Predictive method of inventory optimization in industrial manufacturer performance

Strong collaboration in supply chain at B2B market may improve operational and financial performance of both suppliers and clients. Need for collaboration benefits realization is especially actual for supplying manufacturers with huge investments in inventory as well as high ordering and carrying co...

Full description

Bibliographic Details
Main Author: Makarova O.V.
Format: Article
Language:English
Published: EDP Sciences 2021-01-01
Series:E3S Web of Conferences
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2021/23/e3sconf_icepp21_01066.pdf
id doaj-b6012247dc91442897a675f78420636a
record_format Article
spelling doaj-b6012247dc91442897a675f78420636a2021-04-06T13:56:09ZengEDP SciencesE3S Web of Conferences2267-12422021-01-012470106610.1051/e3sconf/202124701066e3sconf_icepp21_01066Predictive method of inventory optimization in industrial manufacturer performanceMakarova O.V.0St.Petersburg University, Graduate School of ManagementStrong collaboration in supply chain at B2B market may improve operational and financial performance of both suppliers and clients. Need for collaboration benefits realization is especially actual for supplying manufacturers with huge investments in inventory as well as high ordering and carrying costs. Traditional stock level optimization models rely on historic data which makes them inefficient when supply if influenced by changing customized demand of key B2B clients. Strong collaboration with key clients, synchronization of planning process through the whole supply chain up to the end user and a forward-looking demand adjustment (ΔD, %) to the forecasting model are suggested to improve efficiency of planning. The model is validated at the B2B industrial manufacturer with positive effect. Application of the demand adjustment reorients the whole inventory planning practices towards a proactive approach that lead to a higher operational and financial efficiency.https://www.e3s-conferences.org/articles/e3sconf/pdf/2021/23/e3sconf_icepp21_01066.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Makarova O.V.
spellingShingle Makarova O.V.
Predictive method of inventory optimization in industrial manufacturer performance
E3S Web of Conferences
author_facet Makarova O.V.
author_sort Makarova O.V.
title Predictive method of inventory optimization in industrial manufacturer performance
title_short Predictive method of inventory optimization in industrial manufacturer performance
title_full Predictive method of inventory optimization in industrial manufacturer performance
title_fullStr Predictive method of inventory optimization in industrial manufacturer performance
title_full_unstemmed Predictive method of inventory optimization in industrial manufacturer performance
title_sort predictive method of inventory optimization in industrial manufacturer performance
publisher EDP Sciences
series E3S Web of Conferences
issn 2267-1242
publishDate 2021-01-01
description Strong collaboration in supply chain at B2B market may improve operational and financial performance of both suppliers and clients. Need for collaboration benefits realization is especially actual for supplying manufacturers with huge investments in inventory as well as high ordering and carrying costs. Traditional stock level optimization models rely on historic data which makes them inefficient when supply if influenced by changing customized demand of key B2B clients. Strong collaboration with key clients, synchronization of planning process through the whole supply chain up to the end user and a forward-looking demand adjustment (ΔD, %) to the forecasting model are suggested to improve efficiency of planning. The model is validated at the B2B industrial manufacturer with positive effect. Application of the demand adjustment reorients the whole inventory planning practices towards a proactive approach that lead to a higher operational and financial efficiency.
url https://www.e3s-conferences.org/articles/e3sconf/pdf/2021/23/e3sconf_icepp21_01066.pdf
work_keys_str_mv AT makarovaov predictivemethodofinventoryoptimizationinindustrialmanufacturerperformance
_version_ 1721537828722049024