Managing in the face of complexity (part 3.1): Tailoring management approaches to complex situations
This article is part 3.1 of a series of articles featuring the ODI Working Paper A guide to managing in the face of complexity.
Complexity heightens the importance of effective management. As argued in our guide to planning in the face of complexity1, high uncertainty reduces to what extent all relevant aspects of an intervention can be decided before it begins, meaning we should pay more attention to sound decision-making throughout the course of an intervention, rather than enforcing a preconceived approach. The key function of management is (at least) twofold: providing leadership and guidance for the desired change, but also being sensitive to contextual factors and responsive to changes, emerging facts or experience gained during implementation.
However, the management approaches and tools used most widely in international development (e.g. Logical Framework, Project Cycle Management, project management, change management) are founded predominately on the assumption of high certainty, consensus, and concentrated capacities, making them less appropriate for complex situations. A way out of this dilemma would be to follow the growing trend in management for contingency, i.e. moving away from regarding management approaches as a universally applicable set of principles, towards advocating that they should be chosen to match the situation at hand.
Recently some management thinkers inspired by complexity theory (e.g. Stacey, Snowden) emphasise the limits of predictability for choosing the appropriate management approach. They propose to distinguish between the three types of situations described in Box 1 (simple, complicated and complex) and argue that making these distinctions is important for an efficient and effective use of resources. Because of their predictable nature, simple situations are easier to manage and therefore require less resources (e.g. people, money, time). Conversely, managing situations as if they were simple – when in fact they are not – is also a poor use of resources because actions are probably based on wrong assumptions about the relationships between action and their consequences, which can lead to costly failure and revisions. The Cynefin approach outlined in … [part 4.1] can be used as a framework for identifying appropriate management responses.
The need for situational adaptation would also apply to the various forms of ‘performance management’ or Results Based Management (RBM) currently on the rise in development aid. As argued in Box 2, they are based on the assumption of unequivocal and shared definitions for performance as well as knowable relationships between activities and results, which may not be the case for many aspects of an aid agency’s work. There is a growing literature (e.g. Bowland/Fowler, Seddon, Eyben) showing how, applied to complex problems, these approaches lead to perverse incentives and sometimes the undermining of performance (see Box 2). However, RBM and performance frameworks tend to be rolled out wholesale across agencies, without sensitivity to the different types of challenges faced e.g. working on health vs. working on human rights. Despite this growing evidence it remains to be demonstrated how this management approach can be applied in a more reflective and differentiated manner, although there are some efforts undertaken in this direction2.
Box 2: is Results-Based Management (RBM) fit for complexity?
RBM is a broad organisational performance management strategy that emphasises the measurement of results at various levels, and the use of that information to prove and improve performance. By comparing RBM with our three complexity challenges, we can get a better understanding of how and where it might be relevant or useful:
- Uncertainty: RBM is meant to allow teams the flexibility to experiment, adapt and learn, and is hence based on an appreciation that there may not be clear knowledge on how best to achieve an outcome. However, in practice, often the level of ‘results’ at which teams are meant to perform is that of ‘impact’, which is not realistically in the control of any one unit (or even agency) to achieve, especially not in the timeframe of development interventions – and this misalignment disincentivises learning and innovation3.
- Distribution of capacities: As originally conceived, RBM is designed to empower different management units, giving the space and responsibilities required in order to innovate and to formulate their own approaches to achieving results. However, in practice RBM has been implemented in addition to procedural regulations (as opposed to these being relaxed to allow for innovation), meaning that it imposed additional rules and rigidities rather than freeing up space to learn.
- Divergent goals: Most problematically, RBM is based on an assumption of unequivocal and shared definitions of ‘results’ and performance which can be formulated into a hierarchy of quantitative indicators. This is not appropriate in many areas of the public sector; goals that are too narrow promote risk-averse behaviour and disincentivise the kinds of collaboration and relationship- building actually required to achieve them4.
The weight of experience is holds that RBM has not functioned well, either for the complex problems faced in development and or in the public sector more broadly. On points (1) and (2) this would seem to relate to how it has been implemented, where practices do not fit with complexity principles; on (3), there is a more fundamental problem of inappropriate assumptions. The evidence to some extent aligns with the symptoms of mis-applying tools designed for non-complex situations described in section 1: not only with the perverse incentives mentioned above, but and more broadly with respect to the divide between formal structures and implementation realities. For example, evaluations all around the world have recurrently shown that the information about performance information has minimal utility for decision-making in the public sector5,6.
The principle of contingency is the underlying thread to this … [series], running through the links between challenges and principles below, and the more specific approaches that we will suggest. Therefore, if you have found that your project, programme or policy is facing complexity according to the criteria set out above, it is important to choose approaches that fit with the nature of the problems you face. Beyond adopting a generalised contingency approach, we suggest applying the following three principles when one or more of the three complexity challenges (uncertainty, distribution of capacity, uncertain goals) are present:
- A. Move from static to adaptive management [part 3.2]
- B. Move from directive to collaborative management [part 3.3]
- C. Move from centralised to decentralised management [part 3.4]
The relevance of these principles can be seen when applied to any or all of the three complexity challenges. The choice of principles should depend on your assessment of the degrees and types of complexity faced:
- Interventions facing high uncertainty are likely to find all three principles useful, but in particular an adaptive management approach. Managing an intervention as if everything was simple is ineffective, but managing everything as if it was complex is inefficient (management approaches designed to handle complexity will be ‘overkill’ for a simple scenario). Therefore the management response should be adapted to the situation at hand and also be suited to deal with the type of change envisaged.
- Interventions facing divergence are likely to find collaborative management and leadership styles useful. Instead of leadership by a single entity, partners should be involved in ‘steering’ processes based on iterative cycles of negotiation and agreement. Taking account of different perspectives is key for dealing with divergent opinions. But reducing disagreement about what to do may mean having to cope with messy or wicked problems and difficult conversations. Contingency approaches may also be useful to help distinguish between elements most in need of collaborative management and those less so.
- Interventions facing distributed capacities can turn to decentralised management, leadership and organisation. Ownership and responsibility can be strengthened by distributing management tasks throughout a cooperation system that is organised as a set of interconnected subsystems. Leadership styles that support and respect self-organisation, quality assurance measures and adequate information flows will strengthen coherence.
Next part (part 3.2): A. Move from static to adaptive management.
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.
References:
- Hummelbrunner, R. and Jones, H. (2013). A guide to planning and strategy development in the face of complexity, ODI Background Note. London: Overseas Development Institute. ↩
- Wauters, B. (2013). ‘Sourcebook on results based management in the EU Structural Funds’, Community of Practice on RBM in EU Structural Funds. ↩
- APSC (2009). ‘Delivering Performance and Accountability, Contemporary Government Challenges.’ Canberra: APSC. ↩
- Kamarck, E. (2007). The End of Government … As We Know It: Making Public Policy Work. Boulder, CO: Lynne Reinner. ↩
- OECD DAC (2000). Results-based Management in the Development Co-operation Agencies: A Review of Experience. Paris: OECD DAC. ↩
- Thomas, P. (2007). ‘Why is Performance-based Accountability So Popular in Theory and Difficult in Practice?’ World Summit on Public Governance: Improving the Performance of the Public Sector. Taipei, 1-3 May. ↩
