Reliability analysis of productivity enhancement initiatives

Purpose: Process improvement (PI) projects in manufacturing suffer from high failure rates, often due to management capability overstretch. An organisation’s management may be unaware that they lack the necessary capability to achieve desired performance gains from a particular PI project. As a consequence, PI projects containing a level of complexity are undertaken but the organisation is not capable of providing the required resources. The purpose of this paper is to develop a new method for assessing whether a productivity enhancement initiative which develops into PI projects have a good probability of success (POS). The risk assessment method predicts the POS in achieving desired performance targets from a PI project. Design/methodology/approach: The POS of a system can be measured in terms of reliability. An operation with a high POS indicates high reliability of the system’s ability to perform. Reliability is a form of risk assessment. When applied to PI projects, several key factors should be addressed. First, risk should be modelled with a framework that includes human factors. Second, time is an important dimension due to the need for persistence in effort. This research proposes the concept of performance effectiveness function, kP, that links the capability of an organisation with its performance level. A PI reliability function indicating the probably of success of the PI projects can then be derived at the design stage by combining the capability score and actual performance. Findings: The PI reliability function has been developed and tested with an industry case in which a PI project is planned. The analysis indicates that the company is far from ideal to do the project. Research limitations/implications: The reliability function may be used as a decision support tool to assist decision makers to set realistic performance gain targets from PI projects. The data set for deriving the function came from automotive and metal industries. Further research is required to generalise this methodology to other industries. Practical implications: The reliability-based approach fills the gap in PI literature with a more holistic approach to determine the POS. Using the system’s reliability as an indicator, decision makers can analyse the system’s design so that resources can be used to increase key capabilities and hence the overall system’s POS can be increased more effectively. Social implications: Many manufacturing organisations are looking to improve their operations by projects that aim to reduce waste in their operations. However, researches show that while achieving desired performance gain from PI is possible, it is by no means certain due to human factors. This research provides a decision support tool that evaluates human factors as well. Originality/value: The originality lies in integration of the reliability theory to PI risk assessment and the novel method of characterising organisational capabilities to work towards meeting desired performance targets from manufacturing PI projects. This work has good potential to generalise for estimating the POS of other types of development projects.