network design

Strategic Supply Chain Design and the Product-Relationship Matrix

Daniel Dumke — Mon, 14 Feb 2011 14:06:00 +0000

Yet another case study. This time on strategic network design. Why? A major problem for businesses is to find the right strategy for a given situation. And “right” here means optimal (for a given KPI).
Research question might be: Are there general categories which can be used to make different decision situations comparable? And if yes, what would optimal strategies under these circumstances be?

Definitions

Seuring (2009) tries to answer the first research question using case studies. From literature he defines the strategic decision fields to be

Product design/engineering (products or parts),
Plant and equipment (plant),
Organisation and management (processes),
Labour and staffing (people) and
Production planning and control (planning).

For Seuring the SC decisions best can be categorized using a two dimensional matrix with the supply chain at the y-axis and the product dimension on the x-axis. As you can see in figure 1 he does not focus on the supply / demand side (like eg. Fisher 1997), but in both dimension aims at the process view.
The supply chain dimension with can be divided into configuration and operation, the product dimension into the product design, production and return phase.

Figure 1: The Product-Relationship-Matrix in Supply Chain Management (Seuring, 2009)

Advantages

Overall this framework shows a sequential view on the strategic decisions in a supply chain. But it also supports dynamic adaptations to differing origins, eg: A redesigned product within an existing supply chain would only make the steps II (Product design) and IV (Process optimization) necessary; changes to the network, like adding a new supplier, would concern square III (Formation of production network).

Cases

Using five different cases Seuring goes through the above mentioned strategic decision categories. The cross-case analysis reveals that the categories may sometimes be overlapping (production and return phase), but the decision can still be sorted into one or the other category.

Conclusion

As described in the introduction, the next step would be to use these categories to find general, optimal strategies which should be followed in each of the parts of the matrix in figure 1.
But while I was reading the paper I realized that this might not be possible, since the steps are to vague for that.

Hence, the framework offers an alternative approach, which not only takes a look at the content of the decision, but also adds a process perspec- tive. Such a more dynamic approach allows structuring the related decision based on the relationship and the product life-cycle dimension.

So my question, how can you use this framework beside finding optimal solutions for network design problems?
One suggestion might be, to use the process nature of the framework and analyze the organizational relationships while going through the different decision phases.

What do you think?

Reference:

Seuring, S. (2009). The product-relationship-matrix as framework for strategic supply chain design based on operations theory International Journal of Production Economics, 120 (1), 221-232 DOI: 10.1016/j.ijpe.2008.07.021

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Decision Support for Supply Chain, Product and Process Design

Daniel Dumke — Wed, 02 Feb 2011 13:46:00 +0000

Many companies are struggling with the idea to use modern optimization techniques to support decision making in strategic supply chain management.

But beside mathematical modeling of the supply chain there are other methods as well, such as network based approaches. In their 2005 paper Blackhurst, Wu and O’Grady present a more intuitive decision support method with the goal to improve decisions within the supply chain context.

Methodology

Figure 1: Example Product Chain Decision Model (Blackhurst et al. 2005)

Complex and dynamic systems like supply chains are hard to understand as a whole. The PCDM (Product Chain Decision Model) uses a network based approach. The network (example see figure 1) therefore consists of different nodes (place nodes: marked by circles and transition nodes: marked by bars). Transition nodes are used for processes, transferring input into output (eg. a transport, production, …), where place nodes are used for components within the supply chain (eg. production facility). The connections are marked by an arrow.

Case Study

Figure 2: Case Study for Chassis Assembly using PCDM (click to enlarge, Blackhurst et al. 2005)

As an example Blackhurst et al. use a case study, where they model the chassis assembly of Rockwell Collins, using actual data of their processes. The result of the status quo can be seen in figure 2. The network presentation is enhanced by the added information, like the lead time (LT) and the reorder point (ROP) at the nodes.

With the help of these networks the authors then optimize the network from the base case with local informations first to an information sharing network. This already helps reducing echelon inventory a lot. The second adjustment is to change raw materials to improve the product and the network even further.

Conclusion

The presented method for improving the supply chain network is intuitive, easy to understand and implement. Yet, it does not seem to be so new, nevertheless, it is a nice addition to the usual supply chain networks to add some key indicators directly at the nodes.
Even though this tool might seem overly simplistic, I really recommend using more tools like these. Many companies do not even analyze their network on a systematic basis, so this looks to be a good starting point for companies which have not used similar tools before.

Reference:

Blackhurst, J., Wu, T., & O’Grady, P. (2005). PCDM: A Decision Support Modeling Methodology for Supply Chain, Product and Process Design Decisions Journal of Operations Management, 23 (3-4), 325-343 DOI: 10.1016/j.jom.2004.05.009

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Supply Chain Design: Capacity, Flexibility and Wholesale Price Strategies

Daniel Dumke — Wed, 24 Nov 2010 16:49:00 +0000

This is the forth contribution to my series on doctoral dissertations on Supply Chain Risk Management. An immense effort and dedication is spent on these works only to find the results hidden in the libraries. So the goal is raise interest in the research of my peers.

Author / Topic

This dissertation was written by Brian Tomlin in 1999 as his doctoral thesis at the Massachusetts Institute of Technology, Cambridge, USA. It can be downloaded here at his homepage at his current employer (Tuck School of Business at Dartmouth). The title is:

Supply Chain Design: Capacity, Flexibility and Wholesale Price Strategies

Summary

Tomlin cumulates three distinct topics and analyzes them in depth in his dissertation. His core question is always the supply chain design, with demand uncertainty as the dominant risk.

Wholesale Pricing Strategies
Using a game theoretic model with two actors (supplier and manufacturer) he explores the best strategies for setting the wholesale price. The objective is to maximize the supply chain profit (think of it as a return on investment in the supply chain). He shows, that no matter if quantity-discount or quantity-premium pricing schedules are used, non-linear pricing schedules outperform linear pricing schedules.
Process Flexibility Strategies
He then tackles flexibility strategies in a multi-product, multi-stage supply chain environment. He first identifies two inefficiencies which only occur in a multi-stage environment, namely stage-spanning bottlenecks and floating bottlenecks. He develops a mathematical supply chain optimization model and based on the results he concludes, that “in supply chains with a large number of products or stages, additional flexibility is advisable, especially for stages in which the capacity is not much greater than the expected demand.”
Capacity Decision
With this chapter on capacity decision making in multi-product, multi-stage supply chains he walks on new grounds, since up to then only single-stage models have been analyzed. He uses two criterion for his analysis: service level and expected shortfall. The results of his analysis show that under optimal capacity allocation: for every stage must hold true: for a small increase in a stage’s capacity, the decrease in shortfall divided by the capacity cost should be the same for all stages.

Conclusion

I have to admit that I do not really like the segregated design of the thesis itself, analyzing one topic in depth usually should be sufficient for one dissertation. On the other hand the work by Tomlin on the three topics would probably also have sufficed for two or three separate dissertations as well.

Compared to other dissertations I read it was refreshing to see, that he did not spend (too) much time on making an in depth literature review beforehand but focussed very much on his own works.

Reference:

Brian T. Tomlin (2000). Supply Chain Design: Capacity, Flexibility and Wholesale Price Strategies Massachusetts Institute of Technology, Dissertation

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The Supply Chain Uncertainty Circle

Daniel Dumke — Wed, 27 Oct 2010 16:17:00 +0000

How to shrink the “Uncertainty Circle” is the topic of a paper I read today. It has been written by Rachel Mason-Jones and Denis R. Towill and can be downloaded here free of charge.

This article from 1998 focusses on how to shrink the uncertainty within a supply chain and therefore improve performance, since

we believe that those companies which cope best with

uncertainty, are most likely to produce internationally

competitive bottom-line performance.

This hypothesis is also backed by several other authors like, Craighead et al. (2009) or Hendricks and Singhal (2005).

Within the product delivery process for a single company, the authors find four causes of uncertainty: supply side, manufacturing processes, control systems and demand side (see figure 1).

Causes of Supply Chain Uncertainty (Mason-Jones and Towill 1998)

The Circle

With the Uncertainty Circle it is now possible to visualize to effect of shrinking one of the risks without the other: Overall risk is only reduced by a (comparatively) small amount. This furthermore implies the goal for supply chain risk managers: Reduction of risk on all frontiers!

Uncertainty Circle and Risk Reduction Process (Mason-Jones and Towill 1998)

This of course does not have to happen at the same time. Companies usually start with improvements in their own manufacturing processes and establish lean thinking to improve lead times and quality. As a next step this concept may be enlarged to the companies suppliers as well to reduce supply side risks.

The authors then argue that much potential is left untouched on the reduction of demand side uncertainties and control systems.

Demand side risks can be reduced by improving the information flow from the end-customer throughout the supply chain and companies can tackle control risks by improving their ability to act on this new information with a adequate Decision Support System.

Supply Chain Design Strategies

The authors then simulate a given supply chain and test strategies to improve (in figure 3) “Information pipeline time compression only”, “Material flow pipeline compression only”, “Total Cycle Time compression”.

Rating Risk Mitigation Strategies (click to enlarge; Mason-Jones and Towill 1998)

Conclusion

Even though the article has been published twelve years ago the concept of the Uncertainty Circle can still be used as a framework to reduce risks within a supply chain. The comparison table shows the effects of different risk mitigation strategies clearly and should adapted and used by more companies.

Reference:

Mason-Jones, Rachel, & Towill, Denis R. (1998). Shrinking the Supply Chain Uncertainty Circle IOM Control, 24 (7), 17-22

Craighead, C., Hult, G., & Ketchen Jr., D. (2009). The effects of innovation–cost strategy, knowledge, and action in the supply chain on firm performance Journal of Operations Management, 27 (5), 405-421 DOI: 10.1016/j.jom.2009.01.002

Hendricks, K., & Singhal, V. (2005). An empirical analysis of the effect of supply chain disruptions on long-run stock price performance and equity risk of the firm Production and Operations Managment, 14 (1), 35-52

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Supply Chain Design - Robust Planning with differentiated Supplier Selection

Daniel Dumke — Wed, 13 Oct 2010 13:28:00 +0000

This is the third contribution to my series on doctoral dissertations on Supply Chain Risk Management. An immense effort and dedication is spent on these works only to find the results hidden in the libraries. So the goal is raise interest in the research of my peers.

Author / Topic

This dissertation was written by Stephanie Freiwald in 2005 as her doctoral thesis at the University of Bochum. It was published by Peter Lang, Frankfurt a.M. and can be ordered here from amazon.deor your local library. The title can be translated as:

Supply Chain Design – Robust Planning with differentiated Supplier Selection

Summary

In her work Freiwald builds a mathematical model of a four echelon supply chain (supplier, producer, distributor / inventory, customer) starting with a literature review of existing models. Building up from there she first adds variables to include sophisticated criteria for the supplier selection extending the traditional price-only selection.

Robustness can be oriented towards the models optimality, reliability, result-robustness and goal robustness. So as the next step the author set the goal to include robustness to uncertainty and unsettled preferences of the decision maker to the model.

As a final step the author applies her model to an industrial case, with the goal to find optimal, robust solutions for an Supply Chain Design problem.

Conclusion

Stephanie Freiwald’s work stands apart in including multiple aspects of the supply chain design problem into one concise model for optimization without neglecting the implementation of such a “theoretical” model.

Reference:

Stephanie Freiwald (2005). Supply Chain Design – Robuste Planung mit differenzierter Auswahl der Zulieferer Peter Lang, Frankfurt a.M., Dissertation

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Strategic Supply Chain Management @CSCMP 2010

Daniel Dumke — Mon, 27 Sep 2010 15:04:00 +0000

Yesterday I finished the “Strategic Supply Chain Issues” Pre-Conference Workshop “Where Tactical Functionality Meets the Big Picture”. The following key points were intensively discussed:

Fundamental SC Strategies: Operational Excelence (eg. Walmart), Customer Intimacy (like Zara) and Product Leadership (example: Apple)

A broad view on customers has been propagated, customers equal stakeholders
Lean SCM, premise: Thinking of inventory as being without (direct) value for the customer, a strong focus on flexibility and inventory reduction therefore is necessary
Introduction to the method of value stream mapping for Supply Chain Analysis as a Basis for Supply Chain Design
Supply Chain Design: The network should be checked permanently for necessity of change
As the subtitle of the workshop suggests the right communication of the strategy is of the utmost importance. The optimal balance between short term actions and long term strategy have to be sought (without being disaligned)
Importance and categorization of Collaborations (Vendor-Buyer, Focussed, Partnership, Alliance)
Planning (S&OP)
SCM Metrics
SCM Future

But of course there are many, many more things. A really new thing I learned about the definition of core competency:
It’s the “capability to kick their ass”.

Disclaimer: The experiences described here do not necessarily reflect the my views and I haven’t found a singled peer reviewed reference. But that’s business, isn’t it?

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Simulation of Supply Chain Disruptions

Daniel Dumke — Wed, 22 Sep 2010 13:06:00 +0000

Still too many cooperations do not analyze their supply networks using consistent and scientifically proven methods. Some already do. One case of a company (ABC) is described below.

Goals and Methods

ABC company wanted to know more about their exposure to supply chain disruptions originating from their own plants but also the connected transportation links, suppliers and customers. Specifically, the goals were:

Assess the current level of supply chain disruption risk in the system
Test different mitigation strategies
Provide a tool that can be used in the case of a disruption to validate recovery steps before putting them into action
Identify redundancy in the system that can be removed without affecting the risk level

The authors therefore designed a supply chain model for two major products (one high, one low volume product) using discrete event simulation in Arena, one of the most often used simulation environments. To obtain distributions for the resulting performance measures the authors take advantage of Monte Carlo simulation using an excel tool called @Risk.

Simulation

The demand and risk patterns were evaluated using available data and expert interviews. In the second step mathematical distribution functions were adjusted to fit the empirical observations / forecast to input those into the model.

The company was very concerned with the effects of the disruptions on their customer service, so the Fill Rate was chosen as the relevant performance measure.

Results

The model was analyzed in two ways: First in an steady state analysis the current risk levels in the model were analyzed. In a second step the model was adjusted, by implementing one of the following strategies: implementation of inventory control and improvement of sourcing.

Even though only one simple measure was used, the ABC company was able to gain valuable insights into their supply chain.

Status Quo: All runs of the risk model experienced at least one week where 0% of the incoming orders were satisfied for the available inventory levels (two to six weeks)
Mitigation Strategies: The output clearly showed that reducing response times or increasing capacity of back-up methods were able to reduce the impact of a disruption and speed recovery.
ABC realized that they lack a database with historic distribution information for disruptions
There were no formal strategic-level mitigation procedures
Risk exposure is very dependent on the current state of the models parameters (eg. if a disruption occurs in a low inventory state, recovery lasts much longer)

The most important result is that the process of implementing such a simulation model can help the company think about supply chain disruptions more intensively and such a project can be used as a starting point for systematically documenting the risks and contingency plans in case of a disruption.

Reference:

Schmitt, Amanda J., & Singh Mahender (2009). Quantifying Supply Chain Disruption Risk Using Monte Carlo and Discrete-Event Simulation Proceedings of the 2009 Winter Simulation Conference, 1237-1248

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Risk considerations in Purchasing

Daniel Dumke — Mon, 30 Aug 2010 06:37:00 +0000

Today I start an irregular series on doctoral dissertations on Supply Chain Risk Management. An immense effort and dedication is spent on these works only to find the results hidden in libraries. So the goal is raise interest in their research.

Author / Topic

The first dissertation was written by Ingo Schneider in 2009 as his doctoral thesis at the Helmut Schmidt University in Hamburg, Germany. It was published by Shaker, Aachen and can be ordered here from amazon.deor your local library. The title translates in:

Risk as Strategic Part of the Supply Chain Design: Analysis and Case Study in the German Automobile Industry

Summary

The goal of this dissertation is to create a framework for finding strategies to optimally design the supply side of a supply chain. The author starts with basic thoughts about the risk management in supply chain design and uses a case study to test his results within the German automobile industry.

His research finishes with an eight step framework that should lead to optimal supply chain design.

Develop strategies to consistently assess risks within the supply chain
Work out the possible structural decisions for the SC
Determine packages of measures that should be used
Assemble the necessary price and cost information
Develop a concept for the risk management and analyze the supply chain
Calculate the cost of the risks
Present the optimal connections to the supply and demand side from a monetary point of view
Discuss the risks to reach a final decision

Conclusion

Ingo Schneider’s work shows a clear path to optimal design of the supply side of the chain. He writes very detailed about the basics of supply chain risk management and takes special care to highlight the methodological aspects of his study.

Reference:

Schneider, Ingo (2009). Die Risikobetrachtung in der Beschaffung als strategische Komponente im Supply-Chain-Design : eine Analyse am Beispiel Karosserieblechteile in der Automobilindustrie Shaker, Aachen, Dissertation

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Identifying important Activities within the SCOR Processes

Daniel Dumke — Mon, 16 Aug 2010 10:07:00 +0000

The Supply Chain Operations Reference (SCOR) model has been developed by the Supply Chain Council to provide a best-practice framework for supply chain management practices and processes with the goal to increase performance.

SCOR

The SCOR model consists of five major process categories: Plan, Source, Make, Deliver and Return

Starting from that best practice processes are defined up to level three.

Supply Chain Operations Reference Model (SCOR, SCC 2000)

Research Question

In 2004 Lockamy and McCormack published an exploratory study on the question

What are the most important supply chain management planning practices in the Plan, Source, Make, Deliver decision area that relate to supply chain performance?

Results

From literature and the questionnaires nine general practices are derived, that might influence performance.

Planning processes
Collaboration
Teaming
Process measures
Process credibility
Process integration
IT support
Process documentation
Process ownership

Using factor analysis the authors find that “Planning processes” and “Collaboration” is especially important for supply chain performance within all SCOR process categories. The aggregated results are shown in the following table.

Results Lockamy and McCormack (2004)

Reference:

Lockamy, A. III, & McCormack, K. (2004). Linking SCOR planning practices to supply chain performance: An exploratory study International Journal of Operations & Production Management, 24 (12), 1192-1218 DOI: 10.1108/01443570410569010

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Internal

Designing the Green Supply Chain

Daniel Dumke — Mon, 09 Aug 2010 11:20:00 +0000

Nowadays green logistics is an often heard buzz-word, but already eleven years ago Beamon published an article about the challenges with creating Green Supply Chains.

Traditional vs. Extended Supply Chain

A traditional supply chain has been mostly a one-way street. The issues analyzed were eg. the number of echelons, buyer-supplier relationships and inventory levels.

As a basis the extended supply chain has to consider at least the recycling / re-use and remanufacturing processes to be complete. More important though the strategy of the company has to be adjusted to include environmental aspects as waste, resource / energy use and pollution as well.

Emerging Risks & Performance measures

These new aspects also come with certain problems.

The uncertainty associated with the replacement/recovery process (in time requirements, quality, and quantity of returned products, packaging, and/or containers)
The reverse distribution process itself (collection and transportation of used products, packaging, and/or con- tainers)

In addition new performance measures beside the traditional customer satisfaction and cost have to be established to assess and manage the environmental aspects. Measures have to be created which can be used to estimate the total impact of the product life cycle.

Evolving to a Green Supply Chain

Beamon suggests the following steps to evolve into a green supply chain:

Identify processes
Develop a performance measurement system
Measure the supply chain system
Prioritize
Develop alternatives and select approach
Establish auditing and improvement procedures

Conclusion

I was thinking a lot about the risk measures suggested in this article. The concept of Beamon concludes with steps on how to evolve to a green supply chain (not as the title suggest “design” it). For this “re-design” task, where each single process has to be analyzed, a detailed measuring system might be adequate. But how should you design a new green supply chain from scratch?

Reference:

Beamon, B. (1999). Designing the green supply chain Logistics Information Management, 12 (4), 332-342 DOI: 10.1108/09576059910284159

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Learning from the Military how to handle Disruptions

Daniel Dumke — Mon, 02 Aug 2010 08:45:00 +0000

Disruptions are a fact of life not only since the Supply Chain literature gained awareness of it. So some institutions in fact specialized on handling disruptions as their core competency.
The article “Responding to Disruptions in the Supply Network – from Dormant to Action” tries to transfer the knowledge and best practices present at the military and humanitarian organizations to Supply Chain Management.

Methodology

The authors (Kovács and Tatham) are using case research and a resource based view to find common patterns in military and humanitarian practices to efficiently and effectively act on disruptions.

Military vs. Humanitarian Organizations

The authors find three decision categories common to the two institutions: Physical Capital, Human Capital, Organizational Capital.

Capital	Military	Humanitarian Organizations
Physical Capital	Relative abundance of materials and equipment due to focus on preparation “just in case” Internal resources: importance of individual ownership Location in country of origin or at allies’ site	Lack of own materials External resources: focus on supplier relations (vendor managed inventory, capacity reservation systems), postponement of ownership Pooling of resources Location close to disaster-prone areas
Human Capital	Emphasis on own training of personnel Focus on the knowledge of the doctrine	Mapping potentially available personnel from other organisations In-sourcing personnel from external resources Focus on local knowledge
Organizational Capital	Command and control structure Focus on hierarchy Codified internal processes (doctrine) Limited interoperability	Case-based structure (disruption / programme based) Establishment of common standards Co-ordination with other actors

Results

The article identifies two states for the observed institutions: During times without disruptions they are dormant and only when a disruption occurs they come to action. Though preparation for the “action” phase is very important.
The Military and Humanitarian Organizations exhibit distinct approaches to it.

The Military uses a strong asset focus (acquisition of equipment, training personnel, abundance of internal resources) at the same time they keep a high inventory level and have a rigid command-and-control structure within their organization.

Humanitarian Organizations often specialize in a specific type of disaster, region or type of material. The “Human Capital” is seldomly trained extensively and most often only held in a loose connection to the organization. From the organizational point of view they focus on a strong local presence and, due to the limited resources, focus on postponement (decide on purchasing orders as late as possible), therefore Physical Capital is often local and low.

Conclusion

Supply Chain managers and researchers can learn from both cases alike. The major difference is the resource position from which one acts. Therefore the first step for a company must be to assess the resources available to act on disruptions as soon as they occur.

Reference:

Gyöngyi Kovács, & Peter Tatham (2009). Responding to Disruptions in the Supply Network from dormant to action Journal of Business Logistics, 30 (2), 215-229

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Disruption-Management Strategies for Short Life-Cycle Products

Daniel Dumke — Sat, 10 Jul 2010 07:05:00 +0000

In his 2009 paper Brian Tomlin analyzes strategies to mitigate disruption risks in a three echelon supply chain.

Setting

Focus in his research is a single company, with its suppliers and customers. The objective is to maximize expected utility, while demand and supply are uncertain. There are two products available which can be used as substitutes. The time horizon for the decision maker is one season where the products can be sold.

Three different sourcing structures are considered.

Different sourcing structures (Source: Tomlin 2009)

Variables / Attributes of the SC

The following attributes in the supply chain are used as free variables and can therefore be modified:

Suppliers
- Supplier reliability
- Correlation between supplier failures
- Proportion of order cost charged in the event of a failure
- Relative cost of emergency supplier
Products
- Contribution margin
- Demand uncertainty
- Demand correlation
- Substitutability
Firm
- Risk aversion of the decision maker

Strategies

The effects of three major adaption strategies on the risk exposure / expected profit are tested:

Supplier diversification
adding another supplier to lower the overall risk for failure
Contingent sourcing
adding a supplier which is only used in case the main supplier fails to deliver
Demand switching
shifting customer demand to a different product

There is also the possibility not to engage in any activity and accept the risks.

Results

It is shown that contingent sourcing is the preferred strategy to supplier diversification for the firm, if the failure probability of the supplier increases. Furthermore, demand switching is an effective strategy for controlling demand risk and therefore is the preferred strategy with low supply risk.

Higher levels of risk aversion lead to a preference for contingent sourcing over the other strategies.

Conclusion

Tomlin shows viable and effective strategies to increase profit (utility) in supply chain settings with disruption risk. He therefore calculates the expected profits in different situations and uses the results to give suggestion for situational optimal strategies to mitigate these risks.

Reference:

Tomlin, B. (2009). Disruption-management strategies for short life-cycle products Naval Research Logistics, 56 (4), 318-347 DOI: 10.1002/nav.20344

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Design of Agile Supply Chains

Daniel Dumke — Tue, 29 Jun 2010 13:28:00 +0000

I already reviewed two other articles about agile supply chains. One on the role of distribution centers in supply chains and one on the migration from lean to agile supply chains.

But the question comes to mind if lean and agile supply chains have to be mutually exclusive or if it is possible to combine them. Christopher and Towill (2001) had a look at this question regarding the supply chain design.

Factors for Leanness / Agility

Several factors influence the design decision if a supply chain should be more agile or lean. Nowadays more often than not supply chains compete, not companies. This implies that not only companies must act market orient, but also supply chains.
Market orientation can be analyzed using the market winner / market qualifier concept. This also means that there are different foci of the lean and agile supply chain.

Correlation of Agile / Lean Supply Chains to Market Winners / Market Qualifiers

Strategies

Christopher and Towill mention three ways to combine the lean and agile paradigm in one supply chain:

80/20 approach
Usually in a supply chain with multiple products only a few of them make most of the overall volume (20% make 80% of the volume). Result: for the high volume products choose a lean approach, while for the low volume products an agile strategy might be better suited.
Decoupling point approach
Strategic inventory can act as a decoupling point within a supply chain. If you select this point wisely, it can be beneficial to use a lean strategy up to this point and an agile strategy after this point.
Base and surge demand
the strategies can also be combined if the demand pattern shows a base demand. This demand could be produced using a lean strategy, while the surge implements a more agile approach.
Base and Surge demand
Source: Christopher and Towill (2001)

Conclusion

It is important to see, that not only leanness and agility can be combined, but also the strategies mentioned above can be used complementarily.

Reference:

Christopher, M., & Towill, D. (2001). An integrated model for the design of agile supply chains International Journal of Physical Distribution & Logistics Management, 31 (4), 235-246 DOI: 10.1108/09600030110394914

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Supply Chain Performance and its Topological Features

Daniel Dumke — Thu, 24 Jun 2010 08:04:00 +0000

Perhaps this research by Pero et al. can support small and medium sized companies with the design and redesign of its supply chain network.
The goal of the study was to analyze the connection between topological features of the supply chain and the resulting supply chain performance.

Method and Model

The authors used simulation techniques and statistical analysis to simulate a pull based supply network. The network consists of a retailer-, distributor- and manufacturer-level.
Demand and lead times were random, the supply chain performance was measured with stock outs that occured.

Results

The results show that:

An increasing number of nodes at each level increases the probability of stock outs.
The performance of the supply chain was not affected by the number of levels in the supply chain and the distance between the nodes.
Furthermore the number of sources for each node seems to increase the risk for stock outs.

Conclusion

Due to their simple structure the results are very compelling. To get the perfect supply chain performance all you have to do is following the above mentioned “rules” (results).

But you have to keep in mind the premises on which the model builds:
For example, supply chain performance is only measured in terms of “stock outs”. Stock out should never be the single performance measure you rely on, since there may not be a direct correlation with more important company goals like profit, …

Besides, it would be advised to model your own individual supply chain to accommodate for your specific configuration and needs. Especially strategic decisions like the supply chain configuration should be important enough to not take the shortcut.

Reference:

Pero, M., Rossi, T., Noé, C., & Sianesi, A. (2010). An exploratory study of the relation between supply chain topological features and supply chain performance International Journal of Production Economics, 123 (2), 266-278 DOI: 10.1016/j.ijpe.2009.08.030

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Corporate Strategy and Supply Chain Network Design

Daniel Dumke — Wed, 26 May 2010 13:22:00 +0000

Obviously Corporate Strategy should have an effect on the supply chain network design and its parameters. In their exploratory study Demeter, Gelei and Jenei (2006) show two examples of how supply chains are affected by different corporate strategies.

Setting

The authors analyzed the supply chains of two major car manufacturers with assemblies in Hungary. The focal companies were Audi and Suzuki. They conducted several interviews with the focal companies themselves and their best rated suppliers.

Results

From the interviews the following supply chain was extracted:

Audi / Suzuki Supply Chain (Demeter et al. (2006))

Strategies

Audi and Suzuki follow different strategies when deciding for Hungary as a production location. The major differences were: Audi came for the resource basis (skilled and cheap labor), Suzuki came for the european market and lower cost.
Audi decided to invests heavily in capacity (which was enlarged later) to produce for the world market, Suzuki only produces for the regional market (with step-by-step enlargements).

Effects

The authors find that the strategy affects supply chain configuration as well as supply chain practices.
Due to its high capacity strategy, it was possible for Audi to bring some of its suppliers to Hungary, resulting in the same sourcing pattern as elsewhere. Suzuki was not able to achieve this, instead had to insource, due to missing Integrators.
Supply chain practices can be divided into buyer-supplier relationships and the use of different management tools:
Due to the missing Integrators in the Suzuki supply chain, it was possible for them to have a much tighter control over their suppliers.
The strategies affected also the tools chosen (eg. directprice negotiations or the establishment of industrial parks by Suzuki)

Conclusion

As long as the corporate strategy is implemented effectively it must affect the supply chain as well, especially critical parameters as configuration and practices. For managers, this has to be kept in mind to forecast effects of strategic change.

Reference:

Demeter, K., Gelei, A., & Jenei, I. (2006). The effect of strategy on supply chain configuration and management practices on the basis of two supply chains in the Hungarian automotive industry International Journal of Production Economics, 104 (2), 555-570 DOI: 10.1016/j.ijpe.2006.05.002

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network design

strategy

corporate strategy