Supply Chain Forecasting in a Government Owned Corporation
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Xiande Zhao and Baoding Liu
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Hong Kong
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Abstract
This paper looks at identifying factors affecting forecasting decision making in the supply chain of a government owned corporation (GOC), and how a recent Enterprise Resource Planning System (ERP) implementation was perceived with respect to the usability of the forecasting modules available. It is argued that GOCs represent a distinct form of organisation and that ERP implementation strategies may need to modify some of their basic assumptions in order to be successful. The research approach used was a case study as this was seen as the most appropriate to uncovering the deeper issues which may be unique to GOCs. The study consisted of two major steps. The first step identified 31 key personal in the supply chain and these people were interviewed to determine the level of need for decision support tools prior to the implementation of a new ERP. The second step of the research involved conducting interviews with16 of the original 31 staff and this was done after the ERP had been implemented for over a year. The feasibility of improving forecasting through the use of decision support system (DSS) and the degree to which the technology can assist forecasting in the supply chain was then explored. It was discovered that data accuracy was a problem. This was not associated with the ERP implementation, but rather with social factors such as different preferences among groups of staff on how to configure procurement and payment of invoices resulting in a lack of a consistent approach across the entire GOC. A lack of trust in the ERP and ineffective training methods were also identified. This research suggests that ERP implementations within GOC's, in particular those with an extensive distributed network such as transport and electricity, are special cases and should be treated differently to implementations in other industries. Further research studies are needed to determine if ERP implementation in GOCs represent a distinct population with special requirements.
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The 11th Annual Conference of Asia Pacific Decision Sciences Institute
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© The Author(s) 2006. The attached file is posted here with permission of the copyright owners for your personal use only. No further distribution permitted.For information about this conference please refer to the publisher's website or contact the authors.