a commercial bakery has recorded sales (in dozens) for three products, as shown below:

Forecasting & Smoothing Methods

Solved Problem #1: see text book

Solved Problem #2: see textbook (manual example using seasonal relatives)

Solved Problem #3: see textbook

Solved Problem #4: see textbook (you do not have to do this problem manually, use the template and notice how the template answers differ slightly from the seasonal relatives provided in the manual example)

To avoid manually entering the data into the templates it can be copied and pasted from Data Sets on the Lesson Page. Use “copy, paste special, values” to transfer the data to the template.

#1: A commercial bakery has recorded sales (in dozens) for three products, as shown below.

  Day BlueberryCinnamon Cupcakes  
   Muffinsbuns   
  1 3018 45  
  2 3417 26  
  3 3219 27  
  4 3419 23  
  5 3522 22  
  6 3023 48  
  7 3423 29  
  8 3625 20  
  9 2924 14  
  10 3126 18  
  11 3527 47  
  12 3128 26  
  13 3729 27  
  14 3431 24  
  15 3333 22  
a.  Determine the Naïve forecast for day 16.     

b.   What does the use of sales data rather than demand data imply?

#2: National Scan, Inc., sells radio frequency inventory tags. Monthly sales ($000) for a seven-month period were as follows:

MonthSales
Feb19
Mar18
Apr15
May20
Jun18
Jul22
Aug20
  1. Plot the monthly data.
  2. Forecast September sales volume in thousands of dollars using the following methods: Show your answers in the space provided.

1.       Naïve

2.       Five-month moving average

3.       Weighted moving average using .60 for August, .30 for July, and .10 for June

4.       Exponential smoothing with a smoothing constant of .20

5.       Linear trend equation.

#3: A cosmetics manufacturer’s marketing department has developed a linear trend equation that can be used to predict annual sales of its popular Hand & Foot Cream.

Ft  =80+15t where

F t= annual sales (000 bottles)

t   = 0corresponds to1990

  1. Indicate how much the sales are increasing or decreasing?
  2. Predict sales for the year 2006 using the equation? This is a manual problem!

#4: Freight car loadings over a 12-year period at a busy port are as follows: The units are in thousands of tons.

YearLoadings
1220
2245
3280
4275
5300
6310
7350
8360
9400
10380
11420
12450
13460
14475
15500
16510
17525
18541
  1. Determine the linear trend equation for the freight car loadings.
  2. What is the slope? Interpret it.
c.Use the trend equation to predict the freight loadings for years 20 and 21.
d.The manager intends to install new equipment when the loadings exceeds 800 (thousand tons) per
 year. Assuming the current trend continues the loading volume will reach that level in
 approximately what year? This is a manual problem!

#5: A manager of a store that sells and installs spas wants to prepare a forecast for January, February and March of next year. Her forecasts are a combination of trend and seasonality.

The linear trend equation is

Ft  =70+5t where

t =0 corresponds to June of last year

The seasonal relatives are 1.10 for January, 1.02 for February, and .95 for March.

  1. What demand should she predict for January, February and March of next year? This is a manual problem! If you need some hints on this problem, refer to solved problem #2 in the textbook.

#6: Obtain estimates of daily relatives for the number of customers at a restaurant for the evening meal given the past 4 weeks of historical data. Day 1 is day 1 of week 1, day 8 is day 1 of week 2, etc.

DayServed
180
275
378
495
5130
6136
740
882
977
1080
1194
12125
13135
1442
1584
1677
1783
1896
19135
20140
2137
2287
2382
2498
25103
26144
27144
2848

a.  Construct a graph that will enable you to visualize the daily variation in meals served.

b.       What are the daily adjusted seasonal relatives?

c.        Plot the adjusted seasonal relatives on a graph for each day of the week?

  1. Determine the forecast for meals to be served for the next 7 days.
  2. Plot historical demand with forecast on the same graph.

#7: A farming cooperative manager wants to estimate quarterly relatives for grain shipments, based on the 5 years of data shown below (quantities are in metric tons). You will have to enter this data into the template manually.

  QUARTER 
Year1234
1200250210340
2210252212360
3215260220358
4225272233372
5232284240381

a.       Calculate the quarterly adjusted seasonal relatives.

b.       Use the adjusted seasonal relative to determine what percentage shipments in quarter 4 are greater than shipments quarter 3.

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