Risk Mitigation

Impact of Product Design Changes on Supply Chain Risk

Daniel Dumke — Mon, 21 May 2012 14:06:24 +0000

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.

Concept

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.

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

Method

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.

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.

Results

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.

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.

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”

Conclusion

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.

Reference:

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

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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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Supply Chain Risk Management for SMEs in Automotive SCs

Daniel Dumke — Mon, 30 Apr 2012 14:02:46 +0000

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.

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.

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:

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.

Results

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):

Figure 4: Advantages of Natural Hedging for the Stakeholders (Hofmann, 2011)

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

Preparation of managerial prerequisites, as well as examination of contractual and legal framework.

Business model decision and concept evaluation.

Ramp-up and organizational integration.

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.

Conclusion

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.

Reference:

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

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Conceptual and Analytical Framework for SCRM

Daniel Dumke — Mon, 12 Mar 2012 18:18:16 +0000

A supply chain risk management framework should help to define the cornerstones of risk related supply chain problems and give hints on how to take actions to mitigate impending disruptions.

Today’s full paper has been published in 2004 and in it the authors (Gaonkar and Viswanadham) deal with this problem.

Core definitions

At the core of their framework the authors define the risk/supply chain related terms.

First, risks can be seen from an organizational-, supply chain- or industry-level.

Network- related risk sources represent the second category of risk sources, which are the primary focus of this paper. These risks are of two broad kinds:

Firms are vulnerable not only to attacks on their own assets, but also to attacks on their suppliers, customers, transportation providers, communication lines, and other elements in their eco-system.

Firms are also vulnerable to irregular behavior of their network partners such as a supplier sharing sensitive product design with a competitor manufacturer.

Second, there are different classes of risk problems:

Deviations: “A deviation is said to have occurred when one or more parameters, such as cost, demand, lead-time, etc., within the supply chain system stray from their expected or mean value, without any changes to the underlying supply chain structure.”
Disruptions: “A disruption occurs when the structure of the supply chain system is radically transformed, through the non-availability of certain production, warehousing and distribution facilities or transportation options due to unexpected events caused by human or natural factors.”
Disasters: “A disaster is defined as a temporary irrecoverable shut-down of the supply chain network due to unforeseen catastrophic system-wide disruptions.”

This classification also contains an implicit rating of the risk impact and while it is possible to create a robust supply chain which can withstand deviations and disruptions “it is impossible to design a supply chain network that is robust enough to react to disasters. This arises from the constraints of any system design, which is limited by its operational specification.”

The authors require the supply chains to be robust at three levels: the strategic, tactical and operational level. So each of these levels has to be prepared for deviations, disruptions and disasters.

For example, at the operational level, companies require decision support systems that can act on information from various partners regarding various deviations and disruptions to reschedule activities so that the business processes are synchronized and deliveries are undertaken within customer delivery windows and cost limitations. At the tactical level, plans need to have redundancies in terms of human and machine resources and also logistics and supply organizations. At the strategic level, more reliable partners with intrinsic capabilities in deviation and disruption handling, and the skills and ability to adapt to changing market conditions will be preferred and selected.

There are two distinct ways to supply chain risk mitigation:

“The first approach involves the time tested “just in case” way of maintaining inventories all along the chain, employing dual or multi-sourcing and manufacturing at multiple sites. This is a highly inefficient option.”
“A better option would be to first design a sourcing strategy taking into account the disruption costs for the most relevant failure modes and then putting in place contingency plans for each disruption that include both description of the procedures to follow and a definition of roles and responsibilities.”

The authors distinguish three analytical approaches to risk management:

Mathematical planning models,
Adaptive control, and
Rule-based control.
And they continue to explain their preventive and interceptive approaches to risk management. Some of which can be found summarized in this article in the blog.

Results

Based on their framework of supply chain risks the authors develop two strategic level (mathematical) models which include risk considerations.

Strategic-level Deviation Management Model: Given the expected costs and variability (deviation) of costs for all suppliers, the first problem relates to the selection of an optimal group of suppliers such that the expected cost of operating the entire supply chain and the risk of variations in total supply chain costs is minimized.

Strategic-level Disruption Management Model: Given the expected probabilities for various supplier disruption scenarios and the supply shortfalls under each of these scenarios the objective for the manufacturer is to choose a set of suppliers that minimize the expected shortfall during the operation of the supply chain.

With the models numerical example case studies are executed and the authors conclude:

Robustness is build into our supply chain design by selecting a portfolio of suppliers that minimize the variability of supply chain performance in terms of cost and output. The models we develop are preventive in nature and employ mathematical programming tools.

Conclusion

This article is a double publication, the models and their results have already been discussed here. Even though this is questionable behavior from a scientific point I did include this article due to the good and aggregated summary of the terms and definitions used in the field of supply chain risk management.
Using those as a minimum to analyze supply chains can already help a great deal in finding fitting mitigation strategies.

Reference:

Gaonkar, R., & Viswanadham, N. (2005). A Conceptual and Analytical Framework for the Management of Risk in Supply Chains Robotics and Automation, 3, 2699-2704

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Managing Global Sourcing Risk

Daniel Dumke — Mon, 23 Jan 2012 17:34:15 +0000

Probably most companies source at least some parts for their products from global sources. This could be the steel from Australia, electronics from Taiwan or cloth from India. The reasons for international sourcing usually include cost and quality, which might be superior compared to local sources.

On the other hand longer shipment ways and less direct access and control may also increase the risks of quality failures, delays or even disruptions.

So at the moment a lot of companies struggle to find the right balance between increased risks and reduced cost in international sourcing. This study gives an inside view into fifteen companies and how they handle risks related to global sourcing, and therefore this overview is a good example for current practices in the field of supply chain risk mitigation.

Method

The authors still see a gap in the knowledge about how other companies analyze their sourcing related risks and how these risks are mitigated by them.

Therefore they use a multiple case study approach with 15 cases / companies within seven industries. In each company several information sources were tapped, including expert interviews.

Afterwards the authors compared the individual results in a cross case analysis.

Sourcing globally

But first the authors start with a literature analysis to analyze the reasons and risks of global sourcing.

Figure 1 shows their results regarding the advantages and risks of sourcing globally.

Figure 1: Sourcing Globally: Advantages and Risks (Christopher et al., 2011; click to zoom)

From this the authors extract a risk classification for global sourcing risks (figure 2).

Figure 2: Sourcing Globally: Risk Classification (Christopher et al., 2011; click to zoom)

Risks in global sourcing

Building on this literature review the authors conduct their case study. The cross-case analysis reveals risks in the following industries:

retail,

fashion retail and wholesale,

consumer electronics,

oil/gas,

mechanical and electrical equipment,

fast moving consumer goods (food and drink), and

aerospace.

The risks are shown in figure 3.

Figure 3: Risk Overview (Sourcing Globally) (Christopher et al., 2011; click to zoom)

Strategies for risk mitigation

The identified risks are handled very differently by each of the companies. Figure 4 shows the different approaches to identify and manage the risks.

Figure 4: Risk Management Strategies and Tools (Christopher et al., 2011; click to zoom)

Overall the authors find:

The study proposes four generic strategies for managing global sourcing risk: network re-engineering, collaboration, agility and a risk management culture. Evidence of each of these strategics was found in the case studies although no single company was applying all of them.

The study also shows that even though many managers were aware of the risks their companies were exposed to, risk management strategies were not implemented in a systematic and holistic manner.

Conclusion

It is not possible to generalize these results for any company, due to the specific exploratory nature of the method used. But I find the findings quite interesting and I think they could be used as a foundation to build your own mix of mitigation strategies.

Reference:

Christopher, M., Mena, C., Khan, O., & Yurt, O. (2011). Approaches to managing global sourcing risk Supply Chain Management: An International Journal, 16 (2), 67-81 DOI: 10.1108/13598541111115338

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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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Exception Handling for Robust Supply Chain Design

Daniel Dumke — Wed, 07 Dec 2011 18:33:00 +0000

This article considers the design of robust supply chains from the viewpoint of exception handling. Disruptions of the supply chain happen all the time. Smaller disruptions like quality issues are part of the daily business; but a look at the recent ten years shows that large disruptions, happen more often as well (think of terrorist attacks or earthquakes). “Thus, exception management is an important issue in global supply chain networks.”

Basics and definition

If one accepts the fact, that exception cannot be eliminated completely there are two ways to treat them: preventive and interceptive. Figure 1 shows different exception management strategies.

Figure 1: Exception Management Strategies (Gaonkar and Viswanadham, 2003; click to zoom)

The authors define a supply chain exception as the opposite to the classical seven-Rs of logistics:

We can use this description to define a supply chain failure or exception occurring whenever the supply chain deviates from any one of the […] required specifications – either in terms of delivering the wrong product, in the wrong quantity, in the wrong condition, at the wrong place, at the wrong time, at the wrong cost and to the wrong customer.

Exception management

In this case exception management is addressed “at the strategic level through the preventive selection of supply chain partners that mitigate risk in the network.”

In the first step the consequences of a given exception (here: supplier non-performance) are analyzed. The authors use a Cause-Consequence-Diagram for this end (figure 2).

Figure 2: Cause and Consequence Diagram for one Example (Supplier Non-Performance) (Gaonkar and Viswanadham, 2003; click to zoom)

Then, “given the probability of occurrence of the initiating event, which is supplier non-performance, and the probabilities for the various intermedialy events, we can calculate the probability of occurrences for each of the end states or outcomes. Furthermore, each of these end states may result in different levels of supply shortfalls and financial cost. Hence, given the probability of each end state and the supply shortfall or financial cost for each end state, we can calculate the expected shortfall or financial risk for the non-performance of a given supplier.”

If repeated for each supplier, the supplier with the least expected impact can be identified.

Model

To implement their approach the authors develop a small linear mixed-integer model.

The model was formulated in Microsoft Excel and solved using the Solver add-in. The model was solved for a problem with a single manufacturer (located in the US), dealing with 5 suppliers. The probabilities of supplier disruption for all the suppliers (individually and in various combination) were considered as given [the first part is shown in figure 3]. The relation cost was taken as $5000 and the quantity required by the manufacturer was 520 units.

Figure 3: Scenario / Probability Table (Gaonkar and Viswanadham, 2003)

Conclusion

The presented approach makes it easy to include uncertainty into the supplier selection process. Considering the moderate efforts necessary for implementing the supplier assessment and implementing the model, I would like to read more about the effectiveness in a real business situation.

Reference:

Gaonkar, R., & Viswanadham, N. (2003). Robust Supply Chain Design: a Strategic Approach for Exception Handling Proceeings of the 2003 IEEE International Conference on Robotics & Automation, 1762-1767

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Predicting and Managing Supply Chain Risks

Daniel Dumke — Mon, 21 Nov 2011 15:40:00 +0000

I often recommend Supply Chain Risk: A Handbook of Assessment, Management, and Performance as a good overview of supply chain risk management literature. In this article I summarize chapter four of the book on the problem and processes to predict supply chain risks.

Structure and basics

In first section the author starts by defining the basics of risk and uncertainty. The next section briefly introduces different categories for supply chain risks:

Internal to the firm: Process, Control

External to the firm but Internal to the Supply network: Demand, Supply

External to the network: Environmental

These risk can then impact the different dimensions of a supply chain:

Physical movement of goods
Flow of information
Flow of money
Security of the firm’s internal information systems
Relationship between supply chain partners
Corporate social responsibility and the effect on a firm’s reputation.

The next section provides an overview on supply chain risk management, its steps and mitigation strategies.

Predicting Supply Chain Risks

One of the main requirements for an effective proactive risk management process is to obtain good estimates of the probability of the occurrence of any particular disruption and accurately measure the potential impact.

So the estimation of probabilities and impacts, depending on the characteristics of the supply chain and the environment it might be harder to identify all risks and assess them.

The author describes two tools for the estimation of risks: Data Mining and Failure Mode Effect Analysis (FMEA).

Data Mining

The role of data mining is to analyse historical data, to improve prediction capability. Some of the common analytic approaches used by data miners are:

Estimation of the parameters of past performance: Means, Standard deviations, Correlations, and Associations for hypothesis testing

Classification: Segmentation, or Clustering of data units to facilitate the modelling process

Construction of a functional relationship: or model between responses and explanatory variables.

The following tools should be used by a data miner:

Estimation: […] These tools will not lead to patterns but are more useful in analysing the data to identify the most relevant sets of data to concentrate further analysis.

Clustering/segmentation: This approach is used to logically group observations on the basis of similarity in their characteristics, reducing the level of heterogeneity in the data.

Classification/discrimination: The process of assigning observations to a predetermined number of classes.

Prediction: Formal mathematical models are built for the purpose of predicting the occurrence of the phenomenon.

Failure Mode Effect Analysis (FMEA)

The goal of the FMEA is to

Recognise and evaluate the potential failures of a product or process and the effects of that failure.

Identify actions, which could eliminate or reduce the chance of the potential failure occurring.

Document the entire process.

The author highlights ten steps of the process:

Define scope, functional requirements, design parameters and process steps.

Identify potential failure modes: Failure modes indicate the loss of at least one functional requirement. It is the manner in which a failure occurs. This step in the process takes into account a foresight view (based on past experience and any new information) of what could cause a failure to the system or process.

Potential failure effect: This step investigates the effect the failure will have on other entities or processes.

Severity: “How bad” or “serious” the effect of the failure mode is. Usually severity is rated on a discrete scale from 1 (no effect) to 10 (hazardous effect). Severity ratings of 9 and 10 indicate a potential effect of high importance and this could typically be a safety or government regulation issue. Critical effects need deeper study for all causes to the lowest level, using a method of Fault Tree Analysis.

Potential causes: These are the causes of the failure. In this step, all causes that can be attributed to the failure occurring are investigated.

Occurrence:This is the likelihood of the event happening (i.e. failure in the system) on the basis that “the cause occurs”. FMEA assumes that if the cause occurs, failure will occur too. The probability of occurrence is ranked from 1 to 10, where 1 signifies a remote probability of occurrence and 10 a very high probability of occurrence.

Current controls: The objective of the controls is to identify and detect the deficiencies and vulnerabilities as early as possible. This step looks at the current processes in place to mitigate the failures (if already known).

Detection: A subjective rating is assessed corresponding to the likelihood that the detection method will detect the first-level failure of a potential failure mode. This is ranked from 1 to 10, where 1 signifies that it is unlikely to detect and 10 signifies a very high detection potential.

Risk Priority Number (RPN): These are used to prioritise the potential failures and are calculated as “Severity Occurrence Detection ranking”.

Actions Recommended: The team should then select and manage subsequent actions needed to locate and control the situation.

Predictive – Proactive Methodology

Based on these methods the author suggests a predictive-proactive methodology (figure 1) to manage risks.
The two main steps are called predictive mode and proactive mode. In the predictive mode, the focus is on gathering of information on the potential risk sources. The proactive mode focusses on the identification of the risks within the supply chain and assessing the risk level and setting the strategic objectives of the company.

Figure 1: Schematic Diagram of the Predictive-Proactive Approach Supply Chain Risk Management Approach (Dani, 2006)

Conclusion

I read the chapter with a focus on the description of the prediction tools. The model on the other hand is a nice add-on which could be used as food for thought. But I find it a little bit too simplistic and a little bit confusing. It describes a basically linear process (from a risk to the disruption), but why then did the author choose not to represent this in a linear way, but in a diagram with two main parts/frames instead of a clear process and why are there two different types of frames (dashed and solid)?

Reference:

Dani, S. (2006). Predicting and Managing Supply Chain Risks Supply Chain Risk (Ed. Clare Brindley), 53-66 DOI: 10.1007/978-0-387-79934-6_4

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Improving Supply Chain Performance and Managing Risk Under Weather-Related Demand Uncertainty

Daniel Dumke — Wed, 09 Nov 2011 16:18:00 +0000

The demand of many products is connected to the weather patterns during and before the selling season. Ice cream can be best sold during warm summers, of course. But also other food products or clothes exhibit weather dependent demand pattern.

This article by Chen and Yano (2010) has a look at improving contracting between a manufacturer of a product with weather dependent demand and its retailer. One is for sure: uncertain demand causes negative effects for the whole supply chain, and should be handled as such. The full paper can be downloaded here.

Method

The author utilize the classic news vendor setting with one manufacturer (M) and one retailer (R) to focus on the analysis of their relationship.

M is set as the focal company. Due to several reasons (e.g. long lead times, seasonal products) M wants to offer weather related rebates for the retailers.

Model

The sales process is modeled in three steps:

M designs the contract and offers it to R

R decides on the ordering quantity

Depending on the weather and the quantity ordered, payouts are made from M to R

A weather rebate is an alternative to other supply contracts that manufacturers might use to induce retailers not just to order greater […] quantities, but also to order them well in advance of the selling season. Such inducements fall into two broad categories: (1) early-season incentives that reduce the retailer’s financial obligation for any given purchase or commitment level and (2) end-of-season concessions paid by manufacturers when demand is weak.

In this case the authors only have a look at the second type.

Without loss of generality, the authors focus on the temperature as weather index and design the payoff depicted in figure 1, where t is the measured temperature, t* is the “strike”-temperature and K is the payoff.

Figure 1: Suggested Contract for Weather Rebate (Chen and Yano, 2010)

Results

The results show how the effects of the demand risks for the manufacturer can be mitigated in such a setting:

Choice of strike temperature (t*) and rebate function
t* has an huge effect on the risk sharing between the two parties. So in combination with adjusting the payoffs K, it is possible to cater to different degrees of risk aversion between the manufacturer and the retailer

Additionally risks can be hedged by using weather derivatives
Tapping the growing market of derivative products on weather allows to offset the risks of such a contract by buying a corresponding weather certificate.

Conclusion

The authors suggest a very flexible contracting scheme to optimize the distribution of risks between a manufacturer and retailer.

[The authors also see] very significant side benefits that the weather rebate offers (e.g., no auditing of leftover inventory at the retailer that would be required in the case of buy-back contracts or markdown allowances).

But, on the other hand the authors admit that the difficulty of the negotiation process might be increased since many more parameters (rebate, weather indices,…) have to be agreed upon.

Reference:

Chen, F.Y., & Yano, C.A. (2010). Improving Supply Chain Performance and Managing Risk Under Weather-Related Demand Uncertainty Management Science, 56 (8), 1380-1397 DOI: 10.1287/mnsc.1100.1194

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Supply Chain Crisis and Disaster Pyramid

Daniel Dumke — Wed, 02 Nov 2011 15:43:00 +0000

With this review I take a look at supply chain disruption management. There is a huge number of actual and potential crisis (floods in Thailand, typhoons and risks of a greek collapse).

So it does make sense to think about preparation and recovery ahead of time.

Method

This article presents a new approach on how to improve preparedness and recovery after disaster strikes. It is built completely on a literature review of the resource, risk, crisis and disaster recovery, and preparedness literature. At its core this research is built on four different theories:

resource-based view of the firm

communication theory,

competing values theory, and

relationship management theory.

Figure 1: Four Corners of the Supply Chain Disaster and Crisis Pyramid (Richey, 2009)

Disaster and Crisis Pyramid

The four theories also form the pillars of the Disruption and Crisis Pyramid (DCP; figure 1).

Resource Management

The resources a company controls are an important factor in mitigating the effects of disasters. The authors summarize:

Still, given the prominence of resource management in the literature, and rightfully so, it seems logical that the DCP would “point” to resource management. Human resources must be moved from crisis locations to safe locations or from traditional operations to crisis locations. Physical and technological resources must be allocated, moved, opened, cleared, and customized. Informational resources must be collected, cleaned, warehoused, and redistributed. Financial resources must be acquired, allocated, distributed, and governed. The activity component in DCP research is huge and seems to thus be the consistent under current in the literature.

Collaboration: relationship management theory

The second element of the pyramid is the collaboration between the stakeholders in a disaster situation.

In crisis situations, collaboration will likely be the glue that holds organizations together. Additionally, Stewart et al. (2009) point out the broadness of the web that forms the extended supply chain in disaster and crisis situations. There is little doubt that such a tangled web will provide a huge opportunity for not only new research, but also to challenging the existing assumptions of relationship management logic.

Communication: communication theory

To achieve coordination and collaboration between all stakeholders, established and continued communication methods are essential.

Supply chain disaster and crisis situations demand effective communication. […] Examining issues such as bi-directionality, formality, modality, and frequency could be of serious importance as public and private entities attempt to understand what, when, and how much to communicate.

Contingency planning: competing values theory

A supply chain brings together a multitude of different companies. And usually instead of having on clear cut strategic goal, each company works for its own goals which also often are not properly aligned.

Competing values theory provides grounding for future supply chain disaster and crisis research by suggesting that firms simultaneously pursue various different and often conflicting strategic goals regardless of the situation

Conclusion

All in all Richey’s framework is aimed at providing a guideline for future researchers to find new insights into supply chain disaster management and how to improve supply chain reactions at the intersection of communication, collaboration, resources and values. And these four aspects should not only be considered by researchers, but also by supply chain professionals.

I especially liked the inclusion of the competing value theory, which might lead to a shift in research from the currently leading paradigm that goals of supply chain partners are always well aligned.

On the other hand, this framework could also be used beyond only disaster and crisis management, the aspects could perhaps prove influential in a larger number of supply chain related research fields and applications.

Reference:

Richey, R.G. Jr (2009). The supply chain crisis and disaster pyramid: A theoretical framework for understanding preparedness and recovery International Journal of Physical Distribution & Logistics Management, 39 (7), 619-628 DOI: 10.1108/09600030910996288

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Ways to guard against Disruptions

Daniel Dumke — Mon, 17 Oct 2011 17:49:00 +0000

Today I review an article called “18 Ways to Guard Against Disruption”. It was published in the Supply Chain Management Review in 2005 by Elkins et al.

Goal and method

The goal of this study was to assess the current state of supply chain risk management capabilities across multiple industries. The authors describe the results of several interviews with companies from multiple industries, which have been conducted by the Supply Chain Resource Consortium (SCRC, an university industry partnership for documenting supply chain management knowledge).

Results

Based on this study 18 best practices have been identified, which have been categorized according to their impact location (internal or external) and their time orientation (current business vs. future business).

External orientation / future business (“Strategic sourcing & advanced procurement”)

“Screen and regularly monitor current and potential suppliers for possible supply chain risks.
Require critical suppliers to produce a detailed disruption-awareness plan and/or business-continuity plan.
Include the expected costs of disruptions and operational problem resolution in the sourcing total-cost equation.
Require suppliers to be prepared to provide timely information and visibility of material flows that can be electronically shared with your organization.”

External orientation / current business (“Supply-base management”)

Conduct frequent teleconferences with critical suppliers to identify issues that may disrupt daily operations and discuss tactics to minimize these issues.
Seek security enhancements that comply with the Customs-Trade Partnership Against Terrorism (C-TPAT), Container Security Initiative (CSI), and similar initiatives.
Test and implement technologies to track containers.
Conduct a detailed incident report and analysis following a major disruption.
Create exception-detection/early-warning systems to discover critical logistics events that exceed normal planning parameters.
Gather supply chain intelligence and monitor critical supply-base locations.

Internal orientation / current business (“Real time operations management”)

Improve visibility of inventory buffers in domestic distribution channels at the part level.
Classify buffered material by its level of criticality.
Train key employees and groups to improve real-time decision-making capabilities.
Develop decision-support tools that enable the company to reconfigure the supply chain in real time.

Internal orientation / future business (“Strategic supply chain design”)

Develop predictive analysis systems that incorporate intelligent search agents and dynamic risk indices.
Construct damage-control plans for likely disruption scenarios.
Understand the cost trade-offs for different risk-mitigation strategies.
Enhance systemwide visibility and supply chain intelligence by using improved near-real-time databases.”

The authors note that none of the companies had implemented all of the identified measures at the same time and they suggest:

Companies may want to use the best-practices list as a thought-starter to help them prioritize which supply chain risk management elements to adopt. For example, companies could develop an internal survey, based on the best-practice list, which would assess their supply chain risk management capabilities.

Conclusion

This article closes a gap at the SCRM Blog of some early exploratory research on how supply chain risk management is done in practice. Even though the description of the methodology lacks several important facts, e.g. how many companies have been interviewed and how were the interviews conducted, the results still show an interesting direction.
The next obvious questions, which to my knowledge have not been pursued in an systematic manner, would be:

Which of the strategies is best used in what setting?
How should a company prioritize their efforts, if they wanted to invest in supply chain risk management?

Reference:

Elkins, D, Handfield, R.B., Blackhurst, J., & Craighead, C.W. (2005). 18 Ways to Guard Against Disruption Supply Chain Management Review

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Assessing Vulnerability of a Supply Chain

Daniel Dumke — Mon, 10 Oct 2011 14:42:00 +0000

At this year’s HICL conference in Hamburg, I was able to present some of my own research. In the follow-up discussions several points were highlighted, especially focussing on the viability of supply chain wide cooperation and collaboration efforts and on the difficulties of doing a realistic quantification of supply chain risks.

I already read a great paper on this topic some time ago: “Assessing the vulnerability of supply chains using graph theory” by Stephan M. Wagner and Nikrouz Neshat (2010), which I present you today.

Disruptions and vulnerabilities

Several authors argue that several factors help increase the vulnerabilities of today’s supply chains. When supply chain complexity increases (e.g. supply chain length, higher division of labor, …), the vulnerabilities also rise. Furthermore there is evidence that natural and man-made disasters are on the rise as well (figure 1).

Figure 1: History of Disasters (Wagner and Neshat, 2010)

Figure 2 shows the links between supply chain vulnerability drivers and disruptions.
So, since natural- and man-made-disaster most often cannot be influenced directly, the authors argue that the focus has to be on reducing the vulnerabilities themselves.

Figure 2: Connections between Vulnerabilities, Disruptions and Risks (Wagner and Neshat, 2010)

Assessment of vulnerabilities

Wagner and Neshat suggest a four step algorithm based on graph theory, which is used to calculate a Supply Chain Vulnerability Index (SCVI). The algorithm is based on graph theory (which has been part of another study here). Key to the understanding of the SCVI is the risk driver mentioned above. Figure 3 shows an abstract example with three vulnerability drivers (D1 to D3) and their links.

Figure 3: Vulnerability Drivers and their Links with the corresponding Matrix (Wagner and Neshat, 2010)

To calculate the SCVI the supply chain risk manager has to create a map / graph of the current risk drivers (step 1), find the corresponding relations between the risk drivers (step 2), calculate the “influence matrix” (step 3) and deduce the SCVI. As a forth step SCVIs of different companies can be compared to gain further insights for optimization and risk reduction.

Figure 4 shows the main drivers of supply chain vulnerability.

Figure 4: Selection of Vulnerability Drivers in Structure, Demand and Supply (Wagner and Neshat, 2010)

Using graph theory makes it possible for the risk manager to get an overview of the influencing factors of supply chain risks. It also enables him to act on this knowledge. Figure 5 shows a possible simplification / vulnerability reduction.

Figure 5: Reduction of Supply Chain Vulnerability Drivers leads to a Simplification of the respective Graphs (Wagner and Neshat, 2010)

D3 in figure 5 “is called a ‘sink’ – which means that D3 can only be influenced by three other drivers and cannot influence others. Considering the graph nodes and edges, supply chain managers can apply risk management methods and implement mitigation strategies to omit or alleviate some of the vulnerability drivers. Figure 5 shows the graph after D3 has been omitted. As one can see, the resulting graph contains less vulnerability than it did prior to implementing the measures.”

Empirical data for the SCVI

The authors also conduct a survey with over 700 participants from different industries. Based on their feedback the authors assess the Supply Chain Vulnerability Index for eight different industries. The results are summarized in figure 5. And give support to the hypothesis that the automotive industry has one of the highest risk levels.

Figure 6: Supply Chain Vulnerability within several Industries compared (Wagner and Neshat, 2010)

Conclusion

I really like the graph approach to assessing supply chain vulnerabilities. And I think it is a great method to support the understanding of a complex system like the supply chain. The article combines two very interesting aspects of it: the practical implementation and the assessment of supply chain vulnerability and a survey to compare different vulnerability levels across industries. The complete article, where you find more details on the survey results and the algorithm for calculating the index, can be downloaded here.
From a business and research point of view this article should direct the supply chain risk management efforts especially in the industries with the highest risk levels, Automotive and ICT.

Reference:

Wagner, S.M., & Neshat, N. (2010). Assessing the vulnerability of supply chains using graph theory International Journal of Production Economics, 126, 121-129

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Evaluation of a Firm's Supply Chain Strategy

Daniel Dumke — Wed, 05 Oct 2011 12:10:00 +0000

Today’s paper is brand new and based on the dissertation works of Roberto Perez-Franco. It can be considered as a summary of the current state of the art in supply chain strategy and extends knowledge in the field of strategy evaluation. It can be downloaded for example from Yossi Sheffi’s homepage at the MIT.

Foundation

The authors founded the following findings on two action research project with Saflex and a health care company. Several dozen interviews were conducted on different levels within the companies.

For the further research the authors define the major terms used: supply chain strategy and the difference between the supply chain and the supply chain strategy:

For the purpose of this paper, the supply chain strategy of a firm is understood as the set of ideas behind the activities, decisions and choices of that firm‟s supply chain, which serve as logical bridge between the supply chain operations in the field and the business strategy.

The difference between a supply chain and a supply chain strategy is the difference between a set of physical entities and a set of ideas. So, for example, when AMR Research publishes its “Supply Chain Top 25” list, what they are ranking are supply chains, not supply chain strategies.

Functional Strategy Map (FSM)

The authors introduce a Functional Strategy Map which “is a conceptual representation of the supply chain strategy as a bridge between operations and business strategy”. Three layers are aggregated in the FSM: strategic, functional and operational (figure 1).

Figure 1: Elements of a Functional Strategy Map (Perez-Franco et al., 2011)

A company’s supply chain is then evaluated based on the this concept using the criteria mentioned below.

A example of the FSM might look like that from Saflex in figure 2.

Figure 2: Example of a Functional Strategy Map (Perez-Franco et al., 2011; click to enlarge)

Evaluation criteria

The evaluation criteria were agreed upon before the first action research, but were adapted due to the new findings from the first and second action research.

The final suggested criteria are:

“Support: activities should support the goals of the supply chain strategy”

“Consistency: components of the supply chain strategy should be compatible”

“Coverage: the supply chain strategy should address all important areas”

“Sufficiency: the goals should be fully satisfied by the supply chain strategy”

Figure 3 illustrates the criteria.

Figure 3: Evaluation Criteria (Perez-Franco et al., 2011)

(1) Functional support: the functional themes are expected to support the strategic themes. (3) Strategic consistency: the strategic themes are expected to be compatible among themselves. (7) Functional coverage: the functional themes are expected to address all the areas of interest to the functions. (10) Functional sufficiency: The functional themes should be satisfied by the operational themes.

The authors also defined methods to evaluate these criteria within a company. I highlight the results of the consistency check here and refer you to the full paper if you are interested in more about the methods used here.

Figure 4: Incompatibility Matrix for the Functional Layer (Perez-Franco et al., 2011; click to enlarge)

Figure 4 shows the incompatibility matrix for the second company. Each axis contains the functional goals of the company and the percentages indicate the incompatibility between the ideas as given by the interviewees (lower means more compatible).

Thus this graph gives an good overview of strategic incompatibilities and clashes.

Conclusion

Thats already it. Of course the other criteria have to be evaluated as well and the authors have several of their questionnaires in the appendix.

The topic indeed is cutting edge, since there is not yet any literature on supply chain strategy evaluation.

Maybe the authors also already gave the reason for this lack of literature: Several studies already found that only less than 50% of the companies actually have a supply chain strategy.

But using this concept and these methods is a great way to make the supply chain strategy explicit and documented and evaluate it in the process as well!

Reference:

Perez-Franco, R., Singh, M., & Sheffi, Y. (2011). An approach to evaluate a firm’s supply chain strategy as a conceptual system International Journal of Production Economics

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Diversification under Yield Randomness in Inventory Models

Daniel Dumke — Mon, 03 Oct 2011 10:20:00 +0000

I haven’t really touched on the early research on risks in supply chain management. One major stream is on random yields. Parlar and Wang (1993) were one of the firsts to extend the classic Newsboy and EOQ (Economic Order Quantity) models to include uncertainty.

Models

Both models calculate the optimal inventory while including different cost factors (like setup cost for ordering, inventory holding cost) and decision variables (order volume and order timing).
As an extension the Newsboy problem also includes random demand.

Parlar and Wang now extended these models by a second raw material source and making the availability random of both sources. In this case the yield of the supplier is represented by a exponential distribution with two independent expected yield and standard deviation for both suppliers.

Results

An example of some numerical calculations done on the EOQ model is represented in figure 1.

Figure 1: Cost Function depending on the Quantities ordered (Parlar and Wang, 1993)

For both problems the authors find ways to calculate the optimal order decisions (figure 2, for the EOQ model). But they also admit that solving the newsboy problem required some extra effort and any addition to the model (like a third supplier) would make it even harder to solve.

Figure 2: Optimal Order Quantities for EOQ Model (Parlar and Wang, 1993)

Conclusion

These are operational models and they can and should be applied for operational decisions in inventory management and purchasing. But on the other hand they are also very abstract leaving many parameters out and (according to the authors) being hard to extend.

Reference:

Parlar, M., & Wang, D. (1993). Diversification under yield randomness in inventory models European Journal of Operational Research, 66 (1), 52-64 DOI: 10.1016/0377-2217(93)90205-2

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Managing Disruption Risks using Real Options (SCRM Thesis)

Daniel Dumke — Mon, 26 Sep 2011 13:17:00 +0000

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

Author / Topic

This thesis was written by Sophie Pochard already in 2003 as her master thesis at the Massachusetts Institute of Technology, Cambridge, USA. It can be downloaded here directly at the MITs web site. It has been supervised by Richard de Neufville, Professor of Engineering Systems and Civil and Environmental Engineering. The title is: Managing Risks of Supply-Chain Disruptions: Dual Sourcing as a Real Option.

Summary

In her thesis Pochard focussed on multi-sourcing as sole risk mitigation strategy. But first the author elaborates on how resilience in a company can be achieved and more interestingly some limitations to resilience with a focus on dual sourcing, which are:

Complexitiy, increasing resilience often also increases the complexity of the supply chain (eg. dual sourcing).
Risk trade offs, having only a single supplier can also reduce risks (eg. protection of intellectual properties).
Cost issues, resilience often increases cost.

To analyze multiple sourcing strategies Pochard then introduces real options, where the definition is similar to that of a financial option contract:

Call options give to their holder the right to undertake an investment, at a cost that is fixed in advance (the exercise price), at or before a given date (the maturity). For example keeping unexploited leases can be assimilated to a call option. Oil companies do not sell or exploit these leases as they want to keep the right to develop them later on; they may, for example, decide to use this right if ever new drilling and production technologies allow to increase recoverable reserve. This is a call option since the exploitation makes it possible to get the income of the underlying. Its exercise price is the investment cost to initiate the production, and the maturity is simply the date until which firms have the authorization to exploit.

So as the next step dual sourcing is modeled as a real option. And the author presents her results in several diagrams where I show three here in the blog (figures 1 and 2).

Figure 1: Strategy Selection depending on Disruption Frequency (Pochard, 2003)

Figure 2: Sensitivity Analysis based on the Price of the local Supplier (Pochard, 2003)

Both independent variables (disruption frequency and cost of local supplier in case of disruption) seem to have a major impact towards the selected strategy. Pochard concludes that the real options can be a valid method to analyze the benefits of different strategies.

Conclusion

I think that her thesis can be used as a basis for a variety of topics. She writes about disruption risks, resilience and risk mitigation strategies, of course the definition of real options and how to develop and deploy a corresponding model.
I also think that this variety is also the major weakness of this work. Compared to my last MIT master thesis (Impact of demographics on supply chain risk management practices) Pochard takes a very long time to get to the real topic and browses a long time through other connected fields.
Nonetheless the results are very interesting and seem to be comparable to other (later) papers.

Reference:

Pochard, S. (2003). Managing Risks of Supply-Chain Disruptions: Dual Sourcing as a Real Option Massachusetts Institute of Technology, Master Thesis

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