# BUSINESS MODELLING AND SIMULATION IN SUPPLY CHAINS;

BUSINESS MODELLING AND SIMULATION IN SUPPLY CHAINS;

The coursework comprises elements: individual works. Normally, failure to take an active part in the group work correlates with poor performance in the individual

work. It is advisable that you set about forming groups as early as possible.

Element 2 –Individual work (2000 words)

Read the case in the end of these instructions, download the spreadsheet file ‘TheCase-CurrentState.xls’ from Blackboard and familiarise yourself with it. Use this

file to complete your individual work. Note that you may want to modify the spreadsheet model to complete your analysis.

You are required to complete Tasks 1-4. In Tasks 1-3, your analyses, answers, recommendations, etc. should cover the two products: Magnetic and Spinner bikes. In this

element, you must use impulse signal input to complete your analysis for Tasks 1-3, therefore you should write ‘yes’ on cell ‘Setting!C7’.

TASK 1: RECOMMENDATIONS TO ULTRASPORT

In this task, your final goal is to make a proposal to Ultrasport so that it can minimise its costs and the bullwhip effect. For each product, assess the impact of

different decision policies on Ultrasport’s costs and variability between production and demand. In this task, you should not change any policies used by Amazon. The

following are potential policies and scenarios for Ultrasport’s replenishment system you may want to consider and investigate:

• Use different moving average parameter values

• Use different forecasting method

• Investigate the impact of changing the production lead-time

• Use a different inventory policy (e.g. Base-Stock policy)

Critically evaluate the impact of the different scenarios and justify your answers with the aid of the results of your spreadsheet analysis. You should conclude Task 1

with recommendations to Ultrasport and detailed description of potential benefits to it. Note that you do not have to consider the case where Ultrasport uses the OUT

policy with an MMSE forecasting. This is out of the module scope.

TASK 2: IMPACT OF AMAZON’S POLICIES ON BOTH AMAZON AND ULTRASPORT

You are expected to assess the impact of policy changes in Amazon on both Amazon’s and Ultrasport’s costs and bullwhip measure for each product, assuming that any

policy used by Ultrasport are the policies described in the current situation scenario. You are not allowed to change any policies used by Ultrasport in this task. The

following are potential policies and scenarios for Amazon’s replenishment system you may want to consider and investigate:

• Use different forecasting method (e.g. moving average or exponential smoothing)

• Investigate the impact of changing the replenishment lead-time

• Use the Base-Stock policy

Your report may include a discussion to the following fundamental questions:

• In what case can both Ultrasport and Amazon be better off at the same time?

• Or, is there a trade-off relationship? If so, what kind?

Again you must justify your answer with the results of your spreadsheet analysis.

TASK 3: COLLABORATIVE SCENARIO: SUPPLY CHAIN COST MINIMISATION (need make a table)

Consider again the original situation. Now your task is to minimise the total supply chain cost for each product, which is the sum of Amazon’s and Ultrasport’s costs.

Since it is revealed that changing lead-times is quite expensive, you are not allowed to change the values of the lead-time in this task. However, you are allowed to

exploit different ordering policies (i.e the OUT policy or base-stock policy), and/or different forecasting methods (i.e. moving average, exponential smoothing and

MMSE) for Amazon and Ultrasport. Note again that you do not have to consider the case where Ultrasport uses the OUT policy with an MMSE forecasting. This is out of the

module scope. For each product, to minimise the total supply chain cost, which ordering policy and forecast method do you recommend to Ultrasport and Amazon? What is

the benefit for the supply chain by doing so? Is there any disadvantage of your recommendations? Justify your answer.

TASK 4: MANAGERIAL INSIGHTS

Discuss managerial insights you obtained from this coursework. In your discussion you should reflect upon all results obtained in Tasks 1-3. You are expected to

compare your findings with previous empirical and conceptual research.

You are required to submit a report of 2000 words at maximum. The outline of this report might be:

1. Task 1

2. Task 2

3. Task 3

4. Task 4

5. References

6. Appendices

You are encouraged to exploit figures, formulas, tables, references and appendices effectively in your report. Your individual coursework will be evaluated based

solely on the report, therefore there is no need to submit other files (e.g. Excel or other spreadsheet files). Submission deadline for the Individual Work (Element

One) is Midday on 19th March 2014.

The case

Ultrasport is one of the world’s largest sport equipment manufacturers. In the UK, the company produces two types of exercise bikes: the Magnetic and Spinner bikes.

Ultrasport uses an Automatic Pipeline, Inventory and Order-Based Production Control System to manage its inventory. A production request is submitted to the production

line using an Order-Up-To (OUT) policy with Moving Average (MA) forecast. In the current situation scenario, the moving average parameter used to obtain the forecast

for both products is equal 4. The production lead-time is 4 days for both products. Ultrasport incurs an inventory cost and a production cost at the end of each time

period.

The biggest customer for Ultrasport is the online retailer Amazon. Amazon also exploits the OUT policy to determine its order quantity to Ultrasport every time period.

The forecasting method used by Amazon is a Minimum Mean Square Error (MMSE) forecasting. The replenishment lead-time for Amazon is 4 days. Amazon also incurs an

inventory cost at the end of each time period.

The daily market demands of both two products follow Auto-regressive (AR(1)) type of processes,

where µ is the mean of the demand, ? is the auto-regressive parameter and e is an i.i.d. normal error term with a standard deviation of 10. The value of ? for the

Magnetic bike is 0.7 and for the Spinner is 0. The values of µ for both products are 100. However, an impulse input demand error can also be used for the analysis.

Figure 1 shows a schematic of the supply chain.

Figure 1 Model of the exercise bikes supply chain

The spreadsheet file ‘TheCase-CurrentState.xls’ of this model is available on Blackboard.

When grading the coursework in relation to tasks 1-4, the examiner will make use of the criteria and grade descriptors given below. PG grades and grade point bands

[Senate Regulation 3 (2013 starters onwards)] are: A++ (17), A+ (16), A (15), A- (14), B+ (13), B (12), B- (11), C+ (10), C (9), C- (8), D+ (7), D (6), D- (5), E+ (4),

E (3), E- (2), F (1). For further information about marks, see http://www.brunel.ac.uk/about/administration/university-rules-and-regulations/senate-regulations/sr3-

2013-onwards

Element 2 –Individual work (2000 words)

Read the case in the end of these instructions, download the spreadsheet file ‘TheCase-CurrentState.xls’ from Blackboard and familiarise yourself with it. Use this

file to complete your individual work. Note that you may want to modify the spreadsheet model to complete your analysis.

You are required to complete Tasks 1-4. In Tasks 1-3, your analyses, answers, recommendations, etc. should cover the two products: Magnetic and Spinner bikes. In this

element, you must use impulse signal input to complete your analysis for Tasks 1-3, therefore you should write ‘yes’ on cell ‘Setting!C7’.

TASK 1: RECOMMENDATIONS TO ULTRASPORT

In this task, your final goal is to make a proposal to Ultrasport so that it can minimise its costs and the bullwhip effect. For each product, assess the impact of

different decision policies on Ultrasport’s costs and variability between production and demand. In this task, you should not change any policies used by Amazon. The

following are potential policies and scenarios for Ultrasport’s replenishment system you may want to consider and investigate:

• Use different moving average parameter values

• Use different forecasting method

• Investigate the impact of changing the production lead-time

• Use a different inventory policy (e.g. Base-Stock policy)

Critically evaluate the impact of the different scenarios and justify your answers with the aid of the results of your spreadsheet analysis. You should conclude Task 1

with recommendations to Ultrasport and detailed description of potential benefits to it. Note that you do not have to consider the case where Ultrasport uses the OUT

policy with an MMSE forecasting. This is out of the module scope.

TASK 2: IMPACT OF AMAZON’S POLICIES ON BOTH AMAZON AND ULTRASPORT

You are expected to assess the impact of policy changes in Amazon on both Amazon’s and Ultrasport’s costs and bullwhip measure for each product, assuming that any

policy used by Ultrasport are the policies described in the current situation scenario. You are not allowed to change any policies used by Ultrasport in this task. The

following are potential policies and scenarios for Amazon’s replenishment system you may want to consider and investigate:

• Use different forecasting method (e.g. moving average or exponential smoothing)

• Investigate the impact of changing the replenishment lead-time

• Use the Base-Stock policy

Your report may include a discussion to the following fundamental questions:

• In what case can both Ultrasport and Amazon be better off at the same time?

• Or, is there a trade-off relationship? If so, what kind?

Again you must justify your answer with the results of your spreadsheet analysis.

TASK 3: COLLABORATIVE SCENARIO: SUPPLY CHAIN COST MINIMISATION

Consider again the original situation. Now your task is to minimise the total supply chain cost for each product, which is the sum of Amazon’s and Ultrasport’s costs.

Since it is revealed that changing lead-times is quite expensive, you are not allowed to change the values of the lead-time in this task. However, you are allowed to

exploit different ordering policies (i.e the OUT policy or base-stock policy), and/or different forecasting methods (i.e. moving average, exponential smoothing and

MMSE) for Amazon and Ultrasport. Note again that you do not have to consider the case where Ultrasport uses the OUT policy with an MMSE forecasting. This is out of the

module scope. For each product, to minimise the total supply chain cost, which ordering policy and forecast method do you recommend to Ultrasport and Amazon? What is

the benefit for the supply chain by doing so? Is there any disadvantage of your recommendations? Justify your answer.

TASK 4: MANAGERIAL INSIGHTS

Discuss managerial insights you obtained from this coursework. In your discussion you should reflect upon all results obtained in Tasks 1-3. You are expected to

compare your findings with previous empirical and conceptual research.

You are required to submit a report of 2000 words at maximum. The outline of this report might be:

1. Task 1

2. Task 2

3. Task 3

4. Task 4

5. References

6. Appendices

You are encouraged to exploit figures, formulas, tables, references and appendices effectively in your report. Your individual coursework will be evaluated based

solely on the report, therefore there is no need to submit other files (e.g. Excel or other spreadsheet files). Submission deadline for the Individual Work (Element

One) is Midday on 26th March 2014.

The case

Ultrasport is one of the world’s largest sport equipment manufacturers. In the UK, the company produces two types of exercise bikes: the Magnetic and Spinner bikes.

Ultrasport uses an Automatic Pipeline, Inventory and Order-Based Production Control System to manage its inventory. A production request is submitted to the production

line using an Order-Up-To (OUT) policy with Moving Average (MA) forecast. In the current situation scenario, the moving average parameter used to obtain the forecast

for both products is equal 4. The production lead-time is 4 days for both products. Ultrasport incurs an inventory cost and a production cost at the end of each time

period.

The biggest customer for Ultrasport is the online retailer Amazon. Amazon also exploits the OUT policy to determine its order quantity to Ultrasport every time period.

The forecasting method used by Amazon is a Minimum Mean Square Error (MMSE) forecasting. The replenishment lead-time for Amazon is 4 days. Amazon also incurs an

inventory cost at the end of each time period.

The daily market demands of both two products follow Auto-regressive (AR(1)) type of processes,

(MATH FORMULAS IN THE UPLOAD FILES )

where µ is the mean of the demand, ? is the auto-regressive parameter and e is an i.i.d. normal error term with a standard deviation of 10. The value of ? for the

Magnetic bike is 0.7 and for the Spinner is 0. The values of µ for both products are 100. However, an impulse input demand error can also be used for the analysis.

Figure 1 shows a schematic of the supply chain.

Figure 1 Model of the exercise bikes supply chain

The spreadsheet file ‘TheCase-CurrentState.xls’ of this model is available on Blackboard.

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