Beginning the process of collecting data--or correcting a haphazard approach--doesn't have to be painful or overly time consuming, but the process benefits from having a plan with goals and objectives. Organizations should consider
- why they are collecting data
- who they are going to share their information with
- who is served by their programming
- what type of volunteer involvement they have
- how their programming has changed over the years
- where their programs are in operation
- when they want to be able to share the data
- what the barriers are to information collection
The next step in creating a data collection plan is to think through the logistics of the process. This means answering a few more questions:
- How will staff be involved in data collection?
- Who will be responsible for synthesizing the information?
- What format/program will be used to standardize the collection?
- When will collection occur?
Once these questions have been answered it's time to look at the responses and prioritize. It is rarely possible to do everything all at once, and trying to do so usually just leads to disappointment from expectations that are too high, so it's more useful to think of data collection as a train building speed. Overtime the process will become smooth and an organization can take on ever greater challenges, but by moving slowly and purposefully in the beginning there is plenty of time to course correct before the project picks up too much speed.
Ultimately having good data paves the way for successful grant applications, meaningful conversations with donors, and opportunities for staff and volunteers to pat themselves on the back for work well-done as well as to see openings for improvement. Data collection is a learning process and few organizations get it right the first time, but if these steps are followed then the frustration can be minimized and the reward maximized.