The Logical Framework
The logical framework or logframe is probably the most important document in project planning and in the M&E process. It is particularly valued by donors.
The discussion of this topic will cover:
What is a Logframe?
The Logical Framework is:
- a planning tool that sets out the objectives of a project and how they will be measured
- the most commonly used tool in M&E, favoured especially by funders
- a concise document (usually no more than two pages)
It should be:
- clear, readable and jargon-free
- designed ideally with input from beneficiaries
- the basis for M&E later and hence kept under constant review
- filled in initially with the data you expect to find from the project
- completed at the half-way point/end of your project with the actual data collected
The format of the logframe can vary from one organisation to the next but will often include the following elements:
In other cases, it may simply include:
Here is an example of a blank logframe:
|Narrative Summary||Indicators||Means of verification||Assumptions (& Risks)|
For a blank template and an example of a logical framework, see Tools4dev.
Constructing a logframe
For a detailed explanation of how to construct a lograme click here
Before building your logframe, it helps if you understood the vocabulary associated with it. For an explanation of the key terms click here.
See below the types of data that are often entered in a logframe. This example is drawn from the Centre for International Private Enterprise
Logframe: Pros & Cons
As a rule, donors and other public bodies prefer NGOs to report using metrics-based variables and indicators, particularly the logical framework.
Donors understandably have a concern over value for money and accountability. As such, the focus is on measurable empirical evidence, often in the form of numbers and quantifiable results outputs and outcomes.
Donors like the logframe and metrics-based approaches for some of the clear advantages they bring:
It ensures that:
- Objectives are clear, coherent and measurable
- Concrete evidence is sought for activities that work and those that do not
- Comparisons can be drawn across projects/ programmes and conclusions reached about best practice
- Problems are analysed systematically and risks and assumptions are made explicit
- Helps you organise your ideas and thoughts to express them to other people who might be interested in your projects/ programmes
- It shows you what you should be measuring to determine if you are achieving your goals – clearly stating your outputs and outcomes
- It makes your main goals and objectives clear to anyone who is interested in your outcomes and impact
- It often requires data that is unattainable in contexts like Africa or statistical analysis that NGDOs/ VOs would struggle to undertake
- Your programs may not fit perfectly in the model. There may be multiple steps to your project or there may be several steps that are reoccurring or happen simultaneously
- It does not consider the larger community and context within which your project operates
- It is ‘one size fits all’ approach which does not always capture complexity and nuances
- It can as such lead to numbers being made up
- It over-emphasises measurable indicators and planning. In other words, these indicators can often be forgotten about until such time as a report is required by funders. See also our section on why M&E is avoided.
- It reflects a bias towards planning rather than monitoring
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