Cost Risk Management for a Small to Medium-sized Enterprise in the Cladding Industry

Abstract

To research the management of risk and cost in the cladding industry, this work has evaluated current practice and deficiencies, concentrating on the lack of integration or standardisation resulting in inaccurate cost estimates, unacceptable risks and loss of profit in cladding manufacture. The research presents an approach for integrating process- and technology-orientated improvements into a knowledge-based model to improve a cladding manufacturing SME’s performance. The research also presents a management method for the selection, integration, control and implementation of this approach. Controlling data transfer between systems produces a knowledge-based model, allowing cladding industry designers and estimators to take more accurate decisions, with the objective of reducing risk and improving company profitability. This model, with the addition of external supply chain elements, is a management framework, which can be termed an agile manufacturing system.

The development of this framework has raised the following data certainty questions:

• What is the measured uncertainty of that data?
• How can the industry control and structure high data volumes transferred between systems to produce more accurate cost models?

The answers to these questions were found by applying a structured methodology for the selection, integration and control of technology in the cladding industry, but involving the human factor. In this approach, the principle of entropy was adopted to measure data uncertainty. The structured methodology was made possible by a new categorisation into Innovative, Standard and Semi-Standard cladding projects.

The research applied this structured methodology, combining qualitative and quantitative methods for validating assumptions, to a cladding industry SME case-study. The case-study investigated the validity of real cost and project data and calculated data uncertainty for specific projects, categorised as described, using a risk factor percentage predicted on entropy principles, based on historical data fed back from the SME’s ERP system. This risk factor approach was similar to that previously used in the insurance and banking industries. The risk percentage formulae used were based on assumptions extracted from qualitative and quantitative methods applied to the SME, its partner companies and industry specialists. Assumptions about the gross margins for UK metal cladding projects formed part of the risk percentage formulae.

The results of this case-study found that gross margins varied from 5% in standard projects to 40% in the Innovative projects. An entropy scale was proposed as a basis for comparing risk calculation results, with the highest entropy equalling 100%, signifying the highest risk possible. It was found that risk rises in the case-study were from 23% for Standard to 93% for Innovative projects.

This principle of a risk factor percentage was tested in the UK cladding manufacturer SME case-study and its value to the SME was demonstrated.