On the Development of Theory-Informed Operationalised Definitions of Demand Patterns

不同的库存单位（SKU）与不同的需求模式相关联，这反过来又需要不同的预测和库存控制方法。因此，我们需要对各种SKU进行分类，并为每个特定类别应用最合适的方法。我们执行这项任务的方式显然对库存和客户满意度有着巨大的影响，因此，相关规则构成了每个库存管理系统的重要组成部分。为了解决这个问题，人们倾向于对需求模式进行分类（使用基于经验的规则），然后选择在每个类别中表现最好的预测和库存控制方法。然而，选择最适当的预测和库存控制方法是进行任何分类工作的目的。因此，更符合逻辑的做法是，首先比较替代估算程序和库存控制模型，以确定其上级性能区域，然后根据结果对需求模式进行分类，而不是反过来。像这样的程序显然有望提供更好的结果。在与约翰·博伊兰（John Boylan）和约翰·克罗斯顿（John Croston）进行的研究中，我们沿着上面讨论的路线，开发了一个理论上连贯的分类方案，仅用于预测目的。然而，库存控制问题没有得到解决，这就是我想做的这项拟议的研究。多年来，这一研究领域吸引了非常有限的学术关注。其中一个原因很可能是相关的相当大的复杂性。也就是说，预测和库存控制必须被看作是相互关联的功能（正如它们在实践中所做的那样），而不是更广泛的解决方案中的独立模块，这显然增加了问题的理论复杂性。虽然一些早期的工作已经做了预测和库存控制之间的相互作用，仍然需要一个理论上连贯的方法，这是第一个建议提供它。本研究的主要目标是产生理论上健全的需求分类规则预测和库存控制的目的。要进行这样的项目，业界从业员的意见是非常重要的。在这方面，已选定两家公司作为项目伙伴。这一合作还将确保能够获得本研究所需的经验数据。我的哲学观点是实证主义的，因为我们寻求的是普遍适用的分类解决方案。然而，由于问题的复杂性，所采用的研究策略不能是纯粹的演绎。理论和数据之间的迭代程序是要引入，这样的方法将确保所有重要的因素都identified.In总结，拟议的研究涉及的问题，是值得调查的理论和实践的角度。在需求分类方面开展的工作很少，从迄今为止的研究来看，尚不清楚管理人员应如何为预测和库存控制目的对需求模式进行分类。这一问题的重要性已多次得到报告，相关文献中一致认为，迫切需要进一步提高这一领域的知识，并对相关问题进行经验评估。因此，拟议的研究是一个非常及时的项目。这样一个项目的结果将在所有预测和库存控制软件包制造商中得到应用。事实上，在任何工业环境中也有一个自然的应用程序，其中内部开发或购买的需求分类计算机化解决方案已经到位，以促进库存管理。

Different Stock Keeping Units (SKUs) are associated with different demand patterns, which in turn require different methods for forecasting and stock control. Consequently, we need to categorise the various SKUs and apply the most appropriate methods for each particular category. The way we are going to perform this task has obviously tremendous implications in terms of stock and customer satisfaction and, as such, the relevant rules constitute a vital element of every inventory management system. To deal with this problem people tend to classify, rather arbitrarily, the demand patterns (using rules that, based on experience, work well) and then select the forecasting and stock control methods that perform best in each category. Nevertheless, the choice of the most appropriate forecasting and inventory control methods is the very purpose of conducting any categorisation exercise. Therefore, it is more logical to first compare alternative estimation procedures and stock control models for the purpose of identifying their regions of superior performance and then, based on the results, categorise the demand patterns, rather than working the other way around. A procedure like this one is obviously expected to offer better results. In research conducted with John Boylan and John Croston we developed a theoretically coherent categorisation scheme, along the lines discussed above, for forecasting purposes only. However, stock control issues were not addressed and this is what I would like to do in this proposed research. This research area has attracted very limited academic attention over the years. A reason for that may well be the considerable associated complexity. That is, forecasting and stock control have to be viewed as interrelated functions (as they are in practice) rather than stand-alone modules of a wider solution, and this obviously increases the theoretical complexity of the problem. Although some early work has been done on the interaction between forecasting and stock control, a theoretically coherent approach is still required and this is the first proposal to provide it.The main objective of this research is to produce theoretically sound demand categorisation rules for both forecasting and stock control purposes. To conduct such a project, the input from industry practitioners is very important. In this regard, two companies have been selected as project partners. This collaboration will also ensure that the empirical data required for the purposes of this research becomes available. My philosophical stand-point is positivistic in the sense that universally applicable categorisation solutions are sought to be developed. However, due to the complexity of the problem, the research strategy employed cannot be purely deductive. An iterative procedure between theory and data is to be introduced and such an approach will ensure that all important factors are identified.In summary, the proposed research deals with an issue that is worth investigating from both a theoretical and practitioner perspective. Very little work has been conducted in the area of demand categorisation and, from the research to date, it is not clear how managers should classify demand patterns for forecasting and stock control purposes. The importance of this issue has been reported on numerous occasions, and what is agreed upon in the relevant literature is the immediate need to further advance knowledge in this area and empirically assess the relevant issues. The proposed research therefore constitutes a very timely project. The results of such a project will find application in all forecasting and stock control software package manufacturers. Indeed, there is also a natural application to any industrial setting where an in-house developed or bought-in demand classification computerised solution is in place to facilitate inventory management.