Forecasting the inventory levels of an industrial enterprise in conditions of demand volatility

D. Yashkin
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Abstract

The aim of the article is to provide tools for obtaining reliable forecasts of the level of inventories of the enterprise in conditions of volatility in demand for products. Most types of demand for industrial products are unstable, so it is important to form stocks based on demand forecasts to reduce logistics risks. The results of the analyses. Analytical tools for forecasting maximum level of inventories in conditions of volatility of demand for products of machine-building enterprises have been developed, which provides an opportunity to obtain the most reliable sales forecast and estimate the maximum required stocks for a certain type of demand. The method, which is obtained by analytical tools, is based on a three-stage algorithm: a) identification of trends in a time series of sales; b) obtaining optimal sales forecasting models; c) plotting of interval forecasts of product sales and risk assessment of the formation of its maximum stocks. The developed methodology identifies logistics risks, which depend on sales forecasts, for nine machine-building enterprises of Ukraine. A method for statistical assessment of logistics risks of machine-building enterprises by confidence intervals has been developed, in which maximum stocks are determined by two confidence intervals of sales forecasts, and the risk of error is associated with the appropriate levels of reliability of these intervals. It is proposed to build the upper limits of two confidence intervals, for example, 95% and 99%, according to the forecast inventory level estimates, and to consider them as maximum inventory level estimates with corresponding probabilities. The risk of stock shortages is defined as the probability of going beyond the upper limit of the corresponding interval. It is proved that the dynamics of monthly or quarterly sales of enterprises can be typed by four patterns: the presence of seasonal fluctuations and trends; the presence of purely seasonal fluctuations without a pronounced trend; no seasonal fluctuations, but the presence of a trend; no seasonal fluctuations and trends. Conclusions and perspectives for further research. It is proved that the volatility of monthly or quarterly sales volumes of enterprises can be typed by four patterns: 1) the presence of seasonal fluctuations and trends; 2) the presence of purely seasonal fluctuations without a pronounced trend; 3) no seasonal fluctuations, but the presence of a trend; 4) no seasonal fluctuations and trends. Based on this, the theoretical and methodological principles and analytical tools for forecasting the maximum stocks of an industrial enterprise in conditions of demand volatility were improved. Keywords: seasonality, volatility, inventory level forecasting, maximum stocks, demand forecasting.
在需求波动的情况下预测工业企业的库存水平
本文的目的是为在产品需求波动的情况下获得企业库存水平的可靠预测提供工具。大多数工业产品的需求类型是不稳定的,因此根据需求预测形成库存以降低物流风险是很重要的。分析的结果。开发了机械制造企业在产品需求波动条件下最大库存水平预测的分析工具,为获得最可靠的销售预测和估计某类需求的最大所需库存提供了机会。该方法由分析工具获得,基于三阶段算法:a)确定销售时间序列的趋势;B)获得最优的销售预测模型;C)绘制产品销售的区间预测和最大库存形成的风险评估。开发的方法确定物流风险,这取决于销售预测,为乌克兰的九家机械制造企业。提出了一种用置信区间对机械制造企业物流风险进行统计评估的方法,其中最大库存由销售预测的两个置信区间确定,误差风险与这些区间的适当可靠程度有关。提出根据预测的库存水平估计建立95%和99%两个置信区间的上限,并将其视为具有相应概率的最大库存水平估计。库存短缺风险定义为超出相应区间上限的概率。事实证明,企业月度或季度销售动态可以通过四种模式进行分类:存在季节性波动和趋势;存在纯粹的季节性波动,没有明显的趋势;没有季节性波动,但存在趋势;没有季节性波动和趋势。结论及进一步研究的展望。证明了企业月度或季度销售额的波动可分为四种模式:1)存在季节性波动和趋势;2)存在纯粹的季节性波动,没有明显的趋势;3)无季节波动,但存在趋势;4)无季节波动和趋势。在此基础上,改进了需求波动条件下工业企业最大库存预测的理论和方法原则以及分析工具。关键词:季节性,波动性,库存水平预测,最大库存,需求预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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