Tapio Niemi, Ari-Pekka Hameri, Petro Kolesnyk and Patrik Appelqvist
Delivery punctuality is essential in supply chain management, yet the cost of untimely delivery is usually assumed to be given or based on intuition and not quantified by facts.
Abstract
Purpose
Delivery punctuality is essential in supply chain management, yet the cost of untimely delivery is usually assumed to be given or based on intuition and not quantified by facts.
Design/methodology/approach
The authors used a data set containing detailed transaction data for a nine-year period on orders and deliveries of sport goods. The methodology is based on applying a polynomial distributed lag model to longitudinal data on supply chain transactions.
Findings
The results indicate that small delivery delays up to two weeks decrease the sales by maximum 10% during a period of 3–4 weeks. Longer delays, up to 45 days, have a larger negative effect on sales, which can also last longer. For this case company, the estimated lost sales due to late deliveries (=5 days) were 5.1% of the delivery value. The longer delays got, the large the cost was: delays at least 45 days long were the most costly causing almost 40% of the estimated lost sales.
Practical implications
This study offers a methodology for quantifying lost sales due to delivery delays and estimating how long the poor delivery performance affects retailers' order behaviour.
Originality/value
The results give a quantitative decision-making tool for supply chain managers to estimate the profitability of investments in the supply chain performance, especially on improving punctuality.
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Patrik Appelqvist and Ebbe Gubi
Postponement is known as a way to reduce risk and inventories while still providing high product variety and acceptable response times. The paper is a case study that uses…
Abstract
Purpose
Postponement is known as a way to reduce risk and inventories while still providing high product variety and acceptable response times. The paper is a case study that uses simulation for quantifying these benefits for a consumer electronics company.
Design/methodology/approach
Improvement potential is first evaluated qualitatively through interviews with dealers of the case company. Next, the benefit of postponement is evaluated quantitatively using discrete‐event simulation with data from operational ERP systems. The conclusions identify conditions under which postponement is beneficial in retail.
Findings
In the case company, shop inventory is necessary for high‐volume and low‐variety products. Postponing variety creation to shops has the potential to decrease inventories for these products by 40‐80 per cent. The benefits of postponement depend on delivery speed requirement, product value, product variety and shop size.
Research limitations/implications
Many contributions on postponement have been conceptual. This study contains a quantitative test. The study considers both the spatial dimension (where) and the temporal dimension (when) of postponement.
Practical implications
The research was sufficiently successful that the company implemented the delivery concept arising from the results. Corresponding benefits seem possible for other manufacturers and retailers of consumer goods.
Originality/value
The contribution is real‐life quantitative evidence of how modular product architecture can be utilised to improve operational supply chain performance.
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Patrik Appelqvist, Flora Babongo, Valérie Chavez-Demoulin, Ari-Pekka Hameri and Tapio Niemi
The purpose of this paper is to study how variations in weather affect demand and supply chain performance in sport goods. The study includes several brands differing in supply…
Abstract
Purpose
The purpose of this paper is to study how variations in weather affect demand and supply chain performance in sport goods. The study includes several brands differing in supply chain structure, product variety and seasonality.
Design/methodology/approach
Longitudinal data on supply chain transactions and customer weather conditions are analysed. The underlying hypothesis is that changes in weather affect demand, which in turn impacts supply chain performance.
Findings
In general, an increase in temperature in winter and spring decreases order volumes in resorts, while for larger customers in urban locations order volumes increase. Further, an increase in volumes of non-seasonal products reduces delays in deliveries, but for seasonal products the effect is opposite. In all, weather affects demand, lower volumes do not generally improve supply chain performance, but larger volumes can make it worse. The analysis shows that the dependence structure between demand and delay is time varying and is affected by weather conditions.
Research limitations/implications
The study concerns one country and leisure goods, which can limit its generalizability.
Practical/implications
Well-managed supply chains should prepare for demand fluctuations caused by weather changes. Weekly weather forecasts could be used when planning operations for product families to improve supply chain performance.
Originality/value
The study focuses on supply chain vulnerability in normal weather conditions while most of the existing research studies major events or catastrophes. The results open new opportunities for supply chain managers to reduce weather dependence and improve profitability.
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Patrik Appelqvist, Valérie Chavez‐Demoulin, Ari‐Pekka Hameri, Jussi Heikkilä and Vincent Wauters
The purpose of this paper is to document the outcome of a global three‐year long supply chain improvement initiative at a multi‐national producer of branded sporting goods that is…
Abstract
Purpose
The purpose of this paper is to document the outcome of a global three‐year long supply chain improvement initiative at a multi‐national producer of branded sporting goods that is transforming from a holding structure to an integrated company. The case company is comprised of seven internationally well‐known sport brands, which form a diverse set of independent sub‐cases, on which the same supply chain metrics and change project approach was applied to improve supply chain performance.
Design/methodology/approach
By using in‐depth case study and statistical analysis the paper analyzes across the brands how supply chain complexity (SKU count), supply chain type (make or buy) and seasonality affect completeness and punctuality of deliveries, and inventory as the change project progresses.
Findings
Results show that reduction in supply chain complexity improves delivery performance, but has no impact on inventory. Supply chain type has no impact on service level, but brands with in‐house production are better in improving inventory than those with outsourced production. Non‐seasonal business units improve service faster than seasonal ones, yet there is no impact on inventory.
Research limitations/implications
The longitudinal data used for the analysis is biased with the general business trend, yet the rich data from different cases and three‐years of data collection enables generalizations to a certain level.
Practical implications
The in‐depth case study serves as an example for other companies on how to initiate a supply chain improvement project across business units with tangible results.
Originality/value
The seven sub‐cases with their different characteristics on which the same improvement initiative was applied sets a unique ground for longitudinal analysis to study supply chain complexity, type and seasonality.
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Patrik Appelqvist and Juha‐Matti Lehtonen
Scheduling problems in steel plants tend to be difficult and require complex algorithms due to many constraints. An approach is presented where only the main constraints are…
Abstract
Purpose
Scheduling problems in steel plants tend to be difficult and require complex algorithms due to many constraints. An approach is presented where only the main constraints are included in the scheduling algorithm. The schedule is validated using a discrete‐event simulation model that includes additional detail.
Design/methodology/approach
The combined approach is utilised for production scheduling in a steel mill in Finland. Operational performance of the steel mill is measured before and after software installation. The paper presents the scheduling environment, the software application and the resulting increase of production.
Findings
Case experiences indicate that combining optimisation techniques with simulation is beneficial. The optimisation can be kept simpler as validation with a simulation model increases the credibility and accuracy of the resulting schedule. During software development and testing, the simulation model offered a testing environment for the optimisation algorithm.
Practical implications
The case implementation was a success that increased production without making trade‐offs with other production goals. Company management estimate the productivity increase directly caused by the project to be worth €2,500,000 annually.
Originality/value
The paper presents a successful application of simulation for schedule validation in a complex and demanding environment.
Details
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Johanna Småros, Juha‐Matti Lehtonen, Patrik Appelqvist and Jan Holmström
Information sharing practices such as vendor‐managed inventory (VMI) give manufacturers access to more accurate demand information, e.g. customer sales data, than before. The…
Abstract
Information sharing practices such as vendor‐managed inventory (VMI) give manufacturers access to more accurate demand information, e.g. customer sales data, than before. The value of this type of information sharing has been established in many studies. However, most of the research has focused on the ideal situation of the manufacturer having access to information from all downstream parties. In practice, this is rarely the case. In this paper, discrete‐event simulation is used to examine how a manufacturer can combine traditional order data available from non‐VMI customers with sales data available from VMI customers in its production and inventory control and what impact this has on the manufacturer's operational efficiency. The simulation model is based on a real‐life VMI implementation and uses actual demand and product data. The key finding is that even for products with stable demand a partial improvement of demand visibility can improve production and inventory control efficiency, but that the value of visibility greatly depends on the target products’ replenishment frequencies and the production planning cycle employed by the manufacturer.
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Patrik Appelqvist, Juha‐Matti Lehtonen and Jukka Kokkonen
This paper presents a framework for supply chain decision‐making. The framework is used to gain insights into applications of modelling. Current modelling practice is reviewed…
Abstract
This paper presents a framework for supply chain decision‐making. The framework is used to gain insights into applications of modelling. Current modelling practice is reviewed through a literature survey. The principal finding is a lack of published research in the area of modelling supply chain effects in the product development phase. However, it is in the product development phase where the majority of product life‐cycle costs are determined. As a guideline for further case research, we propose an approach for integration in product life cycle modelling systems. For practitioners, we point out some major requirements for implementation. Finally, we demonstrate an early application of some of the ideas.
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Patrik Jonsson and Stig-Arne Mattsson
The development of information technology has made it possible for companies to get access to information about their customers ' future demand. This paper outlines…
Abstract
Purpose
The development of information technology has made it possible for companies to get access to information about their customers ' future demand. This paper outlines various approaches to utilize this kind of visibility when managing inventories of end products on an operative level. The purpose is to explain the consequences, for capital tied up in inventory, of sharing four different types of planning information (point-of-sales data, customer forecasts, stock-on-hand data, planned orders) when using re-order point (R,Q) inventory control methods in a distribution network.
Design/methodology/approach
A simulation study based on randomly generated demand data with a compound Poisson type of distribution is conducted.
Findings
The results show that the value of information sharing in operative inventory control varies widely depending on the type of information shared, and depending on whether the demand is stationary or not. Significantly higher value is achieved if the most appropriate types of information sharing are used, while other types of information sharing rather contribute to decreased value. Sharing stock-on-hand information is valuable with stationary demand. Customer forecast and planned order information are valuable with non-stationary demand. The value of information sharing increases when having fewer customers, and when the order quantities are large. Sharing point-of-sales data is not valuable, regardless of the demand type.
Research limitations/implications
The use of simulation methodology is a limitation, because the study has to be limited to a specific model design, and because it is not based on primary empirical data. The study is especially limited to dyadic relationships in supply chains, and to distribution networks with a rather limited number of customers.
Practical implications
Guidance is given about what type of information should be appropriate to share when different types of demand patterns and distribution networks, and how order batch sizes and lead times affect the value of information sharing when using re-order point (R,Q) methods.
Originality/value
Very limited research providing specific assessments of potential inventory control consequences when sharing planning information in various contexts has been found in the literature. The findings and conclusions also question some previous research on information sharing.
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Patrik Jonsson and Jan Holmström
– The purpose of this paper is to develop a research agenda for supply chain planning (SCP) relevant for practice.
Abstract
Purpose
The purpose of this paper is to develop a research agenda for supply chain planning (SCP) relevant for practice.
Design/methodology/approach
The authors critically evaluate academic literature on SCP in order to understand how problems are addressed in their particular context, what the outcomes are, and the mechanisms producing the observed outcomes. Four categories of SCP are studied: sales and operations planning (S & OP), supply chain master planning, supply chain materials management, and collaborative materials management. The authors introduce the concept of enabling mechanisms to identify specific innovations in materials management and production management that can facilitate the future improvement of SCP.
Findings
The critical evaluation of current SCP theory presents very limited results that are of practical relevance. SCP is not presented as an intervention and the results are not in a form that is actionable for practitioners. The body of literature is almost absent in addressing problems according to context, it presents limited evidence of intended outcomes, and it fails to identify unintended outcomes. As a consequence, research is unable to bolster theoretical understandings of how outcomes – both intended and unintended – are achieved. In the forward-looking research agenda the authors leverage the understanding of the enabling mechanisms in order to propose research to make mature S & OP and novel types of SCP implementable.
Research limitations/implications
The paper is an example of a structured approach to developing a research agenda that is relevant to practice and can be used more widely in logistics and supply chain management.
Practical implications
This paper presents a research agenda to close the gap between practice and promise in SCP.
Originality/value
The authors operationalize what constitutes practical relevance for an established field of research.