How to Identify Your Data Requirements

March 19, 2019

How can you get rid of all the noise and focus on what you need to get the job done? Well, a clear understanding of your data requirements will help narrow your focus and identify a method of data collection that serves your needs precisely.

The first step in this process is to make a list of what data you already know you need. Sometimes, you will have existing documents to give you a head start, such as results frameworks, M&E frameworks, or requests from supervisors and funders. Other times, you will need to start from scratch. In either case, you should outline an initial list of data requirements, and then stress test that list to identify other factors. There are a number of questions you can ask that will help expand the list and describe each variable in more depth.

 

A data collection program outlines their data requirements on a whiteboard

Organizing your program’s data needs is a tricky process that starts with categorizing what you have

 

Categorize your data needs

Most often in data collection and service delivery programs, your data can be broken down into two categories: (1) program performance metrics and (2) worker performance metrics. These categories help explain which aspect of your program the data affect.

Program performance metrics focus on how well you are meeting the project objectives. On the other hand, worker performance metrics are the best indicators for how well your workers are performing their duties and how much they are contributing to the success of the project.

When you want to know whether you are accomplishing your project objectives, examine your program performance metrics. How many beneficiaries have you reached? What percentage of your beneficiaries have improved health outcomes or crop yield? The answers to these questions are made up of many different variables, such as patient weight, disease contraction rate, or pounds of crops harvested, which will help you determine any improvements to beneficiary outcomes as a result of your intervention.

When you want to know how efficiently your team is working, take a look at your worker performance data. How long does it take for a data collector to submit their data after a field visit? How long does your team spend on data entry? How many beneficiaries does each worker reach and when? Keeping track of metrics such as number of house visits and form submission times will help you optimize individual and team performance.

 

Growth charts outline some data requirements for a data collection program

Some programs require you to track data from the same source over time

 

Describe your data needs

Once you have organized a list of your data requirements by category, flesh out their attributes and characteristics. There are numerous questions you can ask to help with this:

  • Are you searching for quantitative data you can record or qualitative insights from sources close to the subject of your analysis? You don’t have to collect just one type, but the characteristics of the data you are collecting will be integral to selecting the right method of data collection and the questions you ask later on.
  • Are you searching for longitudinal data–that is to say, are you looking to update the same metrics from the same source over time? This type of data requires case management, which means you will need to collate the data you collect from that source over numerous visits.
  • Do your data require outside data sources? Many governments have regular reporting on health, income, agriculture, and many other sectors. This is helpful when you are trying to compare your data to national averages, for example.
  • Does one variable depend on another? For instance, before asking details about a patient’s treatment history, make sure that patient has actually received treatment. When you ask a patient if she has ever received medical treatment, and she replies, “no,” you don’t need to ask about vaccinations, medication, or any other medical treatment. This will require your workers to know all the combinations of questions they might need to ask (or a tool that can be programmed to filter questions for them).

 

There are many more questions you can ask to help describe the characteristics of your variables, but as with everything else, they will depend on your project’s objectives. Marcos Lavandera, a health analyst at Pro Mujer, a woman’s development organization in Latin America, explained that for his project focused on women’s healthcare in Mexico, his entire team took part in the process of defining their data’s characteristics.

“We had our program director, health analyst, and medical director all working together to make sure we looked at the data from all the possible perspectives,” Lavandera said.

All of the characteristics you define will help you later, as you determine the right data collection method for your program.

 

A data collection program's data requirements should be available to the whole project team

Keep track of all the data requirements of your program and make them available to your team

 

Summarize your data needs

With the myriad methods of data collection, developing a clear, written summary of all the variables you need will help keep you focused. Differentiating between program performance metrics and worker performance metrics will help keep your data organized. The characteristics of your variables will help determine the method and features of data collection that will work best for your program. It won’t surprise you to know that data is the most important piece of any data collection program, so a comprehensive understanding of the data you need to collect is vital.

Written by
Dimagi

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