SB Coffee has a large, nationwide supply chain that must efficiently supply over 200 stores. Although the stores might appear to be very similar, they are actually very different. Depending on the
location of the store, its size, and the profile of the customers served, SB Coffee management configures the store offerings to take maximum advantage of the space available and customer
preferences. SB Coffee’s actual distribution system is much more complex, but the information below is directed at only a single item that is currently distributed through five distribution centres
in Australia. The item is a logo branded coffee maker that is sold at some of the larger retail stores. The coffeemaker has been a steady seller over the years due to its reliability and rugged
construction. SB Coffee does not consider this as a seasonal product, but there is some variability in demand. Demand for the product over the past 13 weeks is shown in the following table. The
demand at the distribution centres (DCs) varies from a maximum of 68 at Sydney in Week Number 13 and a minimum of 10 in Week Number 12 at Darwin.
Management would like you to experiment with some forecasting models to determine what should be used in a new system to be implemented. Their initial request is provide recommendations over two
forecasting models: simple moving average and exponential smoothing.
c. Compare all the techniques in Part a and Part b (The table have been done above) and explain which of these would be preferable. Explain the reasons for your choice.
d. What other factors (other than past demand) would you consider to draw up more accurate forecasted figures? Describe also what mathematical technique (or techniques) you would use to derive the
new forecast which will take all these factors into account.
(Note: Limit your answer to 350 words)
e. SB Coffee is considering simplifying the supply chain for their coffeemaker. Instead of stocking the coffeemaker in all five distribution centres, they are considering only supplying it from a
single location. What are the advantages and disadvantages of aggregating demand from a forecasting view?
Are there other factors or issues that should be considered when going from multiple DCs to a single DC?