Understanding the work of the city manager

The managerial behaviour approach to understanding managerial work has developed from research over the course of fifty years. The approach represents a marked departure from mainstream (and still prevalent) management approaches that depict management as a set of general composite functions. The managerial behaviour approach is distinctive in its empirical research background, object, focus and methodology. Its objective is to provide the simple answer to the complex question: what do managers do? However, the emphasis in the studies on managerial behaviour represents a limitation in so far as a context for locating and judging that behaviour is largely absent (Hales, 1986). This paper presents the results of initial research into managers operating in a different and largely neglected context - city councils. The research uses Mintzberg’s (1973) concept of behavioural roles as an analytical tool to explain and understand what city managers do. This study assesses whether these roles adequately capture the important features of managerial work in the city council. It is argued that while Mintzberg’s role framework is useful, structured observation alone does not adequately address the complexities of environments and styles of managers or the cognitive processes of managers. However, by integrating this approach with an appreciation of context and cognitive processes and how they can influence or affect managerial behaviour, we develop a more realistic description of what managers actually do and why they do it.

Towards a model for exploring the relationship between managerial decision problems and decision support opportunities

The organisational decision making environment is complex, and decision makers must deal with uncertainty and ambiguity on a continuous basis. Managing and handling decision problems and implementing a solution, requires an understanding of the complexity of the decision domain to the point where the problem and its complexity, as well as the requirements for supporting decision makers, can be described. Research in the Decision Support Systems domain has been extensive over the last thirty years with an emphasis on the development of further technology and better applications on the one hand, and on the other hand, a social approach focusing on understanding what decision making is about and how developers and users should interact. This research project considers a combined approach that endeavours to understand the thinking behind managers’ decision making, as well as their informational and decisional guidance and decision support requirements. This research utilises a cognitive framework, developed in 1985 by Humphreys and Berkeley that juxtaposes the mental processes and ideas of decision problem definition and problem solution that are developed in tandem through cognitive refinement of the problem, based on the analysis and judgement of the decision maker. The framework facilitates the separation of what is essentially a continuous process, into five distinct levels of abstraction of manager’s thinking, and suggests a structure for the underlying cognitive activities. Alter (2004) argues that decision support provides a richer basis than decision support systems, in both practice and research. The constituent literature on decision support, especially in regard to modern high profile systems, including Business Intelligence and Business analytics, can give the impression that all ‘smart’ organisations utilise decision support and data analytics capabilities for all of their key decision making activities. However this empirical investigation indicates a very different reality.

Enabling effective operational decision making on a Combined Heat and Power System using the 5C architecture

The use of Cyber Physical Systems (CPS) to optimise industrial energy systems is an approach which has the potential to positively impact on manufacturing sector energy efficiency. The need to obtain data to facilitate the implementation of a CPS in an industrial energy system is however a complex task which is often implemented in a non-standardised way. The use of the 5C CPS architecture has the potential to standardise this approach. This paper describes a case study where data from a Combined Heat and Power (CHP) system located in a large manufacturing company was fused with grid electricity and gas models as well as a maintenance cost model using the 5C architecture with a view to making effective decisions on its cost efficient operation. A control change implemented based on the cognitive analysis enabled via the 5C architecture implementation has resulted in energy cost savings of over €7400 over a four-month period, with energy cost savings of over €150,000 projected once the 5C architecture is extended into the production environment.