Monitoring and Evaluation can sometimes feel like a top-down process, where donors direct the data collection requirements.
This can be problematic, because the data that donors require isn’t necessarily the same as the data organizations need in order to deliver projects and activities, and improve service for clients.
At the same time, it’s not practical to collect endless amounts of data to satisfy the needs of all parties. Not only is it time consuming, but ungainly data collection procedures can have a negative impact on client experience, staff productivity, and project efficiency.
So what’s the best way to deal with this? How can you ensure that you get the most out of the data you collect, while also satisfying your donors?
Outline your own data needs
It’s important for you to take the time to define your own data needs. If you’re not sure exactly what you need, and what will be beneficial to your stakeholders, then it will be easy to go along with a donor-driven data collection plan.
Set aside time at the start of projects, and at strategic points during organization operations, to talk about what data you actually need. Outline this in a data collection plan, and include justification for why each measure is important to collect. Then, when you discuss measurement with donors you will already have your own priorities identified.
Before incorporating all donor requested data collection into your data collection plan, see what you already collect and figure out if that will suffice.
Although what you collect might be slightly different to what the donor has requested, if you put a strong argument forward why your version is important then they may accept that.
Automate as much as possible
Take the pressure off those who have to collect data and fill out surveys by automating anything that you can. For electronic forms auto-fill any fields that you already have information for rather than require people to fill them out manually.
This could be automatically generated data (e.g., data and time stamps) or incorporating data that’s already been recorded in other places.
Similarly, compute anything you can without requiring people to figure it out and record it. e.g., if x always occurs 5 days after y, don’t require people to enter both y and x. Much like you wouldn’t require someone to enter in their BMI if you can compute that from their weight and height.
Automating as much as possible relieves some of the burden of data collection, and you are more likely to end up with quality data.
Develop a relationship with the donor
Always aim to develop a good relationship with your main donors over time.
Develop trust, do what you say you will do, and show them how you measure the impact of your programs. With greater trust, and an understanding of how you define and measure impact, they are more likely to take a hands-off approach and introduce less additional measures.
Understand where the donor is coming from
If you are part of a wider funding program, understand that sometimes donors will need to collect certain information from all organizations and projects that they fund.
They may need to analyze data and report on all projects they are funding, and they can only really do this if projects collect the same data in the same way.
It may seem finicky to require you to use the exact wording of a certain question, or to have stringent rules on data collection attached to the funding they give you. But if the donor is requiring this across all projects they fund then it’ll cause a big headache for them if some projects get this wrong.