The McDonald’s store at a busy mall has collected its last 10 months’ sales (in thousands of meal) data for its fast selling a la carte meal—The Feast McChicken. To provide consistent taste in chicken-related meals, McDonald’s buys the raw chicken from a couple of suppliers. The quantity and quality of supply from the suppliers are not uniform. Quantity may vary due to weather, variety, diseases, etc., while the quality of supply is affected due to the appearance, tenderness, and flavor of the meat. The store cannot have a high safety stock since meat cannot be stored beyond an expiry date. All these issues lead to supply fluctuations. The demand from the customers are also uncertain due to eating habits and external factors, for example, recently, people from southern India stopped eating chicken for a few months fearing that the meat might contain the deadly Nipah virus. All these uncontrollable factors make managing supply and demand more complex. One way to manage the problem to a certain extent is to forecast the demand; an accurate forecast of the demand will help the store order the supply at the right quantities at the right time. To help forecast the sales, the store uses its past 10 months’ sales data.

a. Compute a three-month moving average forecast of demand for months 4 through 10.
b. Compute a three-month weighted moving average forecast of demand for months 4 through 10. Use the weights 0.50, 0.30, and 0.20 to the months in sequence starting with the most recent month.
c. Compare the two forecasts in (a) and (b) using MAD. Which forecast appears to be more accurate? Also, recommend the forecast for the 11th month.

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Month 1 2 MASCT00 4 5 6 8 9 10 Sales 12 14 15 16 18 21 24 26 28 32