The Value of Inventory Accuracy in Supply Chain Management: Correlation Between Error Sources and Proactive Error Correction
American Journal of Operations Management and Information Systems
Volume 4, Issue 1, March 2019, Pages: 1-15
Received: Dec. 18, 2018;
Accepted: Feb. 13, 2019;
Published: Mar. 1, 2019
Views 849 Downloads 157
Assaf Avrahami, Faculty of Industrial Engineering, Israel Institute of Technology, Haifa, Israel
Evgeni Korchatov, Faculty of Industrial Engineering, Israel Institute of Technology, Haifa, Israel
One of the key elements in supplay cahin management is accurate information. Decision makers are aware of inaccuracies in inventory levels and, therefore, routinely conduct inventory reviews to correct the discrepancies between IT records and actual inventory. Several studies have investigated error sources and the cumulative effect of errors on holding costs, shortage costs, order-up-to levels and time between inventory counts. In most works, the errors were independent of the demand, which is neither realistic nor accurate. Here we use familiar inventory errors and information scenarios already proposed in several previous papers. We offer a model that considers the correlation between inventory errors and demand. The effect of the relationship between the random variables is tested in the context of several different scenarios. Each scenario contains a different level of information about the underlying demand and inventory errors. We then analyze the effect of changes of the covariance on the cost and time between inventory counts in each scenario. Using these results we formulate the value of information and its dependence on the covariance. We use analytical methods to draw conclusions regarding single parameter set cases and a numerical full factorial study for average multiparameter cases. In both settings, we show that the value of information decreases as the covariance increases. Moreover, the reduction is more significant when the information scenario makes less assumptions. The same behavior is observed in stock review frequency. As covariance increases, the optimal number of periods between inventory reviews drops sharply. Finally, we propose several simple methods for proactive error correction. We show that without prior knowledge, these methods perform better than the basic information scenario. Using these results we are able to formulate recommendations for businesses with different profiles of correlation between demand, and demand and errors, e.g., automated warehouses with weak correlation compared to grocery stores.
The Value of Inventory Accuracy in Supply Chain Management: Correlation Between Error Sources and Proactive Error Correction, American Journal of Operations Management and Information Systems.
Vol. 4, No. 1,
2019, pp. 1-15.
Atali, Aykut, Hau L Lee, and Özalp Özer. 2006. “If the inventory manager knew: Value of visibility and RFID under imperfect inventory information.” SSRN 1351606 http://ssrn.com/abstract=1351606.
Kök, A Gürhan, and Kevin H Shang. 2007. “Inspection and replenishment policies for systems with inventory record inaccuracy.” Manufacturing and Service Operations Management 9 (2): 185–205.
Avrahami, Assaf, Avinoam Tzimerman, Yale T. Herer, and Avraham Shtub. 2012. “The value of inventory accuracy in supply chain management.” Working Paper, Technion.
Lee, Hau, and Özalp Özer. 2007. “Unlocking the value of RFID.” Production and Operations Management 16 (1): 40–64.
Sarac, Aysegul, Nabil Absi, and Stéphane Dauzère-Pérès. 2010. “A literature review on the impact of RFID technologies on supply chain management.” International Journal of Production Economics 128 (1): 77–95.
Ha, Oh-Keun, Yong-Seok Song, Kyung-Yong Chung, Kang-Dae Lee, and Dongjoo Park. 2014. “Relation model describing the effects of introducing RFID in the supply chain: Evidence from the food and beverage industry in South Korea.” Personal and Ubiquitous Computing 18 (3): 553–561.
Huber, Nicholas, and Katina Michael. 2007. “Vendor perceptions of how RFID can minimize product shrinkage in the retail supply chain.” In RFID Eurasia, 2007 1st Annual, 1–6. IEEE.
[Fan et al. (2015)] Fan, Tijun, Feng Tao, Sheng Deng, and Shuxia Li. 2015. “Impact of RFID technology on supply chain decisions with inventory inaccuracies.” International Journal of Production Economics 159: 117–125.
Gavirneni, Srinagesh, Roman Kapuscinski, and Sridhar Tayur. 1999. “Value of information in capacitated supply chains.” Management Science 45 (1): 16–24.
Cachon, Gérard P, and Marshall Fisher. 2000. “Supply chain inventory management and the value of shared information.” Management Science 46 (8): 1032–1048.
Lee, Hau L, Kut C So, and Christopher S Tang. 2000. “The value of information sharing in a two-level supply chain.” Management Science 46 (5): 626–643.
Moinzadeh, Kamran. 2002. “A multi-echelon inventory system with information exchange.” Management Science 48 (3): 414–426.
Gaukler, Gary M. 2011. “Item-level RFID in a retail supply chain with stock-out-based substitution.” Industrial Informatics, IEEE Transactions on 7 (2): 362–370.
Ganesh, Muthusamy, Srinivasan Raghunathan, and Chandrasekharan Rajendran. 2014. “The value of information sharing in a multi-product, multi-level supply chain: Impact of product substitution, demand correlation, and partial information sharing.” Decision Support Systems 58: 79–94.
Sari, Kazim. 2015. “Investigating the value of reducing errors in inventory information from a supply chain perspective.” Kybernetes 44 (2): 176–185.
Gaukler, Gary M, Ralf W Seifert, and Warren H Hausman. 2007. “Item-level RFID in the retail supply chain.” Production and Operations Management 16 (1): 65–76.
Pelton, Lou E, Madhav Pappu, and Gary M Gaukler. 2010. “Preventing avoidable stockouts: The impact of item-level RFID in retail.” Journal of Business and Industrial Marketing 25 (8): 572–581.
Chuang, Howard Hao-Chun, and Rogelio Oliva. 2015. “Inventory record inaccuracy: Causes and labor effects.” Journal of Operations Management 39: 63–78.
Iglehart, Donald L, and Richard C Morey. 1972. “Inventory systems with imperfect asset information.” Management Science 18 (8): B–388.
DeHoratius, Nicole, Adam J Mersereau, and Linus Schrage. 2008. “Retail inventory management when records are inaccurate.” Manufacturing and Service Operations Management 10 (2): 257–277.
Kök, A Gürhan, and Kevin H Shang. 2014. “Evaluation of cycle-count policies for supply chains with inventory inaccuracy and implications on RFID investments.” European Journal of Operational Research 237 (1): 91–105.
Mersereau, Adam J. 2015. “Demand estimation from censored observations with inventory record inaccuracy.” Manufacturing and Service Operations Management 17 (3): 335–349.
Devore, J.L. 2011. Probability and Statistics for Engineering and the Sciences. Cengage Learning. https://books.google.ca/books?id=3qoP7dlO4BUC.
Lau, Hon-Shiang. 1997. “Simple formulas for the expected costs in the newsboy problem: An educational note.” European Journal of Operational Research 100 (3): 557–561.
Chhajed, Dilip, and Timothy J Lowe. 2008. Building intuition: Insights from basic operations management models and principles. Vol. 115. Springer Science and Business Media.