Who does data matter to in the development space, and how do those people use data? Though organizations and funders vary greatly, data can play a role in the decisions of all key actors in development funding and organizations.
Data in Development Funding
Funders keep the money flowing and programs running, influencing broader development outcomes and goals along the way. Whether it’s small individual donors or large foundations that donate thousands of dollars or lakhs of rupees, funders matter and influence the priorities of NGOs around the world.
1. Data Use by Foundations
Foundations rely on data from NGOs to explain how donated money was spent, and to decide where to invest in the future. Foundations collect this data by asking questions and designing grant parameters, both of which keep NGOs accountable for their spending. To get better data from NGOs, foundations must ask better questions and build grant parameters that are achievable, work towards transparent results, and avoid tedious burdens on under-resourced NGOs. Though it can be difficult, improving data quality and the questions being asked is a win-win for all involved.
For an example of a foundation driving decision-making through data collection, see our post on the first-of-its-kind collaboration between the UP government and the Bill and Melinda Gates Foundation.
2. Data Use by Individual Donors
Individual donors make decisions based on how an organization presents their impact. Unfortunately, great presentations raft with evocative buzzwords and powerful photos do not always translate to transformative community impact. If individual donors better understand and trust the data they receive from NGOs, decisions on where to donate become self-evident. When individuals make donating decisions informed by accurate realities, they create incentives for good data collection by NGOs.
Data in Development Organizations
3. Data Use by the Board
Boards set the broad strategy, structure, and priorities of organizations. Often removed from the day-to-day operations of an organization, they rely on the data provided by an organization to inform their decisions. If they receive inaccurate information, there is an acute risk of developing strategy that limits impact for, or even potentially harms, the intended stakeholders.
For an example of what happens what an organization prioritizes large-scale data collection, see our post on Akshaya Patra, the world’s largest school lunch program.
4. Data Use by Upper Management
Upper management are the strategists that translate the vision of the board into the organization’s operational strategy. Data works its way up through the ranks, from the mouth of the community to field staff to program managers. When this data finally lands on the desks of upper management, they need to know that the information is clear and trustworthy. Creating a culture of transparency — based on the importance of honest data, baseline surveys, and intentional question design — helps to improve the data that upper management receives. If this data is trustworthy, upper management can better explain their impact and goals to funders and board members, and they can make informed strategic decisions to help guide their organization.
5. Data Use by Program Managers
Program managers decide and implement what gets done on a day-to-day basis. Program Managers often work closely with field staff by helping to set schedules, plan meetings, and keep teams on track as they navigate the intricate balance between field staff, the board, and funder priorities. Good data is the foundation of a program manager’s work. By creating baseline surveys that examine the root of the problem, they can carefully and meticulously gather information to illuminate their organization’s operating context. Data is an essential part of a program manager’s design process.
Field staff have the most direct interaction with communities. They are the liaisons between the broader organizational goals and the grassroot realities. Unfortunately, the field is often where data is the least understood and prioritized. Often seen as an extra burden on already-long days of interviews, community meetings, and buses, data collection is often rebuffed by field staff as unnecessary tedium forced upon them. However, collecting data at the source makes reporting more accurate, which in turn helps the organization’s efforts become more meaningful and acute.
7. Data Use by the Community
Communities and individuals know their stories best. All too often, sloppy surveys, ill-formed questions, and a disregard for a community’s ability to tell its own story lead to poorly-shaped programs that ignore the needs of the program’s recipients. Data collection and program design begins here, with the community.
For an example of how to use community-based data collection at scale, see our case study on PAISA.
Want more examples of what happens when NGOs use data to drive their decision making? See our post on 7 NGOs that are using data for impact.
Our mobile-based data collection tool Collect can be used to monitor and track data on a real time basis. We’ve helped over 150 partners collect over 20 million data points through Collect, try it out now!