Monitoring and Evaluation (M&E) has been crucial for social sector projects where it is implemented with an intent to track project performance in achieving the intended outcomes. Operationally, the M&E process is often treated as part of support activities to the overall project delivery. Under this traditional approach, most of the M&E activities are around indicator selection to enable reporting per donor preferences.
The traditional approach of positioning M&E as an important but ancillary component of a project has led to siloed implementation practices, with a focus on immediate donor expectations. This approach doesn’t lend itself well to impact analysis at the macro level, as there are rarely any opportunities to meaningfully aggregate data around indicators. Further, the current data handling is often done through paper records or MS Excel files – a highly inefficient solution given that a single indicator with basic disaggregation by age and gender – can potentially produce more than 12,000 data points.
However, in recent times, the interest in M&E has expanded beyond the donors, as multiple stakeholders (like the beneficiaries, communities, government bodies) are keen to track the M&E indicators that can not only measure the progress of these projects but also assess the impact on both the beneficiary level and the overall social sector.
This deepened focus on M&E has engendered a discussion around the current M&E practices and systems, and the need for transformation in this space. Additionally, with the advent of the digital economy and open data architecture, technology has a crucial role in shaping the M&E landscape. A potential future state of this transformation is a centralized approach to M&E that can effectively leverage a digital ecosystem. A centralized framework that directs the M&E implementation both at the operational level (project/donor-specific) and at the strategic level (institutional/global strategy) can enable a more structured approach to M&E. Enabling this centralized framework requires organizations to undertake transformational changes in their M&E practices, covering three key areas: standardization, capacity building, and the introduction of digital technologies.
In this paper, the key factors driving, as well as the barriers limiting this transformation will be discussed.
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