Jennifer V. Blackhurst

Supplier Risk Monitoring for the Automotive Industry

Daniel Dumke — Wed, 23 Nov 2011 10:22:00 +0000

A typical supply chain risk management process consists of four steps: risk identification, assessment, management and monitoring. From those steps, one of the most neglected step is the risk monitoring.
Risk monitoring implies two different actions: Continuous risk assessment and actions, as soon as pre-defined limits are reached.

So this article sheds light on the risk monitoring, from an article by Blackhurst, Scheibe and Johnson (“Supplier risk assessment and monitoring for the automotive industry”).

Literature

After the analysis of the current literature the authors come to the conclusion: “Of the two methodologies we did find to monitor risks, neither addresses measuring, assessing and monitoring supplier risk over time. In addition, research that has examined supplier evaluation models has indicated that most methods are too mathematically complex to implement and understand, require excessive amounts of data, or are too subjective.”

So the authors want to close this gap, by developing a risk assessment and monitoring methodology for a US automotive manufacturer.

Risk assessment and monitoring methodology

Core of the risk monitoring methodology is the risk assessment, which is done using several categories of risk. The authors extend the framework of Chopra and Sodhi (2004), which contains nine risk categories: disruptions, delays, systems, forecast, intellectual property, procurement, receivables, inventory, and capacity.
To adapt this framework to the specific needs of the automotive industry.

For example, in the Chopra and Sodhi framework there was a risk category called delays. While this is a reasonable category in general terms to describe delays in material flows, it is insufficient to capture the necessary detail of risk elicited through our interviews with the auto manufacturer. Consequently, we expanded delays into logistics, supplier dependence, and quality.

Figure 1 shows the selected risk categories divided into internal (controllable) and external (uncontrollable) risks.

Figure 1: Supply Chain Risk Categories (Blackhurst et al., 2008)

Each of these categories are then weighed, so that the sum of all weights adds up to 100%. The subcategories also have to be weighed to show their relative importance within the risk category. In the example of the automotive manufacturer the focus was on quality and disruptions only, with 40 and 60 percent respectively.

Using the example of a disc brake assembly, the next step is to assess the risks of the individual parts of the supply chain product. In this case: caliper, hub and rotor. The results are shown in figure 2 and aggregated in a heat map (figure 3).

Figure 2: Risk Evaluation Sheet (Blackhurst et al., 2008; click to enlarge)

Figure 3: Heat Map for Product Parts (Blackhurst et al., 2008; click to enlarge)

The results can also be interpreted towards the individual suppliers (figure 4).

Figure 4: Heat Map for Suppliers (Blackhurst et al., 2008; click to enlarge)

Continuous process

The authors elaborate extensively on the requirements of a risk assessment and monitoring methodology:

Any risk assessment methodology should be able to develop a list of rank ordered critical parts (whether pre-specified or determined by the assessment tool); with critical risk parts at the top and low-risk parts at the bottom.

Furthermore the main purpose of an implementation of a risk monitoring is to switch from a reactive supply chain risk management to a continuous and proactive one.

To do this, risk ratings and/or risk indices must be tracked over time and trends monitored to determine if they are reaching unacceptable levels.

For this the risk scores developed above have to be updated regularly and can lead to a time dependent analysis shown in figure 6.

Figure 6: Trends in Supplier and Part Risks (Blackhurst et al., 2008)

Operational issues

The authors see four operational issues:

The number of categories and subcategories used becomes a balancing act. As more subcategories are added to a particular category, the relative impact each subcategory has on the score of the overall category declines. Similarly, as more categories are added to the risk assessment and monitoring tool, the relative weight each category contributes to the overall risk index of a supplier or part declines.

A higher weight on a particular factor will cause that factor to have more impact on the calculated risk index. As previously mentioned, the weights can be based on the probability of each category of disruption occurring, the relative impact each category of disruption has on supply, or any other factor considered important to the company.

Each subcategory must be rated. Some factors such as war and terrorism, political issues/unrest, information infrastructure breakdown, level of system integration, etc. are quite subjective and ratings on these factors should be made by higher level managers familiar with assessing these factors.

In order to use the methodology in a proactive manner, the ratings on each subcategory must be updated on a periodic basis and the data analyzed for patterns, high-risk levels, or trends that indicate potential problems. […] Therefore, the time interval between updates will also vary from subcategory to subcategory.

Conclusion

Overall the automobile manufacturer from the case study was reportedly very pleased with the resulting process and its relative ease of use and implementation: “it is too early to use overly sophisticated and brittle methods. We need an easily employable and understandable method such as this.”
I think the authors not only did a good job in summarizing the process, but also reflecting on its implications and shortcomings.

Reference:

Blackhurst, J., Scheibe, K., & Johnson, D. (2008). Supplier risk assessment and monitoring for the automotive industry International Journal of Physical Distribution & Logistics Management, 38 (2), 143-165 DOI: 10.1108/09600030810861215

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Ways to guard against Disruptions

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

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

Goal and method

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

Results

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

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

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

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

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

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

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

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

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

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

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

Conclusion

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

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

Reference:

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

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Decision Support for Supply Chain, Product and Process Design

Daniel Dumke — Wed, 02 Feb 2011 13:46:00 +0000

Many companies are struggling with the idea to use modern optimization techniques to support decision making in strategic supply chain management.

But beside mathematical modeling of the supply chain there are other methods as well, such as network based approaches. In their 2005 paper Blackhurst, Wu and O’Grady present a more intuitive decision support method with the goal to improve decisions within the supply chain context.

Methodology

Figure 1: Example Product Chain Decision Model (Blackhurst et al. 2005)

Complex and dynamic systems like supply chains are hard to understand as a whole. The PCDM (Product Chain Decision Model) uses a network based approach. The network (example see figure 1) therefore consists of different nodes (place nodes: marked by circles and transition nodes: marked by bars). Transition nodes are used for processes, transferring input into output (eg. a transport, production, …), where place nodes are used for components within the supply chain (eg. production facility). The connections are marked by an arrow.

Case Study

Figure 2: Case Study for Chassis Assembly using PCDM (click to enlarge, Blackhurst et al. 2005)

As an example Blackhurst et al. use a case study, where they model the chassis assembly of Rockwell Collins, using actual data of their processes. The result of the status quo can be seen in figure 2. The network presentation is enhanced by the added information, like the lead time (LT) and the reorder point (ROP) at the nodes.

With the help of these networks the authors then optimize the network from the base case with local informations first to an information sharing network. This already helps reducing echelon inventory a lot. The second adjustment is to change raw materials to improve the product and the network even further.

Conclusion

The presented method for improving the supply chain network is intuitive, easy to understand and implement. Yet, it does not seem to be so new, nevertheless, it is a nice addition to the usual supply chain networks to add some key indicators directly at the nodes.
Even though this tool might seem overly simplistic, I really recommend using more tools like these. Many companies do not even analyze their network on a systematic basis, so this looks to be a good starting point for companies which have not used similar tools before.

Reference:

Blackhurst, J., Wu, T., & O’Grady, P. (2005). PCDM: A Decision Support Modeling Methodology for Supply Chain, Product and Process Design Decisions Journal of Operations Management, 23 (3-4), 325-343 DOI: 10.1016/j.jom.2004.05.009

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Severity of Supply Chain Disruptions

Daniel Dumke — Wed, 26 Jan 2011 11:24:00 +0000

We already know that supply chain disruptions can be quite costly, and have not only direct but also indirect effects (eg. on stock prices). So do all supply chain disruptions have the same effect on the focal company? Of course not, but what are the driving factors that influence the impact?

In their conceptual note Craighead et al. (2007) analyse the factors of the impact supply chain disruptions.

As many companies, the authors take the view that supply chain disruptions are inevitable and at some point in time some part of the supply chain will fail. The important question therefore is:

How and why one supply chain disruption would be more severe than another

Categorization of Factors influencing the Severity of SC Disruptions (Craighead et al., 2007)

Methodologies

To answer this question the following methods are employed, to get an holistic image of the relevant factors.

Single Case Analysis

Analysis of the supply chain and interviews with managers from different firms within the supply chain

Semi-structured Interviews
Interviewing experts from different industry sectors

Focus Groups

Refinement of the results found in the first two phases

Results

As a result the following supply chain design characteristics which influence the severity of disruptions have been found:

Supply Chain Density
SC density corresponds to the geographical spacing of nodes within a supply chain. The severity of a supply chain disruption within a supply chain appears to be positively related to supply chain density.

Supply Chain Complexity
The authors propose that disruptions to complex supply chains are more severe than disruptions to relatively less complex chains.

Node Criticality
This refers to the importance of a node for value creation. And the authors propose that a disruptions of more critical nodes will very likely be more severe.

Furthermore the following supply chain mitigation capabilities were found to influence supply chain disruption severity:

Recovery Capability
Can be defined as the coordination of supply chain resources to return the SC to a normal and planned level of product flow. Obviously, a supply chain with a greater recovery capability should experience relatively less severe disruptions.

Warning Capabilities
This is the capability to (early) detect a disruption and distribute the information within the supply chain. The proposition here is that the severity of disruptions is decreased by better warning capabilities.

Conclusion

The authors explain the reasoning and evidence for each of their propositions and they have been very careful describing their results, using words like “[SC density] appears [to have an effect]”. This is very necessary!

Even though the author employed various methods, there is no method which improves the statistical significance of the sample. So, the methods are used to support theory building and not theory testing.

On the other hand, this does not reduce the validity of the theory, but further testing will be needed.

Reference:

Craighead, C.W., Blackhurst, J., Rungtusanatham, M.J., & Handfield, R.B. (2007). The Severity of Supply Chain Disruptions: Design Characteristics and Mitigation Capabilities Decision Sciences, 38 (1), 131-156

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Research Issues for Managing Supply Chain Disruptions

Daniel Dumke — Thu, 06 May 2010 06:37:00 +0000

What do professionals in the domain of supply chain management think about disruptions? How do they prepare for them, how do they act when a disruption occurs?

Blackhurst et al. (2005) answer these questions in their work about “An empirically derived agenda of critical research issues for managing supply-chain disruptions”.The authors are using three different empirical methods to achieve this goal empirically: Case study, surveys and focus groups.

Disruptions

As you would expect from a theoretical article they start with the question: What are disruptions anyway? They can show themselves in different forms: eg. transportation delays, natural disasters, part shortages, quality issues. The common theme is, that disruptions are costly and can trigger stock-outs, which leads to the inability to meet customer needs.

Other authors like Hendricks and Singhal (2003) show that supply chain disruptions can cause huge cost.

And disruptions are on the rise due to global sourcing, which increases the potential for disruptions and the movement towards increased responsiveness, higher levels of agility and lower inventories.

Results

The empirical study results in the following three steps to master supply chain disruptions.

Disruption discovery
Visibility and predictive analysis are most important to discover disruptions, the update of risk measures therefore has to be more dynamic (up to real-time) to be useable.
Disruption recovery
Recovery starts with damage control, it should be build on a model to understand hwo disruptions will affect the supply chain
Supply chain redesign
The goal for redesign is to include all relevant (hidden?) costs of a global supply chain and to aim for a flexible and robust supply chain optimization

Conclusion

The article builds a framework to think about disruptions within a supply chain. As the title already suggests this article only points at the issues researchers are/should be working at the moment. And there is still a lot of work to do.

Reference:

Blackhurst, J., Craighead, C., Elkins, D., & Handfield, R. (2005). An empirically derived agenda of critical research issues for managing supply-chain disruptions International Journal of Production Research, 43 (19), 4067-4081 DOI: 10.1080/00207540500151549

Hendricks, K., & Singhal, Vinod (2003). The effect of supply chain glitches on shareholder wealth Journal of Operations Management, 21 (5), 501-522 DOI: 10.1016/j.jom.2003.02.003

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