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Scenario Planning has been around for some time now. By some companies it is seen as a core tool to assess a risky future and support strategic planning. Up to now I only mentioned it briefly in a few articles.

In 1977 Vanston et al. were one of the first authors to document a complete scenario planning methodology.
So this article answers questions of what scenarios are and how to generate and analyze them.


In order to minimize the risk inherent in planning against a single, unforeseeable future and to be in a position to profit from different possible trends and events, many governmental agencies and private companies are finding it desirable to plan against, not one, but rather a range of possible futures. Obviously, for the technique to be used effectively a set of alternate scenarios which are relevant, reasonable, and logically interrelated needs to be developed.

There are four requirements which each scenario should fulfill:

  1. Plausibility.
  2. Self-consistency.
  3. Inclusion of all critical, relevant factors.
  4. Similarity to other scenarios in form and scope.

Scenario Planning

The methodology consist of twelve steps, which are described briefly and afterwards discussed in a case study. In the case study the University of Texas (UT) was asked by the National Aeronautics and Space Administration ( NASA) to develop a set of alternate scenarios for use in a workshop to assess possible national policies concerning portable fuels.

  1. Define Purpose and Organize Development Team
    The goal has to be set first, building on the objective the candidates for a development team are selected.
    Case study: The general purpose of the workshop and the proposed use of the scenarios to be developed by The University of Texas (UT) team (composed of members of the Center for Energy Studies and the Population Research Center ( PRC)) were outlined in the original NASA work statement. Subsequent meetings of UT, TRW, and NASA representatives allowed further definition of the intended nature of the scenarios and the methodol- ogy for integrating the scenarios into the workshop procedures. It was agreed that approximately six different scenarios could be accommodated-given the size of the workshop. […]
  2. Gather Relevant Data
    The underlying data is key to any good scenario and determines its credibility and completeness.
    Case study: The contract work statement for the university team emphasized nontechnical aspects of the energy problem. The scenario development committee hence focused most of its data-gathering activities on “futures” literature and societal factors and demographic trends.
  3. List all relevant factors
    Now the factors which are relevant for the project in a social, political, economic, technical and ecological way. This selection should be broad.
    Case study: the committee next listed all components of the social structure which could reasonably be associated with energy consumption or which would limit or restrict the production of energy. All relevant factors were listed even though in some cases their impact on the energy dimension appeared remote. In all,
    approximately ninety factors were identified.
  4. Determine the most pertinent factors
    In a team work approach a further specification and selection of the factors has to be conducted. An inclusion of management staff is recommended.
    Case study: At this point three additional consultants were engaged to assist in factor evaluation. These consultants included an economist, a sociologist, and a political policy specialist. After a general meeting of the committee with the consultants, members of both groups were asked to rank the factors in order of their importance to the energy status of the nation.
  5. Choose themes for alternate scenarios
    General topics for the scenarios should be defined. “Obviously, the company or agency can plan against only a finite, generally small, number of futures. Although the exact number of scenarios to be developed will vary, experience has shown that from three to six are usually appropriate. As will be discussed later, one of the scenarios should be the one believed to be the most probable. The other scenarios should be chosen according to the degree to which they provide maximum value to the planning process.”
    Case study: The [6] themes were chosen as follows:
    (a) Economic expansion: A future in which the nation puts primary emphasis on economic growth, increased production, and improved material well-being.
    (b) Environmental concern: A future in which the nation puts major emphasis on environmental and ecological improvement even, if necessary, at the expense of other factors. […]
  6. Arrange factors into related groups
    The factors found in step 4 have to be summarized into groups to describe the interdependencies between them.
    Case study: After the factors developed in step 4 were compared with the six chosen themes, it was decided that the factors could be grouped into nine general topics.
    (a) Population, (b) Urbanization, (c) Labor Force […]
  7. Define present situation in terms of the chosen factors
    “Using information on the status at present and in the recent past of the previously chosen factors, a narrative statement is written regarding the present state of the relevant society and the manner whereby this state came into being.”
    Case study: At this time the scenario development committee prepared a narrative description of
    the present status and recent history of the United States based on the above groups of factors. All listed data were carefully referenced and a glossary of terms was attached.
  8. Develop most probable scenario
    The authors suggest to start of with the most probable scenario and set the factors. To generate the necessary information either own forecast and/or projections of others shall be used.
    Case study: To begin the development process, values were assigned to each of the relevant factors.
    These values were carefully chosen after comparing estimates from various technical and “futures” sources with trend extrapolations developed by the committee itself.
  9. Alter basic factors to support alternate scenarios
    Finding alternative possibilities for factor combinations then support the other scenarios.
    Case study: The scenario development committee next examined each of the relevant factors and
    determined how they might be affected by the futures envisioned in the six alternative themes. When appropriate, factors were modified to reflect projected effects.
  10. Prepare alternate scenarios
    “All scenarios should be as closely alike in format, wording, and style as practical. This congruency will assist in comparison of the planning programs based on the different scenarios. As with the most probable scenario, projections should be referenced where possible, and reasoning carefully explained.”
    Case study: Using the modified factor values developed in Step 9, scenarios were developed for each
    bounding theme. To the extent possible, each alternate scenario had the same format and, in many cases, the same phrasing as the most probable scenario. This parallelism was intended to facilitate comparison of the plans which would be developed using the different scenarios.
  11. Check all scenarios for consistency, clarity, and completeness
    “It is very easy in a complex scenario to overlook internal inconsistencies and normally
    obvious violations of logic and reason. All scenarios should be checked by people not involved in their preparation to guarantee their clarity, correctness, and completeness.”
    Case study: The completed scenarios were then sent to two editors for review and rewrite as necessary. Copies were also sent to selected consultants for suggestions and comments.
  12. Modify scenarios as necessary and organize for use
    Depending on the purpose of this method the scenarios should be organized and finalized.
    Case study: The comments of the trial run participants were carefully weighed and scenarios altered as appropriate.

Scenario planning can help companies to try to get a better grasp of future events and their effects on strategic variables.
The method presented here does show several drawbacks. It does leave a lot of room for interpretation and any reasoning for using exactly this process is just missing.

On the other hand I think the major advantages lie in the communication processes which are induced by using this or any similar methodology and I agree with the authors’ conclusions:

  1. It forces planners to accept and act on the fact that the future can never be exactly known. Thus, the plans resulting from the use of this technique should involve more flexibility than those drawn up to meet one set of postulated events.
  2. It serves as a tool for communication between people with very different points of view and encourages cross-fertilization of ideas.
  3. It provides a vehicle for integrating relevant technical and nontechnical factors into the planning process.
  4. It encourages the development of a structured system for monitoring trends and events of import to the organization. Thus, it aids in preventing the organization from being faced with unexpected threats and from failing to take advantage of emerging opportunities.
  5. It helps to identify the point at which important decisions will Irave to be made in the future. This should allow more time for consideration and data acquisition.


Vanston, J., Frisbie, W., Lopreato, S., & Poston, D. (1977). Alternate scenario planning Technological Forecasting and Social Change, 10 (2), 159-180 DOI: 10.1016/0040-1625(77)90043-9


Originally posted by Daniel Dumke at

My hard drive just crashed. Well, one of two I use to store all a my private media. The disks were arranged as RAID 0. And the 0 already indicates that there is zero redundancy. So the data is gone.

Sure there is a backup, so nothing is really lost. Getting up and running again still will take at least until Sunday. The first thing I did was ordering a new disk on amazon. As soon as it arrives I will have to recreate my raid and play back all of the data. A tedious and long process, since that’s something you don’t do every day…

So my lessons learnt: Never rely on a single weak link, especially if you are not at least prepared to fill the gap.

By the way. Since early 2011 I always buy the same disk by Samsung (HD204UI 2TB). And that’s the price development since then:
January, 2011: 80.39 EUR
July, 2011: 62.99 EUR
August, 2011: 60.99 EUR
June, 2012: 105.17 EUR

As you can see the price nearly doubled after the Thailand flooding.
But now let’s see what others did this week…

  • Apparently Apple is trying hard to defend its top position in supply chain rankings: AppleInsider reports that inspections have increased in number as well as in their depth. ( AppleInsider)
  • Leaders in a new category: According to Market Watch Marsh Rick Consulting has been named best supply chain risk consulting services provider. ( MarketWatch)
  • If you want to read more on Marsh, just have a look at yesterday’s post at Enterra Insights, where Stephen DeAngelis discusses a recent press release by Marsh and his stand on supply chain insurance and alternatives. ( Enterra Insights).

Enjoy your weekend!

Originally posted by Daniel Dumke at
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If people talk about disruptions and network effects within the supply chain, the associations are most often negative.
The picture of an automotive/just-in-time supply chain comes to mind, where a small screw from a distant supplier did not get delivered in time and all production processes within the whole network suddenly come to an involuntary halt.

But on the other hand there are companies profiting from these smaller and larger disruptions: competition.
To analyze these effects we have a look at the consequences of negative default dependence between suppliers. The full paper can be found here.

Default dependence and method

Empirical research on corporate defaults in the finance literature indicates that corporate defaults often cluster in time and that the default of a company is frequently affected by the defaults of other companies. […]
In the automotive industry there are several reasons why positive default correlation may exist in supplier networks. First, automotive suppliers face similar challenges, such as large and powerful customers who force suppliers constantly to cut costs and invest heavily in R&D or the volatile prices of raw materials. It is likely that the automotive suppliers have to suffer from the consequences of these challenges in a similar way or are reacting in a comparable manner to cope with them. Second, suppliers may maintain relationships with other suppli- ers and share “technical and explicit information as well as tacit information” and “work together closely, exchange ideas, and even engage in joint venture projects.” Being linked so closely may result in comparable strategic and operative actions and behavior of the supplier firms. The consequence is that decisions that lead to financial problems are likely to be taken by both suppliers that are linked through close supplier–supplier relationships.

However there are also reasons/situation in which default-events might be negatively correlated:

  • First, after a supplier default, customers might shift business to another supplier in the network.
  • Second, the default of a supplier can result in lay-offs and the competitor will be able to hire more and qualified staff.
  • Finally, due to the reduced number of alternative sources, the buying firm may become more dependent on the surviving supplier who, through the gained power, may be able to incur higher profit margins and, thus, gain in financial stability.

The authors use copula-functions.
Financial data to calculate default probabilities for a case study are derived from Datastream (Thomson Reuters). This data was used to calculate the individual default intensities.

For the worldwide 100 largest suppliers to the automotive OEMs in 2005 that were included in the Datastream database, we extracted the necessary data required for specifying and adjusting our model.

Figure 1 shows the default intensities for selected companies.

Company profiles
Figure 1: Company Characteristics (Wagner et. al, 2011)

The default dependencies were calculated using numerical results of a simulation.

Results and implications

The authors draw three conclusions from the results of their analysis.

  • First, our estimation of default intensities of selected first-tier suppliers in the automotive industry supports the concerns raised in the literature about the financial stability of automotive suppliers. Supplier default intensities above 5% are disquieting for the respective automotive OEMs.
  • Second, the simulation results depict that negative default dependence among suppliers in a supplier network has consequences for the survival probabilities of the entities in the network. The higher the individual default intensity of a supplier, the stronger the effect of negative default dependence on its survival probability after the default of the other supplier. […] for example, the portfolio with low default intensity suppliers demonstrated to increase the survival probability of the second supplier by 2.7% and the portfolio with high default intensity suppliers by 15.4% (in comparison to the independence case).
  • Third, in addition to the dependence level, the dependence structure, reflected in our model by the choice of copula, is an important factor for modeling default dependence in a supplier portfolio.

The following management implications can be given:

  • Purchasing managers should be aware that negative default dependence between suppliers may exist and take this into account for their sourcing decisions. A better understanding of the randomness and relatedness of supplier defaults internal to the supplier network can help firms to plan for uncertainty, take proactive measures to reduce risk (e.g., switch a supplier), and achieve better, less variable outcomes.
  • Firms should preferably establish relation- ships with suppliers that have low default intensities, and with suppliers that will benefit from the default of their competitors – given that the default of the competitor will not significantly shift the power in the buyer–supplier relationship


Not only surviving competitors can potentially profit from the default of its contestant, but also their clients may profit.
This research shows that interdependencies – no matter if positive or negative – have to be analyzed and should included in the decision making process.

One has to keep in mind though, that Wagner et al.‘s results heavily rely on their method to estimate the default dependencies within the supplier portfolio.
This might induce additional uncertainty in the form of model risk.


Wagner, S., Bode, C., & Koziol, P. (2011). Negative default dependence in supplier networks International Journal of Production Economics, 134 (2), 398-406 DOI: 10.1016/j.ijpe.2009.11.013

Originally posted by Daniel Dumke at

This was a slow first week, after my vacation. I am still waiting for some feedback on my dissertation. Regarding my job-hunt: I sent applications to several interesting companies and now I am looking forward to their feedback.

The following articles I found worth reading this week.

  • Short summary, with some impressions of the NOFOMA 2012 logistics conference. ( Interorganisational)
  • Scott Byrnes describes his impressions of the Gartner Supply Chain Conference in Palm Desert, CA, citing resilience as one of the major topics this year. ( Supply Chain Visibility)
  • The Guardian has an article this week on child labor in supply chains. Concluding that: “Eliminating child labour and improving conditions within our supply chains must be a collaborative process with all stakeholders taking on responsibility”. ( Guardian)
  • Andreas from SCM research writes about “Real options in supply chain management”, highlighting a study which shows potential advantages of real-option-models. Another article on this topic can be found here in the blog. ( SCM Research)

I hope enjoy your weekend.

Originally posted by Daniel Dumke at

We are back from Norway. I had a great time there. The first week stayed at a small cabin at the Vindafjord (first picture) later we visited Jotunheimen National Park (second picture), Oslo and Bergen.
Overall I was really surprised by the magnificent fjords, mountains and nice people.

Our cabin at the Vindafjord
Figure 1: Cabin at the Vindafjord

Mountains in Jotunheimen National Park
Figure 2: Landscape at the Jotunheimen National Park

There were only two longer articles I read during that time and you find the links to them below.

  • Enterra Insights discusses aspects of supply chain visibility to reduce supply chain costs and conclude: “The supply chain winners of the future may largely be the ones that have more information at their disposal, and use that information more smartly than their competitors”. ( Enterra Insights)
  • Vivek Sehgal talks about the impact of Business Strategy on the Supply Chain of the company. ( Supply Chain Musings)

Originally posted by Daniel Dumke at
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One basic assumption in risk-aware supply chain design is the notion that the design of the supply chain actually has an impact on the vulnerability of the supply chain.
This question has been analyzed about six years ago in a broad empirical study by Wagner and Bode.


The authors use a rather large sample of companies in Germany. Overall nearly 5000 supply chain professionals were asked to participate and 760 actually took part in the study.
Most sample companies had an industrial focus (72% versus service (20%) and trade (9%)).
This study is founded on a similar sample as this other study by Wagner and Bode analyzing the impact of risks on supply chain performance.


The author focus on some supply chain design variables, which supposedly increase supply chain vulnerabilities. Figure 1 shows the assumed relationship between those drivers of supply chain vulnerability and three supply chain risk categories.

The relationship between drivers of supply chain vulnerability and supply chain risk
Figure 1: Concept: Relationship between Design and Risk

The authors propose the following hypothesis, which are then tested using the empirical data:

  • H1: The higher the drivers of supply chain vulnerability, the higher the level of demand side risk a firm faces.
  • H2: The higher the drivers of supply chain vulnerability, the higher the level of supply side risk a firm faces.
  • H3: The higher the drivers of supply chain vulnerability, the higher the level of catastrophic side risk a firm faces.


The results show that all hypothesis are supported by the findings of the authors. However the design factors/vulnerabilities only explain part of the observed supply chain risks (7% for H1, 13% for H2, 3% for H3).
Demand side risk was influenced by strong customer dependence and strong supplier dependence.
Supply side risk was influenced by supplier dependence, single sourcing and global sourcing.
Lastly, catastrophic risk was impacted by the degree of global sourcing.

The authors draw the following conclusions:

First, the supply chain vulnerability variables in our model explain a rather small portion of the variance in the risk arising from demand side risk sources. It is a low but not astonishing value since the majority of the vulnerability variables focuses on the upstream supply chain. However, the results reveal that customer dependence increases demand side risk. This finding indicates that firms that are dependent on some customers are exposed to a higher risk of suffering from the detrimental effects of demand volatility and poor downstream information. This could be because of order batching or limited possibilities of demand pooling. […] This leads to the hypothesis that, beyond the investigated variables, there are several additional aspects both internal and external to the supply chain that determine a firm’s exposure to supply chain risk.

Second, risk derived from supply side risk sources is elevated by supplier dependence, single sourcing and global sourcing. Supplier dependence obviously amplifies the threat from poor quality, supply shortages, sudden demise of one of these suppliers, and poor logistics performance. Although this argumentation also applies to single sourcing, the single sourcing approach seems to be less hazardous than general dependence on some suppliers. This is because single sourcing is usually aligned with a closer relationship that might absorb some of the supply side risk.

Third, when it comes to risk from catastrophic risk sources it has to be taken into consideration that the sample data was collected in Germany which has been a very “calm” place with regard to disasters. Here, it is solely global sourcing that is a significant factor that exposes firms to higher risk from catastrophes. The implementation of a global sourcing strategy stretches the supply chain geographically which ultimately means more peril points for the information and material flow. The robustness and resilience of regional or national supply chains is usually higher. Surprisingly, the study shows that supplier dependence decreases the risk exposure to catastrophes. Again we would argue that this is because of lack in supply flexibility. Firefighting against the consequences of catastrophic events might be more successful with the ability to quickly adjust the supply.


I would argue that it is always hard to measure risk consistently in a qualitative study. People are likely to evaluate the same risk quite differently, which might lead to unclear results.
Furthermore the low impact of these specific design variables emphasizes the view that there are many more factors (internal and external) that impact the exposure to supply chain risk.


Wagner, S.M., & Bode, C. (2006). An Empirical Investigation into Supply Chain Vulnerability Experienced by German Firms Erich Schmidt Verlag, 79-96

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Agent-based supply chain models are build using small entities (agents), which might represent a single company.
Each of the agents has its own goals and rules of operation programmed into a computer. The interaction between several agents of this kind leads to a more realistic and complex behavior of the system.

There are several different schools for the quantitative analysis of supply chain risks. Simulation is one of them and agent-based models show several distinct advantages: They are both easier to understand and allow for a more complex system behavior, than other quantitative methods.

After this introduction I would like to have a look at a current agent-based supply chain model, which analyzes the effect of bankruptcies on supply chains. The full paper can be downloaded here.


The authors focus on a comprehensive view on the supply chain: several stages (horizontally and vertically) are modeled. Figure 1 shows an exemplary supply chain.

The structure of the supply chain network.
Figure 1: Exemplary Supply Chain Structure (Mizgier et al. 2012)

Each circle represents one node or agent, the connections are drawn as lines.
The model features five additional characteristics worth mentioning:

  1. Price dispersion (prices can vary between companies)
  2. Evolution of supply chain topology (links between companies can be changed, by the agents themselves)
  3. Network reconfiguration (the reconfiguration is based on the price)
  4. Production dynamics (output is determined by the invested working capital)
  5. Dynamics of costs of production (random changes to the environment every five periods, lead to changes in the cost function of the companies)

Last but not least, companies may go bankrupt if they are not able to perform their short therm debts. There are no loans.


First, the network performs as expected. During the first period turbulences can be observed. Figure 2 shows the utilization of working capital during the simulation (1 equals 100%).

Performance of the network
Figure 2: Capacity Utilization (Mizgier et al. 2012)

After 200 iterations a typical start scenario might look like figure 3.

State of the network after the test period
Figure 3: Network Structure after Initialization Period (Mizgier et al. 2012)

Starting from this state the

The firms with the best profit/cost ratio are growing and adding new suppliers, whereas the working capital of the firms whose sales price is higher than the mean price of the given stage is slowly decaying and results in the defaults of firms.

A stable state might look like figure 4.

State of the network after reaching the stable configuration.
Figure 3: Network Structure after Stabilization (Mizgier et al. 2012)

The authors deduce three implications from those results:

  • The first implication is that during the process of assessment of the company’s risk exposure, managers should keep their focus on the global structure of the supply chain network instead of being restricted to the own portfolio of suppliers and customers.
  • Secondly, as a result of the dynamics of the topology of the supply chain network, strong competition in prices and fast changing technology, even the most reliable firms should be monitored and constantly re-evaluated in terms of their production capacity and risks associated with their structure of connections.
  • Third and most important, managers should find ways to cut costs and reinvest the free cash flows in new technology of production, which will allow further cost reductions and the development of new innovative and cheaper products.


Being stuck in the supply chain can lead to negative consequences, when ripple effects cause multiple suppliers and customers to default. Furthermore, these supply chain partners might also not be the most efficient ones, and these prices affect each participating company.
All in all, a great paper, but I would have liked to read more about the authors’ efforts to validate and verify the model’s integrity.


Mizgier, K., Wagner, S., & Holyst, J. (2012). Modeling defaults of companies in multi-stage supply chain networks International Journal of Production Economics, 135 (1), 14-23 DOI: 10.1016/j.ijpe.2010.09.022

Originally posted by Daniel Dumke at

I successfully finished planing for our trip to Norway. I am really looking forward to some days off.
Now the final plans also include a hike to the Preikestolen, a wonderful rock formation at the Lysefjord.

Several articles accumulated this week in my mailbox, here we go:

  • The Operations Room analyzes the impact of the spanish banking crisis on the Airbus and Boing supply chains ( Operations Room)
  • After the consulting firm Roland Berger published some details on their SCRM approach Booz Allen Hamilton did the same and published a whitepaper on Managing Risk in Global ICT Supply Chains ( Booz Allen Hamilton)
  • For some time now I have been passively looking for supply chain risk management software, up to now with only limited success (eg. here). This week Gartner published numbers, which support the notion of a growing SCM software market. So maybe the next trend will be the inclusion of SCRM topics ( Logistics Management)
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These are the tweets from this week. You can follow me on twitter.

The next two editions will be a lot shorter due to my vacation.
Hope you enjoy your weekend.

Originally posted by Daniel Dumke at
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In theory supply chains look really nice. Some even have a serial structure with three or sometimes even only two participants.
Almost any complication to this basic theme is still the focus ongoing research, especially if risks are involved.


So this study focusses on the effects of requests to change the product design on the risk environment of the supply chain.

The core questions are:

  • RQ1. Why do certain supply chain risks occur following design change requests from customers?
  • RQ2. How do customer design changes affect supply chain risk?

Figure 1 shows the concept behind these questions. The product design change is triggered by the customer. This has effects on the supply and demand side equally and induce risks within the company and supply chain.

Conceptual research framework
Figure 1: Research Concept (Lin and Zhou, 2011)


This study uses a case study approach. And this is one of those papers, that I would recommend reading, if you are doing your own case study.

Well, first of all the documentation is really thorough and comprehensive, covering many details from one of the core sources for case study research (Yin 2009).

Secondly, it seems that execution is equally exhaustive.
Figure 2 shows the three case studies covering different supply chains for special purpose vehicles ( SPV). In the lower part some of the properties of the participating companies are detailed.

Multiple-case study
Figure 2: Characteristics of the Case Companies (Lin and Zhou, 2011)

Within each company several interviews were conducted. 20 of them more in-depth, with up to six hour of length, and another 40 shorter/focused interviews.

Of course, an interview question guideline was used to steer the interviews and several other sources were taped to support the data gathered during the interviews. Namely, secondary documentation (company information, design drafts, process files) and archival document like sales records, customer service records, organizational records.

Finally, the authors go the long way, using several trustworthiness criteria, to constitute the validity of their research.


Sometimes in research the focus seems to be much more on the methodological foundations than on the results. Well, that is for a reason: since the results should later be used by other researcher to built their own work on, so it is always good to build on a trusted and valid source.
But, as a regular reader you know, that I am at least as interested in the final results.
So, let’s have a look at them.

First, figure 3 shows the process mapping of the SPV supply chain.

Process mapping of the SPV supply chain
Figure 3: Mapping of the Special Purpose Vehicle Supply Chain (Lin and Zhou, 2011)

The double-dotted line shows the specific processes needed to handle the customer requirements with product design change, while the single-dotted lines show the normal process. According to the case studies, the potential risks might occur in several stages marked with a pointed star.

The SPV industry is a highly customized-demand market. In such a market, the SPV manufacturer always faces quickly changing customer demands. The order change rate is 10-15 percent. Most of the demanded changes are related to product design. For example, changing the requirements of the chassis (new brand or new length) and tank volume are the two most common customer requests.

The authors found the following challenges in supply chain operations:

  • Lack of design capability
    From the internal view, the most important bottleneck is lack of design capability, so manufacturers carry risk in its ability to redesign the product to meet customer requirements. Even as an important strategic partner of a “top 3” automotive company in China that has received great technical support from the relationship, manufacturer M1 itself still lacks in product design and process engineering.
  • Low level of communication
    […] Sometimes the R&D department accepts the product change via the sales department without informing the production department to check whether it has the necessary and available production capacity.
  • Supply uncertainty
    Product design change results in changing material and component requirements; thus, a shortage of materials, especially of key components, occurs as a vital risk to the manufacturers M1 and M2.
  • Unstable production plan
    Production plans are changed frequently to accommodate the customers’ changed requirements. Correspondingly, production processes must be interrupted to restart and adjust to the new designs. Hence, the pace of the assembly line is unstable, and it is impossible to set up a stable standard production process
  • Delivery delay
  • Immature regulation and policy

Furthermore, the authors analyze the risks, which were mentioned during the interviews. Figure 4 summarizes the causes and effects of different risks and mitigation approaches.

Cause effect diagram of supply chain risk in the context of product design change
Figure 4: Cause and Effects of Supply Chain Risks after Product Design Changes (click to zoom; Lin and Zhou, 2011)

The following core risks are affected by product design changes:

  • Internal risk dimension
    • R&D risk
    • Production risk
    • Planning risk
    • Information risk
    • Organizational risk
  • External risk dimension
    • Supply risk
    • Delivery risk
    • Policy risk

The authors conclude that: “the dynamics of product design have significant impacts on the operations of the whole supply chain, including R&D, production, planning, information, organizational structure, supply, delivery, and policy”


The authors already mention it: This research not only can prove useful for the manufacturer and its suppliers which are affected by the design changes itself. But this can also be useful for the customer itself, which then can estimate and weigh the risks connected to any changes from an original product design.


Lin, Y., & Zhou, L. (2011). The impacts of product design changes on supply chain risk: a case study International Journal of Physical Distribution & Logistics Management, 41 (2), 162-186 DOI: 10.1108/09600031111118549


Originally posted by Daniel Dumke at

This week was filled with preparations for our summer vacation. This year we are going to Norway. We will start start in Bergen on the west coast and for the first week stay in a small vacation home nearby Sand directly at the Fjord. Later on we will drive to Oslo (east coast) passing Hardangervidda National Park. On our way back we will use a more northern route, but that’s still in planning.

This week I found three really nice articles for you to read. Have a look!

  • The resource-based view supports the notion that a company can generate competitive advantages from the resources it controls. Andreas Wieland points to an article which discusses the question if a supply chain can be viewed as a company’s asset as well. ( SCM Research)
  • Enterra Insights talks about the obstacles to thorough supply chain risk analyses. Despite the growing need for a more rigorous risk management approach many companies get overwhelmed by the complexities involved. ( Enterra Insights)
  • Infosys put a short presentation online, covering the basic risk concepts included in their SCRM Product Suite. ( Infosys)

Enjoy your weekend!

Originally posted by Daniel Dumke at
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Just recently I took a closer look at some aspects of supply chain risk management in the automotive supply chain. Within limits insights gained from this industry could also be transferred to other examples.

Today I review an early work focussing on another manufacturing industry: the UK aerospace manufacturers.


In 2003 Haywood and Peck published their findings of a case study. These covered the foundations of how the companies understand of supply chain risk management. They also reported on some of the risk measures used by the participating companies.

All in all 47 semi-structured interviews were conducted with managers of differing levels in the aerospace supply chain.

This purposive sampling allowed multiple levels of the supply chain networks to be included in the study, ranging from the focal firm’s customer (purchasing organisations for the armed forces of national governments), through two tiers of suppliers above the Prime. In addition, input came from two industry bodies representing small and medium enterprises ( SMEs) nestling in the higher reaches of the supply networks. It was clear however that at least six or seven tiers existed upstream of the Prime Contractor and downstream the final consumers (pilots and other users) remained unvisited.

As you can see the authors were quite blunt about the limitations of their endeavor to analyze the complete network. Though this constraint should not be taken too seriously, since this study aimed for a preliminary sketch of the status quo only.

Key findings: Risk sources

The first findings come from the assessment of the risk sources faced by the interviewees.

First, the respondents did not deal with either the precise geographical location of a problem or on the impact of other ‘external’ sources of risks. […]
In fact several of the managers interviewed related the sources of risk directly back to the Critical Success Factors ( CSFs) for the focal firm’s Strategic Supplier and Commodity Management processes: Cost Focussed Decisions; Extreme Quality/Performance Requirements; Delivery Schedule Adherence; Customer-Supplier Relationships. […]
Nevertheless, the examples put forward by interviewees highlighted tensions between them. The link between interviewees’ perceptions of ‘sources of risk’ and process CSFs was upheld by members of the industry focus groups involved in the validation exercise. […]
The second theme to emerge was that managers frequently defined a source of risk with reference to acknowledged or perceived constraints imposed by the nature of the product and the structure of the industry.

Furthermore, many interviewees acknowledged that their supply chain is most vulnerable during times of change, but also that change is a constant state in their supply chain activities.

Key findings: Tools

The second stream of findings analyzes the tools and techniques, which were employed by the companies.
The authors therefore divide the realm of supply chain management into three tool categories: Supply Chain Planning, Supply Chain Management and Supply Chain Change Management (figure 1).

The Spectrum of Supply Chain Management Activity
Figure 1: Continuum of Supply Chain Management Activities (From Strategic to Operational; Haywood and Peck, 2003)

The extreme left of the spectrum is occupied by pure supply chain planning, which in an ‘ideal world’ would be unencumbered by the legacy commitments of existing production facilities or supplier contracts. The right by pure supply chain management actives. These are the day-to-day activities undertaken in the management of a mature established supply chain.

Figure 2 summarizes the tools used by or considered useful (marked in italics), by the interviewed managers.

Summary of Tools and Techniques
Figure 2: Selected Measures to mitigate Supply Chain Risks (Haywood and Peck, 2003; click to zoom)

However, it is important to recognise that Figure 2 represents only a summary of what is or could be in use somewhere in the network.
[Also it should be recognized, that] other tools and mitigation techniques again suggest contradictory requirements. For example, to mitigate cost-related risks, lean manufacturing techniques were being used (Set 5), while elsewhere someone is using inventory, capacity and capability buffers on a regular or temporary basis to mitigate delivery or schedule adherence problems (Set 7 and 11).

Key findings: Implementation

Lastly, the authors took a look at the obstacles preventing implementation of the tools.
Three key factors were unveiled.

  • The first was staff training, there was quite a widespread recognition that existing tools could be much more effective if implemented correctly.
  • The second was widespread confusion over terminology.
    The research revealed that there was absence of a common understanding of the scope or extent of supply chain risk management, muc h of it relating to confusing and contradictory interpretations of ‘supply chain’.
  • The third issue was visibility.

Based on the findings the authors developed three methods to help improve implementation.

  • Method 1, a ‘go it alone’ option was motivated by the possibility of achieving competitive advantage over rival organisations through exclusive or advanced identification of sources of risk. For example, if the consequences of an anticipated event were expected to disrupt others in the same industry sector, an organisation might gain advantage by simply improving its tolerance relative to its competitors.
  • The second method tabled was a more limited audit encompassing the focal firm, its immediate customers and suppliers. The method involves organisations acting collaboratively, in interlocking risk management relationships to produce overlapping information flows all along the supply chains. Such an approach would allow organisations to identify relevant sources of risk within their locus of control or immediate supply chain vicinity and enjoy the confidence that others were doing the same.
  • Method 3 was an extension of Method 2, based on interviewees’ suggestions that the effectiveness of their current management tools would be improved by the introduction of a shared data environment. It was felt that this would significantly reduce the commercial risks attached to sub-optimal supply chain performance. The majority of interviewees considered Method 3 to be sound in principle. It reflected the frequently expressed view that improved sharing of data would lead to consequential improvements in profitability and facilitate the continuous improvement practices that contribute to longer term supply chain health.


This research gives an glimpse into the early stages of risk management in supply chains in the UK around the turn of the millennium.
For many companies and supply chains the detected problems still exist.
Two tasks still remain: First, opening the eyes of decision makers to include a trans-corporate view on risks and embrace supply chain strategies to battle supply chain risks. Ergo, applying holistic system thinking to system problems.

Second, finding ways to circumvent the implementation obstacles. How can risks be reduced without compromising the competitiveness and autonomy of the focal company?


Haywood, M., & Peck, H. (2003). Improving the Management of Supply Chain Vulnerability in UK Aerospace Manufacturing Proceedings of the first EUROMA/POMS Conference, 2, 121-130

Originally posted by Daniel Dumke at

This week I started the first official round of talks with potential future employers.
Overall the meeting went very well, there were however two particular research related questions, I wanted to go into here.
In two unrelated instances the senior risk manager indicated that he had strong doubts about the possible congruence of research and practice; and later, if one could really believe that “models” are even applicable to any real-life situation. Probably those questions were meant to provoke me a little, but I am not sure.

I would like the chance to stress my point of view again here:

  1. I think in scientific research the selection of the methodology or approach is usually guided more by the needs of the research subject than by the efficiency restrictions set in practice. So of course, a scientific study may very well contain all aspects which would also be part of the same task in practice.
    Let me give you an example: In one part of my dissertation thesis I analyzed the structure of the supply chain risk management processes and strategies used to reduce supply chain risks within several companies. Based on the different environments of the questioned companies, recommendations were given on the optimal design of the processes and strategies.
  2. Models of a given system (e.g. supply chain) have to be tailored both to the system in focus and the case of application. Models are applied in a variety of industries: Banking shows some of the weaknesses of relying too much on models which are too abstract. On the other hand in logistics, production and supply chain design models are used successfully in everything from route-, shop-floor or location-planning.

Right now I am sitting on a train on my way back from Stuttgart, listening to Philip Glass. I am looking forward to two days in Berlin, visiting my former roommate.
But now, let’s have a look at what was worth reading this week.

  • First off, Forbes discusses the question “Can Your Business Survive the Butterfly Effect?” ( Forbes)
    We’re seeing a growing interest from companies who are looking for ways to leverage these technologies and the social aspects of business networks to predict supplier risk and help improve supplier performance across the n-tier supply chain.
  • Furthermore Tom Groenfeldt presents supply chain risks from the point of view of an insurer ( Zurich Financial). ( Forbes)

Hope you have a nice weekend.

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If you think about it. Postponement is one of the more involving strategies available in supply chain management. At least from a design perspective, postponement requires changes to the value-generation process, which may comprise several echelons within the supply chain.

The paper I review today analyzed the implementation of postponement strategies in China and suggests factors to help with the decision which kind of postponement to select.

Types of postponement and its determinants

Figure 1 shows a summary of different types of postponement strategies, found in literature.
It can be defined “as a strategy that changes the differentiation of goods (form, identity and inventory location) to as late a time as possible.”

Today researchers view postponement differently. Van Hoek (2001) views it as an organizational concept whereby some of the activities in the supply chain are not performed until customer orders are received.

The complement of postponement is speculation, “which means changing form and moving goods to inventories as early as possible to reduce the cost of supply chain.”

Types of postponement
Figure 1: Different Postponement Strategies (Yeung et al., 2007)

Several factors affect the decision on which type of strategy to use. Other researchers already found the following determinants (beside others):

  1. technology and process characteristics (feasible to decouple primary and postponed operations, limited complexity of customizing operations, modular product designs, and sourcing from multiple locations);
  2. product characteristics (high commonality of modules, specific formulation of products, specific peripherals, high value density of products and product cube and/or weight increases through customization); and
  3. market characteristics (short product life cycle, high sales fluctuations, short and reliable lead times, price competition and varied markets and customers).


Beside the literature review, of which some of the results are summarized above, the authors use a grounded theory approach to come to their conclusions.
This method comprises several semi-structured interviews with senior executives. The sample companies were taken from the Pearl River Delta ( PRD) a region within the Guangdong province bordering Hong Kong.
Overall the interviews with eight companies were used for the grounded theory. The characteristics of the sample companies are presented in figure 2

Overview of sample firms
Figure 2: Sample Companies and their Supply Chains (Yeung et al., 2007)

Cross-case analysis

In figure 3 the results of three (of eight) companies are compared.
Cross-case comparisons
Figure 3: Cross-Case Comparison (extract; Yeung et al., 2007)

The supply chain structure is characterized by a four letter acronym (second column in figure 3):
The first two letters refer to the supply side the second pair to the demand side.
Of those pairs the first letter (O/F) refers to the market type: *o*ligarch or *f*ree-market.
And the second letter (C/L) refers to the closeness of the actors: *c*lose or *l*oose.


From these results the authors draw the following propositions:

P1. When a supply chain has a balanced structure, it should use speculation or production postponement.

In the balanced supply chain structure, no single actor is significantly more powerful than any other actor. In order not be “locked” in by a specific partner and losing business opportunities and/or bargaining power, a company will not tailor their processes for a specific partner. However, the key concept of postponement is to produce based on actual orders instead of forecasts, and this requires a close relationship between partners.

P2. When the supply chain has an unbalanced structure, it should use purchasing postponement or product development postponement.

The unbalanced supply chain is characterized by a leading company who has more power than other companies in the supply chain. In order to improve efficiency and provide a high service level, the leading company often demands other companies to tailor their production process and share information. As such, it is easier to build close relationships in an unbalanced structure than it is in a balanced one. This makes high degree postponement possible and suitable.

Figure 4 shows the summary of the strategic implications.
Classification of cases
Figure 4: Strategy Selection based on Supply Chain Structure and Information Sharing (Yeung et al., 2007)


First the ugly:
Key to a grounded theory approach in accordance with Strauss and Corbin (as the authors want to do) is the number of cases used. This number has to be determined by the so-called point of theoretical saturation. This means that the researcher only stops once the last case(s) did not produce any new insights. A typical number of interviews for a grounded theory would be between twenty and thirty.
In this case the authors set themselves an artificial limit of about 7 cases. This is actually often used in case-study research, which is another research methodology. But in case study research one usually taps on several other data sources to triangulate and validate the data.
To conclude, I really do not know what method the authors used. And therefore the validity of the study suffers.

Second the good:
Nonetheless figure 4 can be used as a guideline to select from different types of postponement strategies depending on the supply chain characteristics. It should just be used with a certain wariness.


Yeung, J. H. Y., Selen, W., Deming, Z., & Min, Z. (2007). Postponement strategy from a supply chain perspective: cases from China International Journal of Physical Distribution & Logistics Management, 37 (4), 331-356 DOI: 10.1108/09600030710752532


Originally posted by Daniel Dumke at

So, yet another week gone by. Taking advantage of labor day on Tuesday my wife and did a bicycle tour to Copenhagen and had a great time on the trip and in the city. Have a look at the pictures if you like to see some shots of the city.

Copenhagen: Churchhill Park Churchhill Park Copenhagen: Kastellet Kastellet Copenhagen: View to the Baltic Sea View to the Baltic Sea

Back to business. These are my favorite articles related to supply chain management of this week.

  • The Financial Post asks: “Does Asia really need to be part of your supply chain strategy?”. Supply chain professor David Simchi-Levi discusses some of the drawbacks of far-away manufacturing and the potential shift towards a more local approach. The article is based on another article published in the MIT Sloan Management Review. ( Financial Post)
  • Zurich Financial highlights some details of an earlier study on supply chain risks focussed on Australian companies. ( Zurich Australia)

Enjoy your weekend!


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When it comes to supply chain management some positions within the network have better chances of fighting supply chain risks, due to structural and negotiating-power-related issues.

In this case the focus is on a supplier of a automotive OEM. Natural hedging, as defined below, is the core strategy analyzed in this study.

Natural hedging

The author utilizes a literature review to found his conceptual approach.
He defines natural hedging as “an instrument of real economical risk management, where transactions are hedged through real economic counter deals.”
The term “natural” is seen as a contrast to immaterial hedging using financial derivatives.

This strategy can be employed to mitigate price risk of commodities.

Theoretical case

The author develops the following theoretical case study with three echelons: tier 2 supplier, tier 1 supplier (focal company) and the OEM.
Tier 2 supplier is located within a different currency area.
In the short run there are no substitute products available for the OEM and vice-versa there is no other demand for the tier 1 supplier than the OEM.

For the tier 1 supplier the following risks can be observed:

  • Owing to relatively small purchase quantities, a potential risk of unavailability exists for the SME-supplier. This could probably be expected if the Tier 2-commodity supplier has capacity constraints and thus prefers to supply larger customers.
  • Because of volatile commodity prices on the world market, the SME-supplier faces a price risk for the required raw materials. An adequate hedge of single components with “classical” financial derivatives is difficult, due to limited management capacities and lack of know-how. In addition, respective fees for listed hedges hamper an economic execution of futures or options contracts.
  • Continuous fluctuations on the derivative markets, as well as exclusive activities in currency area B on the purchasing side, and on the sales side in currency area A, lead to a currency risk for the SME-supplier. Cost-intensive development of currency management or billable usage of hedging instruments prevents an economic reduction of currency risks.

The OEM on the other hand also faces risks:

  • The SME-supplier’s accumulated risks could lead to non-availability of input goods for the OEM, due to supply bottlenecks or even insolvency. This would trigger unemployment, damage the company’s image or force the award of supplementary grants, in order to finance damage limitation activities.
  • Like the supplier, the OEM is exposed to many commodity price and currency risks. It does, however, possess larger resources to deal with single risk sources within the scope of supply chain risk management.

The flow of goods and money in the initial situation is displayed in figure 1.

Initial situation of the supplier-buyer-relation in a supply chain without natural hedging
Figure 1: Case Study Supply Chain (Hofmann, 2011)

Figure 2 shows the implementation of a financial hedge. If the OEM also has end-customers in the currency area B, it would be possible to have the OEM directly pay the tier 2 supplier in currency B using the money obtained by the customers.

Natural hedging in supply chains with a financial component - financial hedge
Figure 2: Natural Hedge using an purely Financial Angle (Hofmann, 2011)

In figure 3 a natural hedge is conducted which focusses on a re-design of the supply chain structure:

Natural hedging in supply chains with a physical component - physical hedge
Figure 3: Natural Hedge using a Physical Angle (Hofmann, 2011)

The OEM shall (for now) not be active in the currency area B. Nonetheless, it takes over currency risk and pays the Tier 2-commodity supplier directly in the respective currency. The flow of materials is also “reorganized and not carried out through the Tier 1-supplier, but initially through the OEM. This alternative, which corresponds to a “vertical purchasing cooperation” or a centralized purchasing approach on the network level […]. Due to the modified flows of materials, it is called “physical component of natural hedging in supply chains” or for short: “physical hedge”. In this version, the OEM carries the sole supply risk for purchased commodities.

Overall, the risk management costs in a supply chain section can be reduced through die natural hedging approach on the network level, since the costs to hedge single risks arc higher for one actor than the costs for harmonized hedging of bundled risks.


Beside this theoretical foundation the author calculates an example with figures for the steel-price-fluctuations in 2008.
The following advantages can be summarized (figure 4):

Supply chain situation without and with natural hedging
Figure 4: Advantages of Natural Hedging for the Stakeholders (Hofmann, 2011)

The author prescribes the following process to implement the natural hedging.

  1. Preparation of managerial prerequisites, as well as examination of contractual and legal framework.
  2. Business model decision and concept evaluation.
  3. Ramp-up and organizational integration.
  4. Performance measurement of results.

The following issues should be considered:

  • Framework contract model. The OEM signs the contract with the pre-material Tier 2-suppliers. Part of the framework contract is usually a quantity purchasing structure, serving as a target figure for a certain amount of time.
  • Coaching model. The OEM takes on the role of the “purchasing advisor”, supplying his SME-suppliers with information about purchasing sources and prices of the needed raw and prc-material, as well as financing alternatives.
  • Trade model. Within this resale or buy-sell approach, the OEM is the broker for prc-material. Thereby, he typically waits to purchase from the commodity Tier 2-supplier until an order from the Tier 1-supplier-basis comes in (order pass-dirough).
  • Procurement service provider model. The use of a procurement service provider constitutes the intersection point between the supplier and his assortment and the OEM. The OEM signs a framework contract with the service provider about die purchase of materials or product groups. This could also include financial aspects (e.g. prc-financing conditions or payment terms for the Tier 1-suppliers).
  • Marketplace model. Within such an “infomediary” model, the OEM initiates a platform (often a web-based E- marketplacc), through which suppliers can mutually access pre-material suppliers or pre-material offers. This model could also include payment processing in the
    supply chain.


Not only natural disasters pose risks to supply chains. Also ordinary price changes can pose a threat to the profitability of a company.
But those risks have been on the risk management agenda for quite some time now. Still, supply chain risk management enables companies to handle some risks differently and natural hedging as described here may be one option.

Even though the empirical support for this strategy presented in this paper is quite weak, it should give food for thought and using some concrete figures should help with the decision if and how such a strategy might help your company, be it OEM or supplier.


Hofmann, E. (2011). Natural hedging as a risk prophylaxis and supplier financing instrument in automotive supply chains Supply Chain Management: An International Journal, 16 (2), 128-141 DOI: 10.1108/13598541111115374

Originally posted by Daniel Dumke at