An introduction to complexity in Management Science: a personal view

1. An introduction to complexity in Management Science: a personal view Mike Pidd Management Science M.Pidd@lancaster.ac.uk

2. Starting points Models Definitions Complexity? Occam’s razor Soft systems methodology Emergence

3. Management science? • An oxymoron? • Interested in intervention and improvement as well as understanding (See: Pidd M. (2003) Tools for thinking: modelling in management science (2nd ed) Wiley, Chichester)

4. Some definitions of complexity • Commonsense • A function of the number of elements in some whole, and of their interactions • IEEE, 1990 • the degree to which a system or component has a design or implementation that is difficult to understand and verify • Mikulecky, 2003 • the property of a real world system that is manifest in the inability of any one formalism being adequate to capture all its properties It’s complicated & out there! Some of it’s in here! Some of it’s in here!

5. Occam’s razor • Do not multiply entities unnecessarily • Prefer a simple theory if two theories offer the same explanatory power • But … some questions … • How do we know what is necessary? • What type of explanation do we want? • Who’s giving this instruction? • Who’s obeying this instruction?

6. Permeable boundaries Behave More than one component Internal organisation Emergence 1: open systems

7. Emergence 2: what is it? Emergent behaviour: two views • Is what causes us to see a system • May be ‘out there’ • May be in the eye of the beholder • We can’t/won’t see what we won’t/can’t see • Is a property of the elements and their interactions

8. Checkland’s soft systems methodology Two core notions for coping with complexity • The methodology of enquiry can be systemic • Cyclic, dynamic, open system • Core metaphor: human activity system • Artefacts • Purposefully designed wholes that include human action and intent • The importance of worldview • Lead to conceptual models

9. Using models to cope with complexity: 2 views • Representations • external and explicit representations of part of reality • as seen by the people who wish to use that model • to understand, to change, to manage and to control that part of reality • need to be validated and tested • Devices to support debate • transitional objects • embodying beliefs and opinions • explicit for debate and scrutiny

10. Conceptualisation Extract Create Reflect Test Models as tools for thinking • ‘Reality’ • Complex • Ill-defined • Abstract • Model • Simple • Defined • Concrete

11. Bringing it all together: complexity in management science • Complexity: may be • a function of external complication • or of internal uncertainty • Emergence: may be • what brings a ‘system’ to our notice • or a function of its internal structure and operation • Coping with complexity: requires • Rigorous methodology • Sensible use of models as tools for thinking