Benefits of Conventional M&E
One of the main reasons why conventional M&E is often used is because it produces objective and quantifiable results. Data is collected by someone outside of the project, which is argued to eliminate potential bias. Additionally, data is collected using pre-determined quantitative indicators. This provides information that can be expressed in numerical terms and can answer questions like “what”, “how many”, and “when”. It is argued that this form of traditional scientific M&E is necessary to eliminate bias and ensure objective decision making in sustainability, especially when multiple interests or stakeholders are involved (Bennett, 2016; Koontz & Thomas, 2006; Sutherland et al., 2004). Scientific measures tend to be favoured for their reliability and accuracy, thus preventing mislead intuitions while increasing accountability (Cook et al., 2010; Forster et al., 2017; Pullin & Knight, 2003; Sutherland et al., 2004).
Conventional M&E is also easier to coordinate because there is inherently less people involved in the process. This includes scheduling activities, making key-decisions, and so on.
It can also be more timely in comparison to other approaches, as there are less steps involved (compared to PM&E), and therefore less variables that could slow or impede the process (for example, navigating conflicting objectives between community members).
Challenges of Conventional M&E
Conventional M&E often focuses on the examination of quantitative indicators, such as biological measures and outcomes (Goparaju et al., 2006). While this is critical for providing information on the degree to which anticipated results are achieved, it has become increasingly important to move beyond looking strictly at ecological indicators (Bennett, 2016; Trimble & Plummer, 2018).
Another prominent challenge deals with having an external expert conducting the evaluation. Although this is done to ensure objectivity, the external expert does not have familiarity regarding the project history, or details of day-to-day operations. This can impact an evaluation in many ways. In line with this, the disconnect between external evaluator and project members can cause challenges in relation to interpreting results. Project members may be unable to understand, or make use of the evaluation information provided by an external entity. This negatively impacts the next decision-making steps in the process, as project members may be unclear on the actual results.
In conventional M&E, donor agencies often drive and influence the M&E process. This includes making decisions about what type of data to collect and how. This can lead to collecting data that is not necessary or relevant, as it only answers the concerns of the donor.
Conventional M&E is known to have higher costs, often associated with the type of data needing to be collected as well as the hiring of an external professional evaluator.
Finally, concerns have been raised regarding the alienation of local stakeholders and rights holders from initiatives and decisions that directly affect them (Goparaju et al., 2006). Local knowledge and perspectives are often unaccounted for in conventional M&E projects. This is problematic because it results in incomplete information about an initiative. It may also be more challenging for community members to understand, accept, and support decisions made for them instead of with them. In fact, without employing a wide range of approaches and methods of inquiry, important contextual factors may be obscured or misinterpreted, and can lead to culturally inappropriate, socially unjust, and ultimately unsound actions (Bennett, 2016). One of the biggest critiques of conventional M&E is the lack of engagement with respect to key stakeholders, rights holders, and other community members in projects. This lack of engagement impacts the likelihood of local knowledge and perspectives being included in the project. This can also negatively impact the results.