Evidence-based decision making is a process of making decisions about an intervention using the best available research evidence and experiential practice. At the center of evidence-based decision making is the collection, management and analysis of different kinds of data. Social development organizations produce large volumes of data every day, most of which do not get to be organized and used effectively. One of the reasons this data is not used very effectively is that, as the data is generated, not much effort is put into harnessing it to extract meaning from it. In this article, I will round up the most common sources of data in social development organizations, that if managed, may provide insight that will improve the delivery of program results.
Activity data is data generated when activities are being implemented. This is the most common form of data collected and used in social development organizations. In most cases, this data is collected in order to track the outputs of a project and feed into the project’s M and E.
Activity data allows the program managers to track the extent to which project inputs are being used and what outputs are being realized from the implementation of such activities.
Every project must have a way of collecting data from activities or services being given directly to project beneficiaries such as training, meetings, sensitization, distribution of materials etc.
Periodical monitoring data
Apart from activity data, in certain cases monitoring and evaluation staff have to go in the field for monitoring visits to collect data about activities and outcomes realized from such activities.
In most cases, this data feeds into the periodical reporting of project results, such as quarterly project reports.
Unlike activity data, periodical monitoring data may also be able to track short to medium term outcomes apart from output data.
Social development organizations usually have two classes of expenditure: program expenditure and administration expenditure. In many cases these transactions are captured in elaborate accounting systems such as QuickBooks. In other cases, spreadsheets are used.
Nevertheless, financial data is a very important piece of evidence-based decision making.
Social development organizations have to, in most cases, use very limited resources to deliver development results. Decisions of what kind of expenditures are critical and must be prioritized will come both from M and E data as well as financial data.
Being able to record correctly, read and analyze financial data is a crucial element that any organization must have.
In most cases, before a project is rolled out, identification of beneficiaries is done. At this stage, information like the names, location and contact details of beneficiaries are captured.
This database is important for transparency. The demographic information about beneficiaries will also be important for contextualizing the projects results when conducting periodical monitoring or in evaluations.
Baseline data and end-line data
Before a project is rolled out, data about the current levels of project indicators is collected. This is called project baseline data.
After the project has been completed, the closing conditions of project indicators are also collected. This is called end-line data.
Baseline and end-line data is important for comparing initial condition of areas of development with conditions after the project has been implemented.
The data may also be used to inform the development of other new projects in the organization
Human resources data
No matter the size of the organization, managing human resources is an extremely important piece for getting project results. Interventions are implemented by project staff supported by administrative staff. Information about staffing levels in projects and departments, payroll, skills and qualifications as well names, contacts and skills of volunteers and community agents, among other human resources data must be gathered and used.
Project evaluations are systematic assessments of ongoing or completed projects. Projects are evaluated to find out the extent to which project objectives were achieved. Data is collected on the relevance and fulfillment of objectives, development efficiency, effectiveness, impact, and sustainability of the project.
This data is crucial for learning across projects. Lessons from one project can be used to inform the design and implementation of another project.
Even well after the project is finished, this data will still be important when developing new projects. So it is imperative that this data is manage well.
Information about current and past donors, donations and contact info is very important for the survival of the organization. Every organization must keep a database of their donors and historical transactions with them
Data s at the center of evidence-based decision making. Social development organizations have many opportunities for collecting data that if managed, analyzed and used well, could make a big difference in driving results from development initiatives.