RANGER - Supply Chain Risk Management

RANGER will enable a more extensive analytical analysis and evaluation of supply chain risks that will lead to substantial improvements in cost, quality, schedule, and responsiveness of defense industrial base supply chain operations.

Capital markets severely penalize supply chain disruptions and attach high value to supply chain robustness. Supply chains are more vulnerable today because of:

• Globalization of markets driving competitiveness, leading to more outsourcing and offshoring
• Increase in interfirm dependence, as well as longer and more complex supply chain setups and operations
• Emphasis on efficiency, lean, and agility amplify the fragility of supply chains
• More complex interactions and tighter coupling in the supply chain lead to more disruptions from unexpected events in the supply chain

Twenty-first century supply chain risk management requires a means to identify, assess, and mitigate risk; it also requires a methodology that includes a total life-cycle approach across the supply chain. To address these challenges the RANGER program addresses the following four gaps:

• Lack of methodologies to identify and quantify seemingly unrelated risks.
• Lack of effective models that are interoperable across different platforms and easy to use.
• Lack of models that integrate risk management with the total life-cycle of the product.
• Lack of effective metrics and optimization models for supply chain risk management.

Risk identification

The RANGER program was established with the intent to provide an interoperable software tool suite that will help the focal organization identify and predict future risks across the design, manufacture, use, and post-use phases of the product life-cycle.

The elements of risk are broadly classified as: organizational, industrial, and environmental risks. The relationship between the risk drivers and their impact on the focal organization’s performance will be validated through extensive research and by program test bed partners.  A sample visual representation between the risk drivers and measures of performance is given below.

Predicting Risk

The Bayesian Belief Network (BBN) approached developed within the program will have the ability to predict risk. This helps organizations to assess various what-if scenarios, in advance of disruptions – whether minor or catastrophic. Advantages of BBN:

• Accommodates models where statistical data is unknown or missing
• Provides a way to understand causal relationships and thereby the prediction of the consequences of intervention
• Allows inclusion of expert knowledge in the risk assessment to fill a void from the use of traditional statistical methods

Advantages of RANGER

• Provides the ability to quantify cumulative risks throughout the supply chain
• Provides a comprehensive set of risk drivers based on the Risk Taxonomy developed that will be useful to the non-expert user
• Enables knowledge capture via risk network creation and conditional probabilities assignment
• Provides the flexibility to tailor the risk model to a specific industry or product through user customization of the risk network, risk drivers, and conditional probabilities
• Provides the flexibility for automated, manual or a combination of automated/manual inputs. The Bayesian Network can both capture "expert knowledge" as well as be "trained" with data.
• Supports modeling the interrelationship between risk drivers and performance metrics to more accurately reflect the complexity of supply chain risks
• Supports "what if" analyses and sensitivity analyses to assess risk drivers influence on desired outcomes

RANGER Participants

For more infomation, contact:

Gerry Graves, Ph.D.
SCRA
(843) 760-3793
gerald.graves@scra.org