Reference no: EM13907609

Read the following case study and answer the questions that follow.

MUZTAFAH is a consumer product retailer located in Singapore. One of the products sold by MUZTAFAH all over Singapore is the GREEN brand air-conditioners. MUZTAFAH has the exclusive retailing rights from its German manufacturer. Based on a survey conducted in 2012, It was found out that Singapore families replace their air-conds roughly once every 5 years. When they do replace their air-conds, they tend to visit the same retailer that sold them the first one, building a relationship with the retailer. This has kept sales relatively stable for all the retailers in the city. However in recent years, customers have begun expanding their shopping options. MUZTAFAH believes this is due to the rise of the Internet, social media and changes in customers' preference for the type of air-conditioners required for their homes. Customers have begun corning to the retail shops with an exact idea of what air-conds they would like and have a price in mind, especially young couples who are getting their first HDB flat. When MUZTAFAH does not have the model available like energy saving and environmental friendly air-conds or cannot meet the price, customers go to their competitors. MUZTAFAH only sells its product through a 20.000 square feet outlet at Serangoon. It is a very traditional company and does not have any website or online e-commerce capability.

This trend has the Managing Director of MUZTAFAH, Mr Ali Ahmed, worried. Mr Ali's retail shop relies on repeat customer orders. MUZTAFAH is not a chain and has little access to outside capital, so cash flow is critical. If sales are low. Mr Ali has to take out a loan to pay the manufacturer for the air-cond. If sales are high. MUZTAFAH loses potential customers due to lack of inventory. Mr Ali has decided that he needs to be able to forecast this new variability to keep the business healthy.

Mr Sani is the demand manager at MUZTAFAH and has historically prepared the forecasts. Mr Sani usually just takes the sales numbers from last year and adjusts them upwards or downwards based on his "gut feeling." This has worked well in the past, but Mr Ali has told him to look into other forecasting methods and the changing consumer buying behavior and patterns. Mr Sani is preparing the 2014 sales forecast for MUZTAFAH and is not sure where to start.

For the August 2011 forecast. Mr Sani used the sales number from August 2010. That means, he applied 2010 monthly sales number to be 2010 monthly sales forecast with an adjustment. The August 2011 forecast was off by 3 units of air-conds and Mr Sani is extremely proud with his forecasts. Mr Sani assumed the sales representatives would always work a little harder if sales were low and they could always take holidays if they were above target for the month.

Mr Ali has told Mr Sani to look into both time series and causal forecasting models. but Mr Sani is not sure of the differences. Mr Ali also wants Mr Sani to determine the amount of profit being lost due to poor forecasting from the past 18 months. Mr Sani has access to sales and forecast data from the past 18 months but does not how to proceed to analyze the data further. See Table 1.

Table 1- MUZTAFAH Sales Forecast History

Month	Forecasted (wits)	Actual Sales (units)
Aug-11	103	100
Sept-11	120	129
Oct-11	441	478
Nov-11	418	398
Dec-11	204	210
Jan-12	103	123
Feb-12	135	104
Mar-12	101	98
Apr-12	108	100
May-12	109	93
June-12	99	108
July-12	115	102
Aug-12	101	88
Sept-12	119	125
Oct-12	453	509
Nov-12	115	120
Dec-12	108	108

Questions:

1. Describe the characteristics of the product (GREEN Air-conds) sold by MUZTAFAH. How has consumer preference on this type of product changed over the years? Do you think MUZTAFAH understands its customers' changing needs?

2. Looking at Table 1, is MUZTAFAH currently using a time series or causal forecasting method? Explain the difference between these two (2) types of forecasting methods and how do you identity with each of the method.

3. Based on the data given, how would you advise Mr Sani in measuring the performance of his forecasts? What metrics would you recommend to Mr Sani and how would it help him?

4. Is this type of forecast appropriate for MUZTAFAH if the management would like the tracking signal (TS) to be within +/- 2.00?

5. What are the different forecasting methods that are appropriate for MUZTAFAH's product?

6. If Mr Sani's forecasts are consistently too high or consistently too low, how would you recommend him to remedy the situation? Why?

7. If the average sale price for one set of air-cond for a typical HDB 5-room unit is $8,000 and the average cost to acquire is $6,800, how much profit is being lost each month as a result of poor forecasting( over forecast or under forecast)

Note: For ease of calculation, assume all air conditionings arrive on 1 of the month and all air-conds remaining at the end of each month are sold at 15% discount to customers or competitors.

8. Suggest what else MUSTAFAH can do to improve future forecasts.

9. Suggest what are the relevant supply chain processes or technologies that MUZTAFAH can implement in order to achieve a better service supply chain performance?