Please use this identifier to cite or link to this item: https://repositori.mypolycc.edu.my/jspui/handle/123456789/7156
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dc.contributor.authorTejas Belgamwar-
dc.contributor.authorNinad Sayare-
dc.date.accessioned2025-10-27T05:27:49Z-
dc.date.available2025-10-27T05:27:49Z-
dc.date.issued2021-
dc.identifier.issn2277–3193-
dc.identifier.urihttps://repositori.mypolycc.edu.my/jspui/handle/123456789/7156-
dc.description.abstractThe purpose of the exercise was to find fitting solution to the problems faced in supply chain – How to decide the Inventory? How to maintain lean operations without hampering service levels? In our experience in the industry, we have found that in the lack of a better solution, companies have adopted simplistic methods, incorrectly assessing their need and in turn taking a strategic backseat in the competitive space. Ironically the answer to this archaic problem has always been in their hands – Data. Our module leverages sophisticated statistical models like Holts winter, AR, ARMA, ARIMA & SARIMA available in Python Libraries. The module is made so that an average excel user will be able to leverage available data and decide optimum inventory.ms_IN
dc.language.isoenms_IN
dc.publisherResearch India Publicationsms_IN
dc.relation.ispartofseriesInternational Journal of Operations Management and Services;Volume 11, Number 1 (2021), pp. 1-10-
dc.subjectInventory management systemms_IN
dc.subjectMaximum profitms_IN
dc.subjectLean inventoryms_IN
dc.subjectTime series forecastingms_IN
dc.subjectTrendms_IN
dc.subjectSeasonalityms_IN
dc.titleINVENTORY MANAGEMENT USING DEMAND SALES FORECASTINGms_IN
dc.typeArticlems_IN
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