Naive method forecasting excel

Every day managers must make decisions on future demands for their product or service. Knowing the future demand for your product is important so that staffing levels can be adjusted or more equipment and raw material procured. However, future demand is unknown, so managers turn to forecasts to make good estimates of future demand for their product or service.

Now put yourself in the shoes of the plant manager. This chart provides historical data for the past demand for your product. Your task is to apply the naïve, moving average, exponential smoothing, and trend methods of forecasting and determine which method is the most accurate.

Week

Demand

Week 1

55

Week 2

75

Week 3

65

Week 4

70

Week 5

80

Week 6

85

Week 7

75

Week 8

80

Week 9

90

Week 10

75

Assignment

Use the Excel OM plugin and the data to run the forecast using naive, weighted moving average, exponential smoothing, and trend projection (without exponential smoothing) methods. Use this information.

· Weighted moving averages method - use two periods with 0.1 and 0.4 as the weights.

· Exponential smoothing method - use an alpha of 0.1.

After you run the data, determine which method provided the most accurate forecast and explain your reasoning.

Submit your spreadsheet and include your selected method and explanation on the spreadsheet.

Install Excel OM

After you have installed Excel on your computer, download and install Excel OM.

Use the following resources to download Excel OM:

· Download Excel OM for PCs, Version 5.3 (Pearson) (Links to an external site.)Links to an external site.

· Download Excel OM for Macs, Version 5.3 (Pearson) (Links to an external site.)Links to an external site.

Note for Windows Users: Windows Defender, Windows SmartScreen, and some virus protection programs on Windows computers may prevent Excel OM/QM from installing. For troubleshooting, refer to the Security Program Prevents Installation (Links to an external site.)Links to an external site.document created by the application developer, Dr. Howard Weiss.

Note for Mac Users: The download file for Macs is a ZIP file with the Excel OM/QM for Macs program. Unzip the file. To start Excel OM/QM, open the file named ExcelOMQMV5.xlam.

To use Excel OM, you must launch Excel using the Excel OM shortcut and enable macros.

Forecasting Methods

Every day managers must make decisions on future dema

nds for their

product or service. Knowing the future demand for your product is important

so that staffing levels can be adjusted or more equipment and raw material

procured. However, future demand is unknown, so managers turn to forecasts

to make good est

imates of future demand for their product or service.

Now put yourself in the shoes of the plant manager. This chart provides

historical data for the past demand for your product. Your task is to apply the

naïve, moving average, exponential smoothing, and trend methods of

forecasting and determine which metho

d is the most accurate.

Week

Demand

Week 1

55

Week 2

75

Week 3

65

Week 4

70

Week 5

80

Week 6

85

Week 7

75

Week 8

80

Week 9

90

Week 10

75

Assignment

Use the Excel OM plugin and the data to run the forecast using naive,

weighted moving average, exponential smoothing, and trend projection

(without exponential smoothing) methods. Use this information.

·

Weighted mov

ing averages method

-

use two periods with 0.1 and 0.4 as

the weights.

·

Exponential smoothing method

-

use an alpha of 0.1.

After you run the data, determine which method provided the most accurate

forecast and explain your reasoning.

Submit your spreadshe

et and include your selected method and explanation

on the spreadsheet.

Forecasting Methods

Every day managers must make decisions on future demands for their

product or service. Knowing the future demand for your product is important

so that staffing levels can be adjusted or more equipment and raw material

procured. However, future demand is unknown, so managers turn to forecasts

to make good estimates of future demand for their product or service.

Now put yourself in the shoes of the plant manager. This chart provides

historical data for the past demand for your product. Your task is