Department of ISOM Business Logistics The University of Auckland Semester 1, 2017

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Individual Assignment

Due on Friday, 5 May 2017

Instructions Read the following three cases, CoolWipes, Sunchem, and SPC, and answer the questions at the end of each case. An Excel file including the inputs and incomplete models for the three cases has been provided. Download the file (from Canvas) and use the existing worksheets inside the file to complete your assignment. Submit your work to Canvas by the deadline (5 May). Please follow these easy but important rules:

1. Rename the Excel file as your “upi_full name” (all lowercase), and do not change the name/order of the worksheets inside the file.

2. Do not change/add/remove worksheets and their inputs, tables, titles, formatting, and any content that already exists when you first open the file. All you need to do is to complete the provided worksheets to answer the questions, and then write a short discussion summarising your findings.

3. Three of the worksheets contain an empty blue box where you should write your discussion (of up to 150 words) for each case.

4. Do not submit anything else than your completed Excel file for this assignment. Marking rubric This assignment has a total of 100 points which are allocated to the questions based on the following table:

Case Item Points

CoolWipes

Q1 5

20 Q2 5

Q3 5

Discussion: Summarising answers to the questions, and discussing/justifying the results. 5

Sunchem

Part a 7

30 Part b 7

Part c 7

Discussion: Justifying results of part c, and answering part d.

9

SPC

Forecasting via method 1 10

50

Error analysis for method 1 10

Forecasting via method 2 10

Error analysis for method 2 10

Discussion: Reasoning why the two selected methods are correct choices. Comparing and discussing the outputs of the methods, identifying which one is better and why.

10

Total 100

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Case 1: CoolWipesi

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Case 2: Sunchemii

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Case 3: SPCiii

Hint: Select the two potential best forecasting methods first, run the forecast using both methods, then decide which is better based on the forecast error analyses.

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i, ii, iii Chopra S., Meindl P., Supply Chain Management; Strategy, Planning, and Operation, 6Ed, Pearson, 2016. pp.152, 146, and 219.