In today’s data-filled society, institutions are abundant with data but lack data literacy, the ability to transform data into usable information and further utilize the knowledge to facilitate actionable change.
Data literacy is a foundational driver in understanding institutional capacity to gather, consume, and utilize various data to build insight and inform actions. Institutions can use a variety of strategies to determine the maturity of their data utilization culture. The following list provides a set of methods that can be used to better understand your organization’s level of data literacy:
- Conduct a survey that provides insight into areas of awareness, access, application, and action associated with data utilization. For example, Coastline College uses a data utilization maturity index tool, the EDUCAUSE benchmark survey, and annual utilization statistics to get this information. The survey can be conducted in person or electronically, based on the access and comfort employees or stakeholders have with technology. The goal of this strategy is to gain surface-level insight into the maturity of your organizational data culture.
- Lead focus groups with a variety of stakeholders (e.g., faculty members, project directors) to gather rich insight into ideas about and challenges associated with data. The goal of this approach is to glean a deeper understanding of the associated “whys” found in broader assessments (e.g., observations, institutional surveys, operational data mining).
- Compare your organizational infrastructure and operations to similar institutions that have been identified as having successful data utilization. The goal of this strategy is to help visualize and understand what a data culture is, how your organization compares to others, and how your organization can adapt or differentiate its data strategy (or adopt another one). A few resources I would recommend include Harvard Business Review’s Analytics topic library, EDUCAUSE’s Analytics library, What Works Clearinghouse, McKinsey & Company’s data culture article, and Tableau’s article on data culture.
- Host open discussions with stakeholders (e.g., faculty members, project directors, administrators) about the benefits, disadvantages, optimism, and fears related to data. This method can build awareness, interest, and insight to support your data planning. The goal of this approach is to effectively prepare and address any challenges prior to your data plan investment and implementation.
Based on the insight collected, organizational leadership can develop an implementation plan to adopt and adapt tools, operations, and trainings to build awareness, access, application, and action associated with data utilization.
Avoid the following pitfalls:
- Investing in a technology prior to engaging stakeholders and understanding the organizational data culture. In these instances, the technology will help but will not be the catalyst or foundation to build the data culture. The “build it and they will come” theory is not applicable in today’s data society. Institutions must first determine what they are seeking to achieve. Clay Christensen’s Jobs to Be Done Theory is a resource that can may bring clarity to this matter.
- Assuming individuals have a clear understanding of the technical aspects of data. This assumption could lead to misuse or limited use of your data. To address this issue, institutions need to conduct an assessment to understand the realities in which they are operating.
- Hiring for a single position to lead the effort of building a data culture. In this instance, a title does not validate the effort or ensure that an institution has a data-informed strategy and infrastructure. To alleviate this challenge, institutions must invest in teams and continuous trainings. For example, Coastline College has an online data coaching course, in-person hands-on data labs, and open discussion forums and study sessions to learn about data access and utilization.
As institutions better understand and foster their data cultures, the work of evaluators can be tailored and utilized to meet project stakeholders (e.g., project directors, faculty members, supporters, and advisory boards) where they are. By understanding institutional data capacity, evaluators can support continuous improvement and scaling through the provision of meaningful and palatable evaluations, presentations, and reports.
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