Identifying the root causes for inventory accumulation and prioritizing them using an MCDM-based TOPSIS approach

Abstract

PurposeInventory accumulation is a major problem for any organization, as it not only occupies the valuable storage space, but it also blocks the company's capital, leaving the owners with less cash to run the company's business. Aggregation of inventory in any organization contributes to inventory carrying cost; it affects labor productivity, increases equipment expenses and creates a loss of opportunity associated with it. Therefore, it is essential for any organization to come up with a solution to deal with the stockpile of inventory.Design/methodology/approachThis research aims to examine the potential causes of inventory aggregation in an organization. First, the potential factors for the build-up of inventory are identified from survey data collection, such as questionnaire approach and discussion with industry experts, and then weights are assigned to attributes to study the effects for these factors. After the identification of probable causes, they are analyzed through a multi-criterion decision-making (MCDM) approach and the technique for order of preference by similarity to ideal solution (TOPSIS) to prioritize the severity of these causes toward the accumulation of inventory and take corrective actions to prevent their disruptive effect on the business.FindingsThe top three causes identified from the TOPSIS analysis are sales and forecasting error, defects and quality related issues and communication gap between departments. Firstly, we focus on these major contributors and prioritize them using the TOPSIS analysis. Then, we proceed further toward other factors. The main reasons identified for the accumulation of inventory are (1) forecasting error, (2) bulk purchase, (3) data entry error, (4) communication gaps, (5) quality-related issues, (6) product category not traceable and (7) wrong material being procured.Research limitations/implicationsTo carry out the data analysis in this research paper, first survey data collection is done. Then, discussions with managers and executives in the particular domain are carried out, and weights are assigned to the attributes and the criteria to study the effects of the identified factors. After that root cause analysis (RCA) is performed to get to the genesis of the problem and to take necessary corrective action, for carrying out this study, a total of seven potential causes were identified and the contribution of these seven causes on five attributes or criteria, i.e. quantity (in tons), holding and carrying cost, effect on labor productivity, loss of opportunity cost and storage space were studied.Originality/valueThis research paper is the author’s original work, and all the analyses carried out are from the discussion with experts in the field and through the in-depth analysis carried out. This research aims to examine the potential causes of the accumulation of inventory in organizations and their contribution toward factors like inventory carrying cost, labor productivity, and opportunity loss and excessive storage space have been analyzed. This research provides great value to the readers in the respective domain.

A System-Based Classification and Prioritization Model to Prevent Dead Stock Occurrence in Retail Store Systems

“…To perform the classification of inventory, there must be a monitoring of key indicators that warn retailers about the presence of potential dead stocks in the inventory system. The indicators include product expiration [3][7], inventory movement [2], and inventory level [8]. The monitoring of product expiration and timely action on products that have short actual remaining shelf life allow retail businesses to prevent dead stocks in the warehouse that occur in the form of spoiled products [7].…”

Logistics Service Provider Evaluation and Selection: Hybrid SERVQUAL–FAHP–TOPSIS Model

“…MCDM models are developed to support decision making problems which involve multiple criteria. These models are frequently applied to solve problems in supply chain management such as supplier evaluation and selection [4][5][6][7], facility location selection [8][9][10], inventory management [11][12][13], etc. However, MDCM models are also utilized in other disciplines such as health science [14,15], banking and finance [16,17].…”