case study

Management of Vulnerabilities in the UK Aerospace Industry

Daniel Dumke — Mon, 14 May 2012 13:40:33 +0000

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.

Method

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).

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.

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.

Conclusion

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?

Reference:

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

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Case Study and Conference - This Week in Supply Chain Management (14 / 2012)

Daniel Dumke — Fri, 06 Apr 2012 18:46:46 +0000

This week I received my first full-version feedback on my PhD-thesis. A big thanks to my reviewer! Luckily I do not have too many adjustments to make, so I will use time during the easter holidays to commit the changes. I hope to be done by Tuesday, and I already got an appointment with my Professor on Wednesday, to officially hand over the dissertation.

Articles

The Bangkok Post rethinks the supply chain and supplies a few measures to reduce risks. (Bangkok Post)
Greg Duncan explores a real life case study of two U.S.-based manufacturing companies and the differences in the impact of last years tsunami in Japan. (Risk Management Magazine)

Conference – sponsored message

IQPC’s Supply Chain Risk Management Summit is set to take place May 14 to 16, 2012 in Boston. This event will provide you with the tools and techniques you need to ensure business continuity, implement risk mitigation strategies and minimize financial implications of supply chain glitches. Other topics to be covered include emergency reaction plans, protection against currency fluctuation, and cumulative energy prices.

Take advantage of our early bird registration by calling IQPC now on 1-800-882-8684, email info@iqpc.com or visit www.SupplyChainRiskMgmt.com for more information.

Update: This conference has been canceled.

Already tweeted

These are the tweets from this week. You can follow me on twitter.

RT @KennionGroup: Sourcemap, an MIT-Incubated Startup, Offers Solution to National Security Risk Posed by IT Supply Chain http://t.co/5s
The Dirty Little Secret Of Overnight Successes | Fast Company http://t.co/6M4cVXaK
PwC Finds “Critical” Need for Younger Supply Chain Managers – Article from Supply Chain Management Review http://t.co/bbDQb1yz
How Strategic Risk Management Improves a Company’s Competitive Standing http://t.co/3IP5If3O
IPCC Climate Change Report Highlights Managing the Risks of Extreme Events and Disasters http://t.co/WLF2GLEM

Enjoy your weekend!

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Hedging against Disruptions with ripple Effects

Daniel Dumke — Mon, 02 Jan 2012 17:10:00 +0000

I have read several articles by Mark Daskin (also reviewed another one here). So with him on the author list of today’s paper I think one can expect a clearcut research question, some kind of mathematical model, a fitting solution method and a definite answer to the underling problem. Well, let’s have a look!

Topic and method

The goal of this research is to analyze disruptions with a regional effect (as opposed to local, single facility disruptions). An example for a regional disruption may be an earthquake, storms or floods. The results should show how to better handle disruptions which are not locally limited and exhibit contagious tendencies.

The authors approach the problem by modeling three separate sub-models, namely the Defender Problem, the Attacker Problem and the User Problem.
The basic assumptions are:

each facility has a fixed capacity,
the capacity is affected by a disruption,
a defense strategy can be defined for selected facilities, it protects the facilities against the disruption

Defender Problem:
“The objective of the defender is to minimize the impact of the disruption by optimally choosing Q facilities to protect. Constraints states that no partial protection of a facility is possible.”

Attacker Problem:
“The objective of this program is to strike the system as hard as possible by identifying the worst-case set of exactly R facilities chosen among those which are not protected (6).2 Finally, no partial interdiction is possible.”

User Problem:
“The user level problem deals with the minimum cost assignment of customer demands to facilities. The total cost is given by the cost for the service provided, plus the penalties paid for the demand which is not met.”

Correlation Matrix:
“The correlation matrix represents the interdependence among the facilities when an attack occurs or, in other words, the extent to which other facilities are affected when a target facility is disrupted.

Figure 1: Map of the 2009 earthquake in L’Aquila, Italy (Liberatore, et al. 2012; USGS)

Solution and Case

The authors develop a solution method, to optimize the given problem.
Data from the 2009 earthquake in L’Aquila, Italy was used to test the model.
Figure 1 shows a map of the area.

The dataset represents the Abruzzo region, a seismically active region of Italy, where L’Aquila is located. The set of the demand nodes, N, includes all the 305 towns and cities in the region and the associated demands, ai, correspond to the number of inhabitants as at beginning of April 2009 expressed in thousands of citizens. The set of initial facilities, F, represents the 35 hospitals of the region.

The model is solved for different parameters in two steps: first calculating the optimal defense program and second calculating the “optimal” attack, also calculating the incurred cost and correlated disruptions.

Figure 2 shows the example for two different solutions:
The buildings represent the available hospitals, stars mark the defended locations and the colored circles represent the disruption, which causes the worst effects.

Figure 2: Two solution Results (a and b). Buildings representing Hospitals, Stars protected Locations, Circles worst possible Disruption Effects (Liberatore, et al. 2012)

Conclusion

The attacker (in this case an earthquake) always looks for the place where it can hit hardest, so the focus is on the worst case scenario: How can one fortify a system so that even in the worst case it still performs at a desired level?

But keeping that in mind also leads to the conclusion that this system might not be for everyone: What if the earthquake does not hit at the worst point? Or not at all? As a rule of thumb, I would say the investments suggested by this model are magnitudes higher than those of an “optimal” (in terms of money) solution. So when do you use such a model?
I think there are two cases: Either if one is dealing with critical infrastructure, like water, food or possibly military installations and (I know its related) if one has to decide how to safe lives: As in the case study itself, where the optimal hospital location has to be found.

Reference:

Liberatore, F., Scaparra, M.P., & Daskin, M.S. (2012). Hedging against disruptions with ripple effects in location analysis Omega, 40 (1), 21-30

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Supply Risk Management from a Small Company's Perspective

Daniel Dumke — Mon, 14 Nov 2011 15:53:00 +0000

This study takes a closer look at supply risk management, but this time from the perspective of several small companies. This article tries to answer the questions what risks small company owners (SCOs) see and how SCOs mitigate those risks.

Method

A case study with eleven small companies was conducted. The companies had between 1 and 12 employees. Overall 26 interviews were conducted (90 minutes on average). In addition, two seminars were held, to present the preliminary results and discuss the findings. The seminars were also used to generate additional data and validate existing results.

Informants rarely used terms such as supply risk, risk management, probability reduction, supply chain or even purchasing. [… So] Instead of forcing risk management terminology upon informants, possibly provoking misunderstandings and incomplete accounts, the idea was to let the SCOs provide rich accounts of their purchasing and SCM practices in layman’s terms. In the dialogue information was sought out that allowed plausible interpretations of supply risk management practices.

Figure 1 summarizes some facts about the companies.

Figure 1: Facts on the Case Study Companies (Ellegaard, 2008; click to enlarge)

Risk mitigation approaches

From literature the author develops three types of supply risk management / mitigation activities, namely: increased knowledge, reduced probability and reduced impact (figure 2).

Figure 2: Risk Management Alternatives (Ellegaard, 2008)

Knowledge

Knowledge increasing practices were infrequent among the studied SCOs. They spend limited time and resources actively acquiring knowledge about suppliers and supply markets and therefore possessed limited information […]. Only one SCO interacted with suppliers often.

Probability reduction

Probability reduction had the highest priority in these companies. Elimination of severe risks formed the backbone of SCO practices. […] In order to eliminate certain severe risks, the SCOs sourced locally, exhibited source loyalty, and were careful not to reveal proprietary product knowledge to suppliers.

Effect reduction

None of the SCOs held reserve capacity and practiced mainly single sourcing, with the aim of tying up as few resources as possible. The very limited reserves left the SCOs quite vulnerable to certain types of risks. Any specific events with the potential to obstruct delivery capabilities of suppliers, such as a fire, take-over, bankruptcy, up-stream material shortages etc. could bring SCO production to a halt.

All results are summarized in figure 3.

Figure 3: Supply Risk Mitigation Approaches (Ellegaard, 2008; click to enlarge)

Lessons learned

Despite the autodidact and informal purchasing practices of

the studied SCOs, there may be much to learn from these practices, even for state-of-the-art purchasing/SCM departments. The SCOs specialised in a few supply risk management practices that seemed to complement each other well. The study suggests that effective supply risk management is not only about adopting a wide range of sophisticated risk reduction practices. The challenge may be more connected to finding the right mix of practices, which fits the available resources and is sufficient to secure against supply risks. Supply chain managers should realise that:

different supply risk management practices require different levels of expertise and resources;

only a limited number of potential supply risk management practices may be necessary; and

supply risk management means adopting the exact mix of practices that provides security.

Conclusion

This study provides some missing insights into risk management practices of small enterprises. As the author, I do think that there are still things even larger companies can learn from their mitigation strategies: Prioritization and focus of risk management activities which deem to be most effective with the given resources may be one of those.

Reference:

Ellegaard, C. (2008). Supply risk management in a small company perspective Supply Chain Management: An International Journal, 13 (6), 425-434 DOI: 10.1108/13598540810905688

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Supply Chain Flexibility in an uncertain Environment: exploratory Findings from Five Case Studies

Daniel Dumke — Mon, 07 Nov 2011 12:47:00 +0000

This is another look at flexibility strategies to reduce uncertainty in supply chains. This time from the point of view of five Chinese companies in the apparel industry.

Method

The authors use a case study to “illustrate and examine the different flexibility strategies adopted by supply chain participants as a result of different environmental uncertainties.”
The five companies cover different parts of the apparel supply chain. A garment and a fabric manufacturer (companies A and E, respectively), two trading companies (C and D) and a brand company (B). This diverse sample should enable the authors to make more general deductions from the generated data.
Figure 1 shows some relevant background information for the companies.

Figure 1: Case Study Companies (Yi et al., 2011; click to enlarge)

Results

The first questions revolved around the perceived uncertainties experienced by the participants. All companies mentioned that emergent orders, uncertainties about material cost and the aggressiveness of the competition are perceived as major uncertainties (figure 2).

Figure 2: Perceived Uncertainties by the Companies (Yi et al., 2011; click to enlarge)

Several different supply chain strategies were employed, a summary is displayed in figure 3.

Figure 3: Flexibility Strategies employed (Yi et al., 2011; click to enlarge)

The authors especially wanted to highlight the influence of different environmental aspects on the chosen strategies. No pattern emerged when analyzing which flexibility strategies are used for which uncertainties.
So next the authors examined the impact of the general level of uncertainty experienced by the companies and compared it with the supply chain flexibility level chosen.
The authors came up with a matrix (figure 4). Where they contrast SC uncertainty and flexibility. Companies D and B find themselves in the conservative corner while E, C and A employ a high level of flexibility to combat the uncertainties. From the interviews the authors also deducted the future positions of the companies A and B, which are indicated as A’ and B’.

Figure 4: Supply Chain Flexibility vs. Uncertainty (Yi et al., 2011)

Next the authors discuss their findings and reach four conclusions:

A low level of uncertainty in the supply chain leads to the adoption of a conservative flexibility strategy.
A high level of uncertainty in the supply chain leads to the adoption of an agile flexibility strategy.
An aggressive flexibility strategy can be proactively adopted through restructuring a firm’s operating system to reduce environmental uncertainties.
An aggressive flexibility strategy can be proactively adopted through creating new opportunities to improve a firm’s supply chain flexibility.

Conclusion

I like case study research, since usually you can gain some really genuine and new insights, in this case: What are other companies doing to contain uncertainty and how are they employing flexibility for that?

In this case I liked the paper a lot as well… up to the matrix. I don’t like matrices where the axes are not independent, because that’s not how you generate a matrix. Take the Growth-Share-Matrix, where you have the axis market growth and market share. The one is dependent on the market and the other on one company’s share in it. Relation to one another: Independent.
Here we have uncertainty on one axis and a strategy to reduce uncertainty on the other. So of course most companies would lie somewhere in the middle. So there is not much to learn from it. Of course there is not a one-to-one relationship, but anyway.

I had several more points to complain (number of interviews also only five, conclusions drawn are directly linked to their flawed matrix-framework and no quantitative measures to assess the flexibility and uncertainty levels).
But I still think the strategies mentioned from the interviews are still worth considering when choosing your own strategies.

Reference:

Yi, C.Y., Ngai, E.W.T., & Moon, K.-L. (2011). Supply chain flexibility in an uncertain environment: exploratory findings from five case studies Supply Chain Management: An International Journal, 16 (4), 271-283

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Managing Supply Chain Disruptions in the Chemical Industry

Daniel Dumke — Wed, 14 Sep 2011 17:19:00 +0000

This is already my second article (click here for the first) about managing supply chain risks in the chemical industry. This time by Paul R. Kleindorfer and Germaine H. Saad from Wharton and the Widener University. But this industry is quite interesting since it has to withstand a multitude of risks, so let’s get right to business:

Goal

As the title indicates: the authors focus on risks from disruptions to normal activities and not the omnipresent risk of coordinating supply and demand.
The authors aim to achieve three goals:

Development of a conceptual framework for risk assessment and mitigation
Analyze accident history from the six years between 1995 and 2000
Derive implications for the design of management systems to cope with supply chain disruptions

Figure 1: Risk Management Process in the Extended Supply Chain (click to enlarge; Kleindorfer and Saad, 2005)

Literature analysis

The authors use the SAM method, where the goal is first to analyze the risk S ources, then A ssess the risks and find the right M itigation strategies.
The authors first investigate the SAM process using literature analysis and conclude with the process depicted in figure 1 and a four step process to manage disruption risks:

“Obtain senior management understanding and approval, and set up organizational responsibilities for managing the Disruption Risk Management process.”
“Identify key processes that are likely to be affected by disruptions and characterize the facilities, assets, and human populations that may be affected.”
“Traditional risk management is then undertaken for each key process to identify vulnerabilities, triggers for these vulnerabilities, likelihood of occurrence, and mitigation and risk transfer activities.”
“Reporting, periodic auditing, management, and legal reviews of implementation plans and on-going results (e.g., of near-miss management and other disruption risks) complete the business process for disruption risk management.”

Case study chemical industry

The further analysis of disruption risk management is done using a case study approach. The authors used a database with access to accident activities in the chemical industry during the time between 1995 and 2000. Sources were natural hazards, equipment or human failure and sabotage.

The framework depicted in figure 2 was used as a basis for the analysis.

Figure 2: Research Framework for the Analysis of the Chemical Industry (Kleindorfer and Saad, 2005)

Results

Kleindorfer and Saad conclude that, “two key dimensions emerge as fundamental in guiding management practice of disruption risk in supply chains:”

The first dimension consists of strategies and actions aiming at reducing the frequency and severity of risks faced, at both the firm level and across the supply chain. The second element focuses on increasing the capacity of supply chain participants (whether a separate firm or a subsidiary facility) to sustain/absorb more risk, without serious negative impacts, or major operational disruptions.

Furthermore in the chemical industry special care has to be taken to include the stakeholders, like regulators or the employees in mitigation activities.

Lastly, the authors state two conditions which have to be met to ensure effective implementation of risk management measures:

Condition C1. The approaches used to mitigate disruption risks must “fit” the characteristics and needs of the underlying decision environment. Different supply chain environments will give rise to different approaches to assessment and mitigation. Even within a given sector such as mass retailers with global supply chains, the approaches taken by different companies will be different, given their differences in corporate culture and their methods of managing their supply chains. In the business of disruption risk management, one size will definitely not fit all.

Condition C2. Trust, information and continuing profitability are the basic glue that makes supply chain partnerships a reality. Continuous coordination, cooperation, and collaboration among supply chain partners are needed for risk avoidance, reduction, and mitigation such that the value and benefits generated are maximized and shared fairly. Different contractual and incentive schemes are now emerging as practical means toward this end. Linking risk assessment and risk management to identify vulnerabilities and opportunities for cost-effective mitigation is the first step in providing a rational basis for individual and group action among supply chain partners. Random investments or shots in the dark that do not properly account for the interdependencies across the supply chain will ultimately waste resources and destroy trust.

Conclusion

The authors already admit that the data used for their case study is based on a facility level. These facilities are of course part of the supply chain, but one can pose the question if the results are really relevant for supply chain risk management.

Moreover, one has to differentiate between supply chain security and supply chain disruptions. At least from my practical experience especially in the chemical industry facility security has played a major role since many decades and is deeply rooted in the companies themselves. Supply chain risk management on the other hand is a new approach and very much separated from it. So for a paper on exactly this topic I am missing a discussion of the question how these aspects should be integrated.

Reference:

Kleindorfer, P.R., & Saad, G.H. (2005). Managing Disruption Risks in Supply Chains Production and Operations Management, 14 (1), 53-68

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Improving Performance in Food Supply Chains by Reducing Uncertainty

Daniel Dumke — Mon, 12 Sep 2011 15:51:00 +0000

Today’s article is from the late 90s, but sets a great example for research methodology in supply chain risk management. But don’t worry, I will focus on the results, since they’re very interesting as well. The objective of today’s article (Supply Chain Management in Food Chains: Improving Performance by Reducing Uncertainty) is to show strategies (here called principles) to reduce uncertainty, and at the same time show the beneficial effects of reduced uncertainty.

Methods

Three methods were deployed to ensure the validity of the results. Based on a case study (1) of a chilled salads supply chain sources of uncertainty were generated and improvement principles designed. The analysis of the case study’s processes was also used to feed into a simulation model (2) of the supply chain, which was validated using (another) pilot study (3).
The approach is shown in figure 1 and is meant to ensure that the results presented below are worth reading.

Figure 1: Research Approach (van der Vorst et al., 1998)

Results case studies

The sources of uncertainty, which were uncovered during the process analysis in the first case study, can be found in figure 2.

Figure 2: Sources of Uncertainty and Improvement Strategies (click to enlarge; van der Vorst et al., 1998)

For the pilot study not all of the above mentioned improvement principles have been employed. The authors evaluated the following strategies (figure 3).

Figure 3: Improvement Strategies used at the Pilot Case Study (click to enlarge; van der Vorst et al., 1998)

By implementing them a very drastic decrease in inventory levels could be achieved (examples see figure 4). Overall results can be found in figure 5.

Figure 4: Inventory Level at the Distribution Center before and after implementing the Improvement Strategies (van der Vorst et al., 1998)

Figure 5: Results of the Pilot Study (click to enlarge; van der Vorst et al., 1998)

Results simulation

The results of the pilot study were then compared to the simulation model. Overall there seems to be a good fit between the model and the real data (figure 6).

Figure 6: Validation of the Simulation Model by comparing with Real World Data (click to enlarge; van der Vorst et al., 1998)

Further results were generated using the simulation model:

For fast moving goods optimization could be achieved by increasing the delivery frequency both to the retailer and to the DC by a certain amount. Even though the picking cost rose, inventory levels could be decreased significantly.
Implementation of a computer aided ordering system lead to an improvement of supply chain performance between 10 and 20%.

Conclusion

For the authors the simulation model is a logical extension of the prior case studies. Using it makes it possible also to test alternatives which in reality might be too expensive or even impossible to test.
Another key lesson: Reduction of uncertainties again is a major driver of supply chain performance and therefore should not be neglected.

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Supply Chain Risk Management in Financial Crises

Daniel Dumke — Wed, 03 Aug 2011 14:44:00 +0000

I am still abroad right now, but nonetheless I still want to keep the German share within the articles high. So I present to you the second article from German authors in just one week. On monday I already talked about Supply Chain Risk Management in the German Automotive Industry and so the second is today on how supply chain risk management is performed during a financial crisis.

The authors Constantin Blome and Tobias Schoenherr are both from the European Business School (EBS), one of only few privately owned German business schools. Their 2011 paper is on supply chain risk management during times of a financial crisis.

Methodology

The authors employ a case study design for two reasons:

Only little is known of the consequences of a economic crisis on supply chain risk management (and there are no other studies concerned with this topic).
Case study research is furthermore a good method to study complex phenomena.

The authors decided to focus on the procurement departments of eight participating companies, overall conducting 25 interviewees.

Results

From the interviews the authors inferred propositions in four categories:

Impact on SCRM

The effect of the financial crisis on SCRM process (risk identification, analysis, mitigation and monitoring) has been analyzed. The interviews indicate that the tasks within SCRM process are shifting towards a more comprehensive approach concerning all aspects.

A typical statement concerning the risk analysis is:

Before the financial crisis we didn’t have a very professional assessment of our suppliers’ financials; now we have a very good system working

Risk mitigation vs. acceptance

The authors differentiate two major strategic orientations: Risk acceptance and risk mitigation. They were able to identify two company classes: direct spend (most purchases are raw materials and input products; especially in manufacturing companies) and indirect spend (mostly service companies).
Based on this classification the authors found:

The current financial crisis fosters especially a risk acceptance (as opposed to mitigation) approach in direct spend firms. Indirect spend firms are already more focused on risk acceptance approaches and have not changed their behavior.

Service vs. manufacturing

Next the authors analyze the findings concerning the relationship between manufacturing and servicing companies and conclude:

Overall, we found that the emphasis on the four risk management processes was greater among firms procur- ing predominantly direct materials (manufacturing firms) than for firms producing primarily indirect items (service firms).

Enterprise risk management and SCRM

Finally the author analyzed the relationship between supply chain risk management and enterprise risk management and find that:

“The financial crisis has not influenced the relationship between ERM and SCRM.”
“The existence of an ERM system is a major antecedent for the implementation of a SCRM process.”

Conclusion

Case study research is meant to be the qualitative foundation for further in depth analysis using other methods like surveys, simulation or similar. Blome and Schoenherr deliver exactly this basis, by stating their results in the form of four propositions.

Reference:

Blome, C., & Schoenherr, T. (2011). Supply chain risk management in financial crises – A multiple case-study approach International Journal of Production Economics

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Simulation as a Tool for Supply Chain Optimization

Daniel Dumke — Wed, 27 Jul 2011 13:54:00 +0000

Sometimes I am really amazed by the research topics of others. Even though I already read much about simulation and its potential benefits, up to now I have never seen a analysis of supply chain simulation performance on a larger sample. So I would like to share those insights here.

Simulation method

In this paper the authors (Manzini et al.) used a visual interactive simulation (VSI) approach for five case studies. In this case VSI refers to a simulation model that can be directly manipulated by the user of the model during simulation. So for example the effects of a change in inventory levels could be viewed directly after the fact.

This approach therefore allows for quick testing of different scenarios and possible strategies for optimization of the supply chain.

Case example

The authors elaborate five different cases where they employed the above mentioned methodology. I will just highlight one case example here: A make-to-order producer of packaging systems for the pharmaceutical industry. The produced machines consist of a large number of different components, which are supplied by external suppliers. The authors build a model containing the 18 major suppliers, which supply overall 53 modules for the final product.

Figure 1: Case Study: Comparison of Module Lead Times (Manzini et al., 2005)

Based on the simulation model different measures have been developed to reduce lead times from the suppliers. Figure 1 shows the effects of those measures for each of the 53 components. The lead times could be reduced in nearly all areas.

Case analysis

As in any multi-case study after the description of the different examples a cross case analysis and synthesis is necessary to compare the results and draw further conclusions. In this case the author calculate five indicators for each case study which describes the effort for the simulation study and the resulting benefits:

General indicators of model complexity:

NE index is the number of entities used in the simulative model so as to describe the real situations that can occur; and

PT takes into account the programming time in terms of man-hours dedicated by the programmer to develop the model.

General indicators of model effectiveness:

SI is the saving index, defined as the ratio between savings forecast and costs of simulation approach; this is introduced to show the economic feasibility of the simulative model;

SCI, simulation costs index, is the ratio between simulation costs and plant modification costs required for the supply chain optimisation so it deals with the simulation’s economic weight in a complete project; and

RI, readiness index, is the ratio between the lead-time of the simulative approach and real project time extension; it measures the capability of the dynamic model to give rapid solutions to a problem.

Result

The above mentioned indices are then used to compare the different case studies concerning the effective and efficient use of the VSI simulation method within each of the settings.

Figure 2 shows the savings index of the companies which compares the savings the company could achieve using the selected measures versus the cost of the simulation (more is better).

Figure 2: Comparison of the Cases: Saving Index (Manzini et al., 2005)

Figure 3 shows the simulation cost index which refers to the cost of simulation versus the overall project costs for implementing the measures within the respective supply chain (less is better)

Figure 3: Comparison of the Cases: Simulation Cost Index (Manzini et al., 2005)

Figure 4 displays the readiness index. This describes the amount of time it took to execute the simulation versus the total project time necessary to make the changes (less is better).

Figure 4: Comparison of the Cases: Readiness Index (Manzini et al., 2005)

The authors conclude based on these results that the VSI method is very suited for deployment in a business setting.

Conclusion

The authors make a strong case for “their” simulation approach: visual interactive simulation and claim that it is especially useful from a cost / benefit point of view. Also the results in the cases are delivered quickly.

I would love to see another comparison including other simulation approaches, since at least from a theoretical point of view, the VSI is a very simplistic simulation method. There is no optimization selecting the best strategy from several alternatives, but the simulation modeler has to select and evaluate the “best” strategy by himself.

Nonetheless a simple approach has advantages from the complexity perspective. As always: Case studies are not representative, but should give a hint for further research, so go ahead and do some research!

Reference:

Manzini, R., Ferrari, E., Gamberi, M., Persona, A., & Regattieri, A. (2005). Simulation performance in the optimisation of the supply chain Journal of Manufacturing Technology Management, 16 (2), 127-144 DOI: 10.1108/17410380510576796

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Managing Supplier Sustainability Risks

Daniel Dumke — Mon, 30 May 2011 12:47:00 +0000

For many years sustainability risks have been largely neglected. Reputational damages caused by incidents like the Brent Spar platform can reach tens of millions of dollars. But in a supply chain context companies are not only held responsible for their own actions but also for the actions of their suppliers.

In their 2010 paper Foerstl et al. analyze supplier sustainability risk and develop and test a framework for its mitigation.

Research question

Scholars agree that sustainable supplier management (SSM) cannot only rely on a supplier’s compliance declaration. Nonetheless, there has also been consensus, that risk mitigation measures are costly and therefore have to be targeted towards the most risky suppliers. The authors address the following research questions:

How do firms configure sustainable supplier risk management processes in congruence with dynamically changing sustainability requirements?

How can supplier sustainability risk mitigation strategies and processes be a source of competitive advantage to the buying firm?

Research framework and methodology

The authors use the research framework in figure 1 as foundation for their further research. The framework describes the process within a company from the “supplier sustainability risk identification” to the related “performance outcomes”.

Figure 1: Extended Research Framework to Manage Supplier Sustainability Risks (click to enlarge; Foerstl et al., 2010)

Since the research on how firms account for sustainability-related risks are still in an exploratory / early stage the authors decided to use a case study design to build new hypothesis is this field.

The case study participants (5 overall) have been selected to be from the chemical industry, since

first, environmental protection has high strategic relevance in the chemical industry since its costs are among the highest of all industries. Second, the industry’s high profitability and a long history of incidents have led to close scrutiny by its stakeholders, emphasizing the relevance of responsible environmental and social behaviour.

Data analysis

The findings fit into the above mentioned framework and are denoted in figure 2 by P1 to P5.

Figure 2: Summary of Research Findings (click to enlarge; Foerstl et al., 2010)

Proposition 1
The initial development of sustainability risk assessment is based on the perceived stakeholder pressure, but the chosen risk assessment method is independent of the pursued sustainability dimension.

Proposition 2a
Supplier sustainability risk assessment enables an effective sustainability risk mitigation response.

Proposition 2b
The initial configuration and deployment of supplier sustainability risk management capabilities is valuable in building excess capacity, which enables firms to broaden the scope of their sustainability risk management processes.

Proposition 3a
The ability of sustainable supplier selection, development and phase-out strategies to mitigate sustainability risks depends on the rigor with which they are applied.

Proposition 3b
The ability of sustainable supplier assessment and development capabilities to mitigate sustainability risks depends on the astuteness with which they are created and applied.

Proposition 4a
Sustainability risk assessment capabilities allow for effective supplier selection, leading to risk reduction, which constitutes a source of competitive advantage.

Proposition 4b
Beyond the reduction of supplier sustainability risks, sustainable supplier development has a positive effect on operational performance and hence competitive advantage.

Additionally, the author discovered the issue of “external responsiveness”, which has not been part of the original model. It relates to the response time towards new social and environment standards. Two of the interviewed companies also directly approached Non Governmental Organizations (NGOs) to integrate these groups into their sustainability risk management processes.

Proposition 5
Under the presence of dynamic stakeholder stimulus, external responsiveness has a positive effect on sustainability risk identification, assessment and mitigation processes, which in turn affect sustainability risk performance outcomes.

Results

As a summary the authors conclude that

the earlier firms begin to assess their suppliers for sustainability, the greater the accumulation of sustainability-related risk management capabilities relative to their competitors will be.

sustainable supplier assessment and development has positive effects on the buying firm: 1) more profound mitigation of corporate reputational risk and 2) enhanced operational performance.

supplier assessment, selection, and development must be tightly interlocked to effectively manage the sustainability risk exposure caused by individual suppliers or the supply base as a whole

Conclusion

The authors did a great job presenting their results. I was positively surprised to see that they elaborated on three pages about the application of the case study methodology and the sample companies. The sample selection towards companies with great emphasis on sustainability overall (e.g. the companies have all been picked from major sustainability related stock indices) of course leads to a skewed sample which cannot be seen as a representative average, but more as a best practice example.

Reference:

Foerstl, K., Reuter, C., Hartmann, E., & Blome, C. (2010). Managing supplier sustainability risks in a dynamically changing environment—Sustainable supplier management in the chemical industry Journal of Purchasing and Supply Management, 16 (2), 118-130 DOI: 10.1016/j.pursup.2010.03.011

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Case Study on Managing Disruptions in Supply Chains

Daniel Dumke — Wed, 11 May 2011 14:07:00 +0000

Disruptions are an often recurring research objective in this blog. After writing about the severity of disruptions and conceptual research on how to mitigate them, todays article is concerned with how disruptions are managed in practice.

Research Questions & Methodolgy

From their literature review the authors deduct the following research questions:

What are the different types of risks in a retail supply chain?
What are the mitigation strategies required to manage different types of supply chain risks?

To answer those questions a case study is conducted with a retail supply chain in focus. The supply chain consists of a large retailer for pet products and several manufacturers and vendors in North America. The product flow is usually from the producer to the producer’s distribution network, the retailer’s distribution network and finally to the stores. For the case study several interviews were held with employees from the retailer and two of the vendors.

Risk Categorization and Mitigation

The interviews led to a categorization of supply chain risks (supply, demand and miscellaneous risks), with corresponding sub-categories, like natural disasters in supply risks or economic risks on the demand side.
The risks are then aggregated in a matrix with the business impact on the x-axis and the frequency / likelihood on the y-axis (see figure 1).

Figure 1: Risk Classification by Impact and Likelihood (Oke and Gopalakrishnan, 2009)

The authors conclude:

Most supply chain risks fall into two fairly distinct categories—high-likelihood, low-impact risks (or inherent and frequent risks) and low-likelihood, high-impact risks (or disruption and infrequent risks). However, a few will have moderate likelihood of occurring and moderate impact We argue that the classification of a specific type or category of risk may depend on the type of supply chain in question or on contextual characterization or in fact on the supply chain design.

Two types of strategies can be used: generic strategies, which are applicable for a broad range of risk types, and specific strategies, which can only be used for specific risks. From the case study the authors further conclude that specific strategies are primarily used with risks that tend to increase the cost of doing business in a retail supply chain (e.g. increasing gas prices). Generic strategies on the other hand with a focus on coordination of supply and demand can be used to mitigate high-likelihood, low-impact risks. Disruptions require specific strategies which identify the weak point in a supply chain and mitigate by contingency planning.
The aggregated results can be found in figure 2.

Figure 2: Aggregated Results (click to enlarge; Oke and Gopalakrishnan, 2009)

Conclusion

To reap general recommendations from this research one had to perform a representative survey. But the results of Oke and Gopalakrishnan can be used as food for thought by practitioners. Are your risks more more frequent or less frequent? How about their respective business impact? Are you using different strategy types for different risks?

If you are interested in more articles on supply chain disruptions and their effects have a look at the Disruption category here in the blog.

Reference:

Oke, A., & Gopalakrishnan, M. (2009). Managing disruptions in supply chains: A case study of a retail supply chain International Journal of Production Economics, 118 (1), 168-174 DOI: 10.1016/j.ijpe.2008.08.045

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Purchasing's involvement in risk management

Daniel Dumke — Tue, 15 Mar 2011 09:02:00 +0000

I already reviewed one of the articles of Zsidisin (Perception of Supply Risk). Today I had a look at an article about how the purchasing organization is involved in the supply chain risk management activities.

Exploratory Study

Zsidisin et al. did an exploratory study with semi-structured interviews with purchasing professionals in nine companies from the manufacturing industry.

Semi-structured, open-ended interviews were employed to gain an understanding of how purchasing organizations conduct supply risk assessments and incorporate contingency plans.

Findings

The analysis show that the formalization of the risk management techniques used are quite different. The most commonly used method for risk mitigation is: multiple sourcing for strategic parts. But some of the respondents also had more elaborate approaches to reduce risk, like:

Closer relationships with suppliers
Taking suppliers responsible for risk mitigation
Common product platforms and industry standards

Furthermore buffer strategies are used, as of course holding safety stock, controlling stock within the whole SC or multi-sourcing strategies.
Risk management are seen as important functions, but most also stated that the priority is set very low.

Conclusion

It is interesting to see that similar patterns, like the divergence between the expressed need for risk management activities and the current state of those, arise also in talks I had with SC professionals in the last year. So compared to ten years ago not so much seems to have changed in this regard.

Reference:

Zsidisin, G., Panelli, A., & Upton, R. (2000). Purchasing organization involvement in risk assessments, contingency plans, and risk management: an exploratory study Supply Chain Management: An International Journal, 5 (4), 187-198 DOI: 10.1108/13598540010347307

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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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Case Study Research for Theory Creation

Daniel Dumke — Mon, 20 Dec 2010 11:52:00 +0000

How is new knowledge generated in the social sciences? One method is case study research.

Case Study

A case study is an in-depth investigation of a specific question regarding an individual research object, it can be differentiated using the following criteria:

Number of objects investigated: single / multiple cases

Number of levels of analysis: embedded design

Data collection: used data collection methods (eg. interviews, written files,…)

Kind of data ascertained: qualitative / quantitative

Purpose of the study: provide description / test theory / generate theory

Theory development

Theories are usually developed using observations (Newton’s Apple), using grounded theory, or by analyzing qualitative data. This article shows how case research can be used for the development of theories as well.

Process of Building Theory from Case Study Research

Process of Building Theory from Case Study Research (Eisenhardt, 1989)

According to Eisenhardt (1989), the process shown in the figure above should be used. I would like to highlight the following important steps:

Selecting cases
Instead of random sampling used in surveys, where statistical significance is important, cases should be selected using theoretical sampling, to focus efforts on useful cases

Data collection
Triangulation is used here to analyzing the object from different angles, eg. using data from interviews, company presentations and publicly available data.

Data analysis
The analysis of the data should happen as soon as possible, in contrast to surveys where the questionnaire does not change during execution, case research should adapt to the results of previous findings.

Eisenhardt (1989) further lists the following advantages / factors when to use case research.

Strength:

Higher likelihood of generating novel theory

Emergent theory is likely to be testable with constructs that can be readily measured and hypotheses that can be proven false

Resultant theory is likely to be empirically valid

Weakness:

Empirical evidence can yield theory which is overly complex

The result may be a narrow and idiosyncratic theory

Applicability:

When little is known about a phenomenon

Current perspectives seem inadequate

Current opinion conflict with each other or common sense

Conclusion

Case studies cannot support a theory with statistical relevant findings, but case studies are turned into theories by finding common patterns within the gathered data. After this step further support will be needed to establish the validity of the theory, which can be using modeling approaches or statistically significant surveys.

Reference:

Eisenhardt, K. (1989). Building Theories from Case Study Research The Academy of Management Review, 14 (4) DOI: 10.2307/258557

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Supply Chain Risk Management Sessions @CSCMP 2010

Daniel Dumke — Mon, 04 Oct 2010 12:20:00 +0000

Most of the time during the conference I was busy interviewing companies for my dissertation, but I also found time to listen to some of the sessions on SCRM.

SCRM Keynote

The first session on supply chain risk management was held by Garry Lynch (Marsh, author of “Single Point of Failure”) on Supply Chain Risk Management. The contents were: Challenges, Current State, Successful and unsuccsessful practices.
Sadly, I had to leave before the practice part, but the key strategies can be found in his book mentioned above.

Combining Research and Practice

The second session SCRM was on “Global Supply Chain Resilience”. The presentation was held by: Dow Chemical Company (Darrel Zavitz, Martin Fernandes), Ohio State University (Joseph Fiskel, Center for Resilience), US Air Force (Timothy Pettit). They described a research project on SC resilience and its execution.The first interesting point was their highlighting of the interrelation between sustainability and resilience, since the focus of resilience is on being able to work under changing/turbulent conditions and missing sustainable behavior may exactly lead to these conditions.

The speakers defined supply chain variability as consisting of supply risks, deliberate threats, market change and internal change. Resilience on the other hand is described as the capability to adapt to turbulent change.

On the above mentioned definition Fiskel and Pettit built a framework of resilience consisting of vulnerabilities, capabilities and a resulting zone of balanced resilience.
One underlying premise of the process described below is, that usually SC managers do not worry about the unforeseen but about the familiar, but the goal has to be adaptability to real uncertainty!
Together with Dow Chemical they developed a process of “Design for Resilience” which consists of:

Supply Network Mapping
SCRAM (SC Resilience Assessment and Management) Analysis (vulnerabilities and capabilities, where is improvement potential)
Supply Network Simulation (stress testing the SC, weekly basis, the goal is to find clues how to improve resilience)
Strategy selection (a weighing of increasing capabilities vs. cost has to be done, the suggestion was to use kind of a break even analysis for the probability of an adverse event)

Pettit and Fiskel also build a list of possible vulnerability / capability combinations using literature review, a survey and focus group interviews. They use method triangulation to increase the validity of the resulting listing.

All in all they presented a very business oriented modeling system (including a software using a systems dynamics model) to show effects of different scenarios on the supply chain. It is important to note they are not trying to predict future events, but focus on more general agility and resilience of the SC in case of a disruption.

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