An engineering approach to risk assessment of project improvement
Creators: name: Nicholds, Boyd
Publisher: name: RMIT University
Year: 2024

description: A review of the research literature and observations obtained from personal professional experience in process improvement indicate process improvement success is not guaranteed and there are many factors that conspire to push improvement initiatives toward failure. Indications are that process improvement failure rates in manufacturing environments are high and that performance gains attained struggle to be sustained over time. The same mistakes appear to occur repeatedly and it would appear at first glance that manufacturing organisations on the whole are slow and ineffective learners. However often before undertaking a course of education it is first necessary to understand that an entity, either person or organisation, has a knowledge gap that would be beneficial to close. It is difficult to take action on risks inhibiting the likelihood of success if that organisation is oblivious to the existence of these risks. A further problem occurs when organisations attempt process improvement and set performance targets which in practice the organisation has little chance of achieving. In these circumstances personnel involved may experience frustration and discontent when improvements initiatives continually flounder and as a result avoid further participation at all costs. This situation is not inevitable and is avoidable.<br><br>A risk assessment method has been developed in this research with the aim of providing manufacturing organisations in particular with knowledge they require to increase their probability of success in process improvement projects. The method provides knowledge the organisation requires of the capability areas they need to strengthen and guidance on areas to tackle first. From data collected on the state of the manufacturing improvement system the risk assessment model provides an estimate of the probability of success or odds of achieving defined performance targets. Access to this quantitative probability of success predictions for future performance allows a more realistic matching of performance gain expectation to the capability of achieving that gain. Use of the new developed risk assessment method provides therefore a benefit to manufacturing industry by better matching improvement expectations to existing capability to achieve them.<br><br>New variables and functions have been developed as components of the innovative risk assessment model. The ‘performance effectiveness’ variable kP is a new measure of the effort applicable to obtain a level of performance gain. The new function P vs kP matches performance gain to the effort required to attain that gain based on characteristics of the specific process improvement project. The function kP vs SC specifies the range of effort kP an organisation can apply to an improvement based on their level of improvement capability defined as the ‘capability score’ SC. Integration of these functions provides a quantitative estimate of the probability of success in attaining a desired performance target. As a result performance targets may be set with the knowledge of the probability or odds of achieving them and less on misplaced optimism and wishful thinking. Proof of application of the new model is provided by two industry case studies.<br><br>Accumulated risk factors once known may be used to drive capability improvement. This drive is not possible if potential risk factors are not known. Realistic matching of performance gain expectations to current improvement capability improves odds of success resulting in increased willingness over time for personnel to contribute and participate in further improvement projects. This then is the basis of successful continuous improvement in a manufacturing organisation. <br><br>