Identify pain points in the employee data literacy journey to learn what matters most to them. The insights you collect can help create your own Data Literacy journey map.
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Assess your business needs
Similar to the last step, the key to making an effective data literacy program is knowing where your business has needs and areas of opportunity. If you don’t think through the unique issues of your organization you might fall into the trap of applying generic frameworks from consultants or finding something on the Internet. Critical thinking, the ability to think end-to-end about an issue, is a primary data literacy skill. Not engaging in end-to-end thinking means your solution might be 3-degrees off course–which can prove costly.
To help focus your efforts, consider 8-10 broad business needs, such as the following:
Program attractiveness: What makes this initiative stand out and make it worthy of investment? Profit-Loss / Financials: How much will this cost? Competitive Landscape: What is everyone else doing, and do I need to keep up or lead? Strategic Alternatives: What else could/should we be doing? Company Capabilities: Do we have the skills to do this in house or do we need to outsource? Risks & Mitigations: What do we need to consider if we do this thing? Employee Needs: what are people’s needs and pains and how will Data Literacy help solve them? Create your own here, specific to your business needs. Let’s return to the Acme Co. example in which we are asked to determine whether or not they should create a Data Literacy Program. Running through the questions above, you can find where your business is well-suited to the work and where it needs additional support.
- Program attractiveness: Would employees engage in Data Literacy content made by Acme Co.? Are there sufficient motivators to encourage engagement?
- Profit-Loss / Financials: Will creating a data literacy program deliver more ROI than the cost going into creating it?Competitive landscape: How would a data literacy program help Acme Co. outcompete competitors in people measures (eg., employee recruitment, engagement, retention) and business measures (e.g., productivity, efficiency, etc.)
- Strategic alternatives: Are there other programs Acme Co. could prioritize that would add to its bottom line faster/easier? Such as investing in more sales people/sales training?
- Company capabilities: Does Acme Co. know how to produce data literacy content? If not, does it have the budget to outsource? Where would the outsourcing support come from?
- Risks: What are the risks of creating (or not creating) a Data Literacy program? How can you mitigate those risks in the beginning?
- Employee Needs: Think back to your employee journey map. What do your employees really need? How can you address those needs through this new program?
Answering all of these questions effectively is the first step to creating your framework.
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Fill out your initial framework
Now that you have your important questions above, it’s time to fill out your initial framework. We’ve provided examples below to help you as you take your next steps.
Firstly, pick which of the statements we listed above are most important for your company. In this case, for the hypothetical Acme Co. we’ve chosen four: Program attractiveness, competitive landscape, our internal capabilities, and cost vs return.
Framework Example Employee engagement attractiveness Competitive Landscape Our Internal Capabilities Cost v Value Is there a need? Do your employees want/need this training? Is there heavy competition (do other companies provide DL training)? Do we have capabilities to build out this program? Will developing this program make employees more productive? Next, let’s add a few bullet points under each area to add more detail to our case framework.
To determine whether the Data Literacy program is an attractive proposal, we would need to know the employee target size, the employee growth rate, and the average people measures and organizational measures.
To assess whether the opportunity is competitive, we would need to know who the competitors are, how much market share they have, and if they have any differentiation or competitive advantages.
To decide whether Acme Co. has the capabilities to produce an effective Data Literacy program, we need to know if there are any capability gaps or if there are significant synergies that the organization can leverage internally or through external partnerships.
Finally, to determine the expected cost-benefit of developing the program, we would need to know what expected benefits are, what expected costs are, and how long it would take Acme Co. to break even.
This gives us our case framework.
Framework Example Employee engagement attractiveness Competitive Landscape Our Internal Capabilities Cost v Value Is there a need? Is there heavy competition (do other companies provide DL training)? Do we have capabilities to build out this program? Will developing this program make employees more productive? What is the size of the employee-target population? How many competitors are there? Are there any significant capability gaps? What are expected employee engagement gains and program costs? What is the employee growth rate? How much share do they have? Are there significant synergies we can leverage between internal teams? How long will it take to break even (costs v efficiency gains)? What are the people-measure gains? Competitive advantages? You can repeat the above process as many times as needed to create an outstanding framework for your company. Just be sure to focus on the areas in your business that have a real need.
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Teach data skills
The next step is, of course, to teach your employees to ensure everyone has the same basic set of skills when it comes to handling data. Regardless of if they work with data or not, it’s important for all of your employees to have at least a basic understanding in order to build a culture of data at your company.
There are three types of skills that are important for data literacy. The first two are at an individual level, and they include non-technical and technical skills. The last are organizational-level skills.
- Non-technical: These include skills such as critical thinking, research, communication, domain knowledge, etc.
- Technical: Includes data management, analysis, and visualization skills, as well as advanced mathematics and programming.
- Organizational: Includes data-driven decision-making, a data culture, and a blueprint for success.
Challenges of implementing a data literacy framework
As with any major initiative, you may find yourself facing challenges both foreseen and unforeseen. These shouldn’t stop you from moving forward, but being prepared for them will help you face them as they happen.
Some challenges you may face when implementing your data literacy framework are:
- Data skills gap: Even though you’re benchmarking and teaching data skills, you may find it difficult to gauge everyone’s skill level. If your employees aren’t invested, they may not put the time or effort into learning. It’s important to incentivize the learning process and ensure everyone on the team knows how important these skills are.
- User resistance: Similar to the above point, you may find that introducing new tools and processes to the team meets resistance. Sometimes people don’t like change, or don’t see why the change is important, which can make adopting these new practices difficult.
- Budget restrictions: Both the use of different data tools, and the teaching of the skills can be quite expensive, especially if using outside resources. Make sure you have the budget to do the educational work properly, or you’ll end up with a partially-trained team unable to use your new tools to their fullest potential.
The importance of a data literacy framework
Hopefully, this has given you some things to think about when implementing data literacy program to strengthen the data culture at your company. Having a framework, roadmap, or blueprint of where you’re headed will help to navigate the path there, identify roadblocks sooner, address challenges, and meet your goals more quickly and effectively.
If you need help creating your own framework, our team has crafted an effective strategy to implementing data at your company using our blueprint. Learn more about Tableau’s data blueprint today.