This article is part 11 of a series of articles featuring the ODI Background Note A guide for planning and strategy development in the face of complexity.
Given their format (a matrix with narrative descriptions) logical frameworks, or logframes, assume a linear and quasi-automatic progression of effects. The assumption is that if activities are carried out as planned, this will guarantee the achievement of expected outputs or purposes. Some of the underlying assumptions, such as perfect advance knowledge and full control of implementation, are not valid in complex situations. To mitigate these limitations, adjustments can be made to logframe content and use.
The following framework was developed recently for the United Nations Industrial Development Organization (UNIDO) to make logframes a more flexible and adaptive planning tool. The starting point is situational recognition. Outputs are categorised into three types of domains (simple, complicated, complex), by using the (dis)agreement/(un)certainty parameters (see Box 1) and clustering them with the portfolio technique (Figure 1).
This output portfolio then has two key implications for the completion of other elements of the logframe:
- if outputs lie predominantly in the ‘complicated’ domain, indicators and assumptions should be identified carefully to enable monitoring (and evaluation) of effective practice, relevant factors and context conditions
- if many (or even the majority of) outputs are considered to be ‘complex’, the indicators should allow the documentation of initial conditions and – in combination with assumptions – capture emerging phenomena.
This framework places specific emphasis on the ‘Assumptions & Risks’ column of a logframe. The assumptions are used explicitly to connect the various levels in a logframe. They address, therefore, the processes that are expected to transform the achievements of one level (e.g. outputs) into the next level of effects (e.g. outcomes). They should, in particular, describe expected changes, behaviour or communication patterns of specific actors (e.g. beneficiaries, recipients or partners) and articulate intended combinations (e.g. of outputs).
For interventions that achieve their objectives through the contributions by specific actors or by ensuring that expected effects reach specific target groups, the logframe should capture the actor dimension. This can be done in several ways.
- A complementary ‘influence matrix’ can be used to show the intended linkages between effects (e.g. outputs) and actors (either as contributors or beneficiaries), which also allows the capture of multiple relationships.
- Each level of a logframe can be associated with various actors, who are expected to collaborate for their achievement. Their relationships can be shown at each level and also across levels (e.g. by using social network analysis). The various time stages are, therefore, complemented by a sequence of actors (‘social framework’). The intended pathways for information, resources or material objects between these actors can be defined at the planning stage, which then also clarifies the division of responsibilities across a range of actors.
- For interventions that involve social change processes or where capacity building plays a major role, a fusion of logframe and outcome mapping can be applied. This combines the results-oriented focus of logframes with the process-oriented learning pathways of outcome mapping. Elements of outcome mapping (e.g. outcome challenges or progress markers) can be inserted in the logframe structure to highlight the expected changes in the behaviour of relationships, actions or activities of the people, groups, and organisations with whom an external agent is working directly and seeking to influence.
Next part (part 12): Conclusions.
See also these related series:
- Exploring the science of complexity
- Managing in the face of complexity
- Taking responsibility for complexity.
Article source: Hummelbrunner, R. and Jones, H. (2013). A guide for planning and strategy development in the face of complexity. London: ODI. (https://www.odi.org/publications/583-exploring-science-complexity-ideas-and-implications-development-and-humanitarian-efforts). Republished under CC BY-NC-ND 4.0 in accordance with the Terms and conditions of the ODI website.