Basics

Models for Production Planning under Uncertainty

Daniel Dumke — Mon, 19 Mar 2012 16:51:59 +0000

Today will be a one-article-long-excursion in the world of production planning models.
Supply chain management of course should take a high level view of the supply and demand networks, nonetheless there is probably no supply chain which will work without physical products and most even have one or more at their core.

So production planning is a key part of a companies success.
Even in a world where companies focus on their core competencies, and may even outsource all of their production processes, knowledge about how the products are manufactured is still a vital component for understanding the supply chain and the associated risks.

Understanding the models used in production planning supports the awareness of the decision processes, which are applied in production management.

The full article can be downloaded here

Method

In their 2006 article the authors employ a literature review to gather information on which production management models are used.
First, the authors lay the foundations for their work by proposing a classification for models of manufacturing systems (figure 1, for general models; figure 2, for models including uncertainty). For basic model types are distinguished: conceptual-, analytical-, artificial-intelligence-based- and simulation-models

Figure 1: Classification for General Uncertainty Models (Mula et al., 2006)

Figure 2: Classification Production Planning Models under Uncertainty (Mula et al., 2006)

Next, in figure 3 the papers are classified according to the model type used and the decade.

Figure 3: References by Modelling Approach and Year (Mula et al., 2006)

Overall 87 papers are gathered from 1980 until 2004.

Results

Using the categorization suggested above as a frame the authors go through all the papers and add a short description for each of the 87 models. Afterwards the authors conclude:

The analytical modelling approach, in particular stochastic programming was the most frequently encountered. In the case of dynamic programming, few models were found and were mainly theoretical. Most of the analytical models addressed only one type of uncertainty, and assumed a simple structure of the production process. For more complex processes, with many different final products and more than one type of uncertainty, the analytical approach is replaced by methodologies based on artificial intelligence and simulation.
Although many works use simulation approaches to model uncertainty, very few studies exist on the comparative evaluation of the advantages and inconveniences of different simulation languages. With respect to artificial intelligence models, those based on fuzzy set theory represent an attractive tool to aid research in production management. Lastly, conceptual models with different approaches complete the taxonomy.

Conclusion

This article is a great basis to get a short (15 pages) and concise overview on production modelling under uncertainty within the last 22 years.

I was however was surprised to see that the authors did not include clues on how they selected the 87 papers. Or should we really believe that within a 22 year period there were only 87 papers published on production planning?
The authors included also a very short section on supply chain planning models, starting in 1994 with a few papers and I can therefore confirm that there are definitely gaps.

But, as said before, this really is a great overview. And if you are interested in more papers on supply chain planning just have a look here in the blog.

Reference:

Mula, J., Poler, R., García-Sabater, J., & Lario, F. (2006). Models for production planning under uncertainty: A review International Journal of Production Economics, 103 (1), 271-285 DOI: 10.1016/j.ijpe.2005.09.001

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Demand Forecasting, Resilience and Mapping (Book Review)

Daniel Dumke — Mon, 31 Oct 2011 14:30:00 +0000

I am a huge fan of Open Access in research and a while ago I was made aware of a book on supply chain management, which has recently been published under an open access license. The full book can be downloaded on the web site of the publisher.
The book contains 27 chapters / articles on a range of supply chain related topics, such as optimization, public sector supply chains, modeling and simulation, but also several papers which addressed supply chain risks in one way or the other.
I was especially interested in the risk related chapters, so I will give you a short overview on three of the papers:

A Hybrid Fuzzy Approach to Bullwhip Effect in Supply Chain Networks, by H. Tozan and O. Vayvay

The authors of the first paper propose a fuzzy-neural-network approach for demand forecasting. In supply chain management a test case for demand forecasting, has always been the bullwhip effect. The better your demand forecasting the less pronounced the bullwhip effect will be. And this can be a real money saver.

A simulation of their new approach shows that for a three tier supply chain (customer, retailer, factory) especially the fluctuations at the retailer can be reduced quite drastically (figure 1 a and b).

Figure 1: Orders and Production in the Base vs. Proposed Model (Tozan and Vayvay, 2011)

Integrating Lean, Agile, Resilience and Green Paradigms in Supply Chain Management (LARG_SCM), by H. Carvalho and V. Cruz-Machado

The second article I would like to highlight, tries to integrate the supply chain concepts of lean, agile, resilience and sustainability / green. One of the weaknesses in supply chain management research has always been the strong focus on one of the concepts, neglecting the fact that successful companies often have to integrate different aspects in one supply chain. A supply chain of a high-end computer manufacturer for example might have to be green and agile at the same time, a military supply chain probably should integrate the concepts of agility and resilience to be successful.
First the authors introduce the mentioned concepts and compare them in a nice table view.

Next they build a graphical model of the supply chain and added vectors to symbolize how the different concepts influence decisions in the supply chain.
Figure 2 aggregates the results.

Figure 2: Impact of different Concepts on Supply Chain Management Decisions (Carvalho and Cruz-Machado, 2011)

Supply Chain Resilience Using the Mapping Approach, by A.P. Barroso, V.H. Machado and V. Cruz-Machado

The last paper analyzes supply chain resilience using the example of a supply chain in the automotive industry. Supply chain mapping is a simple technique where the elements and connections of a supply chain are drawn on a map. The elements and connections are the enriched with additional information like inventory levels and policies or lead times.
After describing the methodology the authors use a case study to analyze the resilience of the chain. The supply chain mapping enables them to unveil several points for improvement:

The assembler has no alternative suppliers for part B. An identical situation is found for all the other parts.
Like the assembler, the 1st Tier B has no buffer stock. There is no inventory of raw materials, work in progress, and final products.

Conclusion

The first paper shows a quite interesting approach to demand forecasting, which (at least in the simulation) was able to produce much better results than more traditional approaches. If you are interested in this topic, I already discussed several other aspects of forecast risk and problems with forecasting, but I also touched other methods to improve forecasting (e.g. by information sharing).

The second paper contributes to the understanding of the effect of different aspects of some generic concepts in supply chain management. Even though it only considers a small amount of supply chain decisions, the results are quite clear: It is not possible to easily combine the different concepts and it highlights the need either to find trade-offs or to develop new approaches to satisfy all goals.

The third paper introduces the supply chain mapping methodology, which is quite simplistic in nature, but in my point of view one of the most powerful methods to analyze supply chain risks in practice. The case study should be read as an example only and gives a few hints on how to implement the methodology and analyze the results.

Reference:

Tozan, H., & Vayvay, O. (2011). A Hybrid Fuzzy Approach to Bullwhip Effect in Supply Chain Networks Supply Chain Management, 49-72

Carvalho, H., & Cruz-Machado, V. (2011). Integrating Lean, Agile, Resilience and Green Paradigms in Supply Chain Management (LARG_SCM) Supply Chain Management

Barroso, A.P., Machado, V.H., & Cruz Machado, V. (2011). Supply Chain Resilience Using the Mapping Approach Supply Chain Management

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Introduction to Risk Management in Supply Chains

Daniel Dumke — Wed, 21 Sep 2011 13:09:00 +0000

This is another introductory article (book chapter) to supply chain risk management. I included it, since it is an early (2003) view on supply chain risk management from another perspective. Many other articles I reviewed up to now are following the “Cranfield School Approach” with (Christopher, Jüttner, …) and this one by Peter Kajüter (Münster University, Germany) shows a different approach developed in parallel.

Basis and literature

Risk is defined as

a future development or event that might adversely impact the achievement of corporate goals.

Kajüter argues that risk management is a entrepreneurial need, which should be established by any company. Most developed countries also “support” this need by further regulation requiring risk management systems to contain the risk on a company level. But there seems to be no regulation demanding risk management which covers the supply chain and

consequently, companies are free to extend the scope of risk management beyond the company level and develop inter-organizational approaches to managing risk.

The literature review shows that two streams regarding risks in supply chains can be distinguished:

Investigation of mathematical models to analyze risk sharing instruments.
Focus on conceptual issues in supply chain risk management based on exploratory case studies.

Figure 1: Stages of Supply Chain Risk Management Implementation (Kajüter, 2003)

Corporate and supply chain risk management

Based on the review of the conceptual literature, Kajüter identifies three approaches in supply chain risk management (figure 1).

Depending on the integration stage of the supply chain network and the intensity of collaboration.

Corporate risk management is characterized by individual risk handling of a single company. Supply chain related risks are considered by purchasing risk assessments which are part of the overall risk management.

If buyers and suppliers start to cooperate in managing risks, supply chain risk assessments can be observed. They are characterized by a rather informal communication of risks among the supply chain members and joint efforts to handle them.

Supply chain risk management finally constitutes a structured and formal approach to managing risks by collaboration of supply chain partners. A specific risk management process for the supply chain is established.

So supply chain risk management can be defined as:

Supply chain risk management is a collaborative and structured approach to risk management, embedded in the planning and control processes of the supply chain,
to handle risks that might adversely affect the achievement of supply chain goals.

Risk strategy

The author next proposes the elements of the risk strategy in a supply chain risk management framework: basic principles of risk management, defined risk limits and responsibilities.
The risk management principles are shown in figure 2. Risk limits refer to the levels of maximum damage which can be tolerated and have to be set for each individual company and the overall supply chain.
Lastly the responsibilities have to be defined for the identified risks within the chain. Kajüter suggests establishing a risk owner for each risk and a cross-functional, cross-company risk management committee.

Figure 2: Principles of Supply Chain Risk Management (Kajüter, 2003)

Risk management process

Kajüter suggest a three step process to manage supply chain risks.
The first step includes the risk analysis which has to be conducted on a supply chain level. Figure 3 shows an example.
Step two refers to the risk control, where risk management strategies are employed to mitigate risks, those include: risk avoidance, reduction, transfer and acceptance.
The last step includes risk monitoring and reporting, where processes continuous monitoring of identified risks have to be found.

Figure 3: Risk Assessment Portfolio (Kajüter, 2003)

The author concludes:

An interorganizational approach to risk management in supply chains facilitates risk management at the single firms and offers opportunities to improve supply chain performance. It requires a high level of trust and mutual respect among the individual companies, though.

Conclusion

Kajüter delivers answers for three basic questions in supply chain risk management.

What are the stages of supply chain risk management and how is it different from corporate risk management?
What are the three major parts of supply chain risk management?
How can the process of supply chain risk management be employed in a supply chain and company?

Of course, this 16 page chapter can only give hints on the implementation side, but not cover every aspect. I did not like the risk categorization very much, or at least the wording (mathematical models for risk sharing or conceptual works) leaves out much quantitative literature which just investigate risk mitigation strategies.

But all in all the article makes a great starting point for supply chain risk management endeavors in business and research.

Reference:

Kajüter, P. (2003). Risk Management in Supply Chains Strategy and Organization in Supply Chains, 321-336

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From Supply Chain Vulnerabilities to Risk - Important Concepts in Supply Chain Risk Management

Daniel Dumke — Mon, 27 Jun 2011 13:43:00 +0000

This blog may be a good starting point for supply chain risk management related research and literature, but even with more than 140 articles reviewed in the blog I still just touched the tip of the iceberg. There are still many basic articles left. Like this one by Helen Peck (2006): “Reconciling supply chain vulnerability, risk and supply chain management”

Terms in SCRM

Today I have a look at, what is basically a literature review concerned with clarifying the confusion with the terms used when talking about risks in supply chains.

There are a wide range of different terms and concepts used in the wider field of supply chain risk management. How do the terms vulnerability and risk correlate and how are those embedded in supply chain management? On another level: How are corporate governance, business continuity management and security and emergency planning relating to SCRM?

Supply Chain

Starting from a “standard” supply chain definition as a system, comprising…

…flows of materials, goods and information (including money), which pass within and between organisations, linked by a range of tangible and intangible facilitators, including relationships processes, activities and integrated (information) systems.

The first definitions for “supply chain management” came up in the early 1980s and developed from a very logistical view on a supply chain towards a network understanding, comprising aspects like marketing or product development as well. There also has to be a clear distinction between a strategic level tasks in SCM and their functional execution.

Vulnerability and resilience

Within SCM there is no clear consensus as to whether supply chain vulnerability is simply a symptom of poor SCM—to be remedied with more effective SCM and the wider adoption of a SCO—or whether it is the unintended downside consequence of its successful application. Perhaps it should rightly be regarded as a combination of all of these.

Supply chain vulnerability can be defined as an “exposure to serious disturbance, arising from risks within the supply chain as well as risks external to the supply chain” and as “a condition that is caused by time and relationship dependencies in a company’s activities in a supply chain”. Vulnerability is therefore seen as a combination of a disturbance and the resulting negative consequence.

The concept of “resilience” is related to risk and vulnerability in so far as it accepts that not all “risks” (hazards or threats) can be avoided, controlled, or eliminated. Instead, resilience focuses on the “ability of the system to return to is original or desired state after being disturbed”, i.e. its ability to absorb or mitigate the impact of the disturbance.

Corporate risk management

Supply chain (risk) management and its counterpart on a corporate level do not share the same origin. Where supply chain management stems from a more comprehensive view on operational management aspects like logistics and operations; corporate risk management originates in a strategic / macroeconomic view on the company.

These roots also lead to a different understanding for risk management. In a case where corporate risk management suggests outsourcing of non-core processes for risk reduction, a supply chain risk management view would imply a larger weight on the negative effects of the reduction in control.

Conclusion

Finally, Peck emphasizes the different aspects of risks in supply chains and highlights the distinctive factors:

Consequently, it is suggested that managerial views of supply chain risk, based on assumptions drawn principally from best practice in manufacturing enterprises, offer a familiar, convenient but incomplete picture of supply chain vulnerability. SCM is an integrative, cross-functional discipline, so it must be recognised that supply chain vulnerability is also a concern for practitioners and academics in other disciplines, including BCM and corporate risk management.

Reference:

Peck, H. (2006). Reconciling supply chain vulnerability, risk and supply chain management International Journal of Logistics, 9 (2), 127-142 DOI: 10.1080/13675560600673578

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Issues in Supply Chain Management

Daniel Dumke — Wed, 22 Jun 2011 10:26:00 +0000

Very often this blog is concerned with the risk part of supply chain risk management. But to understand the risks within supply chain management, one has to understand the supply chain part as well. In 2000 Lambert and Cooper published a paper on the current “Issues in Supply CHain Management” and I want to highlight the main points here.

Understanding of supply chain management

Since the development of the supply chain management concept there has been and still is some discussion on what supply chain management actually includes? A very broad definition of the term can be:

Supply Chain Management is the integration of key busi- ness processes from end user through original suppliers that provides products, services, and information that add value for customers and other stakeholders.

The process frontiers between the companies merge into one and with the help of the information flow all processes are managed (figure 1).

Figure 1: Integrated Business Processes within a Supply Chain (click to enlarge; Lambert and Cooper, 2000)

In the sense of this definition, logistics therefore…

… is that part of the supply chain process that plans, implements, and controls the efficient, effective flow and storage of goods, services, and related information from the point-of-origin to the point-of-consumption in order to meet customers’ requirements.

Methodology

To come to a better understanding of supply chain management the authors used an practice oriented approach and conducted a case study of nine supply chains with over 90 in-depth interviews spanning 15 companies. The interviews were guided using a 36 question interview guide and lasted between one and three hours.

Results

Based on this large research base it is now possible to derive several key findings.
Figure 2 highlights the elements of supply chain management.

Figure 2: Framework of Supply Chain Management (Lambert and Cooper, 2000)

The Network Structure contains the identification of supply chain members (and non-members), furthermore the structural dimensions of the network in horizontal (number of tiers) and vertical (number of elements in each tier) terms.
Supply Chain Business Processes, where key processes are:

Customer relationship management
Customer service management
Demand management
Order fulfillment
Manufacturing flow management
Procurement
Product development and commercialization
Returns
Concerning the business processes the author find that the links between processes can be categorized into four different classes:
Managed process links, which are actively integrated and managed by the focal company
Monitored process links, are not seen as critical but still monitored
Not-managed process links, are links where the focal company is not actively involved in
Non-member process links, managers are aware of other, parallel supply chains.
An example of such supply chain with its links can be found in figure 3.

Figure 3: Example of a Supply Chain with different Links (click to enlarge; Lambert and Cooper, 2000)

The Management Components of SCM are described in figure 4.

Figure 4: Management Aspects of Supply Chain Management (Lambert and Cooper, 2000)

Missing pieces

Based on their research the authors state eight key questions related to their framework which need further research in the future:

What are the operational definitions of the key business processes and what are the relationships among these processes?
How should the existing supply chain be mapped? Should the map include all connected firms or only the primary firms?
What is the value proposition at the consumer level or end point of the supply chain?
What metrics should be used to evaluate the performance of the entire supply chain, individual members or subsets of members?
What is the process to take the map of the existing supply chain and to modify it to obtain the best supply chain given the desired outputs?
What determines with whom to link business processes?
What determines the processes to link with these key members?
What determines the type/level of integration that should be applied to each process link?

Conclusion

Of course some of these questions have already been answered in the meantime, at least partially. But I wanted to highlight this general framework since it shows several important aspects for risk management as well. E.g. the categorization of the links, which could be a great tool to maximize the efficiency of risk management efforts or that supply chain mapping overall also has positive effects for risk management.

Reference:

Lambert, D.M., & Cooper, M.C. (2000). Issues in Supply Chain Management Industrial Marketing Management , 29, 65-83 DOI: 10.1016/S0019-8501(99)00113-3

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Categorization of Supply Chain Risk and Risk Management

Daniel Dumke — Mon, 16 May 2011 14:13:00 +0000

Several questions I receive concern the very basic elements of supply chain risk management. Since reading “Categorization of Supply Chain Risk and Risk Management” by Norrman and Lindroth (2004) I often referred to it, to describe the different aspects.

Framework

Norrman and Lindroth suggest a three dimensional framework to analyze different supply chain risk management issues (figure 1). The dimensions are:

Unit of analysis, describing the levels which are affected by this issue (more local to the company or affecting the whole supply network)

Type of risk or uncertainty, describing if the issue is operational or strategic

Risk and business continuity management process, which shows the stage within the risk management process

Figure 1: Supply Chain Risk Management Framework (Norrman and Lindroth, 2004)

The framework can be applied to many supply chain problems, an example of which can be found in figure 2.

Figure 2: Application of Supply Chain Risk Management Framework (click to enlarge; Norrman and Lindroth, 2004)

Definition of SCRM

Supply chain risk management can be defined as,

… to collaboratively with partners in a supply chain apply risk management process tools to deal with risks and uncertainties caused by, or impacting on, logistics related activities or resources’ (Norrman and Lindroth, 2002)

Since SCRM is dealing with more than the risk from a single company it takes a broader perspective than the traditional risk management approach. It also considers the rippling effects of events connected entities.

There are several definitions for risk. The Royal Society defined it in 1992 as:

risk is the chance, in quantitative terms, of a defined hazard occurring. It therefore combines a probabilistic measure of the occurrence of the primary event(s) with a measure of the consequences of that/those event(s)

An important dimension of risk is its contextual association, which can be strategic, financial, operational, commercial or technical:

Strategic: the risk of plans failing or succeeding, e.g. marketing strategy, changes in consumer behavior or political/regulatory changes.

Financial: the risk of financial control failing or succeeding.

Operational: the risk of human error or achievement, e.g. design mistakes, unsafe behavior, employee practices risk, sabotage.

Commercial: the risk of relationships failing or succeeding, e.g. business interruption due to loss of key executive, supplier failure or lack of legal compliance.

Technical: the risk of physical assets failing/being damaged or enhanced, e.g. equipment breakdown, infrastructure failure, fires, explosion, pollution, etc.

But the locational source of the risk is as important and can be divided into (a) externally-driven or environmental risk, (b) internally-driven or process risk, © decision-driven or information risk.

Risk Management Process

After highlighting some basic aspects of SCRM and risks in the supply chain context, the authors present their risk management process, which contains three elements: Risk Analysis and Assessment, Risk Management and Business Continuity Management (BCM).

The process starts with a listing of the risks affecting the supply chain using Fault Tree Analysis (FTA) and assessing the effects of those events in case they happen on the supply chain using Event Tree Analysis (ETA). As the second step, the decision has to be made if the risk can be accepted or if the risks can be mitigated by reducing the likelihood or impact.

Thirdly, one can argue if BCM (see figure 3) has to be part of a risk management process, nonetheless it is related, since it covers the aspect of planning for when an adverse event happens.

Figure 3: Business Continuity Management (Norrman and Lindroth, 2004)

Conclusion

The framework combines several important aspects of risk management in general and specifically supply chain management. It is therefore very suitable for an introductory purpose on supply chain risk management.

Reference:

Norrman, A., & Lindroth, R. (2004). Categorization of Supply Chain Risk and Risk Management Supply Chain Risk (Ed. Clare Brindley), 14-27

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Supply Chain Simulation and the Bullwhip Effect

Daniel Dumke — Wed, 20 Apr 2011 08:59:00 +0000

I already reviewed some articles by Denis Towill primarily because he does some interesting research on simulation and supply chains, but also because I like his clear style in his articles.

In one of his early papers (1992) he teamed up with Naim and Wikner and described state of the art strategies to fight the bullwhip effect or as it is called in the paper by its older name: Industrial Dynamics.

Industrial Dynamics

I already described the causes of the bullwhip effect and how to measure it in an older post. The bullwhip effect describes amplifications in demand within the supply chain. Exemplary effects can be seen in figure 1.

Figure 1: Effect of the Bullwhip Effect (Towill et al. 1992)

Improving SC Dynamics

One way to improve the supply chain dynamics is to introduce a leaner supply chain, which in turn will lead to lower lead times and lower amplifications.

In a lean supply chain stocks are located at a low level of “added value”, to keep the inventory cost lower.

The next decision to make is to find the right trade-off between stock levels and production rates. If you increase the flexibility of production, you might be able to reduce the inventory overall. There are two alternatives:

Fixed process rate / varying inventory levels

Varying process rate / fixed inventory

There are four sectors where where further improvements can be acchieved:

Industrial engineering improvements, eg. changing the product design or changing the layout of the production

Production engineering improvements, eg. integration and sequencing of processes to reduce lead times

Information technology improvements, eg. quicker data capture and electronic data interfaces

Operations engineering improvements, eg. pull system instead of push, shared planning

Optimization

To examine their points, Towill et al. design a simple supply chain simulation model with four stages (retailer, distributor, warehouse and factory). The results (figure 2) show that above mentioned improvements can lead to a reduction in the amplification.

Figure 2: Strategies for Reducing Demand Amplification (Towill et al. 1992)

The authors conclude that reducing the overall lead times in the supply chain may be an expensive solution. As an alternative they suggest to remove some stages from the chain which also leads to significant reductions in the amplifications. Probably the cheapest way to reduce the bullwhip effect may be to increase collaboration in the chain, in this case especially concerning forecasts and planning.

Conclusion

Simulation model cannot only help in theoretical exercises. There are very important applications in real life applications as well when the task is to optimize generic strategy recommendations like those mentioned above.

Reference:

Towill, D., Naim, M., & Wikner, J. (1992). Industrial Dynamics Simulation Models in the Design of Supply Chains International Journal of Physical Distribution & Logistics Management, 22 (5), 3-13 DOI: 10.1108/09600039210016995

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Supply Chain Management Literature Review

Daniel Dumke — Mon, 11 Apr 2011 14:29:00 +0000

It’s not that there are no articles on supply chain risk management anymore. But after writing on current research in the last weeks (like the one on system failure here) I have been wondering more about the foundations of supply chain management in general. So I decided to review an article today on general supply chain management research, in this case a literature review by Sachan and Datta (2005).
The complete article can be found here.

Analysis

The analysis is pretty straight forward, Sachan and Datta start with showing the different research designs used: empirical/descriptive and quantitative/qualitative. In supply chain management the research methods range from surveys, interviews and case studies, to more quantitative approaches like mathematical modeling or simulation. Using these categories the authors reviewed 440 supply chain management articles from 1999 to 2003.

Authors’ Conclusions

The authors themselves draw the following conclusions from the data at hand:
Conclusion 1:

If academicians today do not expand the approaches to research, managers will continue to perceive them as irrelevant academicians, which address fictitious problems and are not interested in the real world.

Conclusion 2:

Simulation is often performed to check for validity of the models developed in an paper, or to examine the efficiency of heuristics, or to assess model solution times.

Conclusion 3:

It is remarkable that not more papers have an inter-organizational level (dyad, chain and network) of analysis despite the increasing attention toward these level had started at the beginning of the 1980s.

Furthermore they identify the following gaps in the research:

Theories of other discipline are applied in very few papers
Secondary data sources are used in many papers, but not in an innovative way
The research at inter-organizational level is very less.

Conclusion

There are two major conclusions drawn in the article: Academicians make themselves irrelevant, because they only use a specific set of methods, to solve problems which are not rooted within business problems.
Secondly, only few papers focus on a supply chain network, most of them only view single relationships between one or two elements of the chain, ignoring most network effects.

The conclusions drawn are both very intriguing, but they are really missing some more explanations. So, for example, why are they sure that the choice of methods is the reason for the great gap between research and business?
Anyone reading papers on supply chain management realized the gap between the title of the field and much of the research done there. Still, it would be more interesting to know why most research is only done on sub systems.

Reference:

Sachan, A., & Datta, S. (2005). Review of supply chain management and logistics research International Journal of Physical Distribution & Logistics Management, 35 (9), 664-705 DOI: 10.1108/09600030510632032

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Analysis of Logistics Strategies from 1990 to 2008

Daniel Dumke — Mon, 21 Mar 2011 16:02:00 +0000

Do supply chain strategies evolve over time? Are there the same strategic options nowadays compared to 20 years ago?
Since at least the meaning of the term logistics has evolved during the last 20 years, especially due to the emergence of supply chain management, logistics and supply chain management are used interchangeable in this article.

In 1987 Bowersox and Daugherty created a logistics strategy framework, concluding that there are basically three SC strategies:

Process Strategy
management of the traditional logistics activities with a primary goal of controlling costs
Market Strategy
management of selected traditional logistics activities across business units with the goal of reducing complexity faced by customers
Information Strategy
management as a system, with the goal of achieving inter-organizational coordination and collaboration through the channel.

Hypothesis

Building on this framework McGinnis, Kohn, Spillan (2010) executed and analyzed four surveys from the years 1990, 1994, 1999, 2008 with the above mentioned research questions in mind. The following hypothesis were designed:

Importance of Bowersox framework remained constant
Dependent variables (statistical data on the survey participants like: logistics coordination effectiveness, customer service commitment and competitiveness) remained constant
Within a logistics strategy, process strategy, market strategy, and information strategy will be of equal importance.

Results

First, the results show, that the dependent variables and the perception of the strategies did not change too much to make a comparison between the studies impossible.
To analyze the results further the authors clustered the respondents into three strategy clusters (intense, intermediate and passive cluster), depending on their propensity for the mentioned strategies. Here is what they found:

Intense Logistics Strategy increased
That means that either the importance of logistics strategy in U.S. manufacturing firms increased in importance or the firms were more intensely managed overall, including logistics
Relative Importance
Process strategy (cost control) is generally more important than market strategy (reducing complexity faced by customers), and that both are more important than information strategy (inter-organizational cooperation and collaboration).

The authors conclude that the Bowersox and Daugherty (1987) typology still provides an excellent framework and that strategy is more stable over time than expected. The primary focus of an intense supply chain strategy is cost efficiency and complexity reduction; furthermore it appears that cost efficiency and reduced customer complexity are facilitated by the information strategy in the intense logistics cluster.

Conclusion

I think this kind of historical analysis is much to seldom in current research. In the popular reporting very often the hypothesis is made: This topic has experienced growing attention / relevance / … But has the world really become eg. more dangerous haven’t there always been violent attacks on people and property? I think McGinnis et al. provide a great basis for this kind of discussion. The answer is: Yes, there have been to the logistics strategies used by companies in the last 20 years, but not so much though. Of course this does not make a great headline like…

Reference:

McGinnis, M.A, Kohn, J.W., & Spillan, J.E. (2010). A Longitudinal Study of Logistics Strategy: 1990-2008 Journal of Business Logistics, 31 (1), 217-235

Bowersox, D.J., & Daugherty, P.J. (1987). Emerging Patterns of Logistical Organization Journal of Business Logistics, 8 (1), 46-60

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How Systems Design Themselves

Daniel Dumke — Wed, 02 Mar 2011 08:22:00 +0000

Continuing with on with articles on general Systems Design and foundational articles, today I would like to talk about Conway’s seminal paper on “How Do Committees Invent” from 1968. If you want to read the paper completely, you can do so on Conway’s web page.

In his article Conway describes system design at its most generic level. Be it a system to prevent natural disasters or a new product of a company.

Actors and Stages of Design

Under most circumstances the newly designed system has a sponsor who needs the system for an specific end. The task to can be carried out by the affected organization or an external group.
Two basic milestones have to be reached to continue with the design:

Understanding the boundaries, those can be in place by reality or set by the sponsor of the design
Information about the status quo of the system

The next step is then to organize the design team and set the scope of the the tasks of the sub groups.
The fourth and fifth step are the coordination of the tasks and the consolidation into a single design.

The System itself

A given system can be divided into a number of subsystems. Conway gives the example of the public transportation system, which consists on the top level of buses, trains, planes, etc. On the next level an airplane can be split up into subsystems for structure, propulsion, … and so on.

To illustrate this concept the author draws the following picture. The circles represent a (sub)system and the lines the connections between them.

System and Subsystems with Interfaces (Conway 1968)

This thinking about systems can be deployed for other concepts as well. So not only the “to be designed” system can be described this way but also the organization which designs it.

Systems / Design Group

The system and its design group are related. For a given subsystem x there will be a (part of the) design group (X) which designed this subsystem. The same holds true for the connections between subsystems (eg. x and y). If they are connected, we know that the design teams X and Y had to communicate at some point in time to design the interface.

So the design of the finished system is dependent on the preexisting design of the design group.

This kind of a structure-preserving relationship between two sets of things is called a homomorphism.

To underline his point Conway describes the following example from informatics:

A contract research organization had eight people who were to produce a COBOL and an ALGOL compiler. After some initial estimates of difficulty and time, five people were assigned to the COBOL job and three to the ALGOL job. The resulting COBOL compiler ran in five phases, the ALG0L compiler ran in three.

Results

The author summarizes the following thesis:

Organizations which design systems are constrained to produce designs which are copies of the communication structures of these organizations.

Since the initial organization of the design group may not be the right one for the newly designed system, flexibility is a key to effective design. Rewards have to be given to support the design manager in keeping the organization lean and flexible

Conway also takes a short detour, that especially large systems might be prone to failure, since the task of designing those systems is huge and overwhelming so that already the communication within the design group disintegrates, leading to the same result in the designed system.

Conclusion

What effects does this have for a supply chain designer? Can the supply chain be seen an image of the company’s structure itself? How does this affect business and research for the “optimal” supply chain design.

Update: Have a look at the comments below, Eleanor recommends a working paper from the Harvard Business School testing above hypothesis: https://hbswk.hbs.edu/item/first-look-feb-8

Reference:

Conway, M. E. (1968). How Do Committees Invent? Datamation, 14 (4), 28-31

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Supply Chain Risk Sources, Consequences, Drivers and Mitigation

Daniel Dumke — Wed, 23 Feb 2011 09:35:00 +0000

I just stumbled upon one of the articles I already read about a year ago, shortly after I started my research. Beside indication of a future research agenda (see as well here), Jüttner et al. (2003) also explain some fundamental concepts of supply chain risk management.

How to get there?

Jüttner et al. decided to conduct a exploratory study with practitioner interviews and compare these results with a literature review. Four basic concepts for Supply Chain Risk Management evolved from this, namely Risk Sources, Risk Consequences, Risk Drivers and Risk Mitigation Strategies.

Risk Sources

[are] environmental, organisational or supply chain-related variables which cannot be predicted with certainty and which impact on the supply chain outcome variables

So there are three categories for risk sources: Environmental, Network and Organization.

Environmental risk sources may for example be the result of accidents (eg. fire), socio-political actions (eg. terrorist attacks) or force majeure (like hurricanes or earthquakes)
Network-related risk sources unfold from interactions between organisations within the supply chain, examples are: Lack of Ownership (unclear responsibilites between supply chain partners eg. due to increased concentration and outsourcing), Chaos can result from missing trust or badly communicated information, finally Inertia describes a lack of flexibility within the supply chain.
The interviews showed
a consensus that network-related risks are an important and so far neglected source of risk.
Organisational risk sources can be found within one of the participants of the supply chain in focus and can be found within the production factors like labour (strikes), machines (failure), etc.

To conclude: From the point of view of the links within the supply chain, environmental and organizational uncertainties can be seen as risks “to” the links in the supply chain whereas network-related uncertainties are risk sources “of” the links.

Risk Consequences

Risk can have consequences can be measured ex post by the performance indicators used. Ex ante they are contained within the variances of the indicators. Three different consequences can be named:

Financial consequences
Reputation damage
Health and safety concerns

Risk Drivers

Risk drivers further increase the risk experienced by the supply chain participants (examples: competition increases the risk indirectly, outsourcing (increased complexity) has a direct effect on risks)

The major drivers for risk are: focus on efficiency rather than effectiveness, globalization of supply chains, focussed factories and centralized distribution, the trend to outsourcing and the reduction of the supplier base.

Risk Mitigating Strategies

… can be defined as

strategic moves organisations deliberately undertake to mitigate the uncertainties identified from the various risk sources (Miller, 1992)

Conclusion

The results of this article experienced a widespread use and are accepted by many researchers. The definitions mentioned can be used as basis for further research in the supply chain risk management field.

Reference:

Juttner, U., Peck, H., & Christopher, M. (2003). Supply Chain Risk Management: Outlining an Agenda for Future Research International Journal of Logistics Research and Applications, 6 (4), 197-210 DOI: 10.1080/13675560310001627016

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System Failure

Daniel Dumke — Mon, 21 Feb 2011 09:14:00 +0000

I was looking for more general insights into the topic on why systems fail. I stumbled on a talk of Eleanor Saitta from last years Chaos Communication Congress in Berlin. There is a recording of the talk here and the slides for the talk can be obtained here.

I am going to summarize some of the key points Saitta made in her talk in this article.

Types of System Failures

There are two general types of system failures: Simple and chained failures.

The systems propensity for failure is related to the complexity of the system and affected by the aspiration to increase efficiency, optimality and accelerate the Prozesses weithin the system.

Example of the Determinants of System Collapse

Figure 1: System Effect Circle (in Saitta 2010; from Vinay Gupta 2009)

In many cases, system complexity is very overwhelming. So the task of analyzing why a system fails can be very demanding.

To answer the specific question what kind of failure of the economic system (eg. the near-collapse of the financial system in 2008) leads to the death of one or more individuals, Saitta presents the system effect circle.

The individual is placed in its center, next come the possible causes of ones death, the essential foundations of society (like work, resources, transportation and communication). The last two circles show the underlining concepts to generate and sustain the former items.

Multiple systems are affected by those concepts, the following example should clarify the logic.In Figure 2 Saitta shows the connections between the individual systems and how they affect each other.

Figure 2: Example of Connections within the System Effect Circle (Saitta 2010; from Vinay Gupta 2009)

Preventing Collapse

To prevent collapse systems have to be designed to be resilient. The graphic shown in the example above can be used as a basis for the analysis of “what can go wrong”. These results can be generated by defining the Need-Matrix (Figure 3) for the system in focus.

Figure 3: Need Matrix for System Analysis (click to enlarge; Saitta 2010; from Vinay Gupta 2009)

A system not only consists of the foundation factors found in the Need-Matrix, but also the assets and actors within the system, and the rules which control the the access from the actors on the resources.

The goal for building resilient systems is therefore to analyze the connections between actors and assets and explore how the rules have to be designed for the system to work effectively.

Conclusion

Building resilient systems is hard on every level. On a large scale (eg. banking system) existing power distributions often prohibits the establishment of a resilient infrastructure. Nonetheless an in-depth analysis might help prevent the most severe consequences.

For smaller scale systems, like a supply chain, analyzing the foundational factors, actors, assets and rules is mandatory for building a resilient system.

The key concepts are the same on every level: actors, assets, their connections and access rules.

Update:

You can find more on the Simple Critical Infrastructure Model on these slides by Vinay Gupta.

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Supply Chain Disruptions and Operating Performance

Daniel Dumke — Wed, 12 Jan 2011 09:39:00 +0000

I just realized, that up to now I have not written much about why Supply Chain Risk Management should be an important factor many more companies.

Hendricks and Singhal wanted to understand this as well and researched on what effect a missing supply chain risk management can have on a company’s performance. They therefore started a research series, the first article was on the “Effect of Supply Chain Glitches on Shareholder Wealth” (mentioned here). And today I have a look at their second article in this series: “Association between Supply Chain Glitches and Operating Performance”.

Introduction

The authors conducted an empirical study to learn more about the relationship between supply chain glitches (which are defined as supply exceeding or not meeting demand) and operating performance of the company.

Negative Impact of Glitches

First it is important to think about how supply chain glitches work and why the can have negative impacts on different parts of the company and its supply chain:

Demand Side
- short and long-term loss in sales
- market share
- lower sales price
- oportunity costs of unavailability of products
- customer service (dissatisfaction, lower loyalty)
- reputation / credibility
Cost Side
- expediting
- premium freight
- obsolete inventory
- additional marketing
- penalties paid
- increase public relation expenses
- capital cost
Assets
- productivity
- utilization of assets (over- or underutilization)

Methodology

A sample of public announcements is analyzed for supply chain glitches. 885 glitches are identified and on that basis the performance during a period before (4 quarters) and after the glitch (8 quarters) is assessed for effects of the glitch. A typical glitch announcement looks like this:

“Apple Computer Inc. Cuts 4th-period Forecast Citing Parts Shortages, Product Delays,” The Wall Street Journal, September 15, 1995.

Hypothesis and Results

The following hypothesis are then tested using available data:

Supply chain glitches will be associated with a decrease in profitability
Supply chain glitches will be associated with a decrease in net sales
Supply chain glitches will be associated with an increase in costs
Supply chain glitches will be associated with negative asset and inventory performance

Single firm performance is compared to a peer company before and after the glitch.
The analysis reveals that before the glitch operating income is down by 107%, return on sales is down 114% and return on assets down by 93%.
After a glitch the authors found that the changes in operating income, sales, total costs, and inventories are insignificantly different from zero.

Conclusion

Hendricks and Singhal also provide an interesting statistic on the responsibilities for the glitches, on the top: internal (then customers and suppliers). This might indicate a priority for supply chain risk management as well: a reduction in internal errors and disruptions can have a huge leverage on company performance.

Reference:

Hendricks, K.B., & Singhal, V.R. (2003). The effect of supply chain glitches on shareholder wealth Journal of Operations Management, 21 (5), 501-522 DOI: 10.1016/j.jom.2003.02.003

Hendricks, K., & Singhal, V. (2005). Association Between Supply Chain Glitches and Operating Performance Management Science, 51 (5), 695-711 DOI: 10.1287/mnsc.1040.0353

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Managing Supply Chains with multiple Pipelines

Daniel Dumke — Mon, 10 Jan 2011 15:42:00 +0000

Companies offer a smaller or larger range of products serving different markets, depending on their history and primarily the respective business model.

From a supply chain management point of view this poses the question if it is ok just to use the same supply chain strategy for all those products.

Pipelines vs. Supply Chains

Aitken et al. (2005) make a convincing argument against this approach and instead suggest the “pipeline” to describe

the specific operational mechanisms and procedures that are employed to service specific product/market contexts

within one supply chain.
So one supply chain usually contains several different pipelines.

Case Study

The authors conducted a case study with a lightning company producing a range of lighting products for diverse markets.
During the four year project there were two major phases: first the introduction of lean production, and second increasing the responsiveness of the plant.

Four different pipelines were identified by clustering the products. The clusters were defined by considering the trade off between economies of scale, economies of scope and the diseconomies of averaging.

Cluster 1: low volume products
Cluster 2: high volume, low variant products
Cluster 3: multiple variants of standard products
Cluster 4: customized products

Pipeline Strategies

Different pipeline strategies were identified and are listed in table 1.

Table 1: Categorization of Pipeline Strategies (Aitken et al. 2005; click to enlarge)

Conclusion

Pipelines are a useful way of differentiating supply chain and selecting the right strategies depending on the market and product properties. Aitken et al. describe a normative scenario, in practice differences in supply chains are often due to missing integration of different parts of a company (eg. after a merger). But especially in those cases it is necessary to develop an approach for reintegration without loosing sight of the different needs of the customers.

Reference:

Aitken, J., Childerhouse, P., Christopher, M.G., & Towill, D.R. (2005). Designing and Managing multiple Pipelines Journal of Business Logistics, 26 (2), 73-95

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Definition of Risk

Daniel Dumke — Wed, 05 Jan 2011 12:59:00 +0000

What is risk anyway?
I read this paper already some time ago. It is very important to have a clear definition of the terms used in research. But from my previous experience I know that also in business a clear understanding of the different aspects of risks is important to stay consistent.

Case Study

At a client I was involved in a company wide risk assessment. The participating middle managers were required to list and assess relevant risks using an Excel sheet. There were predefined categories for impact (eg. less than €1m, between €1m and €10m and above €10m) and probability (eg. p 50%).
The survey was therefore aimed at high impact, low probability events. One of the biggest tasks during this assignment was to train the managers on how these categories should be interpreted. But honestly, this categorization does not make this task very easy. Suppose the following disruption: missing employees due to an outbreak of the swine flu. The line in Excel might look like this:

Swine Flu: p But if you think about it, this task is not very straight forward, the following questions remain:

There is of course also a more remote chance that the outbreak cannot be contained so quickly as assumed here and the loss might be larger than € 1m. How should you account for this? Add another line, with p Risks can be differentiated into different kinds like business risk, social risk, economic risk, safety risk

Risk and uncertainty
There is a difference between risk and uncertainty, where risk is when you know about the probabilities and uncertainties when you don’t. So most real life situations (beside the Casino) you are in the realm of uncertainty. If you are using uncertainty, then you have to think about the probabilities of the probability, how likely is it that your estimated probabilities are correct?

Relativity of risks
There is usually no objective measure for risk, only perceived risks.
The notion of absolute risk always ends up being somebody else’s perceived risk quantitative definition of risk

Risk should be view using the following triplet
Scenario, Likelihood and Consequence

There are different types of damage
There is no continuous measure which you can use for loss of life vs. loss of property

Conclusion

Kaplan shows several important factors of risks that are relevant when applying the concept of risk in a business setting. Several other researchers have built on his work, and for example extended the definition of the consequence of risk, to not only contain a single digit for the impact but also aspects as duration, etc.

Reference:

Kaplan, S., & Garrick, B. (1981). On The Quantitative Definition of Risk Risk Analysis, 1 (1), 11-27 DOI: 10.1111/j.1539-6924.1981.tb01350.x

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