Are you collecting data with a purpose?

Many nonprofits begin collecting data haphazardly, sometimes focusing on what seems important to them and paying less attention to what might be important to potential funders.  Other nonprofits may collect very little data at all, which can happen for a variety of reasons: staff/volunteers are focused on mission and believe that focus means data has to fall by the wayside, an organization's programs don't seem to be suited for collecting data, no one seems interested in taking the lead, or any number of other reasons.  But whatever the reason, it is vital to create a plan for correcting the situation and getting on track, because otherwise funding opportunities are bound to be missed--and no one wants that!

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

Answering these questions will give a nonprofit ideas for where to look for data, both quantitive and qualitative (numbers and stories).  For example, thinking about who is served by a nonprofit's programming could lead to a desire to collect demographic information.  But this may also trigger a barrier, like not being able to gather demographics because program beneficiaries are served indirectly and getting their information would require cooperation from a third party.  This doesn't mean it isn't possible to collect data, but rather that the brainstorming needs to continue to figure out solutions to barriers and/or what type of data could successfully be gathered.

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?

It is absolutely crucial for there to be a standard format in which the data is collected, because otherwise the process can devolve into a time consuming, frustrating task.  For example, if 10 staff are all using a spreadsheet they designed themselves then the person who has the task of bringing all the data together into a graph will have to figure out which data point in Graph 1 lines up with which data point in Graph 2, and so on.  Also, non-standardized formats often result in data gaps, because someone will inevitably forget to include a piece of information.  

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.   

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