Managing in the face of complexity (part 2.2): Task 1: Assess the level of uncertainty
This article is part 2.2 of a series of articles featuring the ODI Working Paper A guide to managing in the face of complexity.
First, we must decide whether there is clear advance knowledge on how to achieve the desired outcomes in the given context. For example, if the intervention aims to build a school or road, the required ingredients and outputs are well-known, and we can rely on standards and best practices methods. It is worthwhile, therefore, to work according to pre-determined and detailed procedures in order to produce the expected outputs. For other interventions, such as improving human rights practices or combating poverty, neither the outputs nor the means to achieve these goals are well established: experience and ‘good practice’ from other contexts may not be appropriate and will need to be ‘re-learned’. It may be that our goals change over time, as we learn from implementation and experience gained elsewhere – or have to adapt to changes in context. This might include intermediary outcomes (e.g. when outcomes are considered inappropriate or have negative effects that could not have been foreseen) or even top-level goals, as well as outputs. If the best ways to address a problem are not yet well understood, and if alternative routes are available or innovative solutions could be developed, it can be difficult to fix detailed deliverables or rigid divisions of labour. What is possible is to have a broad understanding of relevant roles and responsibilities, an evolving list of tasks and activities and an emergent understanding of how to achieve outcomes.
Second, we should assess whether the intervention’s success depends in part on forces that are outside the control of its managers, or on trends about which there is little advance knowledge. While traditional project management tools are designed to function best in controlled environments, interventions must often proceed without outright control, and sometimes without any significant influence, over key factors that will affect its success. A programme of reform might rely on achieving political and bureaucratic buy-in at various stages, but securing genuine ownership can only be influenced, rather than guaranteed. For example, a project working to protect migrants leaving to work abroad is strongly influenced by the behaviour of employers in another country, over whom the project has very limited influence. This is particularly true for interventions that require a combination of resources and, therefore, the collaboration of various actors.
Why does uncertainty matter for management?
- In situations when it is not clear how to achieve the best result in a given context, using only fixed plans and procedures to guide management could reduce the relevance of formal tools to key management tasks and decisions. The actual work and outputs of the team may itself become irrelevant due to having to fit within a rigid framework. Without space for learning or innovation in performing key functions, the intervention may not get the best end result or not achieve its aims at all.
- Changes in the context which are outside an intervention’s control (and often therefore difficult to predict) have major implications for its success. If emerging windows of opportunity are not responded to, opportunities for success might be missed. Where unexpected new blockages or crises arise, interventions may not achieve desired outcomes if they do not adapt.
Next part (part 2.3): Task 2: Assess the level of agreement.
See also these related series:
- Exploring the science of complexity
- Planning and strategy development in the face of complexity
- Taking responsibility for complexity.
Article source: Hummelbrunner, R. and Jones, H. (2013). A guide to managing in the face of complexity. London: ODI. (https://www.odi.org/sites/odi.org.uk/files/odi-assets/publications-opinion-files/8662.pdf). Republished under CC BY-NC-ND 4.0 in accordance with the Terms and conditions of the ODI website.
Header image source: pxhere, Public Domain.
