Forecasting and inventory management of short life-cycle products
Forecasting and inventory management of short life-cycle products
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DOI：
10.1287/opre.44.1.131
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发表时间：
1996-01-01
影响因子：
2.7
通讯作者：
Matsuo, H
中科院分区：
文献类型：
--
作者：
Kurawarwala, AA;Matsuo, H
本文为短生命周期产品的预测和库存管理提供了一个集成的框架。关于预测和库存管理的文献没有充分处理与短生命周期产品有关的问题。我们首先提出了一个增长模型，可以用来获得对产品整个生命周期的准确的月度预测。该模型避免了传统方法对数据需求的限制。相反，它从过去的产品历史中提取相关信息，并利用关于总生命周期销售和销售高峰期的信息。使用来自个人计算机(PC)制造商的伪装需求数据，我们验证了该模型。接下来，我们对短生命周期环境下的库存管理问题进行了建模。需求的不确定性是通过预测模型参数实现值的不确定性来建模的。码头库存的高成本、短缺和快速变化的采购成本都包括在模型中。并对基本模型进行了扩展。利用最优控制理论，我们得到了一个解决方案，提供了关于采购截止时间和码头服务水平的有价值的信息。一个详细的例子解释了该政策的特点及其在决策中的相关性。模型中涵盖的许多问题是在一家PC制造商实施预测模型时引起我们的注意的。基准月度预测和相关的库存水平提供的信息对计划和控制营销、销售和生产非常有帮助。
In this paper, we provide an integrated framework for forecasting and inventory management of short life-cycle products. The literature on forecasting and inventory management does not adequately address issues relating to short life-cycle products. We first propose a growth model that can be used to obtain accurate monthly forecasts for the entire life cycle of the product. The model avoids limiting data requirements of traditional methods. Instead, it extracts relevant information from past product histories and utilizes the information on total life-cycle sales and the peak sales timing. Using disguised demand data from a personal computer (PC) manufacturer, we validate the model. Next, we model the inventory management problem for the short life-cycle environment. The uncertainty in demand is modeled through the uncertainty in the realized values of the parameters of the forecasting model. The high cost of terminal inventory, shortages, and rapidly changing procurement costs are all included in the model. Extensions to the basic model are also developed. Using optimal control theory, we derive a solution that provides valuable information on procurement cutoff time and terminal service levels. A detailed example explains the characteristics of the policy and its relevance in decision making. Many of the issues covered in the models were brought to our attention while implementing a forecasting model at a PC manufacturer. The benchmark monthly forecasts and the associated inventory levels provide information that can be very helpful in planning and controlling marketing, sales, and production.