What can one data champion realistically do?
One data champion can realistically keep your organization's data organized, answer colleagues' questions, produce the regular summaries and reports, and serve as the connection between the team and an outside evaluator. That's a valuable role, and having one person who understands the data well can make everyone else's responsibilities easier.
What a champion can't do alone is make everyone else's records reliable or make the organization use the information. A champion working with data that was recorded inconsistently, by colleagues who don't know why it's collected, spends much of their time correcting it. The role is most effective when it's a recognized part of the person's position, with time designated for it, instead of an assignment added on top of a full workload.
What happens if all our data skill sits with one person?
If all of your data skill sits with one person, your organization's ability to use its information depends on that person staying, and on their having the time and energy to do the work. When they leave, the knowledge of how the spreadsheets operate, where the files are located, and why information is recorded the way it is often leaves with them, and their replacement starts over.
The arrangement can also take a toll on the champion. Being the only person who can answer every data question, while still performing their original responsibilities, can lead to overwhelm and burnout, particularly near reporting deadlines. Supporting the champion is part of supporting the team, because the people others depend on need support themselves if they're going to provide it sustainably.
A single champion can also make it easier for everyone else to treat data as someone else's responsibility. How do I get my staff comfortable collecting and using data? looks at developing that comfort across an entire team.
What should everyone on the team know, and what can stay with a few people?
Everyone on the team should understand why the information they collect matters, how to record it consistently, and how to interpret the basic results that come back, while deeper skills such as survey design, analysis, and managing the data system can remain with a few trained people. The table below sorts the most common responsibilities.
Who needs which data skills
| Skill | Who needs it | Why |
|---|
| Why each piece of information is collected and how it will be used | Everyone | Knowing the purpose helps people see why accuracy matters |
| Recording information accurately and consistently | Everyone who enters data | Inconsistent records cost the champion time and limit what the data can show |
| Interpreting a summary and asking what it suggests | Everyone, including leaders | The data is only valuable if people use it |
| Designing surveys, cleaning data, and analyzing it | One or two trained people | These require depth, practice, and consistency |
| Managing the database or spreadsheets | One primary person and a backup | The system continues working when someone is away |
| Designing an evaluation and determining what caused a change | An evaluator, working with your team | These require evaluation expertise |
The last row deserves attention. A champion can coordinate with an evaluator and help the team use what an evaluation shows, but expecting one staff member to design the evaluation as well places specialized work on someone who wasn't trained for it. What parts of evaluation should we never DIY? explains where that line falls.
How do we support a data champion so the skill spreads?
To support a data champion so the skill spreads across the team, give the role protected time, train a second person alongside them, and create regular occasions where colleagues use the data. Document how the key spreadsheets, forms, and reports work, so the knowledge isn't held in one person's memory. Asking the champion to share one result at a monthly team meeting gives everyone practice interpreting data and demonstrates that the organization intends to use it. And make sure leaders ask for the relevant data before making decisions, so the champion's work has a purpose.
When you do train the whole team, keep the shared training brief and connected to their daily work, and give the champion deeper training that builds on it. What makes a workshop worth pulling my team off their work for? covers how to evaluate whether a particular training is worth the time.
The Grantibly perspective
Angelika's perspective
We want the teams we work with to understand their own data. That means explaining what we're doing and why, making results accessible, and helping teams develop stronger evaluation thinking over time.
We're interested in both individual and organizational responsibility. People can develop healthier ways of working, but that alone isn't enough. Organizations and leaders also have a responsibility to create conditions that support them, and the people others rely on need support themselves if they're going to provide it sustainably. A data champion is one of those people.
We help clients build knowledge, skills, systems, and practical capability that remain useful after an engagement ends. Lasting capability is a meaningful form of value.
