Supporting the Forecasting of Uncertain Product Demand in Supply Chain with Digital Tools

Publication Type:
Thesis
Issue Date:
2021
Full metadata record
This thesis examines the barriers faced in forecasting uncertain product demand within an electrical luminaire manufacturer in Australia. As luminaire technology has rapidly advanced in the last decade, the organisations' processes and systems for forecasting demand are no longer adequate. Forecasting uncertain product demand is a fundamental part of the supply chain's sales and operations planning process. The size and complexity of forecasting uncertain product demand are regarded as one of the more challenging activities in the supply chain. This is especially the case in the luminaire industry, where demand uncertainty, lack of historical data, and competitive environments coexist. Our industry research's general premise is that the process of forecasting uncertain product demand in the supply chain could be improved in terms of transparency, efficiency, effectiveness, and useability by embedding a form of a digital toolkit. Many of the existing methods, tools, and approaches in forecasting uncertain product demand are either too complex for practice or cannot solve the barriers. In this research, we take a design science approach to investigate both state-of-the-art and state-of-the-practice to identify the barriers in forecasting uncertain product demand. We then develop and evaluate a software toolkit to support practitioners in forecasting uncertain product demand. The first stage of the research is a systematic literature review involving a thorough review and critical analysis of existing theories. A pilot study is then conducted to gain in-depth information about the overall supply chain domain. This is followed by a field study at the Australian Luminaire Manufacturer (ALM ), which consists of semi-structured interviews with end-to-end supply chain stakeholders and the elicitation of stakeholder requirements which we prioritise by using the card-sorting method. Based on the requirements prioritised, a toolkit is designed and developed to support the organisation in forecasting uncertain product demand. The designed and developed toolkit provides a set of tools, yet a cohesive set of software components that can be utilised to support the forecasting of uncertain product demand. The toolkit includes market segmentation and market intelligence reporting, a full forecasting model, and a framework to make forecast adjustments. The final stage of the research involved the evaluation of the toolkit. This involved a focus group and questionnaire with end-users. The research findings were also presented to the organisations executive management. This thesis offers interesting insights and valuable directions for managers contemplating investing in improving accuracy in forecasting uncertain product demand in the supply chain.
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