  Intelligent agents offer a new and exciting way of understanding the world of
work. Agent-Based Simulation (ABS), one way of using intelligent agents,
carries great potential for progressing our understanding of management
practices and how they link to retail performance. We have developed simulation
models based on research by a multi-disciplinary team of economists, work
psychologists and computer scientists. We will discuss our experiences of
implementing these concepts working with a well-known retail department store.
There is no doubt that management practices are linked to the performance of an
organisation (Reynolds et al., 2005; Wall & Wood, 2005). Best practices have
been developed, but when it comes down to the actual application of these
guidelines considerable ambiguity remains regarding their effectiveness within
particular contexts (Siebers et al., forthcoming a). Most Operational Research
(OR) methods can only be used as analysis tools once management practices have
been implemented. Often they are not very useful for giving answers to
speculative 'what-if' questions, particularly when one is interested in the
development of the system over time rather than just the state of the system at
a certain point in time. Simulation can be used to analyse the operation of
dynamic and stochastic systems. ABS is particularly useful when complex
interactions between system entities exist, such as autonomous decision making
or negotiation. In an ABS model the researcher explicitly describes the
decision process of simulated actors at the micro level. Structures emerge at
the macro level as a result of the actions of the agents and their interactions
with other agents and the environment. 3 We will show how ABS experiments can
deal with testing and optimising management practices such as training,
empowerment or teamwork. Hence, questions such as "will staff setting their own
break times improve performance?" can be investigated.
