Making sense of supply chain management: acomparative study of aerospace and construction

Current recipes for learning across business sectors too often fail to recognize the embedded and contextual nature of management practice. The existing literature gives little emphasis to the symbiotic relationship between supply chain management and the broader dynamics of context. The aerospace and construction sectors are selected for comparison on the basis that they are so different. The UK aerospace sector has undergone extensive consolidation as a result of the imperatives of global competitive pressures. In contrast, the construction industry has experienced decades of fragmentation and remains highly localized. An increasing proportion of output in the aerospace sector occurs within a small number of large, globally orientated firms. In contrast, construction output is dominated by a plethora of small firms with high levels of subcontracting and a widespread reliance on self-employment. These differences have fundamental implications for the way that supply chain management is understood and implemented in the two sectors. Semi-structured interviews with practitioners from both sectors support the contention that supply chain management is more established in aerospace than construction. The introduction of prime contracting and the increasing use of framework agreements within the construction sector potentially provide a much more supportive climate for supply chain management than has traditionally prevailed. However, progress depends upon an improved continuity of workload under such arrangements.

Learning across business sectors: Knowledge sharing between aerospace and construction

This report addresses the extent that managerial practices can be shared between the aerospace and construction sectors. Current recipes for learning from other industries tend to be oversimplistic and often fail to recognise the embedded and contextual nature of managerial knowledge. Knowledge sharing between business sectors is best understood as an essential source of innovation. The process of comparison challenges assumptions and better equips managers to cope with future change. Comparisons between the aerospace and construction sectors are especially useful because they are so different. The two sectors differ hugely in terms of their institutional context, structure and technological intensity. The aerospace sector has experienced extensive consolidation and is dominated by a small number of global companies. Aerospace companies operate within complex networks of global interdependency such that collaborative working is a commercial imperative. In contrast, the construction sector remains highly fragmented and is characterised by a continued reliance on small firms. The vast majority of construction firms compete within localised markets that are too often characterised by opportunistic behaviour. Comparing construction to aerospace highlights the unique characteristics of both sectors and helps explain how managerial practices are mediated by context. Detailed comparisons between the two sectors are made in a range of areas and guidance is provided for the implementation of knowledge sharing strategies within and across organisations. The commonly accepted notion of ‘best practice’ is exposed as a myth. Indeed, universal models of best practice can be detrimental to performance by deflecting from the need to adapt continuously to changing circumstances. Competitiveness in the construction sector too often rests on efficiency in managing contracts, with a particular emphasis on the allocation of risk. Innovation in construction tends to be problem-driven and is rarely shared from project to project. In aerospace, the dominant model of competitiveness means that firms have little choice other than to invest in continuous innovation, despite difficult trading conditions. Research and development (R&D) expenditure in aerospace continues to rise as a percentage of turnovers. A sustained capacity for innovation within the aerospace sector depends crucially upon stability and continuity of work. In the construction sector, the emergence of the ‘hollowed-out’ firm has undermined the industry’s capacity for innovation. Integrated procurement contexts such as prime contracting in construction potentially provide a more supportive climate for an innovation-based model of competitiveness. However, investment in new ways of working depends upon a shift in thinking not only amongst construction contractors, but also amongst the industry’s major clients.

Achieving quality through statistical prediction for building services systems

The application of prediction theories has been widely practised for many years in many industries such as manufacturing, defence and aerospace. Although these theories are not new, their application has not been widely used within the building services industry. Collectively, the building services industry should take a deeper look at these approaches in comparison with the traditional deterministic approaches currently being practised. By extending the application into this industry, this paper seeks to provide the industry with an overview of how simplified stochastic modelling coupled with availability and reliability predictions using historical data compiled from various sources could enhance the quality of building services systems.

Learning across business sectors: facets of innovation in aerospace and construction

Innovation is notoriously difficult to define and is invariably intertwined with issues of knowledge creation, continuous improvement and organisational change. An extensive literature classifies numerous types of innovation and militates against any simplistic attempt at definition. It is widely accepted that innovation is at least partly dependent upon the surrounding environment. Industry recipes and institutionally embedded practices shape the environment within which innovation occurs. Recent research directions have addressed the diffusion of innovation and its dependence upon social and institutional structures. In this respect, it is highly pertinent to compare the way that innovation is interpreted and enacted in different industrial sectors. The comparison between UK aerospace and construction is especially revealing because the two sectors are so different and therefore constitute radically different climates for innovation. Empirical research is reported based on semi-structured interviews with practitioners from both sectors. Interpretations of innovation are found to differ dramatically between aerospace and construction. Within the context of an ongoing struggle to define innovation, both industries are striving to become more innovative. The aerospace sector is found to emphasise technical innovation whereas the construction sector emphasises process innovation. An overriding cultural bias in Western economies towards technological innovation results in the common perception that aerospace is much more innovative than construction. The experienced realities of practitioners in the two sectors are much more complex.

High value information in engineering organisations

The management of information in engineering organisations is facing a particular challenge in the ever-increasing volume of information. It has been recognised that an effective methodology is required to evaluate information in order to avoid information overload and to retain the right information for reuse. By using, as a starting point, a number of the current tools and techniques which attempt to obtain ‘the value’ of information, it is proposed that an assessment or filter mechanism for information is needed to be developed. This paper addresses this issue firstly by briefly reviewing the information overload problem, the definition of value, and related research work on the value of information in various areas. Then a “characteristic” based framework of information evaluation is introduced using the key characteristics identified from related work as an example. A Bayesian Network diagram method is introduced to the framework to build the linkage between the characteristics and information value in order to quantitatively calculate the quality and value of information. The training and verification process for the model is then described using 60 real engineering documents as a sample. The model gives a reasonable accurate result and the differences between the model calculation and training judgements are summarised as the potential causes are discussed. Finally, several further issues including the challenge of the framework and the implementations of this evaluation assessment method are raised.