SCM Chapter 5 Forecasting

Using the actual demand shown in the table below, what is the forecast for June (round to whole number) using a 3-month weighted moving average and the weights 0.2, 0.3, 0.5 (remember how to apply them)? Dec. 39 Jan. 36 Feb. 40 Mar. 44 Apr. 48 May 50

= Mar(.2) + Apr(.3) + May(.5) = 44(.2) + 48(.3) + 50(.5) = 8.8 + 14.4 + 25 = 48.2

Mean square error (MSE)

An indicator of forecast accuracy. The forecast errors are squared and then summed and divided by the number of periods to determine the mean square error. The measure penalizes large errors more than small errors.

Proper demand forecasting enables _____________________ for businesses to be competitive.

Better planning and utilization of resources

Which forecasting method would use the size of the advertising budget as a variable in the forecasting technique?

Cause-and-Effect forecasting

According to the text, for long-term forecasts, it is recommended that which type of forecasts be used?

Combination of both qualitative and quantitative

Collaborative planning, forecasting, and replenishment (CPFR)

Concept aimed at supply chain integration, joint inventory visibility, and replenishment through the supply chain.

A company is conducting forecasting that revolves around the global recession and real estate crises. This type of forecasting can be referred to as what component of a time series?

Cyclical Variations

Period ; Actual Sales Volume 1 ; 10,000 2 ; 11,400 3 ; 14,550 4 ; 15,050 5 ; 17,250 6 ; 18,500 7 ; 15,700 8 ; 19,500 9 ; 22,200 10 ; 21,550 Using Data Set A1, what would be the forecast for period 6 using a four period simple moving average?

F6 =(11,400+14,550+15,050+17,250)/4 = 58,250/4 = 14562.5

The real value of CPFR comes from:

Firms exchanging forecasting information

CPFR relies heavily on?

Firms sharing information

Period ; Actual Sales Volume 1 ; 10,000 2 ; 11,400 3 ; 14,550 4 ; 15,050 5 ; 17,250 6 ; 18,500 7 ; 15,700 8 ; 19,500 9 ; 22,200 10 ; 21,550 Using Data Set A1, what would be the forecast for period 5 using the exponential smoothing method? Assume the forecast for period 4 is 14000. Use a smoothing constant of α = 0.4

Given F4 = 14,000 ; a = 0.4 F5 = F4 + a(A4 - F4) = 14,000 + 0.4(15,050 - 14,000) = 14,000 + 0.4(1,050) = 14,000 + 420 = 14,420

Which of the following is NOT a benefit of CPFR? a. Allows collaboration on future requirements and plans b. Improved corporate image among regulators c. Strengthens partner relationships d. Provides analysis of sales and order forecasts

Improved corporate image among regulators

Benefits of better forecasts are

Lower Inventories Reduced stockouts Smother production plans Reduced costs Improved customer service

Forecast Bias

Measures the tendency of a forecast to be consistently higher or lower than actual demand, over time.

Which one of the following is NOT a type of qualitative forecasting? a. Consumer survey b. Naïve method c. Jury of executive opinion d. Delphi method

Naïve method

Which type of forecasting technique would a firm likely use when launching a new product and historical data does not exist?

Qualitative

The impact of poor communication and inaccurate forecasts along the supply chain can cause:

Results in Bullwhip Effect Stockouts Lost sales High costs of inventory and obsolescence Material shortages Poor responsiveness Poor profits

According to the text, which of the following is NOT one of the top three challenges for CPFR? a. Cost b. Trust c. Sophisticated forecasting algorithms d. Difficulty making internal changes

Sophisticated forecasting algorithms

Forecast Error

The difference between the forecast quantity and the actual et = At - Ft

What component of a time series is based on increasing or decreasing movements over many years and are due to factors such as population growth, population shifts, cultural changes, and income shifts?

Trend Variations

Random variations in a Time Series component are due to:

Unpredictable events

Running Sum of Forecast Errors (RSFE)

provides a measure of forecast bias. RSFE indicates the tendency of a forecast to be consistently higher or lower than actual demand.

Mean absolute percentage error (MAPE)

the MAD adjusted to measure how large errors are relative to the actual demand quantities

Tracking Signal

used to determine if the forecast bias is within the acceptable control limits Tracking Signal = RSFE/MAD