Supply Chain Management, 8th
Edition by Sunil Chopra
Complete Chapter Solutions Manual
are included (Ch 1 to 19)
** Immediate Download
** Swift Response
** All Chapters included
** Case studies included
** Exercises included
** Tables, figures and
examples
,Table of Contents are given below
1.Understanding the Supply Chain
2.Achieving Strategic Fit in a Supply Chain
3.Supply Chain Drivers and Financial Performance
4.Network Design in the Supply Chain
5.Building and Evaluating Optionality in Global Supply Chain Networks
6.Demand Forecasting in a Supply Chain
7.Planning Supply in a Supply Chain: Aggregate Planning
8.Sales and Operations Planning in a Supply Chain
9.Coordination in a Supply Chain
10.Managing Economies of Scale in a Supply Chain: Cycle Inventory
11.Managing Uncertainty in a Supply Chain: Safety Inventory
12.Growing Supply Chain Profits Using Product Availability
13.Transportation in a Supply Chain
14.Sourcing Decisions in a Supply Chain
15.Information Technology in a Supply Chain
16.Pricing and Revenue Management in a Supply Chain
17.Sustainability and the Supply Chain
18.Segmentation and Tailoring of Supply Chains
19.Building Resilience to Disruption in Supply Chains
,Solutions Manual organized in reverse order, with the last chapter displayed first, to ensure
that all chapters are included in this document. (Complete Chapters included Ch19-1)
CHAPTER NINETEEN
Discussion Questions
1. What is the difference between recurrent and disruption risk?
Recurrent risk arises from uncertain fluctuations in factors like demand, exchange
rate, and transportation costs. Recurrent risks correspond to fluctuations that occur
frequently with changes that are small from one period (day) to the next.
Recurrent risks can generally be forecast based on historical data given the large
number of historical instances typically available. For example, a firm can
forecast future demand of a product based on historical sales. The impact of these
fluctuations tends to be small in the short term.
Disruption risk corresponds to some supply chain processes being interrupted for
a significant duration of time. Examples include a fire or a pandemic shutting
down a factory. Disruptive events are rare and impossible to forecast based on
history because of the relatively rare occurrence. The impact of a disruption can
be quite large based on the duration of time that a process is disrupted.
2. Why is disruption risk difficult to estimate?
Disruptive events caused by weather, fires, or pandemics tend to be rare. As a
result, there is little data available. For example, it is impossible to estimate the
risk of a fire, an earthquake, or flood shutting down a plant. This is also true for
financial markets where the bursting of a bubble or a crisis is impossible to
forecast.
For example, in a Financial Times article in August 2007, David Viniar (CFO of
Goldman Sachs) attempted to excuse the implosion of Goldman hedge funds by
claiming, "We were seeing things that were 25-standard deviation moves,
several days in a row.“ Given that 25-standard deviation moves should occur
once in over a trillion years, the fact that they occurred several days in a row
indicates that Goldman’s estimation of the probability distribution of such events
was completely mistaken.
3. Why is ignoring disruption risk likely to result in a higher total expected cost
compared to overestimating the risk of disruption?
Ignoring disruption risk is equivalent to estimating the probability of a disruption
to be 0. In such a situation a firm will make no investment in resilience, which
reduces upfront costs but is expensive when a disruption occurs. In contrast,
overestimating the risk of disruption results in over investment in resilience by
increasing alternate sources, flexibility, risk management inventory, or reserve
capacity. These investments are expensive upfront but can also be used to
effectively deal with recurrent risks. For example, if a firm has multiple sources
, CHAPTER NINETEEN
Discussion Questions
of supply it can also use them to deal with geographical fluctuations in demand or
fluctuations in transportation costs. Whereas ignoring disruption risks results in
actions that are vulnerable to both recurrent and disruption risks, overestimating
disruption risks results in actions that are helpful in dealing with both recurrent
and disruption risks. Thus, long term costs of over estimation tend to be lower
than long term costs of ignoring disruption risk.
4. What factors affect TTR for a disrupted node? What actions can help decrease
TTR?
Time to recovery is affected by how quickly a disruption is sensed and investment
in rapid recovery. A successful example is from the oil and gas industry where
sensors have allowed for the real-time monitoring and online evaluation of
equipment operation, enabling the timely detection and maintenance of
anomalies. Timely detection allows for preventive maintenance before the
equipment fails resulting in a much shorter and cheaper shutdown than if the
equipment had failed. In general, early detection combined with the capacity to
take corrective action before the actual disruption occurs can help reduce TTR.
Availability of alternate supply sources helps increase TTS, allowing for
corrective action to be taken without hurting supply chain output.
5. What factors affect TTS for a disrupted node? What actions can help increase
TTS?
TTS is affected by how quickly a disruption is sensed, available inventory beyond
the disrupted node, and any alternative capacity available. TTS can be increased
by decreasing the detection lead time for the disruption, increasing available
inventory, and increasing alternate capacity that can substitute for the disrupted
node. For example, having more than one warehouse capable of supplying various
markets, Amazon increased TTS by shifting to alternate warehouses when any
warehouse had to be shutdown during COVID.
6. Why does the inclusion of disruption risk increase the total expected cost of
centralized supply chains to a greater extent than for decentralized supply chains?
Centralized supply chains have a few locations where capacity or inventory is
concentrated. This concentration increases the impact of any disruption at these
locations. Decentralized supply chains, in contrast, have many locations that carry
capacity or inventory. This reduces the impact of any location being disrupted.
Decentralized supply chains are also more likely to have duplicate capabilities at
locations making it easier to use a backup in case of a disruption.
Edition by Sunil Chopra
Complete Chapter Solutions Manual
are included (Ch 1 to 19)
** Immediate Download
** Swift Response
** All Chapters included
** Case studies included
** Exercises included
** Tables, figures and
examples
,Table of Contents are given below
1.Understanding the Supply Chain
2.Achieving Strategic Fit in a Supply Chain
3.Supply Chain Drivers and Financial Performance
4.Network Design in the Supply Chain
5.Building and Evaluating Optionality in Global Supply Chain Networks
6.Demand Forecasting in a Supply Chain
7.Planning Supply in a Supply Chain: Aggregate Planning
8.Sales and Operations Planning in a Supply Chain
9.Coordination in a Supply Chain
10.Managing Economies of Scale in a Supply Chain: Cycle Inventory
11.Managing Uncertainty in a Supply Chain: Safety Inventory
12.Growing Supply Chain Profits Using Product Availability
13.Transportation in a Supply Chain
14.Sourcing Decisions in a Supply Chain
15.Information Technology in a Supply Chain
16.Pricing and Revenue Management in a Supply Chain
17.Sustainability and the Supply Chain
18.Segmentation and Tailoring of Supply Chains
19.Building Resilience to Disruption in Supply Chains
,Solutions Manual organized in reverse order, with the last chapter displayed first, to ensure
that all chapters are included in this document. (Complete Chapters included Ch19-1)
CHAPTER NINETEEN
Discussion Questions
1. What is the difference between recurrent and disruption risk?
Recurrent risk arises from uncertain fluctuations in factors like demand, exchange
rate, and transportation costs. Recurrent risks correspond to fluctuations that occur
frequently with changes that are small from one period (day) to the next.
Recurrent risks can generally be forecast based on historical data given the large
number of historical instances typically available. For example, a firm can
forecast future demand of a product based on historical sales. The impact of these
fluctuations tends to be small in the short term.
Disruption risk corresponds to some supply chain processes being interrupted for
a significant duration of time. Examples include a fire or a pandemic shutting
down a factory. Disruptive events are rare and impossible to forecast based on
history because of the relatively rare occurrence. The impact of a disruption can
be quite large based on the duration of time that a process is disrupted.
2. Why is disruption risk difficult to estimate?
Disruptive events caused by weather, fires, or pandemics tend to be rare. As a
result, there is little data available. For example, it is impossible to estimate the
risk of a fire, an earthquake, or flood shutting down a plant. This is also true for
financial markets where the bursting of a bubble or a crisis is impossible to
forecast.
For example, in a Financial Times article in August 2007, David Viniar (CFO of
Goldman Sachs) attempted to excuse the implosion of Goldman hedge funds by
claiming, "We were seeing things that were 25-standard deviation moves,
several days in a row.“ Given that 25-standard deviation moves should occur
once in over a trillion years, the fact that they occurred several days in a row
indicates that Goldman’s estimation of the probability distribution of such events
was completely mistaken.
3. Why is ignoring disruption risk likely to result in a higher total expected cost
compared to overestimating the risk of disruption?
Ignoring disruption risk is equivalent to estimating the probability of a disruption
to be 0. In such a situation a firm will make no investment in resilience, which
reduces upfront costs but is expensive when a disruption occurs. In contrast,
overestimating the risk of disruption results in over investment in resilience by
increasing alternate sources, flexibility, risk management inventory, or reserve
capacity. These investments are expensive upfront but can also be used to
effectively deal with recurrent risks. For example, if a firm has multiple sources
, CHAPTER NINETEEN
Discussion Questions
of supply it can also use them to deal with geographical fluctuations in demand or
fluctuations in transportation costs. Whereas ignoring disruption risks results in
actions that are vulnerable to both recurrent and disruption risks, overestimating
disruption risks results in actions that are helpful in dealing with both recurrent
and disruption risks. Thus, long term costs of over estimation tend to be lower
than long term costs of ignoring disruption risk.
4. What factors affect TTR for a disrupted node? What actions can help decrease
TTR?
Time to recovery is affected by how quickly a disruption is sensed and investment
in rapid recovery. A successful example is from the oil and gas industry where
sensors have allowed for the real-time monitoring and online evaluation of
equipment operation, enabling the timely detection and maintenance of
anomalies. Timely detection allows for preventive maintenance before the
equipment fails resulting in a much shorter and cheaper shutdown than if the
equipment had failed. In general, early detection combined with the capacity to
take corrective action before the actual disruption occurs can help reduce TTR.
Availability of alternate supply sources helps increase TTS, allowing for
corrective action to be taken without hurting supply chain output.
5. What factors affect TTS for a disrupted node? What actions can help increase
TTS?
TTS is affected by how quickly a disruption is sensed, available inventory beyond
the disrupted node, and any alternative capacity available. TTS can be increased
by decreasing the detection lead time for the disruption, increasing available
inventory, and increasing alternate capacity that can substitute for the disrupted
node. For example, having more than one warehouse capable of supplying various
markets, Amazon increased TTS by shifting to alternate warehouses when any
warehouse had to be shutdown during COVID.
6. Why does the inclusion of disruption risk increase the total expected cost of
centralized supply chains to a greater extent than for decentralized supply chains?
Centralized supply chains have a few locations where capacity or inventory is
concentrated. This concentration increases the impact of any disruption at these
locations. Decentralized supply chains, in contrast, have many locations that carry
capacity or inventory. This reduces the impact of any location being disrupted.
Decentralized supply chains are also more likely to have duplicate capabilities at
locations making it easier to use a backup in case of a disruption.
