Proposal design

Logframe + monitoring and evaluation design

The logical framework (or logframe) is a table that summarises your project in a standard format. It should help anyone to understand the proposed action and its contexts in a brief but effective way. Thus, it is good to define abbreviations and avoid them at least in the logframe. You will find additional information on the logframe in ECHO’s helpdesk website and in the EU Project Cycle Management Guidelines. The logframe needs to be firmly linked to the monitoring and evaluation design. This will make your life easier later when assessing, learning and reporting on the implementation. It will also contribute to support accountability of the implementation.

Let us now first focus on the logframe.

You should not change the basic purpose of the action without consulting with the donor first (or contractor, if you prefer – please see ECHO’s information on changes to actions). The basic purpose of the action can be defined by the intervention logic (first column of the logframe), which includes principal and specific objectives, results and activities. Funders, donors and taxpayers assume that one first did careful planning before submitting a proposal and clearly highlighted any important pre-conditions, risks and assumptions that can affect the action’s implementation. Following that principle, however, the logframe should be seen as a “live” document, which needs to be updated throughout the implementation based on context changes and new synergy opportunities.

When designing the logframe, one critical aspect is to develop quantified and clear activities. They need to reach their respective result and should be presented in a sequential or chronological order. Sub-activities are usually not presented in the intervention logic in order to ensure clarity by simplicity. Optionally, one can include sub-activities in the work plan, which you will need to submit as well. Activities, however, need to be defined in detail in order to ease estimation of direct beneficiaries, indicators and budget. In the example below, for a two-year action, one could use the information between parentheses for internal purposes only (e.g., budget estimation and direct beneficiary estimation): 

To conduct 24 trainings on disaster-safe buildings to 480 workers in districts W, X, Y, and Z (3 yearly trainings of 180 hours per location in the first two years for 20 participants each).

Please check ECHO’s Key Result Indicators or KRIs. KRIs are proposed for the five sectors that jointly cover 80% of ECHO funding: food, nutrition, health, wash and shelter. KRIs enable ECHO to aggregate data on the results of the actions it has funded. In addition to highlighting some of ECHO’s priority development changes, KRIs will also help you inspiring yourself for designing any custom indicators you may need to use. Therefore, the logframe is where you can plan a viable and solid monitoring and evaluation system for your action.

Technical care about transparent and statistically sound data (from sampling, to collection, cleaning and analysis) are key here not only for one’s proposal but also for the improvement of the humanitarian and development policy sector in general. Powerful statistical computing (e.g., RStudio) and geographic information system (GIS) applications (e.g., QGIS) are available for download free of cost to anyone. Wonderful online courses on websites such as Coursera (I particularly like the one on Data Science, but there are many others, including on questionnaire design for social science) and videos can help one evolving ones understanding on such tools. In short, although you will be under time pressure (remembering our starting question), donors expect you to clearly explain and demonstrate the technical qualities of your M&E plans. Some external support (contact us) here can make your life easier later while ensuring validity and reliability of your data and results. A good yardstick to help thinking on what one should invest for the action’s M&E can be: Go for a monitoring and evaluation design for which you would not mind publishing its documented procedures and results.

The increased rigour comes in some extent from the improved accessibility to high-quality data analysis and sharing tools (e.g., cloud databank services) combined with pressure for improved transparency in national and international public service delivery, including the delivery of national and international humanitarian action.

Documenting all your steps from sampling to analysis in some freely accessible markdown language (e.g., RMarkdown) is becoming more and more important. In line with nowadays’ scientific age and good-governance standards, I see five crucial characteristics of high-quality and modern M&E design. Such a design:

1. Tries to account for bias through reproducible sampling and source triangulation, clearly explaining limitations and margins of error.
2. Ensures (statistically) true beneficiary participation for valid and reliable results (e.g., beneficiary satisfaction surveys with trained, independent interviewers) while maximising efficiency in the data collection process,
3. Employs a good blend of quantitative and qualitative data collection methods,
4. Ensures transparent implementation by documenting well all procedures (e.g., using the freely accessible RMarkdown or syntax of other paid statistical packages) and publicly sharing them together with monitoring and evaluation data (e.g., publishing online while ensuring beneficiaries’ anonymity), and
5. Counts on some form of validation by an independent evaluator comparable to what financial auditors do, although in a more supportive and learning-oriented manner. I tend to think that evaluators nowadays need to work more as facilitators of a multi-stakeholder dialogue, providing constructive feedback for improvement, as a good research supervisor in an institute or university would do. This is particularly important for projects testing innovative approaches with potential for replication in other geographical areas, since scaling them up requires robust analysis.