It’s Friday afternoon and your best data analyst just walked into your office and resigned. She’s leaving in two weeks. What do you do next?
A. Cry and curl up on the floor
B. Raid her desk and computer for any files that might help
C. Open a shared documentation folder for materials to share with her replacement
If you answered A or B, you’re at risk of a process breakdown if you have turnover among key staff in a data management, data collection, or reporting role.
The reality is that good employees won’t stay in their same jobs forever. The Bureau of Labor and Statistics indicates a worker’s median tenure is just 4.2 years. Employees who are successful in their positions are promoted or shift roles within their agencies. Others leave for new opportunities, retire, or win the lottery. Regardless of the circumstances, it can be shocking to find that one of the cornerstones of your team is leaving. While the loss can be difficult emotionally, it does not have to amount to the collapse of your team’s good work.
Education agency managers and executives can implement strategies with their teams to minimize disruption when inevitable turnover occurs.
Agency teams working with education data are familiar with best practices for data management documentation (metadata, standards for null data, policies for who can access data, and plans for protecting privacy and data sharing). Documentation practices can – and should – be applied to the process for working with data, too. Documenting how you collect and report data, and the related policies and procedures for doing so, can reduce risk of knowledge loss caused by turnover and build capacity among your staff.
Learn more about metadata and standards: CEDS: Not Just Another Education Acronym
This post discusses how to use data process documentation to prepare your organization for when a key team member leaves.
Use existing documentation as building blocks for a robust documentation library.
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Documentation is used across industries: checklists save lives and cut costs in intensive care units, critical design reviews ensure the safety of NASA rockets, and diagrams allow us to experience immersive art installations years after an artist’s death.
Documentation can be crucial, comprehensive, and creative. For education data, documentation may not be a matter of life or death, but it supports organizational sustainability, governance, and agency-wide continuous improvement.
- Documenting data processes may be a slow effort, but it’s not all or nothing; for a quick win, start small by developing a shared folder and a list of existing and needed documentation.
- Documentation does not need to fall to one
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What Does Process Documentation Look Like?
- Roles and responsibilities of team members
- Timelines
- Data flow diagrams
- Metadata
- Data governance documentation
- Business rules
- Common problems/how to troubleshoot
- Audit/review policies
- Data quality procedures
- Who to call when
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person.The old adage, “many hands make quick work” applies here. Building documentation practices into the daily work of multiple team members will help to document the work faster, allow for conversations around current practices, and build the team’s capacity for conducting data activities.
- Don’t start from scratch. Look for resources around sustainability and data governance for tools and templates. AEM’s Center for the Integration of IDEA Data (CIID) has a Data Governance Resources Guide and Data Integration Project Sustainability Sheet.
- Documenting processes now (“current state”) prepares an organization for modernization and improvements. Check out Technical and Business Documentation for an SLDS from AEM’s Statewide Longitudinal Data Systems.
Compare long-term benefits of process documentation to short-term effort.
Agency staff have multiple competing priorities and deadlines for submitting data. They have minimal time to devote to reviewing and documenting processes when it takes them away from day-to-day work on data collections.
That’s why it is important to consider the long-term benefits of good documentation. These include efficiencies in process and communication, which lead to more time to devote to agency priorities, such as decreasing time to certify data or review EDFacts files before submitting.
Additional benefits of data process documentation to agency leaders and their staff include:
- Reduced risk of lost information when data or reporting staff leave: Having a set of tools and resources for new hires or new staff in the role allows for a smoother transition, giving outgoing staff time to tie up loose ends instead of chasing down processes. This also gives incoming staff a clear starting point for their work.
- Consistency of best practices in collecting and reporting data: Bumps in the road can be minimized by implementing documented repeatable processes, especially when a team member has worked overtime to establish the continued use of best practices within the agency.
- Opportunity for continuous improvement in data collection and management processes: Documenting and circulating current practices creates an opportunity to examine the work and discuss lessons learned, opening the conversation for how practices can be improved in future years.
- Increased capacity: Having shared documentation creates transparency and clarity of work. When staff are able to identify processes, capacity at their agency increases since those team members can act as back-ups as needed because they know what work needs to happen.
- Improved employee retention: Studies indicate that employee satisfaction has a negative relation to turnover (higher satisfaction = lower turnover). Factors that contribute to satisfaction include communication, teamwork, and opportunities to use skills. Employees who are spinning their wheels or starting from scratch may not feel like they are using their skills to do the work at hand or may encounter breakdowns in communication, which can lead to job frustration and lower satisfaction. Proper process documentation can help mitigate these issues.
Don’t let compliance and data quality suffer at the hands of poor documentation.
While it may seem like a large investment to establish clear data process documentation, poor (or no) data process documentation will result in more time needed to review data quality and ensure data submitted are accurate and compliant with timelines.
- Inability to hit the ground running: When a new team member must figure out how to reenact a process, there may be delays in submitting required data, which can mean missed deadlines for compliance with Department of Education data collections.
- Comparing apples to oranges: Data users may face challenges when a new process doesn’t account for business rules that were previously in place. For instance, if this year’s data is not comparable to last year’s, it could be difficult to draw comparisons or show improvements in special education identification.
- Losing out on a lesson learned: Bad data may not be worse than no data at all, but poor data quality is a problem. When a process suffers from lack of documentation, there is little opportunity for identifying improvements that support data quality, such as minimizing handoffs of data so user error is not introduced. You cannot build on a foundation you do not have.
Learn more about improving local education data quality: 4 Focus Areas to Improve Local Education Data Quality
Do you have questions or comments about data process documentation or minimizing the impacts of staff turnover? Contact us and let us know.
