With each passing year, organizations and decision-makers are gaining access to more information and data than ever before. This presents a great number of opportunities for making better informed decisions about how to manage operations and interact with clients and members. It can also be overwhelming if you don’t have systems in place to receive and organize this data, or if your teams don’t possess the skills to use this data to inform their work. Data is only as good as your ability to organize, understand, and apply it to your everyday decision-making. That’s why it’s critically important to create a culture of data literacy at your organization.
What does it mean to be data literate?
On an individual level, data literacy is not only the ability to interpret and analyze data, but also the ability to incorporate data insights into strategic decision-making. You don’t have to be a data scientist or a statistician to be data literate. What you do need is an understanding of basic elements of arithmetic and data analysis, such as knowing the difference between means and medians, causation and correlation, and quantitative and qualitative data. Understanding these concepts, as well as gaining some experience in reading data charts and tables and drawing insights from them, are some of the key components of data literacy.
At many organizations, data analysis skills are isolated to a small group of individuals who often work within the same business unit. True data literacy at an organizational level comes when many employees across different departments and specialties have access to data, the ability to read and understand that data, and an environment that encourages them to make decisions informed by data insights.
5 Things You Can Do To Encourage Data Literacy at Your Organization:
1. Engage a Diverse Array of Stakeholders – It can be difficult to know where to begin when looking to improve data-driven decision making. Try starting by bringing together a diverse group of employees from throughout your organization to establish the current state of data literacy among your various teams and talk about the benefits of improving skills and access to data. It’s important to understand what kinds of data are currently available and how that data is being used. From there, you can better identify opportunities for improving access to and usability of data as it relates to management and operations. These conversations with organizational stakeholders should become regular occurrences as they are critical to the mission of improving data literacy and data usage at your organization.
2. Create a Self-Service Data Platform – Make data available to staff throughout your organization by implementing a visualization and analytics platform that allows users to interact directly with the data to extract the information that’s most relevant and valuable to them. As interests and needs vary greatly across users and business units, it’s imperative that the platform be flexible enough to house different types of data and offer multiple options for saving and sharing insights.
3. Offer Critical Thinking and Data Skills Training – Some at your organization may not have much experience in data analysis, and may find a data literacy program or a new data platform intimidating. Consider offering lunch-and-learn gatherings or more organized training sessions to introduce employees to the concept of data literacy, gain skills in basic data analysis, and discuss best practices for transforming insights into better decision-making.
4. Lead by Example – Encourage Managers to share examples of data-driven decisions with their staff. When explaining a new process or initiative, team leaders should refer to any relevant data to help explain how they arrived at their decisions or crafted their policies. Doing so will help establish a culture of informed decision-making and greater data literacy.
5. Frequently Assess Your Progress and Future Needs – The process of improving data literacy and introducing interactive data platforms at your organization should be an iterative one. It’s important to frequently step back and assess your progress. Discuss with your stakeholders what’s working, what’s not, and what can be done in the future to continue improving data literacy and data-informed decision-making.