Disaster preparedness and recovery

The two recent earthquakes, first in Haiti, and then in Chile have made me think about supply chains and disasters. Most recently I reflected on public-private partnerships in disaster response and recovery and how resilience is a prerequisite for surviving disasters. My interest really started last year with the earthquake in Padang, Indonesia, where I highlighted that military and civilian supply chains must work side by side.

No bedrock

Because disasters and crisis situations are so hands-on and demand immediate action they are perhaps neglected by academia, and thus left to the professionals to sort it out. Or maybe not: This paper attempts to rectify this lack of theoretical foundation by developing a novel theoretical framework to support future research in supply chain disaster and crisis situations.

Four theories – one pyramid

The framework seeks to unite four theories by constructing a pyramide with 3 planes or sections, representing a perspective linking three of the four theories:

The three bases are made up of relationship management theories (collaboration), communications theory (communication) and competing values theory (contingency). The pyramid is topped by resource management as the capstone.

Collaboration

Because there are always multiple players in supply chain disaster and crisis situations, collaboration will be the glue that holds organizations together, particular if one considers the tangled web of the extended supply chain. This web is likely to provide ample research opportunities.

Communication

Supply chain disaster and crisis situations demand effective communication. Examining issues such as bi-directionality, formality, modality, and frequency will be of serious importance and provide fertile grounds for research as private and public entities attempt to understand what, when, how and how much to communicate.

Contingency

Contingency theory is based on the premise that things change, and no supply chain disaster will be like the other. One of the strongest supporting theories that could ground the contingency element is competing values theory, by suggesting that one can simultaneously pursue various different and conflicting strategic goals, regardless of the situation.

Resource management

Resources play a vital role in supply chain partnerships and it will be important to investigate how they are employed, how they are impacted and how they interact with other resources, particularly in disaster and crisis situations. That includes human resources, physical and technological resources, informational resources and financial resources.

Three research planes

The authors suggest three research areas, built on the three planes of the pyramids, i.e. the interconnections between the theories.

1 – the independents
resources – competing values – communication
How do firms re(act) as disconnected and disinformed individual organizations?

2 – the proactive partnership
resources – communication – relationship management
How can firms develop communication and collaboration?

3 – the co-opetition resource
resources – competing values – collaboration
How do firms grow their situational awareness balancing when to compete and when to collaborate?

Conclusion

Initially, I was a bit dissatisfied with the article as I was hoping for a practically relevant article, that developed a new framework based on disaster and crisis experience. However, this is a purely theoretically framework, but it is a framework that is well founded, based on the literature review. It will be interesting to see how many researchers pick up on this article and develop the suggested research strands. You can count me in…perhaps.

Reference

Richey, R.G. (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

Author link

• ua.edu: R Glenn Richey Jr

Related

• husdal.com: Public-private partnerships in disaster management
• husdal.com: Military and civilian supply chain collaboration

Flexibility

Why contingency in supply chains? Isn’t flexibility enough? While flexibility is often associated with simply being responsive or adaptive to customer preferences or quick to change to new markets, it also carries with it

the ability to encounter, resolve and exploit an unexpected emergency or opportunity

Flexibility thus becomes a strategic capability. This capability can be enhanced through contingency planning, but not all attributes of the contingency planning process contribute equally to the overall supply chain flexibility.

Contingency planning

Supply chain flexibility is what makes it possible to respond to an unpredicted and unexpected disruptive event in a successful manner. Since it is impossible to predict the exact nature and extent of disruptive events, the response must be generic and open-ended, in other words “flexible” or “contingent”. Contingency planning is thus a key strategic tool to achieve flexibility, as LaLonde writes in his 2005 essay on “Fiddling while Rome burns“:

Contingency planning is a special type of planning that provides a blueprint for responding to the risks associated with an unknown event. The contingency plan document should detail a timely and complete response to a specific risk or a cluster of risks. The specific processes embedded in the plan would depend on the nature of the risk. For example, the risk assessment for a retail operation would likely differ from that of a manufacturer or a transportation company. In general, the process part of the plan should include the following elements: risk assessment, risk evaluation and management, first response, collaborative management, subsequent stages of response, security, operations, stability, and performance evaluation.

While the “fiddling” obviously eludes to the alleged story that the Roman Emperor Nero was playing the fiddle while his capital city burned in AD64, there is a pun to it, as in fiddle = alter, adjust, or change in minor ways without any meaning, essentially: not doing what you were supposed to do, namely responding properly to the burning of the city. Here, a proper contingency plan will help eliminate the fiddling. Contingency planning is a risk management tool.

Hypotheses

The authors identify 10 contributing factors in the contingency planning process and test for whether these factors are positively related to flexibility:

Top management support. Without continuous commitment, support, patience and leadership from management, not much will develop in the lower ranks.

Goal alignment. The strategic goals must be aligned through strategy documents, corporate values, rules, procedures and resource allocation.

Resource alignment. Inter- and intra-organizational resources, if coordinated and aligned can increase flexibility.

Level of IT usage. Information Technology can assist an organization’s ability to generate, combine, capture, process and analyze various streams of information that vital to its survival.

Level of Information sharing. A successful planning process requires the willingness to make strategic and tactical data available across the supply chain.

System connectivity. Following Information technology and information sharing is the ability to connect and integrate different systems, facilitating seamless data exchange.

Comprehensiveness. This is only possible to achieve through an extensive evaluation of objectives and alternatives, risks and benefits at all levels of decision-making, throughout the organization.

Standardization. This entails the establishment of common policies and procedures, thus providing consistency in the way situations are handled.

Intra-organizational and inter-organizational collaboration. True collaboration will result in joint knowledge creation, sharing of expertise and understanding each others intention and strategic approaches to different situations.

Result

The result is – to my mind – perhaps a bit disappointing. Only these four factors in the contingency planning process are positively related to flexibility, according to the regression analysis of the survey performed by the authors:

1. Top management support
2. Resource alignment
3. Level of IT usage
4. Inter-organizational collaboration

Interesting. I would have expected more or all variables to be of importance in contingency planning for flexibility. At least, I would have thought so, judging from a seemingly complete review of supply chain flexibility literature in Babu and More (2008), and even more so from the discussion of the enablers of risk mitigation in Faisal et al. (2006)

Conclusion

It took me some reading to fully comprehend the message of the article. It is not supply chain flexibility that is center stage here. It is the contingency planning process…applied in a supply chain setting, aimed at generating flexibility from within. And is not the contingency plan that makes a supply chain flexible, it’s the contingency planning process that is important. As Dwight D. Eisenhower is supposed to have said

The plan is nothing, planning is everything.

If you have learned how to steer (through the planning process), you will be able to steer and navigate even in treacherous waters, applying flexibility where it is needed.

Reference

Skipper, J., & Hanna, J. (2009). Minimizing supply chain disruption risk through enhanced flexibility International Journal of Physical Distribution & Logistics Management, 39 (5), 404-427 DOI: 10.1108/09600030910973742

Author links

• afit.edu: Joseph B Skipper
• auburn.edu: Joe B Hanna

Downloads

• scmr.com: Fiddling while Rome burns

Related

• husdal.com: Risk disablers
• husdal.com: Supply chain flexibility – literature review

Classification framework

The classification framework of these authors differs considerably from that of Rao and Goldsby that I reviewed most recently. The source of a crisis is either internal or external. The scale of a crisis may affect a single company only, the whole or part of a supply chain, or may have wider and regional impacts. The stage of a crisis refers to the level of crisis management, akin to the definition used by FEMA: mitigation, preparation, response and recovery. The research methodology used in the literature is sometimes analytical, empirical, conceptual or applied. Finally, the respondents are divided into for-profit and not-for-profit (e.g. government) organizations, assuming that either organization puts a different value on crisis management.

• Source
  • Internal
  • External
• Scale
  • Company
  • Supply chain
  • Region
• Stage
  • Mitigation
  • Preparation
  • Response
  • Recovery
• Research method
  • Analytical
  • Empirical
  • Conceptual
  • Applied
• Respondent
  • For-profit
  • Not-for-profit

I find this a simple, yet comprehensive framework that fully captures and links supply chains and crisis management.

Insights

What are some of the insights and implications from the review?

• There is more research on external sources than internal sources
  • More needs to be done on internal sources
• There appears to be more research on the two proactive levels than the reactive levels
  • How to recover needs to receive more attention
• There is limited empirical research on how supply chain managers plan to handle crises
  • There is a need to develop scales for the right level of crisis management
• There is a clear lack of literature on not-for-profit supply chains
  • More research is needed for not-for-profit organizations
• Most of the research looks at crises from the perspective of a single member, while missing the wider picture
  • How does a supply chain crisis affect an entire region?
• Many of the models and solutions are developed for a specific crisis (or/and a specific company or industry)
  • What is needed is the development of more generic management tools

These are just some of the insights the authors wish to highlight. There’s a lot more in the article itself.

Critique

This is one of best reviews of papers on supply chain risk that I have seen until today. Kudos for an excellent job more than well done! That said, again, one of my favorite articles on how to prepare a supply chain for a crisis, The Severity of Supply Chain Disruptions: Design Characteristics and Mitigation Capabilities, has dipped below the radar horizon of the reviewers. Moreover, they also lamented the lack of papers on the wider picture, another one missed:  Reconciling supply chain vulnerability, risk and supply chain management. On the other hand, I have missed many of their articles. The biggest value of this paper, however,  lies in the appendix, where all 188 articles are neatly listed and classified, allowing researchers like me to find the exact factor I am interested in.

Reference

Natarajarathinam, M., Capar, I., & Narayanan, A. (2009). Managing supply chains in times of crisis: a review of literature and insights International Journal of Physical Distribution & Logistics Management, 39 (7), 535-573 DOI: 10.1108/09600030910996251

Author links

• tamu.edu: Arunachalam Narayanan
• tamu.edu: Ismail Capar
• tamu.edu: Malini Natarajarathinam

Related

• husdal.com: Supply Chain Risk literature review (Rao and Golsdby)
• husdal.com: A full literature review of Supply Chain Risk Management (Sørensen)
• husdal.com: Supply Chain Risk – a complete literature review? (Vanany et al.)

Interpretive structural modeling

Interpretive structural modelling (ISM) can be used for identifying and summarizing relationships among specific variables, also called “enablers”. ISM provides a means by which order and relationships can be imposed on such variables, thus categorizing the enablers according to their driving power and dependence.

Enablers of risk mitigation

Based on a solid literature review the authors come up with 11 enablers:

• Information sharing
  • More information means more visibility means less surprises
• Supply chain agility
  • Agility allows for faster adapting to changing circumstances without losing momentum
• Trust among supply chain partners
  • Lack of trust creates opportunism only
• Collaborative relationships among supply chain partners
  • Collaboration creates interdepence and the appreciation of flexibility and responsiveness
• Information security
  • Information is the most critical asset in the chain, so guard it
• Corporate social responsibility
  • Be prepared to manage the consequences of partners’ (wrong) policies
• Aligning of incentives and revenue sharing policies
  • Everybody’s interest must be served, not just one’s own
• Strategic risk planning
  • The supply chain is a strategic asset, not just an operational necessity
• Risk sharing
  • Both risks and rewards need to be distributed evenly throughout he chain
• Knowledge about risks in the supply chain
  • Risk understanding improves decision-making
• Continuous risk analysis and assessment
  • Business environments are dynamic, so are the risks

I cannot think of anything else, can you?

Dependant versus driver matrix

Similar to the later article on information risks management, the authors end up with a matrix showing the interrelations among the enablers, based on their dependency and driving power.

The enablers are further classified as

(1) Autonomous enablers (Southwest quadrant)
(2) Dependent enablers (Southeast quadrant)
(3) Linkage enablers (Northeast quadrant)
(4) Independent enablers (Northwest quadrant)

Autonomous enablers have a weak driver power and weak dependence. These enablers are relatively disconnected from the system. Linkage variables work both ways; they affect the enablers above and are at the same time dependent on the enablers below. Independent variables have a strong driver power and weak dependence. Dependent enablers are dependent on the other variables.

Conclusion

Interestingly, in this paper, the dependent enablers with the least driving force are seen as key enablers, while in the paper on information risks, the independent enablers are seen as the strongest contributors towards risk mitigation. Confusing at first, perhaps, but it depends on your point of view. Most important however, is that the interpreted structural modelling methodology, as the name implies, only provides the framework for interpretation of supply chain risk mitigation. It does not provide the answer.

Reference

Faisal, M., Banwet, D., & Shankar, R. (2006). Supply chain risk mitigation: modeling the enablers. Business Process Management Journal, 12 (4), 535-552 DOI: 10.1108/14637150610678113

Author links

• qu.edu: Mohd Nishat Faisal
• dmsiitd.org: D.K. Banwet
• dmsiitd.org: Ravi Shankar

Related

• husdal.com: Information risks management
• husdal.com: Supply Chain Confidence
• husdal.com: Corporate vulnerability

Interdependence

The social and economic networks that exist in any community will ultimately influence the ability of this community to adapt to and respond to the consequences of disasters.  This includes both private and public entities. The key issue is to recognize and embrace the public-private interfaces that can improve the ability of a community to manage the response and recovery phases of disaster management.

Conceptualized as a dependent variable, community resilience is influenced by the relationships government (public) agencies develop with private sector partners and the resilience of relevant supply chains and critical infrastructures/key resources which exist in their communities.

Why is this important? Because much of the critical infrastructure  necessary for a disaster response is in private, not in public hands. This will of course depend on which country that is struck by a disaster, but in much of Europe and particularly in the US, it is true.

Propositions

The authors set up a list of propositions

• Stronger public-private partnerships will positively influence the capability of participating critical infrastructure and key resource operators to manage disaster consequences.
• Stronger public-private partnerships will positively influence the capability of participating supply chain operators to manage disaster consequences.
• Improvements in the resilience of critical infrastructures and key resources will positively improve supply chain resilience.
• Improvements in the resilience of supply chains will positively improve  the resilience of critical infrastructures and key resources.
• Through improved access to resources, supply chain resilience will positively influence the capability of communities to manage the consequences of disasters.
• Through improved access to resources, the resilience of critical infrastructures and key resources will positively influence the capability of communities to manage the consequences of disasters.

and underpin each proposition with a wealth of examples and a selection of relevant literature.

Managerial implications

The authors also evaluate how resilience can and should be developed.

1. Resilience needs to take center stage:

Failure to recognize the role of resilience could compound post-disaster consequences by relying on managers and public policy officials who who are not capable of adapting the most well-intended plans into strategies which are appropriate for the given situation.

2. Don’t forget the mortality rate of businesses following a disaster:

At each level of government, measures must be taken to influence the preparedness of businesses.

3. Identify important supply chains and critical infrastructures and key resources:

Starting at the lowest level, it is important to understand the position and relative importance of the assets of a community, both on a local, regional and  national level.

4. Establish appropriate relationships with specific business/industries:

First, understand how specific businesses and government agencies work, then develop working relationships in order to discuss the remedies that can contribute to improving resilience.

The essence: In order to achieve community resilience, public and private owners of critical infrastructures and key resources must work together, before, during and after a disaster.

Critique

This is one of the better articles on resilience that I have seen in the long time, but there is one shortcoming, in my opinion. While the authors describe and discuss various aspects of the concept of resilience,  I find it surprising that they missed the New Zealand research project Resilient Organisations, that deals in particular with community resilience. Instead they appear to have a penchant for Sheffi’s concepts of resilience. That said, they do cite a wide range of literature, many of which hitherto unbeknown to me, so I do have a lot of reading ahead of me.

NIMSAT

NIMSAT is a research center established under the auspices of the University of Louisiana at Lafayette and that was conceived based on the experiences of the Institute’s researchers during the devastations of hurricanes Katrina and Rita in 2005. The mission of NIMSAT is to enhance national resiliency to a full range of potential disasters by conducting research leading to innovative tools and applications that empower the homeland security and emergency management community through education, training, outreach and operational support.

Reference

Stewart, G., Kolluru, R., & Smith, M. (2009). Leveraging public-private partnerships to improve community resilience in times of disaster. International Journal of Physical Distribution & Logistics Management, 39 (5), 343-364 DOI: 10.1108/09600030910973724

Author links

• linkedin.com: Geoffrey T Stewart
• louisiana.edu: Ramesh Kolluru
• nimsat.org: Mark Smith

Links

• nimsat.org: NIMSAT
• resorgs.org.nz: Resilient Organisations

Related

• husdal.com: Disasters- Prepare or react?
• husdal.com: Economic Resilience

Terje Aven

I have said it time and again, and followers of this blog will know that I am a qualitative, not a quantitative researcher, and I have always looked at risk and vulnerability from a qualitative perspective, which is why I like Kaplan’s definition of risk better than any other. That is why I have never paid much attention to Terje Aven, a professor from the University of Stavanger, Norway, who I first met some 15 years ago and who I have always regarded as a quantitative researcher. He is a frequent author and co-author of articles in the Reliability Engineering and System Safety, a journal I only look into now and then, and there’s hardly an issue without Aven in it. His most recent contribution, Identification of safety and security critical systems and activities, has made me question my discarding of the quantitative risk and vulnerability perspective.

Risk – traditionally defined

Traditonally, risk is defined as a function of probability and consequences, where the the probability of and event occurring is linked to the expected consequences if the event occurs (as predicted). This way of thinking only considers a certain set of events; it does not consider the full spectre of possible outcomes. This means that the actual consequences may be very different from the calculated expected consequences.

Hence by focusing on the expected consequences given a failure mode, a strong element of arbitrariness in the classification scheme is introduced. This arbitrariness is due to the variation in possible outcomes integrated into the expected value, as well as the difficulty of assigning probabilities producing accurate predictions.

Another approach might be to replace expected consequence with expected loss:

Expected loss = E[C], given by p E [C|A], where C are the consequences of an event A with a probability of p.

This makes comparing different events easier, since one only needs to compare one number. The lesser the expected loss, the better? Not necessarily, since the preferences of the decision-maker are not accounted for. That is why a expected disutility approach should be used:

Expected disutility = Eu(C), where u is a utility function reflecting the preferences of the decision maker.

This too is troublesome, since there still is some arbitrariness as to defining the disutility function, which will have to be the same for all events/consequences, something that may not hold true for the decision-maker. Thus, in order to find which systems that are critical, neither expected loss nor expected disutility may be good approaches.

Risk – alternatively defined

Aven sees risk as composed of:

• Initiating events or triggers (A)
• Consequences of these events (C)
• The values (attributes) at stake
• Uncertainties and likelihoods about occurence of the events and the consequences

Conversely, he sees vulnerability as composed of:

• Consequences of the initiating events
• The values (attributes) at stake
• Uncertainties and likelihoods about occurence of the consequences, given the initiating events

See the differences? Risk looks primarily at the triggering event, vulnerability looks primarily at the resulting consequences.

High uncertainty = high risk

In order to account for uncertainties, Aven suggests the following method

Identify a list of systems for evaluation.

Identify possible initiating events A.

Define categories of consequences C (severity classification).

Rank thesystems according to vulnerability using E[C|A], i.e. the expected consequences given the occurrence of A.
Assign probabilities for the events A, calculate the unconditional expected consequences, EC,
by EC = P(A) x E[C|A], and rank the systems according to EC.

Assess uncertainties in underlying phenomena and processes that could result in surprises relative to EC, and adjust the ranking based on this assessment.

Steps 4 and 5 are based on a traditional risk description. It is only when the uncertainties are added that “true” risk is revealed, e.g. an event with a presumed low risk based on EC, may be reclassified as high risk if the uncertainties regarding the underlying assumptions are high. Uncertainties may be related to e.g. new technology, future events, customer demand or political stability.

Conclusion

I think Aven is on the right track here. As he puts it himself,

…the idea that safety and security critical systems can be identified by considering [...] the expected consequences given given system failures and malfunctions [...] cannot be justified…

It is necessary to use a risk-informed approach, he claims, where calculated probabilities and expected values are enriched with the uncertainties of the underlying phenomena and processes.

Surprises may occur and by just addressing probabilities and and expected values, such surprises may be overlooked.

Surprises will of course occur, as Nassim Taleb notes in his book on Black Swan Events, and also described by Bazerman and Watkins in their book on Predictable Surprises: The Disasters You Should Have Seen Coming. However, taking possible surprises into account already from the beginning will allow for a much broader, richer and more comprehensive approach to risk management.

Reference

AVEN, T. (2009). Identification of safety and security critical systems and activities Reliability Engineering & System Safety, 94 (2), 404-411 DOI: 10.1016/j.ress.2008.04.001

Author link

• uis.no: Terje Aven

Related

• husdal.com: Vulnerability and Criticality Assessment
• husdal.com: Black Swan Events

Two-in-one

Two approaches to risk assessment are used in this paper: First, interpretive structural modelling (ISM) is employed to understand the interrelationships among the enablers of information risks mitigation, resulting in a driving power and dependence matrix. Secondly, graph theory is used to quantify information risks. Unfortunately, unless I missed it somewhere, the paper provides little linkage between the two approaches.

Interdependence – Twelve enablers

In developing the driving power and dependence matrix, the authors come up with 12 “enablers” that contribute towards the mitigation of information risks:

(1) Information sharing among supply chain (SC) partners.
(2) Supply chain wide strategies to mitigate information risks.
(3) Level of supply chain integration.
(4) Collaborative relationships among supply chain (SC) partners.
(5) Support to partners.
(6) Reliable IT/IS infrastructure.
(7) Top management commitment.
(8) Trust among supply chain (SC) partners.
(9) Awareness about information risks.
(10) Availability of funds to implement information risk mitigation strategies.
(11) Incentives alignment.
(12) Metrics for continual information risks assessment and analysis.

Through a set of operations, linking enabler i (e.g. #2 above) with enabler j (e.g. #4 above) ,the relationship between each enabler is investigated, e.g.

(1) enabler i will help to achieve enabler j.
(2) enabler i will be achieved by enabler j.
(3) enabler i and j will help achieve each other.
(4) enablers i and j are unrelated.

Cutting a long story short, in the end they reach the following conclusion:

Driving power and dependence

The above is then presented as a matrix:

The enablers are further classified as

(1) Autonomous enablers (Southwest quadrant)
(2) Dependent enablers (Southeast quadrant)
(3) Linkage enablers (Northeast quadrant)
(4) Independent enablers (Northwest quadrant)

Autonomous enablers have a weak driver power and weak dependence. These enablers are relatively disconnected from the system. Dependent enablers are dependent on the other variables. Linkage variables work both ways; they affect the enablers above and are at the same time dependent on the enablers below. Independent variables have a strong driver power and weak dependence. These enablers are the most important variables and appear at the top of the ISM hierarchy, implying that management needs to address these enabler variables more carefully than perhaps the other enablers.

Quantification of risks – graph theory

I have chosen to deliberately skip this part of the paper in my review. Not because it is not interesting, but because it appears as a separate part unrelated to the aforementioned. Personally, if I were the author, I would have split this one paper into two separate papers; one paper using the interpretive structural modelling and another paper using graph theory. The way it is now I see a mixing, not a linking, of two separate approaches.

Conclusion

The article highlights that information risks are interrelated and that one factor (or “enabler”) cannot be mitigated without taking into account all the other factors that contribute to or are dependent on this factor. This is similar to the argument on corporate vulnerability in Svensson (2004), where

Corporate vulnerability may be influenced by the current and potential direct and indirect dependencies, the vertical and horizontal dependencies, as well as the unidirectional and bi-directional dependencies, between business activities in and between supply chains.

The article also reflect some of the points made in Christopher and Lee (2004) on supply chain confidence, where the argument is made that

Total end-to-end visibility will enable supply chains to be transparent, and the right information would be available to the right member of the supply chain at the right time.

This paper identifies twelve variables which may help mitigate information risks in supply chains. I may not agree with these twelve as such. Maybe there should be more, maybe less. Nonetheless, the approach used in the paper is worth looking into.

Reference

Faisal, M., Banwet, D., & Shankar, R. (2007). Information risks management in supply chains: an assessment and mitigation framework Journal of Enterprise Information Management, 20 (6), 677-699 DOI: 10.1108/17410390710830727

Author links

• qu.edu: Mohd Nishat Faisal
• dmsiitd.org: D.K. Banwet
• dmsiitd.org: Ravi Shankar

Related

• husdal.com: Supply Chain Confidence
• husdal.com: Corporate vulnerability

IRGC

Much of the paper is based on the research undertaken by the International Risk Governance Council (IRGC),  a Switzerland-based independent organization whose purpose is to help the understanding and management of emerging global risks that have impacts on human health and safety, the environment, the economy and society at large.

Critical infrastructure

A 2004 report on critical infrastructures prepared for the EU Commission defines critical infrastructures as those physical and information technology facilities, networks, services and assets which, if disrupted or destroyed, would have a serious impact on the health, safety, security or economic well-being of citizens or the effective functioning of governments:

• Energy installations and networks (e.g. electrical power, oil and gas production, storage facilities and refineries, transmission and distribution system).
• Communications and Information Technology (e.g. telecommunications, broadcasting systems, software, hardware and networks including the Internet)
• Finance (e.g. banking, securities and investment)
• Health Care (e.g. hospitals, health care and blood supply facilities, laboratories and pharmaceuticals, search and rescue, emergency services)
• Food (e.g. safety, production means, wholesale distribution and food industry)
• Water (e.g. dams, storage, treatment and networks)
• Transport (e.g. airports, ports, intermodal facilities, railway and mass transit networks, traffic control systems)
• Production, storage and transport of dangerous goods (e.g. chemical, biological, radiological and nuclear materials)
• Government (e.g. critical services, facilities, information networks, assets and key national sites and monuments)

However, not all “critical” infrastructure is really “critical”. It is the degree of criticality that matters most.

Degree of criticality

The above mentioned EU report suggests three factors to look for when identifying critical infrastructure:

Scope – The loss of a critical infrastructure element is rated by the extent of the geographic area which could be affected by its loss or unavailability – international, national, provincial/territorial or local.

Magnitude – The degree of the impact or loss can be assessed as None, Minimal, Moderate or Major. Among the criteria which could be used to assess potential magnitude are:

(a) Public impact (amount of population affected, loss of life, medical illness, serious injury, evacuation)
(b) Economic impact (GDP effect, significance of economic loss and/or degradation of products or services)
(c) Environmental impact (on the public and surrounding location)
(d) Interdependency (between other critical infrastructure elements)
(e) Political impact (confidence in the ability of government)

Effects of time – This criteria ascertains at what point the loss of an element could have a serious impact (i.e. immediate, 24-48 hours, one week, other).

Seeing it all

Risk issues need to be addressed comprehensively or even holistically because a set of multifaceted factors shape the risks of critical infrastructure as a whole: Societal, System-related, Technological, Institutional and Natural risk factors:

This reminds me of Helen Peck’s holistic approach towards supply chain risk, where she  reconciles supply chain vulnerability, risk and supply chain management with corporate governance, business continuity, national security and emergency planning.

Conclusion

I can only agree with the author when he concludes that

Critical infrastructures deserve increased attention as our societies simply rely on most of their goods and services they are expected to continuously supply. They are subject to fundamental changes in technology and operating environment pushing systems closer to their limits and making them more vulnerable; as a consequence, single failures may develop into serious breakdowns and cascade into dependent systems. To reduce vulnerabilities and better balance social needs, risk governance strategies should be developed including all major actors in the decision-making process and various risk-shaping factors considered important.

This paper is one step closer to developing an approach that fully comprises the complexity and interdependency of critical infrastructures.

References

KROGER, W. (2008). Critical infrastructures at risk: A need for a new conceptual approach and extended analytical tools. Reliability Engineering & System Safety, 93 (12), 1781-1787 DOI: 10.1016/j.ress.2008.03.005

Birchmeier, J. (2007). Systematic assessment of the degree of criticality of infrastructures. Paper presented at ESREL 2007, Stavanger, Norway, 25-27 June 2007. In: T. Aven and J.E. Vinnem (eds.) Risk, Reliability and Societal Safety. London: Taylor & Francis Group.

Author links

• ethz.ch: Wolfgang Kröger
• ethz.ch: Jürg Birchmeier

Links

• igrc.org: The International Risk Governance Council

Downloads

• igrc.org: IGRC Publications

Related

• husdal.com: The security of supply
• husdal.com: Are roads more important than computers?

Slow is better?

In today’s fast-paced business world, where speed is king and where many customers are willing to pay high premiums for overnight package delivery, Maersk has found a new niche: Slow Steaming. By halving its top cruising speed over the last two years, Maersk cut fuel consumption on major routes by as much as 30 percent, greatly reducing costs.

“The previous focus has been on ‘What will it cost?’ and ‘Get it to me as fast as possible,’ ” said Soren Stig Nielsen, Maersk’s director of environmental sustainability. “But now there is a third dimension,” he said. “What’s the CO2 footprint?” Traveling more slowly, he added, is “a great opportunity” to lower emissions “without a quantum leap in innovation.”, and in what reads as a commentary on modern life, Maersk advises in its corporate client presentation, “Going at full throttle is economically and ecologically questionable.”

For the sake of the planet, slow steaming is better. For the sake of you wallet it is better, too.

Slow is more reliable?

Obviously, carriers that think traditionally will resist the idea of slowing down, and argue that speed is indispensable to serving their clients. But is it really? If slow steaming is the rule, it creates a buffer zone in which speed can be increased to meet delivery times. If speed steaming is the rule there is simply no slack for catching up a schedule that is running late. Ergo: slow is more reliable.

To adjust or not to adjust?

Super slow shipping involves adjustments. According to the NY Times article,

Maersk had to prove that slow speeds would not damage ship engines in order to maintain engine warranties that did not cover such slow travel. Moreover, customers have to factor in extra time for delivery, which can be problematic for time-sensitive products. Maersk has also shouldered the labor costs of having crews at sea for longer periods and added two ships on its Germany-to-China route to maintain scheduled deliveries. But those expenses were canceled out by decreased fuel costs.

Maersk is now working with customers, hoping to slow more boats. Customers will be charged variable rates depending on speed. It remains to be seen how many customers will jump the bandwagon…ehrrr ship, in order to save costs, save the planet, and perhaps save the annoyances and disruptions that used to come with a speedy delivery. Now that it is a slow delivery, there are perhaps less worries?

Sustainable Shipping

Maersk Line was named Sustainable Shipping Operator of The Year 2009 for challenging the shipping industry and bringing about significant reductions in energy consumption and emissions. The award, presented by Sustainable Shipping was given to Maersk Line in recognition of the efforts it has made in reducing the environmental impact of its business operations.

Links

• nytimes.com: Slow Trip Across Sea Aids Profit
• toysa.com: Maersk Slow Steaming presentation (pdf)
• maerskline.com: Maersk Line wins award for super slow steaming initiative

Related

• husdal.com: Risk and vulnerability in maritime supply chains

16363 ships, one year

Prof. Dr. Bernd Blasius of the Institute for Chemistry and Biology of the Marine environment (ICBM) at the Carl von Ossietzky University Oldenburg mapped the itineraries of 16,363 cargo ships during the year 2007 to construct a network of links between ports.

On a map, it looks like this:

The worldwide maritime network also plays a crucial role in today’s spread of invasive species.

Two major pathways for marine bioinvasion are discharged water from ships’ ballast tanks and hull fouling. Even terrestrial species such as insects are sometimes inadvertently transported in shipping containers. In several parts of the world, invasive species have caused dramatic levels of species extinction and landscape alteration, thus damaging ecosystems and creating hazards for human livelihoods, health, and local economies. The financial loss due to bioinvasion is estimated to be $120 billion per year in the United States alone

Interestingly, the researcher find that most ships can be classified in three categories: bulk dry carriers, container ships and oil tankers.  These three categories also have distinct mobility patterns and make up separate networks within the larger network.

An important characteristic of the network are differences in the movement patterns of different ship types. Bulk dry carriers and oil tankers tend to move in a less regular manner between ports than container ships. This is an important result regarding the spread of invasive species because bulk dry carriers and oil tankers often sail empty and therefore exchange large quantities of ballast water. The gravity model, which is the traditional approach to forecasting marine biological invasions, captures some broad trends of global cargo trade, but for many applications its results are too crude.

Unsurprisingly, container ships follow regularly repeating paths because they are a directpart of many send consumer supply chains, whereas bulk dry carriers and oil tankers move less predictably between ports. More surprising perhaps is that the directed network of the entire cargo fleet is noticeably asymmetric, with 59% of all linked pairs of ports being connected only in one direction.

Results

The following table shows the results of the investigation:

Container ships typically follow set schedules visiting several ports in a fixed sequence along their way, thus providing regular services. Bulk dry carriers, by contrast, appear less predictable as they frequently change their routes on short notice depending on the current supply and demand of the goods they carry.

The researchers also compare the worldwide airport network (WAN) to the global cargo shipping network GCSN):

The high asymmetry of the GCSN has not been found in the WAN, indicating that ship traffic is structurally very different from aviation. Rather than being formed by the accumulation of back and forth trips, ship traffic seems to be governed by an optimal arrangement of unidirectional, often circular routes.

Reference

Pablo Kaluza, Andrea Kölzsch, Michael T. Gastner, & Bernd Blasius (2010). The complex network of global cargo ship movements Journal of the Royal Society Interface arXiv: 1001.2172v1

Download

• arxiv.org: The complex network of global cargo ship movements

Author links

• icbm.de: Bernd Blasius
• icbm.de: Andrea Kölzsch
• santafe.edu: Michael T Gastner (presumed)
• jacobs-university.de: Pablo Kaluza

Links

• tu.no: Havets pulsårer
• technologyreview.com: The Global Shipping Network is finally revealed

Related

• husdal.com: The BBC box is back