An inherent differentiation and system level assessment approach to inventory management. A safety stock method comparison

Date13 May 2019
DOIhttps://doi.org/10.1108/IJLM-12-2017-0329
Published date13 May 2019
Pages663-680
AuthorPatrik Jonsson,Stig-Arne Mattsson
Subject MatterManagement science & operations
An inherent differentiation and
system level assessment approach
to inventory management
A safety stock method comparison
Patrik Jonsson
Department of Technology Management and Economics,
Division of Supply and Operations Management,
Chalmers University of Technology, Gothenburg, Sweden, and
Stig-Arne Mattsson
School of Business and Economics, Linnaeus University, Växjö, Sweden
Abstract
Purpose The purpose of this paper is to explain the effects of inherent differentiation and system level
performance assessment in inventory management. This is done by comparing the performance of two
common safety stock methods, by considering the methodsinherent differentiation and item group-level
performance effects.
Design/methodology/approach Due to the lack of analytical relationships between the two methods, the
analysis is based on event-driven simulations. Data are collected from eight different case companies.
Findings explain the importance of assessing safety stock performance for groups of items and not for
individual items, as is common in academic studies. It explains how the methodsinherent differentiation and
planning environment characteristics affect the relative performances of the two safety stock methods.
Findings The study explains the importance of assessing performance of safety stock methods on a
system-level, rathe r than on item-level mea sures. It explains why the demand fill-rate metho d has a
negative impact on the pe rformance for groups of items, while the numb er-of-days method has a positive
impact. The study also exp lains how the group-level safety stock pe rformance is affected by five demand
data characteristics .
Research limitations/implications The study explains the importance of assessing performance of
safety stock methods on a system-level, rather than on item-level measures. It explains why the demand
fill-rate method has a negative impact on the performance for groups of items, while the number-of-days
method has a positive impact. The study also explains how the group-level safety stock performance is
affected by five demand data characteristics.
Practical implications Understanding the necessity of system level assessment of safety stock
performance, how methods inherently differentiate service levels, and how demand characteristics affect
methodsperformance can guide the choice of safety stock methods in companies.
Originality/value No research on the characteristics of the number-of-days safety stock method, any
assessment of differentiation characteristics of and comparison with the demand fill-rate method, has been
published. The variable inherent differentiationis also introduced and defined.
Keywords Europe, Decision-making, Simulation, Customer service, Supply chain processes, Logistics cost
Paper type Research paper
1. Introduction
Inventory control is characterized by having to estimate demand in advance of customer
orders since the lead time for replenishing stock typically is longer than the delivery lead
time required by customers. This means that stock replenishments have to be based on
estimates. Since such estimates are always more or less wrong, shortages will occasionally
occur. To be able to maintain a stable and competitive delivery performance, safety stocks
have to be used. Safety stocks means, however, capital tied up in inventory. An important
issue of inventory control is to establish an efficient relation between required service levels
to the customers and the capital tied up in safety stocks.
The International Journal of
Logistics Management
Vol. 30 No. 2, 2019
pp. 663-680
© Emerald PublishingLimited
0957-4093
DOI 10.1108/IJLM-12-2017-0329
Received 3 December 2017
Revised 15 May 2018
14 November 2018
9 January 2019
25 January 2019
13 February 2019
Accepted 13 February 2019
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0957-4093.htm
663
System level
assessment
approach
A commonly used method to calculate safety stocks in industry is number of days
times average demand per day, where number of days is an estimated parameter
representing a safety time margin when replenishing stock-on-hand. This method is
hereafter denoted as the number-of-days method. According to Silver et al. (1998, p. 244),
some 80 percent of US companies used this and similar simple rule of thumb methods to
calculate safety stocks. Similar observations were made in the UK (Wilkinson, 1996).
A survey in Sweden indicated that the method is still very common: some 48 percent of
medium- and large-sized companies used the number-of-days method to calculate their
safety stocks ( Jonsson and Mattsson, 2016). This safety stock method is, however, to a
very limited extent assessed in the academic literature.
A great number of other methods for calculating safety stocks can be found in the
literature. The most published and well known of these are based on targeted service
levels, cycle service or demand fill rate (Axsäter, 2006). They are also rather frequently
used in practice ( Jonsson and Mattsson, 2016). Contrary to the number-of-days method,
both service-level methods consider variation in demand and lead time. The method based
on cycle service has been criticized for not taking replenishment order quantities into
account and accordingly not considering the number of times shortage risks occur.
Due to this, Axsäter (2006, p. 33) argued that the cycle service method cannot be
recommended for inventory control in practice and Tyworth (1992) argued for the
necessity of a paradigm shift and a transition from using cycle service to demand fill rate.
The number-of-days method can accordingly be considered as the most widely used
method for calculating safety stocks in practice, and the demand fill-rate method is also
considered as the most scientifically favored method in the literature of those methods
also used in practice.
But what performance effect can really be expected from using the two types of safety
stock methods? No research on the use and the characteristics of the number-of-days
method is found in the literature. Neither has any assessment and comparison with the
demand fill-rate method been identified. When comparing the performance of safety stock
methods, we need to consider that due to methodsassumptions and incompleteness, the
service-level achieved from a method is always different from the service level it is
dimensioned to deliver: for some items, the service level becomes higher and for some,
lower. This method-internaldifferentiation of service levels is here called inherent
differentiation.We also need to consider that there are various ways of defining and
measuring received service level, and that in order to assess a safety stock methodstotal
effect on a companys tied-up capital at a given service level, it is necessary to assess the
effect on system level (for groups of items) and not for individual items. Finally, the effect
of externally differentiating the service level between items with different order
frequencies and costs should also be considered in order to fully assess a safety stock
methods total performance effect (e.g. Syntetos and Boylan, 2006).
Accordingly, the purpose of this paper is to explain the effects of inherent
differentiation and system level performance assessment in inventory management, by
comparing the performance of the number-of-days method with the demand fill-rate
method for groups of items. The study contributes specific knowledge about the
performance effects of the two most common safety stock methods in practice and
literature. It also contributes to inventory management theory, by defining and measuring
the inherent differentiationeffect and by explaining the limitations of item-level
inventory measurement and the necessity of system-level (item group-level) measurement
in inventory management. The generalizability of the findings is assessed by analyzing
their sensitivity regarding five demand data characteristics. Based on the literature
review, two research questions are formulated and analyzed. The analysis is based on
event-driven simulation using data from eight case companies.
664
IJLM
30,2

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