Monitoring & Evaluation Systems Design
Qualitative data-based systems.
MHPSS and resilience-building interventions project teams must always work with non-tangible and qualitative indicators and are still showing avoidance reactions due the nature of that data.
This complexity is rooted in the nature of mental health and the intricate interplay of emotional, cognitive, and social factors. Additionally, the multi-dimensional nature of mental health and resilience outcomes makes them complex objects that cannot be measured straightforwardly, using the same parameters to measure physical objects.
In M&E simply setting up spreadsheets does not solve the problem of monitoring tasks, nor are they a system. On the contrary, in the absence of a monitoring model, the ordering, transformation and analysis of mental health and resilience data, turn to be a nightmare.
Operations on qualitative data as: transforming, assembling, clustering, identifying cause – effect relations, interpreting results, need an integral system built on structural models that reproduce the reality.
In the absence of those models, the data will be set in pieces which leads M&E to a catastrophe.
We design M&E systems with the finest art of data science and systems modeling. Our M&E systems are inexpensive standalone models that can be modified and adapted anytime, allowing M&E teams to focus on reflecting on what it is really important in M&E: how well is the project doing? How are the activities achieving the change expected? What are the weak points of the intervention? How and what do we need to change?
