How to improve staff data literacy 

“Data literacy” refers to how well a person can read, understand, and communicate data terminology, datasets, analysis, and visualizations. The level of data literacy necessary for each person is dependent on their role within their organizations. 

Given organizations are more data-centric than ever, organizational data literacy is a foundational element of driving a data culture. This guide is designed to support organizations building data literacy among staff. 

Collect information on current levels of data literacy

When developing data literacy within your organization, the first step is to understand your team’s current level of data literacy, in relation to their roles. Data literacy is variable, and depending on the nature of a person’s work, some aspects may be more relevant than others. However, in general, you should be looking to understand how people use, analyse and communicate data.  

To have a better understanding of the current levels of data literacy within your teams, we recommend completing these three types of evaluation: 

1) Observation: Observations of data literacy challenges are based on your or your team’s informal understanding of these issues, so it is a passive, but often useful, means of assessment. You can make observations in many ways, including how staff communicate with data in meetings, interpret data in making decisions, and ask data-related questions.  

2) Surveys: Surveys are an easy method of developing a general understanding of data literacy issues within an organization. We have provided a simple survey template which can be duplicated and used as is, or customized, to your organization’s needs.

3) Interviews: Interviews are the most time intensive means of assessing data literacy, but often yield the most value. When conducting an interview, you have the opportunity to probe further into challenges, and growth areas with individual team members. This allows a more in depth understanding of perspectives.

Identify priorities based on results and observations

Based on your understanding of the current levels of data literacy, you can now see where people need more or less support. The next step is to match the areas for improvement with the needs of your organization. There are many elements to consider when aligning these needs. Some questions to ask yourself in this process include: 

• Given your organization’s core functions, what are the key data literacy needs at various roles?  

• What types of data quality issues, if any, commonly occur? Why do these occur?  

• Do you notice common misunderstandings or a lack of understanding when communicating data? If so, why and with whom?  

• What types of analyses or data visualizations are used in decision making? Are relevant team members comfortable creating, communicating and understanding the insights from them?  

• What types of technologies is your organization currently using and how well do team members understand and work with them? 

• What challenges initially provoked your interest in building data literacy within your organization? 

Consider these and other questions when determining data literacy priorities. After doing so, consider these with what you have evaluated as staff needs to determine gaps and areas where support is needed.

Design and implement a data literacy workshop 

Common to nearly all organizational data literacy efforts is a foundational workshop. A few essential agenda items for this type of workshop include:  

• Definition and discussion of “data literacy” 

• Showcase of the value of data literacy for the organization and its mission  

• Identification of priority gaps based on previous evaluations 

• Introduction of data literacy goals 
• Approaches designed to reach data literacy goals 
• One quick win 

In this workshop, it is important to have balance. Show ambition by challenging your team with goals, information, and discussions, but don’t overwhelm them, or overburden them. To do this, you must know where the workshop sits in the long-term strategy for building organizational data literacy. Ask yourself the following questions:  

• Is the workshop a standalone effort? 

• Is it part of a multi-pronged approach with other support mechanisms (such as office hours, or ongoing professional development?)  

• Is there an intent to embed data literacy further into the organizational culture? 

Depending on the strategy, you will have a better idea on what needs to be included in the initial workshop and what can be left for later. For example, in the above agenda, there was no introduction to data terminology. However, if your evaluations and priorities show that this should be a point of emphasis for the 1st workshop, it should be included.

Finally, customizing workshops to your audience is critical for engagement. A few ideas on how to customize your workshop include: using actual project datasets as case studies, bringing in staff as guest speakers, discussing data challenges relevant to the organization, creating activities related to staff roles, and sharing resources for self-study that can be accessed after the workshop.  

Develop ongoing support plan 

Now that you have identified priority gaps in your organization’s data literacy and held a workshop (or a series of workshops) to support the effort, it is important to keep the momentum. Simply put, there will always be a need for data literacy support mechanisms as technology evolves, new priorities are put in place, and as new staff join the organization.  

While this ongoing support plan could come in many different ways depending on goals and budgets, a few common approaches include: 

• Access to professional development programs – those held in-house are usually the most engaging and relevant, but remote courses are useful as well 

• Office hours with your data team – while you may have an open-door policy on this, it is always useful to communicate this support in regular meetings 

• Regular touchpoints – regularly communicate the need for data literacy, identifying challenges & concerns, progress, and access to support tools to keep your team engaged on the subject 

• Feedback mechanisms – create channels for team members to communicate challenges and requests for improving data culture, trainings, etc. 

• Annual, data literacy surveys and evaluations – as outlined in step one, regular evaluations are needed to identify needs and challenges as they evolve and to improve support programs

‘So what’ and next steps 

Through the steps included in this guide you have kicked off an important shift within your organization. However, going forward, the big challenge will be to continue this support and maintain interest as staff come and go, and as technologies change. 

Continue to be intentional in your efforts, engage others in the process and identify champions. While it takes time, this work leads to more data awareness and expertise, along with buy-in for data-driven practices. All of this ultimately leads to an enhanced data culture. 

In some cases, you may find the data literacy gaps are simply too large to address through capacity building. In that case, you may want to look into Hiring for Data Roles.