As a data and analytics leader, you might sometimes feel like you need a translator to explain important data insights to other decision-makers in your organization. This could make you wonder how data literate your organization is, how much effort it would take to launch a data literacy program, and how important is data literacy in the first place.
According to Gartner, data literacy is very important. In fact, Gartner found that poor data literacy is ranked as the second-biggest internal roadblock to the success of the chief data officer’s efforts . By 2023, data literacy will become essential in driving business value, demonstrated by its formal inclusion in over 80% of data and analytics strategies and change management programs .
Even organizations with small data and analytics teams need to gauge their organizational data literacy in order to address skills gaps that are preventing their company from making better data-driven decisions.
In this article, we’ll dig deeper into the importance of data literacy, and share tips on how to gauge and improve your organization’s data literacy, based on Gartner research.
Data literacy is the proficiency in reading, interpreting, and communicating data findings and insights in context, with an understanding of where the data came from, how it was processed and analyzed, and the tools and techniques used to do so. Advanced data literacy skills also include the ability to make business recommendations and predictions based on this data analysis.
Here are a few steps that any organization can take to start improving data literacy right away, according to Gartner :
Identify the most fluent data communicators in your organization. Before turning to outside resources, you should comb your existing organizational chart for employees who can share their knowledge with those who can benefit from it. This offers several benefits: it’s more budget-friendly to leverage talent that is already on the payroll, and these employees have likely already built relationships across teams. Your BI team is an obvious place to start looking, but don’t overlook other, less obvious teams. For example, your marketing team likely has several employees who are data literate from working with marketing analytics.
Search for data communication problem areas. To make the best use of your time and resources, it’s important to seek out target areas for your data training efforts. Talk to team leaders to uncover missed opportunities where poor data communication led to a failure to use analytical insights. This is also a good time to conduct a business-wide data literacy assessment (more on that in the next section).
Use data ambassadors to lead data education sessions. Using the data communicators that you identified in step one and the problem areas that you uncovered in, set up training sessions to close gaps where data communication barriers have led to missed opportunities. These sessions should be fun and open, rather than formal and prescriptive. Incorporate games and quizzes rather than sticking to a business-like presentation.
Move onto data workshops as a next step. Once your less data-literate employees have become a little more comfortable working with data, it’s time to let them get their hands dirty. Ask participants to bring real-life scenarios from their work where data insights could be useful. Encourage participants to use data terminology as much as possible, and share lessons across teams. Hopefully, you’ll even surface some projects that can be taken on by your BI team.
Encourage data and analytics leaders and their teams to lead by example. Holding education sessions and workshops is a great way to improve organizational data literacy, but it’s not the finish line. Improving data literacy is an ongoing journey, and your data and analytics leaders should focus on continued improvement by encouraging their colleagues to use the language of data in all relevant business situations.
Unfortunately, improving data literacy in your organization isn’t as simple as developing a plan and putting it in place. In the real world, there will be resistance from leadership, difficulty getting employees to buy in, and other unforeseen obstacles to improving data literacy. Here are a few common roadblocks to data literacy, based on real Gartner clients , with potential solutions.
Roadblock: The connection between data insights and positive business outcomes isn’t clear.
Solution: Collect real world examples of how data insights have affected positive business results and share these examples as often as possible.
Roadblock: Non-analytical business leaders have been entrenched in their positions for a long time and are resistant to change.
Solution: Use optional education sessions and data workshops as a way to improve organizational data literacy without having to go through management.
Roadblock: From the top of the organization down, data and analytics are viewed as the responsibility of the IT department.
Solution: Enable IT leadership to use their perceived authority on the topic to lead educational sessions about the value of organizational data literacy.
Roadblock: Individual business units claim that they have no need for more data insights.
Solution: Present the examples that you collected in the first roadblock solution above to senior leadership to clearly show what business units are missing out on by not taking advantage of increased data literacy.
Roadblock: There is a lack of executive sponsorship for data literacy improvement initiatives, resulting in a lack of resources for such efforts.
Solution: Go straight to the top with an airtight business case, using statistics from this article and real world examples to get buy-in from senior leadership.
It can be difficult to gauge data literacy by “feel.” Some employees may be adept at “talking the talk” to fit into most situations without truly understanding what they’re saying, while other soft spoken employees might be a lot more data literate than appearances would suggest. That’s why it’s important to have a structured data assessment to get a true picture of how data literate your employees are.
Here’s a list of questions that you can distribute throughout your organization to get an unbiased assessment of overall data literacy, according to Gartner.
How many people in your business can interpret straightforward statistical operations, such as correlations or judge averages?
How many managers are able to construct a business case based on concrete, accurate and relevant numbers?
How many managers can explain the output of their systems or processes?
How many data scientists can explain the output of their machine learning algorithms?
How many of your customers can truly appreciate and internalize the essence of the data you share with them?
Tech tip: Use survey software to distribute this questionnaire and tabulate results so that you can establish a baseline for your organization’s data literacy.
To supplement the best practices that we outlined above for improving data literacy, there are several different types of software that you can use to support your efforts to improve data literacy.
Learning management system. This software, commonly referred to as LMS, can be used to educate employees about data and analytics through features such as a course library, quizzes and tests, and course completion tracking.
Master data management. This software helps businesses organize, protect, govern, and share all of their important data, as necessary. As employees become more data literate, they’ll naturally earn increased access to data, and master data management software can be used to control that access.
Want to learn more about master data management? Check out our complete guide here.
Data visualization software. Even the most data literate people can benefit from graphics and charts that communicate data insights in the most clear and concise manner possible. This is where data visualization software is useful. The right data visualization can be the bridge between data confusion and data literacy for a new data user.
In this article we looked at why data literacy is so important, how to gauge your organization’s data literacy, and how to begin improving it. To summarize:
Identify data literate ambassadors throughout your organization.
Surface problem areas that are most in need of improved data literacy.
Offer targeted training sessions to begin improving data literacy in key areas.
Hold workshops where newly data literate employees can exercise their new knowledge.
Ensure ongoing data literacy improvement through leadership by example.
To continue your organization’s data literacy education, follow our business intelligence blog where we cover all things data, from visualization techniques to master data management and everything in between.
If your team responds better to video, we welcome you to share our short video on getting started with analytics and business intelligence below:
1. Gartner Annual Chief Data Officer Survey, Gartner
3. Data Literacy Playbook, Gartner
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