Risk, reliability, costs and efficiency

In the article, the authors test the vulnerability of three typical supply chain structures:

• single source
• multiple source
• multiple single source

using these four parameters:

• structural reliability
• consequence score
• organizational costs
• process efficiency
• risk index

The structural reliability parameter follows the traditional reliability setup:

Finding these probabilities, though, is not an easy task in a supply chain with potentially tens, if not hundreds of suppliers.

The consequence score establishes the parameter for evaluating the impact of a supply chain disruption:

The range of the consequence score is between 0 and 1 , because if δ_replace is larger than δ_collapse, the supply chain ceases to exist, and the authors suggest the following categorization for evaluating the consequences:

The organizational costs are straightforward economic terms:

The process efficiency is simply a ratio of interactions:

Finally the risk index, perhaps the most intricate equation, with the most unknowns that are presumed known:

Before calculating these parameters, the following assumptions must be considered:

Each subproduct group is providing the same amount of support to the supply chain.

All suppliers with a subproduct group are independent and non-identical.

All customers are independent and non-identical. All suppliers within a subproduct group are providing the same amount of support to the supply chain.

Processing costs for an interaction is equal to one unit of cost for each firm and structure.

There is no reliability growth.

How often does this hold true in a real supply chain?

Anyway, after running through a scenario of 10 different supply chain configurations the authors discover (not all surprising) that

There is a significant reduction of risk associated with having more than one supplier per subproduct or service.

Adding subproduct diversification does not affect risk, but improves the structural reliability of the supply chain.

The structural reliability of the supply chain increases when the number of suppliers providing the same subproduct or subservice increases.

Coordination costs decrease when the number when the number of suppliers providing subproducts or subservices decreases.

Coordination efficiency increases when the number when the number of suppliers providing subproducts or subservices decreases.

Essentially, the results indicate that excessive diversification is counterproductive, and that there are indeed limitations  as to what can be gained from outsourcing.

Critique

What I enjoy most about the approach these authors use, is how they combine several separate fields of research, i.e. reliability, economics, and operations, into seven equations that make four parameters. I wish I had come up with something similar in my previous attempts at establishing a measure of reliability and vulnerability in transportation networks. In a way they are only echoing what Smith and Buddress wrote in 2005, who said that

Supply Chain Management needs a new way to pursue research, a new way that is focused on theory building based on learned borrowing from other disciplines.

As James Stock wrote in 1997, Broader research makes better research, something Neureuther and Kuhn prove to the full. That said, the model hinges on a lot of assumptions, let alone probabilities, which have to be established or guesstimated first. That done, this model is – in my humble opinion – an excellent tool for exploring supply chain vulnerability.

Reference

Neureuther, B., & Kenyon, G. (2009). Mitigating Supply Chain Vulnerability Journal of Marketing Channels, 16 (3), 245-263 DOI: 10.1080/10466690902934532

Author links

• linkedin: Brian D Neureuther
• lamar.edu: George Kenyon

Related

• husdal.com: Reliability and vulnerability, a matter of cost and benefit?
• husdal.com: Broader research = better research?
• husdal.com: SCM – the new research cocktail?

Do we really need to study disaster supply chains?

The timely delivery of critical goods has always been a crucial element of an effective disaster response, but an effective disaster supply chain is hard to create and maintain, and in their efforts to improve humanitarian supply chains, practitioners have enjoyed only limited help from academics. However, the challenges of disaster supply chain management are rapidly gaining attention in both practitioner and academic circles, and here is a growing number of disaster and crisis management students, but these scholars have paid little or no attention to supply chain issues. The scholars who study supply chains have paid little attention to the special challenges that disaster and crisis pose. This special issue attempts to bring these two worlds together, and as far as I am concerned, they have done an excellent job at at it.

Well worth reading

Here is a rundown of the 13 articles, with links to the publisher’s website, or to my own review.

Resilient supply chains for extreme situations: Outlining a new field of study
In this introductory article, the editors of this issue, Arjen Boin, Peter Kelle, and D. Clay Whybark sketch the contours of this new field. We begin with a brief overview of crisis and disaster management studies, which helps us understand the special challenges that these adverse events pose to supply chain managers.

All the best laid plans…conditions impeding proper emergency response
Céline Thévenaz and Sandra L. Resodihardjo kick the special issue off with an overview of “disaster barriers”—the political-administrative factors that make it hard to organize an effective response. Drawing from a rich body of empirical and theoretical research literature, they check their findings against two recent disaster cases (the 2004 Asian tsunami and Hurricane Katrina).

Coordination in humanitarian relief chains: Practices, challenges and opportunities
Burcu Balcik, Benita M. Beamon, Caroline C. Krejci, Kyle M. Muramatsu, and Magaly Ramirez discuss one of the most pertinent challenges: the coordination of actors in providing humanitarian relief. They review the literature and describe current practices. Intriguingly, they explore what can be learned from general supply chain coordination mechanisms in order to enhance the coordinative capacity of disaster supply chains.

The application of “swift trust” to humanitarian logistics
Peter Tatham and Gyöngyi Kovács consider an important factor in effective coordination: they examine how “swift trust” forms in hastily formed networks. Where trust is prominent, coordination becomes a matter of course. The authors explore under what conditions “swift trust” arises and what can be done to enhance its emergence.

Private goods and services contracts: Increased emergency response capacity or increased vulnerability?
M. Jude Egan addresses one of the most frustrating problems in building disaster supply chains: the legal necessities for securing (and relying on) key contributions of private firms. In his legal analysis, he investigates why seemingly logical and functional collaborations do nevertheless fail when they are needed most. This appears to be quite the opposite of this article on community resilience through private-public-partnerships.

Implications of organizational culture for supply chain disruption and restoration
Rachel A. Dowty and William A. Wallace offer a theoretical perspective for understanding supply chain failures. They build on two painful sagas. One is of an ice truck driving through the southern region of the US unsuccessfully trying to deliver to the victims of Hurricane Katrina. The other is of the failure on the part of the World Food Program delivering maize in South Africa. They “retool” cultural theory to help us understand how these failures could have happened.

Inventory decisions for emergency supplies based on hurricane count predictions
Selda Taskin and Emmett J. Lodree Jr. address the inventory control problem that is often encountered during hurricane preparation: what and how much to buy if you do not even know if the hurricane will hit.

Stochastic optimization of medical supply location and distribution in disaster management
Huseyin Onur Mete and Zelda B. Zabinsky develop a stochastic approach for the storage and distribution problem of medical supplies. Both contributions mark hopeful progress in the use of theory to enhance disaster preparedness.

An analysis of the Cyclone Larry emergency relief chain: Some key success factors
Richard Oloruntoba studies the Australian response to Cyclone Larry. He pays specific attention to the role of the Australian military, which proved a key to the successful response.

The Yogyakarta earthquake: Humanitarian relief through IFRC’s decentralized supply chain
Aline Gatignon, Luk N. Van Wassenhove and Aurélie Charles provide an in-depth study of the International Federation of Red Cross and Red Crescent Societies (IFRC) response to the Yogyakarta earthquake. This contribution documents the history of IFRC’s development of a decentralized disaster supply chain approach and explains why it worked so much better than a centralized approach.

Waffle House Restaurants hurricane response: A case study
Özlem Ergun, Jessica L. Heier Stamm, Pinar Keskinocak and Julie L. Swann highlight the performance of the Waffle House chain in the southern US states. Through intricate preparation, this restaurant chain manages to have its kitchens up and running within hours after a hurricane hits. The authors probe the organizational practices that allow for this effective response.

Assessing the vulnerability of supply chains using graph theory
Stephan M. Wagner and Nikrouz Neshat offer a new method to assess the vulnerability of supply chains.

Measuring the efficacy of inventory with a dynamic input–output model
Kash Barker and Joost R. Santos describe a model for assessing productivity degradations due to disasters. More specifically, the model helps to assess how different risk management approaches for inventories will affect the resilience of disrupted interdependent systems

Conclusion

So far, I’ve only read a few of the articles, but they have not let me down. While disaster management can learn a lot from supply chain management, so can supply chain management learn a lot from disaster management.

The Logistics Uncertainty Pyramid Model

The logistics uncertainty triad or logistics uncertainty pyramid model was first discussed in the authors’ 2008 paper on Establishing a transport operation focused uncertainty model for the supply chain, and was featured on this blog almost three months ago.

The figure above, taken from said article, describes what the authors define as the causes for uncertainty in the supply chain:

• Shipper
• Customer
• Carrier
• Control systems
• External uncertainties

Using a focus group the authors now go about exploring this concept further, by categorizing and mapping the occurrence of individual factors within the above groupings of causes.

Causes of transport uncertainty

The focus group survey then leads to four clusters of uncertainty causes:

• Delays
• Demand and inventory issues
• Lack of coordination
• Delivery constraints

The figure below shows the interlinkage between the causes and clusters.

Conclusion

In my opinion, the Logistics Uncertainty Pyramid Model is an excellent tool that can be used to identify issues of uncertainty, and then map these issues against their sources, from which improvements plans can be developed. As to supply chain uncertainty, this is among the most practically applicable tools I have come across recently. This article is the second stage in the authors’ efforts to develop a framework for analyzing what they define as the causes for uncertainty in the supply chain, and I look forward too seeing their next article.

Reference

Sanchez-Rodrigues, Vasco, Potter, Andrew, & Naim, Mohamed M. (2010). Evaluating the causes of uncertainty in logistics operations International Journal of Logistics Management, 21 (1), 45-64

Author links

• cardiff.ac.uk: Vasco Sanchez-Rodrigues
• cardiff.ac.uk: Andrew Potter
• cardiff.ac.uk: Mohamed Naim

Related

• husdal.com: Transportation – the staple of logistics
• husdal.com: Flexing your SCM muscles

Terminology definitions

The article attempts to define many of the common terms that any researcher in supply chain risk juggles daily, albeit “supply chain risk” itself is not defined; they only refer to a number of definitions in the literature, acknowledging that supply chain risks have to be considered from a wide and complex range of perspectives. Nonetheless, the develop a framework of how certain elements of supply chain risk contribute positively or negatively to the overall firm performance:

Here the authors identify security, resilience, risk, disturbance and disruption is key factors that need to be considered in supply chain risk management.

Implementing supply chain risk management

What I like about this article is what they call the roadmap towards supply chain risk management, where they define 17 principles, which, if taken in the right order, signal an evolution of a firm’s risk management from having none to full and integrated supply chain risk management:

The principles are as follows:

1. The focus of risk management is across company boundaries.
2. The company knows its supply chain in and out.
3. SCM and SCRM are seen as integrated and not independent from each other.
4. Internal RM and SCRM are coordinated and integrated.
5. SCRM is part of the overall corporate strategy.
6. Top management supports and is responsible for SCRM.
7. (All) actors in the supply chain have a mutual understanding of potential risks.
8. Risk information is available to (all) actors in the supply chain.
9. (All) actors in the supply chain have a close, cooperative and fair relationship.
10. (All) actors in the supply chain trust each other mutually.
11. Information asymmetries do not exist.
12. (All) actors take part in mutual goals and planning processes in the supply chain.
13. Risk information is exchanged between (all) actors in the supply chain.
14. Direct supply chain partners cooperate in their SCRM.
15. (All) actors in the supply chain share risks and the rewards achieved.
16. All actors in the supply chain are involved in SCRM, both internally and externally.
17. All actors in the supply chain aim at the same goals in SCRM.

These 17 principles can be applied to a 5-stage evolution like this:

1. No significant risk management activities in the supply chain
2. Risk management in procurement
3. Risk management in all supply chain activities, mainly restricted to tier 1 suppliers
4. Cooperative risk management with tier 1 suppliers, tier 2 and customers
5. Fully integrated supply chain risk management at all supply chain levels and connections

Note here that it it is possible for a company to be at different stages with different supply chain partners or to use different principles with different partners.

Conclusion

I may not subscribe fully to all principles or the five steps, but it does provide a framework or guideline for how to approach and assess supply chain risk management. Furthermore, the article provides insights and discussion of much of the seminal literature on supply chain risk, boosting some 68 references, many of which in German, though. I’m not sure I would agree with “state of the art”, but certainly a highly valuable contribution.

Reference

Pfohl, H., Köhler, H., & Thomas, D. (2010). State of the art in supply chain risk management research: empirical and conceptual findings and a roadmap for the implementation in practice Logistics Research, 2 (1), 33-44 DOI: 10.1007/s12159-010-0023-8

Author links

• tu-darmstadt.de: Hans-Christian Pfohl
• tu-darmstadt.de: Holger Köhler
• tu-darmstadt.de: David Thomas

Related

• husdal.com: SCRM – a complete review?

Resilience. That seems to be the buzzword these days. It seems to be making its way not only around the blogosphere, like on Ken Simpson’s blog, but also in the supply chain and logistics literature. In Ensuring supply chain resilience: Development of a conceptual framework, just out in the Journal of Business Logistics, Timothy J Pettit, Joseph Fiksel and Keely L Croxton develop a concept of supply chain resilience based on an extensive literature search and a focus group study. And quite frankly, this is one of the the better and most comprehensive frameworks for understanding resilience that I have seen, drawing on the quintessence of many years of supply chain risk research. Resilience, in essence, is bridging vulnerabilities by honing capabilities.

It started with a PhD

Like so many other seminal articles, this one too started off with a PhD. Timothy J Pettit was awarded the Doctoral Dissertation Award Winner by the Council of Supply Chain Management Professionals CSCMP for his dissertation titled Supply Chain Resilience: Development of a Conceptual Framework, an Assessment Tool and an Implementation Process, which forms the basis for much of this article. It is well worth reading the dissertation for a fuller understanding of the article.

Resilience

The authors start out their discussion of resilience by quoting three definitions or approaches to resilience and their thoughts on these, and it is the combination of these approaches that makes up their view of resilience.

First, the traditional engineering approach:

“the tendency of a material to return to its original shape after the removal of a stress that has produced elastic strain”

It may be beneficial for a supply chain not to return to its original shape following a disruption, but rather to learn from the disturbance and adapt into a new configuration.

This is something can be clearly seen in Sheffi’s disruption profile that has been mentioned time and again on this blog, where any disturbance will have a long-term effect.

Then the ecological approach:

“the ability for an ecosystem to rebound from a disturbance while maintaining diversity, integrity, and ecological processes”

The concept of adaptability is crucial to living systems, and supply chains may be seen as a network of living systems.

The supply chain life cycle is not a new concept, but it is nice to see an article picking up on a notion  and referring to the same article that I used in my book chapter on Virtual Enterprise Networks.

Finally, the organizational approach:

“more than education, more than experience, more than training, a person’s level of resilience will determine who succeeds and who fails”

Creating resilient leaders “is the best way to ensure that your organization will prosper in a very chaotic and uncertain future,” and those resilient organizations consistently outlast their less resilient competitors.

Resilient leaders may not be at the forefront of the New Zealand research project on Resilient Organisations, but resilient leaders will not be tempted to stick their heads in the sand, as Alex Fullick writes about.

The resilience model

Two postulations and five propositions form the resilience model:

1. Forces of change create supply chain vulnerabilities. Supply chain vulnerabilities are the fundamental factors that makes an enterprise susceptible to disruptions.
2. Management controls create supply chain capabilities. Supply chain capabilities  are attributes that enable an enterprise to anticipate and overcome disruptions.
3. Supply chain resilience increases as capabilities increase and vulnerabilities decrease.
4. Linkages exist between each vulnerability and a specific set of capabilities that can directly improve balanced resilience.
5. Excessive vulnerabilities relative to capabilities will result in excessive risk.
6. Excessive capabilities relative to vulnerabilities will erode profitability.
7. Supply chain performance improves when capabilities and vulnerabilities are more balanced.

Graphically it looks like this:

I find this a very simple, yet extremely elegant model, where the basic assumption is that capabilities must match, and where an overinvestment in capabilities (that are useful but not needed) will erode profits just as much as a lack of capabilities (that should have been there, but that have been neglected)  will increase the exposure to risks.

Vulnerabilities and capabilities

Seven factors that influence vulnerability and fourteen capability factors were further analyzed using a focus group. First, the vulnerability factors, in order of importance:

• Turbulence
  • Frequent and uncontrollable changes in the external environment
• Deliberate threats
  • Intentional attacks in order to cause harm
• Connectivity
  • Degree of interdependence and reliance on outside entities
• Sensitivity
  • Importance of carefully controlled environments for product integrity
• Resource Limits
  • Constraints on output because of unavailability of input
• Supplier/customer disruptions
  • Susceptibility of suppliers and customers to outside forces
• External pressures
  • Influences that create constraints or barriers

Likewise, factors that influence capabilities:

• Flexibility in order fulfillment
  • Ability to quickly change outputs or mode of delivering outputs
• Flexibility in Sourcing
  • Ability to quickly change inputs or mode of receiving outputs
• Organization
  • Human resources, policies and corporate culture
• Visibility
  • Knowledge of the status of operating assets
• Anticipation
  • Ability to discern future events or possibilities
• Recovery
  • Ability to return to normal operational state rapidly
• Security
  • Defense against deliberate attack
• Capacity
  • Ability to sustain or increase production levels
• Collaboration
  • Ability to work with other entities for mutual benefit
• Dispersion
  • Distribution and decentralization of assets
• Financial strength
  • Ability to absorb fluctuations in cash flow
• Efficiency
  • Ability to produce outputs with minimum resource requirements

While the two first capabilities are no surprise, I find it interesting that efficiency ranks low since I would expect the presence of minimal resources during a disruption, i.e. make do with what you have. On the other hand, in such circumstances, flexibility is probably more important, and rightly so. Note also that financial strength is not a prerequisite for resilience.

I highly recommend my readers to view the complete survey and results in the aforementioned PhD dissertation on Supply Chain Resilience by Timothy J Pettit.

Where to find what

Two things are great about this article

For the supply chain professional, the list of vulnerability and capability factors is of great help when analyzing one’s own resilience, and thus managerial implications.

For the supply chain academic, the same factors are also listed with their matching literature reference, making it easy to find out which author that describes what.

This is why I instantly fell in love with this paper and why I decided to review it as soon as I learned about its existence today.

Conclusion

Seldom have I seen such a comprehensive yet to the point article on supply chain resilience that satisfies both academia and the industry at the same time. Usually the weight is on either industry or academia. For sure, this will become one of the articles that I will refer to in my reference lists time and again in my future writings.

Reference

Pettit, T J, Fiksel, J, & Croxton, K L (2010). Ensuring supply chain resilience: Development of a conceptual framework Journal of Business Logistics, 31 (1), 1-21 ProQuest document ID: 2020607081

Author links

• afit.edu: Timothy J Pettit
• osu.edu: Joseph Fiksel
• linkedin.com: Keely Croxton

Downloads

• cscmp.org: Supply chain resilience: Development of a conceptual framework, an assessment tool and an implementation process
  (PhD dissertation by Timothy J Pettit)

Related

• husdal.com: Resilience revisited

Purchasing theory… I have to admit it’s not one of my particular strongholds, but several of my readers and commenters have mentioned this article, most recently in a comment on A future research agenda for supply chain risk management, so I thought that perhaps I should have a look at it. After all, supplier relationships have been on my blog time and again , so why not? In their 2005 article  Risk-based classification of supplier relationships by a Finnish quartet from the Lappeenranann University of Technology, Jukka Hallikas, Kaisu Puumalainen, Toni Vesterinen and Veli-Matti Virolainen set out to develop a new classification scheme for suppliers, based on buyer dependency risk and supplier dependency risk.

Organizational learning

How do risks in supply relationships and and organizational learning play out in risk management?   The idea is that supply chain partners collaborate as a response to uncertainty in the supply and in consequence develop a learning supply chain, in which they share information. While collaboration obviously has a benefit, there is also the risk of collaboration partners behaving opportunistically, since all firm are snakes, according to Cousins (2002). Supplier risk management needs to balance both sides of the scale.

How to classify supplier relationships

The literature generally acknowledges two approaches, the continuum approach and the portfolio approach. The continuum model typically arranges suppliers along a scale or degree of collaboration, e.g. Kampstra et al (2006), while the portfolio model divides suppliers along types of items purchased, e.g. Kraljic (1983), which is a paper I have long planned to but never gotten around to review on this blog.

The supplier’s perspective

The portfolio model appears to be more widely used, so the authors say, but it has its limitations. Firstly, it can become very complex and difficult to manage if the number of against it is that it neglects the supplier’s perspective, i.e. before entering a relationship with a supplier, a company should also consider how this relationship will affect the supplier, something I find an interesting statement. But, there are reasons for why the supplier, not just the buyer, needs to be part of the equation.

Transaction cost economics to the rescue

Why is the supplier’s perspective important? Because supply chains are no longer chains, but a web of interconnected networks, where one depends on the the other(s), many depend on one, or many depend on many. A strand of purchasing and supply research that captures this is the transaction cost approach, where benefits and risks vary according to the type of business relationship.

Sources of risks

Hallikas et al define four groups of risks in a transaction cost context

• asset-specific “hold-up”-risk
  • the higher the asset specificity, the greater the danger for opportunism
• market-related “inefficiency” risks
  • the more buyer/suppliers there are, the lower the transaction cost
• knowledge-related “spill-over” risk
  • the more appropriable new knowledge is, the easier it can be shifted from one to the other
• time-related “timing” risks
  • the greater the difference in planning horizon, the higher the risks of networking

There are other risks in collaborative relationships, but the above are the most dominant.

Case study

In a case study, involving a Finnish OEM, Hallikas et al found that supplier relationships fell into three clusters, as seen in he figure below.

Interestingly, none of the relationships were characterized by a high buyer, but low supplier dependency, meaning hat supplier can chose between buyers, but the buyer has only one supplier. This could be caused by the selection of suppliers, or it could actually be that this is the case in the real world. hat do you think?

Parameters used

What I found very interesting with this paper were the parameters or variables used to describe risks, organizational learning and risk management, in order to underpin the above framework.

• Risks
  • Hold-up risk
  • Demand risk
  • Replaceability
• Risk management
  • Measurement criteria
  • Fault management
  • Innovativeness
  • Prioritization
  • Protection of intellectual property
  • Communication
• Learning
  • Strategic double loop
  • Operational single loop
  • Operational double loop
• External factors
  • Value added to customer
  • Number of shared customers

In particular, the risk management factors are worth noting:

The first factor, measurement, refers to the mutual measurement of collaboration and the common striving for total cost reduction. The second factor, fault management, concerns joint quality and cost control, and the third factor is innovativeness, indicating the mutual development of new products and business areas and other innovations. Fourthly, prioritization of deliveries refers to delivery times, inventory control and contract management. The fifth risk management means include the protection of relationship-related knowledge and sixth, the amount of formal and informal communication.

What struck me though, was this

The suppliers stated that the most significant means were fault management and innovativeness, while reliability of deliveries and protection of knowledge appeared to be the least widely used.

I would argue that the least widely used are as important as the other.

Conclusion

As I stated in the very beginning, purchasing theory is not one of my particular strongholds, and I’ve never looked at it as a tool for researching and expressing supply chain risks, since the risks have been what has mattered to me. This paper however, is about to have me reconsider my attitude towards this strand of supply chain management, as I can see a clear link between transcations costs and risks and benefits in the supply chain. While perhaps not a direct reason for supply chain disruptions in transportation networks, which is what my own research is concerned with, I can see how supplier relationships, collaboration and organizational learning can make a difference  in how organizations are able to handle actual disruptions, i.e. the potential for contingent and mitigative risk management.

Reference

HALLIKAS, J., PUUMALAINEN, K., VESTERINEN, T., & VIROLAINEN, V. (2005). Risk-based classification of supplier relationships Journal of Purchasing and Supply Management, 11 (2-3), 72-82 DOI: 10.1016/j.pursup.2005.10.005

Author links

• lut.fi: Jukka Hallikas
• lut.fi: Kaisu Puumalainen
• lut.fi: Toni Vesterinen
• lut.fi: Veli-Matti Virolainen

Related

• husdal.com: Friend or foe or both?

A perfect title

In the beginning I thought the title to be a bit dull. Nonetheless, the title contains the essence of the article, and after reading it, it has indeed made it clear to me what risk is, how to understand it, and what is necessary to fully describe what goes into a risk assessment.

Risk assessments are imperfect

The starting point for the paper is that the common risk perspectives that describe risk using probabilities combined with events and consequences are too narrow, because probabilities are imperfect tools for expressing uncertainties, since the assigned probabilities are conditioned on a number of assumptions and suppositions that leave out possible surpises and unknowns, effectively creating Black Swans.

Eight common risk definitions

The article provides a list of eight risk definitions, discusses these and then suggests an alternative definition that does capture uncertainty in perhaps a better fashion than the more traditional definitions. For the sake of simplicity I will omit the discussions, and highlight the essence of the article.

First, here are some common definitions of risk:

1. Risk is a measure of the probability and severity of adverse effects.
2. Risk is the combination of probability of an event and its consequences.
3. Risk is equal to the triplet (s_i, p_i, c_i), where s_i is the i^th scenario, p_i is the probability of that scenario, and c_i is the consequence of the i^th scenario, i=1,2,y, N.

The common thread for these definitions is that they relate to initiating events or actions, consequences and probabilities or uncertainties, formalised as

Risk = (A, C, U).

The question is, does this really capture risk?

Is (A, C, P) an adequate description of risk? Are probabilities able to express the uncertainties, about the events and consequences? A probability is a way of expressing to what extent an event or consequence is likely to occur, but what does this mean?

Probability is the keyword to understanding Aven’s article. Probability can be either

• a relative frequency or hypothetical occurence of an event or action if a situation in which it may or may not occur is repeated infintely, or
• a subjective measure of uncertainty, based on prior knowlegde and conditional circumstances

The former produces best estimates of “true” risk. However, it is impossible to now the accuracy of the estimates, and thus it is impossibe to assess the correct risk. The latter assigns probability based on uncertainty, without referring to and thus eliminating probability.

A probability is always conditional on a background knowledge, and given this background knowledge there is no uncertainties related to the assigned probability, as it is an expression of uncertainty.

Consequently, many other descriptions of risk have incorporated uncertainty into their definition:

1. Risk refers to uncertainty of outcome, of actions and events.
2. Risk is a situation or event where something of human value (including humans themselves) is at stake and where the outcome is uncertain.
3. Risk is an uncertain consequence of an event or an activity with respect to something that humans value.
4. Risk is equal to the two-dimensional combination of events/consequences and associated uncertainties.
5. Risk is uncertainty about and severity of the consequences (or outcomes) of an activity with respect to something that humans value.

Note the lack of probability in these definitions.

Two risk perspectives

In summary, two perspectives can be discerned:

Risk=(A, C, P_f), where P_f is a relative frequency-interpreted probability (or a related parameter such as the expected number of occurrences of the event A per unit of time, where the expectation is with respect to a relative frequency-interpreted probability).

Risk=(A, C, U), where U is the uncertainty about A and C (will A occur and what will the consequences C be?), including uncertainty about underlying factors influencing A and C.

According to Aven, these two schools of thought, probability versus uncertainty, is what pervades much of today’s risk research.

An alternative definition of risk

Are there irreconcilable differences between these two schools of thought? Perhaps not, because Aven suggests the following definition:

Risk description = (A, C, U, P, K)

where P is a subjective probability expressing U based on the background knowledge K. This description covers probability distributions of A and C, as well as predictions of A and C, for example a predictor C* given by the expected value of C, unconditionally or conditional on the occurrence of A, i.e. C*=EC or C*=E[C|A]. A sensitivity analysis constitutes an integral part of the risk description.

Not only does this synthesize both perspectives, objective risk is replaced by a description of risk.

Conclusion

This is indeed one of the better papers that I have read on risk. Those of you who follow my blog will know that I am a qualitative researcher with little or no inclination towards the quantitative. That is why you will never find a purely quantitative paper on my blog. The reason why I liked this paper is that it so elegantly combines the qualitative with the quantitative, by upholding the quantitative, but stating that it must be qualitatively judged. In my opinion, Aven’s alternative and comprehensive definition of risk truly captures all aspects of risk.

Reference

Aven, T. (2010). On how to define, understand and describe risk Reliability Engineering & System Safety, 95 (6), 623-631 DOI: 10.1016/j.ress.2010.01.011

Author link

• uis.no: Terje Aven

Related

• husdal.com: Risk versus vulnerability
• husdal.com: Really risky or just uncertain?

Supply chain components

A disaster affects a supply chain by affecting one or more of its components. These components  are either internal or external to the supply chain, and can be classified as belonging to the following realms or contributors to the functioning of the supply chain:

• Transportation
• Utilities/Equipment
• Communication
• Suppliers
• Customers
• Labor
• Finance

Stecke and Kumar only see two sides of the supply chain, the internal side and the external side. While I find this a simplification of Christopher’s supply-demand-process-enviroment framework for supply chain risks, it is still valid.

What I find interesting is the selection of components they have attached to the supply chain; very few papers I have seen have included transportation or finance and labor in the equation.

Vulnerability factors

Current supply chain trends have made supply chains more efficient, but unfortunately also made supply chains more vulnerable, so says Martin Christopher in his book chapter on supply chain risk:

• The trend towards just in time and lean practices
  >>> efficiency rather than effectiveness
• The trend towards reducing costs
  >>> globalization, more complex and longer supply chains
• The trend towards economies of scale
  >>> centralized distribution and manufacturing
  >>> lower costs, but also less flexibility
• The trend towards outsourcing of non-core business activities
  >>> loss of control when it is most needed
• The trend towards consolidation of suppliers
  >>> increased potential for wider impacts of disruptions

Stecke and Kumar add to this list by identifying

• Globalization
• Decentralization
• Outsourcing
• Sole sorcing
• Just-in-Time
• Product complexity
• Litigation

as key supply chain management practices that breed vulnerability by creating

• an increase in the number of exposure points
• an increase in distance and time
• a decrease in flexibility
• a decrease in redundancy

which in end may cause supply chain catastrophes.

Supply chain catastrophes

The list of possible supply chain disruptions reveals a penchant for Paul Kleindorfer’s catastrophic events or Nassim Taleb’s black swans; some of the examples used are:

• Terrorist attacks
  • Mass killings
  • Political assassinations
  • Sabotage of infrastructure
• Natural disasters
  • Earthquakes
  • Extreme weather
  • Epidemic
• Accidents
  • Industrial fire
  • Gas leakage
  • Train derailment
  • Plane crash
• Non-terrorist
  • Strikes and labor disputes
• Environment
  • Changes in rules and regulations
  • New technology

Terrorism or malicious attacks make up most of the list, and considering that global supply chains are increasingly sourcing from politically potentially unstable countries, they should rightly be at the top of the list.

Catastrophe mitigation

• Proactive strategies
  • Select safe locations
  • Chose robust suppliers and transportation media
  • Establish secure communication links
  • Enforce security
• Advance warning strategies
  • Enhance visibility and coordination
  • Increase transportation visibility
  • Monitor weather forecasts
  • Act according to terrorist threat level
  • Monitor trends
• Coping strategies
  • Monitor multiple facilities hat have flexible/redundant resources
  • Cary extra inventory
  • Arrange for alternative sourcing
  • Ensure flexible transportation
  • maintain redundant critical components
  • Redesign products to pool risks
  • Influence customer choice
  • Purchase insurance cover

While it does not appear in their reference list, much of the above can also be found in Christopher Tang’s Robust strategies for mitigating supply chain disruptions.

Benefits

The article also list some of the benefits of mitigating supply chain disruptions:

• Reduction of lead time and lead time variability
• Better inventory management
• Efficient production planning and forecasting
• Reduction of the bullwhip effect
• Increase in customer service
• Better demand management

Incidentally, this list is not so unlike the report on the collateral benefits of supply chain security by he IBM Center for the Business of Government.

Table, tables , tables

What I really like about this paper is the effort they have put into making systematic tables of how everything in supply chains relates to each other, where each factor is graded on a low-medium-high scale. First, there is a table relating each of the catastrophe types to the supply chain components, and the likelihood of impact and severity of impact on each component.

The second table looks at which mitigation strategy that works best when faced with which catastrophe.

The third table shows what impact each strategy has on each of the factors that breed vulnerability.

It is easy to lose oversight here, but nothing is left out, for sure.

Conclusion

This is indeed one of the most comprehensive papers I have found on supply chain vulnerability and mitigation strategies. While many of the suggestions in the tables are based on expert judgement, and thus subjective, I found it to be a sound expert judgement.  Although naming the strategies as mitigation strategies, many of them are just as much contingent as they are mitigative. This is a hands-on paper with significant managerial implications, clearly outlining and identifying a number of strategies and where they are applicable, making this a paper that perhaps is just as much or perhaps even more suited for a professional audience than an academic audience.   It is a paper that every supply chain manager should read, at least once.

Reference

Stecke, K., & Kumar, S. (2009). Sources of Supply Chain Disruptions, Factors That Breed Vulnerability, and Mitigating Strategies Journal of Marketing Channels, 16 (3), 193-226 DOI: 10.1080/10466690902932551

Author links

• utdallas.edu: Kathryn E Stecke
• linkedin.com: Sanjay Kumar

Related

• husdal.com: Mitigative and contingent actions
• husdal.com: Black Swan Events
• husdal.com: Managing risk in global supply chains

Back to the future

Actually, today’s review is the precursor of Aven’s 2009 article on safety and security critical systems that I reviewed earlier this year.  In fact, there is an even earlier precursor to today’s article, which I will come back to later, which means that Terje Aven will be among the more frequently reviewed authors here. He has indeed authored many fine articles on risk and how risk should be viewed and assessed – particularly in the journal of Reliability Engineering & System Safety.

Circular logic?

The article clearly set out a new framework for risk and vulnerability analysis. At times, though, it is difficult to read, and I’m not sure I fully understand the semantics. For example, my favorite quote from this article is this

Having defined risk, we can define risk analysis as an analysis of risk.

Right.

Even the definition of vulnerability is kind of circular:

A vulnerability is a feature or aspect of the system that is judged to give high vulnerability.

Anyway, semantics aside, in Aven’s article, vulnerability is linked to a system, e.g. power production systems, information and communication systems, and transport systems. Systems are exposed to situations or events, that may or may not lead to various consequences or outcomes (so-called observable quantities).  A source is a situation or an event with a potential of a certain consequence. Sources are defined as threats (malicious attacks, related to security), hazards (accidental events, related to safety), and opportunities (“harmless” events that present an opportunity for a threat or a hazard to materialize, e.g. a planned maintenance shutdown that does not go according to plan).

Risk is seen as the combination of possible consequences and associated uncertainties of what will be the consequences. Vulnerability is seen as as the combination of possible consequences and associated uncertainties, given a certain source. Risk is generic, vulnerability is specific.

Risk has vulnerability in it?

While Aven does separate risk and vulnerability, he also sees them as inextricably linked.

As vulnerability is a part of risk, a vulnerability analysis is a part of the risk analysis. [...] A risk and vulnerability analysis comprises source identification, identification of vulnerabilities, uncertainty assessments, and risk description.

Risk and vulnerability analysis

According to Aven, a risk and vulnerability analysis will normally consist of the following main steps:

1. Identify the relevant functions and subfunctions to be analysed, and relevant performance measures (observable quantities).
2. Define the systems to meet these functions.
3. Identify relevant sources (threats, hazards, opportunities).
4. Perform an uncertainty analysis of the sources.
5. Perform a consequence analysis, addressing uncertainties.
6. Describe risks and vulnerabilities.
7. Evaluate risks and vulnerabilities.
8. Identify possible measures, and return to 3.

Mind you, Aven notes

These steps follow in time, but should not be read as a strict time table. For example, having identified a source, a quick consequence analysis is often performed to see if this source represents a significant risk or should be excluded from further analysis. Hence step 5 comes before step 4, as a first run. There are also other iterations. For example, steps 4 and 5 may generate new sources, and the source list need to be updated. Information gathering is a part of the first five steps. The level of depth of the various analysis steps, would of course depend on the purpose and scope of the analysis.

The above list indicates that the analysis is primarily a qualitative analysis up to step 6, which is where the quantitative assessment begins. In describing the consequences, Aven suggests the following scheme:

(a) Potential consequences (outcomes)—represented by representative performance measures (future observable quantities) such as costs, income, production volumes, deliveries, loss of lives, etc.
(b) Ubiquity—which describes the geographical dispersion of potential damages. (c) Persistency—which describes the temporal extension of the potential damages.
(d) Delay effect—which describes the time of latency between the initial event and the actual impact of damage. The time of latency could be of physical, chemical or biological nature.
(e) Reversibility—which describes the possibility to restore the situation to the state before damage occurred.
(f) Violation of equity—which describes the discrepancy between those who enjoy the benefits and those who bear the risk.
(g) Potential of mobilization—which is to be understood as violation of individual, social and cultural interests and values generating social conflicts and psychological reactions by individuals and groups who feel inflicted by the risk consequences. The potential of mobilisation could also result from perceived inequities in the distribution of risk and benefits.
(h) The difficulty in establishing appropriate (representative) performance measures (observable quantities on a high system level).

The key question that now follows, is whether there are any uncertainties related to the above scenarios? How likely is a given scenario actually? How uncertain is the likelihood, i.e. are there many factors influencing the consequences, and what are these factors? Uncertainty thus becomes a determining factor in determining the actual risk. So basically, one must assess the expected value of consequences matched with their probability, as well as the uncertainty of the background information associated with consequences and likelihoods.

When is risk really risk(y)?

In the end Aven suggests a simple yet effective approach for summarizing the risk picture, where consequences (and their probabilities) are viewed dependent on the level of uncertainty that accompanies the assessment.

The risk levels in the table, so Aven says, must be read as a tendency, not as increasing values, and should be used as a starting point for further discussions, taking both the consequences and the uncertainties into full account. The table is not the answer, it is a tool for further handling of risk.

Conclusion

What this framework shows is that risk is ambiguous, ambiguous because uncertainties are part of the picture. Risk has two dimensions: a) Possible consequences and b) associated uncertainties. It also underlines that risk analysis needs to take on a broad perspective that acknowledges that there are uncertainties, that there might be different assessments of these uncertainties, and that there might be different ways of dealing with these uncertainties. In essence, this framework brings together both quantitative and qualitative values, and gives them weight, so that they can be used for decision support.

Reference

AVEN, T. (2007). A unified framework for risk and vulnerability analysis covering both safety and security Reliability Engineering & System Safety, 92 (6), 745-754 DOI: 10.1016/j.ress.2006.03.008

Author link

• uis.no: Terje Aven

Related

• husdal.com: Certain death – not risky. Uncertain death – risky

Many thoughts, one framework

The article approaches supply chain collaboration from a wide range of perspectives , in particular: the theory of constraints, and brings together many thoughts and ideas on how to collaborate and partner in a supply chain, and synthesizes these ideas into one interconnected framework that fully describes the inner workings of relationships in supply chains.

The key to achieving improved relationships will come through better understanding the ways that entities in supply chains work together.

First the authors define supply chain collaboration as one of many forms of linkages in the supply chain: 1) arm’s length, 2) collaboration, 3) partnerhsip, 4) joint venture and 5) vertical integration:

Arm’s length relationships are purely transactional without any collaboration, while partnerships are a special case of collaboration, and where joint ventures have  transcended from collaboration  into an extended linkage beyond collaboration. Vertically integrated supply chain actors no longer collaborate (pun intended), but act as one.

Then they define some of the approaches to supply chain collaboration: 1) dyadic, 2) channel integrator, 3) Fourth party logistics (4PL) and 4) vertical integration, which signifies the deepest relationship.

Collaboration: a matter of cost and benefit?

Supply chain collaboration is immensely popular both in business and academia, but paradoxically, most collaborative initiatives end up in failure. Why?

• No equality between partners
  • one dominates the other(s)
• Hampered by constraints
  • resources, policies or potential market outreach
• Only potentially collaborative
  • only if approached the right way
• Imbalanced priorities
  • short-term local cost-savings come before long-term overall effectiveness

A true collaboration is more than two or more entities working together. A true collaboration must be accompanied by a fundamental change in thinking, otherwise it will not succeed.

Collaboration: three loops

Collaboration involves constant change and alignment, time and again, something the authors illustrate using what they call the three loops of supply chain collaboration: 1) strategy, 2) change and 3) control.

The strategy loop involves 1) choosing strategic partners, 2) Identifying the appropriate supply chain strategy and 3) Aligning with the over overall corporate strategy for each potential relationship. The change loop consists of looking closer at reach relationship and then deciding 1) which entities that should change and 2) what that should change. The control loop governs and control the collaboration, as in 1) the transformational changes, and 2) the strategic objectives, and  3)  by allocating benefits and burdens among the parties involved.

Buying behavior versus supply path

In his book on Dynamic Supply Chain Alignment, John Gattorna identifies four types of supply chains, based on four types of customer behavior. This notion is present also in this paper, where, each buying behavior must be aligned with the matching supply path, creating a critical time path from supplier to customer, based on the CODP:

Here the authors say that

There are three types of capacities to be set: productive capacity to meet demand; capacity to protect against statistical fluctuation of the process; and excess capacity for quickly adapting to customer dynamics.

This leads to a focus on 1) supply chain design and 2) supply chain coordination.

Supply chain design: the locations, number, and the size of supply chain entities, where the right capacities and buffers should be positioned.

Supply chain coordination: risk control, production policies, replenishment policies and distribution policies.

With all this in place, supply chain collaboration is possible.

Levels of collaboration

Base don the above mentioned loops of collaboration implying a step-wise improvement of supply chain performance through collaboration the authors come up with a concept they call “the ladder of collaboration”:

The initial level of collaboration is “Communication” assuming there is no starting collaboration. The second level of collaboration is “Coordination,” which focuses on the coordination of intra- and inter-entity processes. The third level of collaboration is “Intensive  collaboration,” which implies increased involvement of the collaboration members to improve  the strategic management decision-making and enhance innovation in the chain. The fourth level of collaboration is “Partnerships,” which involves extended financial linkages, such as sharing of investments and profits.

I believe that one of the reasons that supply chain collaborations fail is that the collaborating parties want too much too fast, without fully engaging in a stepwise alignment.

Why do collaborations fail?

In summary, this is why collaborations don’t always work out as intended:

• Collaboration comes in many formats and will and should depend on the contextual situation.
• At some point in the collaboration the group will face a supply chain constraint that limits further collaboration.
• Supply chains or channels are not necessarily all collaborative, some are better left as is.
• Collaboration ends up in failure when the start is all wrong and when compromises cover irreconcilable differences.

Sidekick: Coperative strategy

According one of best books I have seen on this topic, Cooperative Strategy by Child, Faulkner, & Tallman (2005), traditional enterprises can enter into various forms of cooperation for a number of reasons: 1) certainty – by developing relationships , 2) flexibility – by being able to quickly allocate a range of resources, 3) capacity – by “outsourcing” work to other network members, 4) speed – by being able to quickly respond to a wide range of business opportunities, 5) skills and competence – by gaining access to resources other than one’s own, and 6) intelligence – by sharing market information. Placing cooperative networks on a scale, going from independent to integrated, five degrees of networks can be discerned: 1) Equal-partner network, 2) Unilateral agreements, 3) Dominated network, 4) Virtual corporation, and 5) Strategic alliance. This arrangement is not unlike the framework proposed by Kampstra, Ashayeri, & Gattorna, perhaps a sign of universal applicability of the model?

Sidekick: Roles in collaboration

The paper makes a point that supply chain collaboration implies that the parties involved establish roles as to who should manage and/or coordinate the collaboration efforts. Interestingly, their framework is very similar to the one I used in my book chapter on a conceptual framework for risk and vulnerability in virtual enterprise networks:

It’s funny, because I never thought of scouring the literature on supply chain collaboration when I wrote that chapter. had I done, I most certainly would have found and used this paper.

Critique

This paper is ripe with SCM acronyms, oops, I meant Supply Chain Management acronyms. Most of them are explained, but a couple are not.  For example, take a look at the supply-path-buyer-behavior-figure above…what is that CODP? While not explained in the paper,  I assume it relates to Customer Order Decoupling Point. Another not explained acronym used in the paper is DIFOT, presumed to mean Delivered In Full, On Time. Perhaps the authors, very familiar with these terms, asume that their readers are too? It’s a small glitch, but n annoying glitch, when you are trying to understand this paper. That said, I have seen far worse glitches in editorial review than this one.

Reference

Kampstra, R., Ashayeri, J., & Gattorna, J. (2006). Realities of supply chain collaboration The International Journal of Logistics Management, 17 (3), 312-330 DOI: 10.1108/09574090610717509

Author links

• johngattorna.com: John Gattorna
• tilburguniversity.nl: J AShayeri
• unknown: R.P. Kampstra

Related

• husdal.com: Dynamic Supply Chain Alignment
• husdal.com: Cooperative strategy