More data, fewer decisions: why M&E rarely steers projects
In almost all development projects today, data is collected in significant quantities: indicators, surveys, activity reports, administrative statistics, monitoring tables. Yet a paradoxical reality emerges: this data is rarely used to genuinely steer projects.
It is used to produce reports, to meet donor requirements, to document what has been done. But it influences little, if at all, strategic adjustments, arbitration decisions or the daily conduct of the project.
Organisations that exploit their data effectively are not necessarily those that produce the most.
This article examines the underlying reasons for this underuse and offers concrete avenues for reconnecting the data produced with the decisions to be made.
The paradox: more data, fewer decisions
In recent years, digital monitoring and evaluation tools have led to an explosion in the volume of data available. Where, twenty years ago, a project produced a few quarterly reports, it now generates:
- Weekly indicator dashboards;
- Beneficiary surveys;
- Geolocated monitoring;
- Detailed financial data;
- Multiple qualitative analyses.
And yet, in most organisations, strategic management remains largely intuitive, based on experience, habit or contractual constraints. This confusion between producing data and producing decisions is not new: it extends a more fundamental challenge, already documented in the distinction between data, information and knowledge.
Data that does not flow back into action loses its purpose.
A culture of collection rather than a culture of decision-making
Three structural mechanisms explain why so many M&E systems stop at data production, without ever reaching the decision threshold.
1. A logic strongly oriented towards reporting
Most monitoring and evaluation systems have been designed to produce reports, not to help make decisions. Indicators are defined to be reported upwards, aggregated and presented, but not necessarily to interrogate operational choices.
Thus, when the data arrives, it is stored, superficially analysed, then integrated into a dashboard. But it rarely triggers a strategic discussion. This posture connects with another structural observation: monitoring and evaluation remains primarily oriented towards institutional reporting, and much less towards learning and decision-making.
2. The weight of compliance
Many M&E frameworks exist primarily to respond to contractual requirements: justify the use of funding, demonstrate achievement of objectives, prove compliance.
In this logic, data is not a decision-making tool, but evidence. And evidence is not discussed, it is presented.
3. The rigidity of logical frameworks
Logical frameworks are generally defined at the project design phase. They play an essential role in structuring interventions and measuring results. However, they can become rigid in the face of contexts that evolve rapidly.
When data reveals a dysfunction, it is often difficult to reorient the project: indicators are contractual, budgets are committed, schedules are set. Data then becomes a statement of fact, without any real capacity to change course.
The mismatch between data and management needs
1. Indicators tailored for donors, not operators
The most monitored indicators are generally those required by donors: execution rate, number of beneficiaries, level of achievement of an output.
These indicators are important, but often insufficient for steering a project, because they do not allow you to understand why an activity is working or why it is struggling.
Project managers would need more operational information:
- Which beneficiaries are being missed?
- Why does one site produce results three times better than another?
- What obstacles are slowing down implementation?
However, this information is almost never formalised in monitoring and evaluation systems.
2. Data with limited accessibility for field teams
A significant portion of data is centralised and remains inaccessible to operational teams. When it is accessible, field staff do not always have the technical skills or the time needed to use it.
Result: field decisions are often made without the data that is nonetheless available.
3. The mismatch between data time and decision time
Data often arrives too late. A mid-term survey may take several months between collection, analysis and presentation. By the time the findings are available, the corresponding decisions have already been taken, or conditions on the ground have changed.
Maternal health programme in Central Africa:
a mid-term survey that came too late
A regional maternal health programme funded by a multilateral donor carried out a mid-term survey of 3,400 women on their access to antenatal consultation services.
Between the end of data collection and the delivery of the final analysis report: 7 months. By that date, the project had entered its final year of implementation. The lessons identified (poor geographical distribution of sites, unsuitable opening hours, weak community communication) could have transformed the results. They fed into the final report, but no operational decision could be taken in time.
Time of steering lost: 50% of the project cycle.
The broken chain between collection and decision
To understand why data is so underused, we need to examine the full journey of a piece of data, from its collection to its possible integration into a decision.
This broken chain is not an individual problem: it is an organisational one. Teams often know what the data is telling them. What is missing is the mechanism that translates this knowledge into movement.
5 signs that your data steers nothing
Your quarterly reports arrive after the decision they should have informed.
No one can name a concrete decision taken thanks to a specific indicator.
Field teams never access the aggregated data.
The dashboard is consulted only before donor committees.
Gaps between target and achievement are reported but never discussed.
If you recognise at least three of these signs, your system is in administrative reporting mode. It produces, but it does not steer.
These three questions, asked upstream of each cycle, are often enough to halve the volume of data collected and double its decision-making value.
Dashboards, adaptive management and continuous learning
1. The strategic role of dashboards
A dashboard is not a reporting tool. It is a discussion tool. Its value lies in its ability to provoke questions, highlight gaps and guide trade-offs.
A good dashboard meets three requirements :
Think of the dashboard as a decision tool, not a reporting tool
Delta Monitoring is built around a methodological conviction: every indicator should be attached to a possible decision. The platform visually connects indicators to expected results, alert thresholds and corrective actions, so that data never stops at the screen.
2. Continuous learning and capitalisation
The underuse of data also reflects a weak learning culture. Organisations that exploit their data effectively are not necessarily those that produce the most, but those that:
- Regularly discuss their data;
- Recognise that gaps are a valuable source of information;
- Accept to readjust their initial choices;
- Capitalise on lessons learned for subsequent projects.
This logic is at the heart of what is known as the “learning-oriented monitoring and evaluation” approach (MEAL: Monitoring, Evaluation, Accountability and Learning).
Towards a culture of useful data
he challenge for monitoring and evaluation today is no longer to produce more data. Tools, processes and institutional requirements already ensure massive production.
The real challenge is to transform this data into operational intelligence, into decisions, adjustments and learning.
This requires a change in posture from organisations, who no longer ask only:
“Do we have enough data?”
but also:
“Are we actually using the data we already have?”
It is this transition that will mark the shift from an administrative M&E to a monitoring and evaluation that is genuinely useful for the beneficiaries, teams and partners of development projects.
RESOURCES
CONTACT
- contact@delta-monitoring.com
- (+1) 514 779 1591