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Data Analytics in Warehouse Management Systems (WMS) Implementations – A Case Study

Natesan Andiyappillai in Information Systems

International Journal of Applied Information Systems
Year of Publication:2020
Publisher: Foundation of Computer Science (FCS), NY, USA
Series: Volume 12 Number 35
Authors:Natesan Andiyappillai
10.5120/ijais2020451894
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  1. Natesan Andiyappillai. Data Analytics in Warehouse Management Systems (WMS) Implementations – A Case Study. International Journal of Applied Information Systems 12(35):19-23, December 2020. URL, DOI BibTeX

    @article{10.5120/ijais2020451894,
	author = "Natesan Andiyappillai",
	title = "Data Analytics in Warehouse Management Systems (WMS) Implementations – A Case Study",
	journal = "International Journal of Applied Information Systems",
	issue_date = "December 2020",
	volume = 12,
	number = 35,
	month = "December",
	year = 2020,
	issn = "2249-0868",
	pages = "19-23",
	url = "http://www.ijais.org/archives/volume12/number35/1106-2020451894",
	doi = "10.5120/ijais2020451894",
	publisher = "Foundation of Computer Science (FCS), NY, USA",
	address = "New York, USA"
}

Abstract

Supply Chain management helps businesses to gain competitive advantage in the market and Logistics plays a vital role in the supply chain when it comes to managing and maintaining the inventory accurately and efficiently. The IT Logistics systems help the businesses to run the processes efficiently in the IT applications. Warehouse Management Systems (WMS) is one of the key elements in IT Logistics systems that help keeping the logistics flow seamless while fulfilling the customer orders as expected. Logistics businesses use the WMS application not just to run the warehouse processes in the IT systems but also to optimize the processes by diligently analyzing the various data available in WMS. This article describes and details the various data captured by a WMS and how the Data analytics plays a key role in optimizing the logistics channel by the business by conducting a case study in a leading logistics and supply chain company.

Reference

  1. Five analytics features to make the most of your WMS data, https://www.explorewms.com/wms-data-analytics.html, Geoff Whiting, 15th December 2016.
  2. The Path Forward for ERP WMS, https://www.logisticsmgmt.com/article/the_path_forward_for_erp_wms1, Gary Forger, June 7, 2018.
  3. The Importance of Real-Time WMS Reporting & Analytics, https://www.irms360.com/news/importance_real_time_wms_reporting_analytics.
  4. Should You Adopt Predictive Analytics in Warehouse Management? https://articles.cyzerg.com/should-you-adopt-predictive-analytics-in-warehouse-management, Hector, 28th Mar 2018.

Keywords

Logistics and Supply Chain, Warehouse Management Systems, WMS and Data Analytics