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14 Table 1. A-Priori Probabilities for Risk Event Variables Supplier Misalignment of Interest Supplier Financial Stress Supplier Leadership Change Tier 2 Stoppage Supplier Network Misalignment Quality Problems Delivery Problems Service Problems Supplier HR Problems Supplier Locked Merger/ Divestiture 1 0.20 0.50 0.50 0.31 0.20 0.46 1.00 0.20 0.20 0.18 1.00 0.11 2 0.20 0.50 0.50 0.31 0.12 0.48 0.95 0.20 0.20 0.18 1.00 0.12 3 0.21 0.50 0.50 0.32 0.16 0.47 0.96 0.20 0.20 0.19 1.00 0.16 4 0.19 0.50 0.30 0.29 0.14 0.36 0.82 0.15 0.07 0.10 0.80 0.11 5 0.20 0.50 0.50 0.31 0.16 0.50 0.96 0.20 0.20 0.18 1.00 0.11 Disasters Table 2. Network Risk Profiles And Value At Risk Impacts Supplier Misalignment of Interest Probability Supplier Financial Stress Probability Supplier Leadership Change Probability Tier 2 Stoppage Probability Supplier Network Misalignment Probability Probability of Revenue Impact Monthly Revenue Impact (Millions) Value At Risk (Probability x Monthly Revenue Impact) Potential VAR Percent Decrease Potential VAR Percent Increase 1 *0.20 *0.50 *0.50 *0.31 *0.20 0.41 $ 18.75 $ 7,687,500 26.8 53.7 0.00 0.00 0.00 0.00 0.00 0.30 $ 18.75 $ 5,625,000 1.00 1.00 1.00 1.00 1.00 0.63 $ 18.75 $11,812,500 2 *0.20 *0.50 *0.50 *0.31 *0.12 0.40 $217.50 $ 87,000,000 25.0 57.5 0.00 0.00 0.00 0.00 0.00 0.30 $217.50 $ 65,250,000 1.00 1.00 1.00 1.00 1.00 0.63 $217.50 $137,025,000 3 *0.21 *0.50 *0.50 *0.32 *0.16 0.41 $136.25 $55,862,500 26.8 56.1 0.00 0.00 0.00 0.00 0.00 0.30 $136.25 $40,875,000 1.00 1.00 1.00 1.00 1.00 0.64 $136.25 $87,200,000 4 *0.19 *0.50 *0.30 *0.29 *0.14 0.32 $ 45.83 $14,665,600 28.1 75.0 0.00 0.00 0.00 0.00 0.00 0.23 $ 45.83 $10,540,900 1.00 1.00 1.00 1.00 1.00 0.56 $ 45.83 $25,664,800 5 *0.20 *0.50 *0.50 *0.31 *0.16 0.41 $ 20.83 $ 8,540,300 26.8 53.7 0.00 0.00 0.00 0.00 0.00 0.30 $ 20.83 $ 6,249,000 1.00 1.00 1.00 1.00 1.00 0.63 $ 20.83 $13,122,900 *Base Case
International Journal of Contemporary Business Studies Vol: 3, No: 1. January, 2012 ISSN 2156-7506 Available online at http://www.akpinsight.webs.com The a-priori probabilities associated with operational and external risk variables were held constant during the sensitivity analysis. Although it may not be possible to fully eliminate the network risks associated with a supplier’s profile, it may be possible to improve the profile by instituting proactive supply chain risk management strategies and tactics in areas that will yield the maximum benefit. Table 2 illustrates the supplier network risk profiles and VAR impacts under the three aforementioned conditions. The first row of values are network risk probabilities associated with Supplier 1 along with its probability of revenue impact. This is referred to as the base case. The second row illustrates the probability of revenue impact for Supplier 1 if it were possible to minimize network risks to the value of zero. The probability of revenue impact for Supplier 1 if it is certain that it will experience network risks is depicted in the third row. The table shows that minimizing Supplier 1 network risk events reduces the probability of revenue impact from the base case of 41 percent to 30 percent. Additionally, the probability of revenue impact due to Supplier 1 increases from 41 percent to 63 percent under the scenario of 100 percent certainty of network risks. An examination of Table 2 reveals that the network risk profile associated with Supplier 2 results in the largest VAR for the base case ($87.0 million), best case ($65.2 million), and worse case ($137.0 million) scenarios. The risk profile of Supplier 5 yields the smallest VAR for the base case ($8.5 million), best case ($6.2 million), and worse case ($13.1 million) situations. The largest potential percentage decrease in VAR between a supplier’s base case and most favorable network risk profile is 28.1 percent for Supplier 4. The largest potential percentage increase in VAR between a supplier’s base case and least favorable network risk profiles is 75.0 percent, also exhibited by Supplier 4. The smallest potential percentage decrease in VAR between the base case and most favorable network risk profile was displayed by Supplier 2 at 25.0 percent. Both Suppliers 1 and 5 offer the smallest potential percentage increase in VAR (53.7 percent) between the base case and least favorable network risk profiles. The average potential increase in VAR is 59.2 percent for all suppliers, and the average potential decrease in this measure is 26.7 percent. Finally, Table 2 reveals that potential percent increases in VAR due to network risks are significantly greater than potential percent VAR decreases for each individual supplier. 6. MANAGERIAL ACTIONS The sensitivity analysis reveals that not only does Supplier 1 have the lowest VAR impact on the company under the evaluated scenarios, but also the smallest potential percentage increase in VAR along with Supplier 5. This result suggests that Supplier 1 has a comparatively favorable network risk probability profile relative to those of the other study participants. However, this supplier also has the lowest monthly revenue impact on the company. Given this result, after considering both operational and external risks associated with Supplier 1, the company may find it prudent to apportion more of its business to this supplier due to its less risky network profile. However, given that this supplier believes that there is a 100 percent chance that it will encounter delivery problems, the company should take immediate steps to mitigate the effects of its eventual occurrence. The sensitivity analysis also reveals that Supplier 2 has the highest VAR impact on the company under the scenarios examined along with the smallest potential percentage decrease in VAR. Thus, Supplier 2 has an unfavorable network risk probability profile relative to the other participants in the study. Ironically, this supplier also has the largest monthly revenue impact on the company. This result suggests that the company should consider allocating more of its business to a supplier with a less risky network profile. The company should also institute risk mitigation strategies and tactics immediately to address the 95 percent probability of an occurrence of a delivery problem with this supplier. Finally, the company may choose to terminate its relationship with this supplier and allocate its business among its remaining supplier base. 15 Copyright © 2012. Academy of Knowledge Process
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