What makes a data training easy to forget?
A data training is easy to forget when participants leave without having applied the skill to anything that matters to them. A common version is a presentation that moves through slides on survey design or spreadsheet formulas, relies on examples from a different organization or field, and leaves little time for questions or discussion. Staff members can follow the material during the session and still be uncertain how to begin applying it the following morning.
Signs the last training wasn't designed around your team's work
- Generic content. The examples, data, and questions came from somewhere else, so participants had to translate everything to their own situation by themselves.
- Too much at once. A single day covered survey design, analysis, charts, and software, and no individual skill received enough attention to become familiar.
- No opportunity to practice. Participants watched someone else analyze data and never attempted it themselves with feedback.
- No connection to a decision. Nobody explained what the team would do differently with the information, so the skill had no obvious purpose.
- Nothing to take back. Participants left with a copy of the slides instead of a revised form, a working spreadsheet, or a plan for what to do next.
Was the problem the training, or what happened after it?
The problem may have been what happened after the training rather than the training itself, because a new skill requires time, a reason, and support before it becomes part of the work. Staff members who learned to summarize survey responses won't continue doing it if no one requests the summary, if their workload leaves no room to try it, or if the database they use makes the new approach more complicated than the old one.
Supervisors and leaders have an important role here. When leaders ask what the data shows before making a decision, and give employees the time to find out, staff members can see that the skill is an expected part of their responsibilities and not an additional task on top of them.
Some of the reasons have little to do with skill. Staff members may consider collecting data an additional responsibility, or may be uncomfortable with how the information will be used. How do I get my staff comfortable collecting and using data? looks at the culture side of that, and My team sees data collection as extra work. How do I change that? looks at the workload side.
How should we design the next data training differently?
The next data training should be designed around a question your team needs to answer and the information your organization already has, so that practicing the skill and doing the work become the same activity. That preparation begins before the session: ask staff members what they find most difficult about working with data and what they would like to be able to do, and identify upcoming decisions the data could inform.
What a data training designed for use includes
- A real question. For example, a team might want to understand which of its sessions participants return for, or why fewer people complete the intake form online.
- Your own data. Staff members work with their organization's own spreadsheets, forms, or reports, with names and identifying details removed where necessary.
- Time to practice. Participants try the skill during the session and receive feedback while the person leading it is still available.
- Something to keep. A revised survey, a template for a monthly summary, or a practical plan for using the information.
- A next step someone is responsible for. Which person will do what with the data, and by what date.
- Follow-up. A second session or a conversation several weeks later, once participants have tried the skill and have questions.
Timing matters as well: a focus group with students scheduled during finals week won't hear much, and a training scheduled during your busiest season will compete with the work it's intended to improve. What makes a workshop worth pulling my team off their work for? covers how to evaluate a particular workshop before you commit the time.
The Grantibly perspective
Angelika's perspective
As former professors and educators, we pay attention to how people learn, how to design engaging learning and feedback experiences, and the real conditions that affect whether people can participate. We don't simply move through a slide deck. We design learning that helps people use what they learn.
We also want the teams we work with to understand their own data. Data doesn't make decisions; people do. Data becomes valuable when people can understand it and use it, which means explaining what we're doing and why, and helping teams develop stronger evaluation thinking over time.
The questions we want teams to become better at asking are practical ones: What evidence would tell us whether this is working? Are we collecting data we actually need? What does this result suggest we should do differently?
