Ba 357 assignment 1: forecasting annual demand with a monthly

General Instructions:

Assignment 1

 

You are to create a set of annual demand forecasts for one year, 2015, using five different forecasting methods as specified later.  After reviewing your annual forecast and error values, pick one annual forecast to recommend and distribute the annual forecast into monthly forecasts using the multiplicative seasonal forecasting method.  Then, prepare a brief executive summary indicating which forecast method you recommend the company to use for its aggregate planning and your reasons for choosing it. This summary page is to include your recommended forecast results listed by monthly demand and with the annual total demand.  Additional pages of your spread sheet file will include a page for each of your five forecasts, an Error summary page which combines error values for all five forecasts and one page for Seasonal Distribution of your demand for your chosen forecast method.  Error and other analysis should be included on the page for each individual forecast as well.

 

A summary Excel template for the executive summary cover page is provided for your use in the Work Assignment 1 folder in Week 5 on Blackboard.

 

Background:

Your company has just acquired a new subsidiary that produces sun hats and swimsuits.  Each product requires about the same amount of labor, time, and materials. All of the managers at the acquired company quit without notice the day your company took possession. You are the person who has been assigned to run this acquisition. Since all of the managers quit, the only planning information you have is historical data, including monthly demand and average annual days of sunshine for the targeted market.

 

Your task is to a forecast for the total demand for one year, 2015. Because the demand in the past has seasonally varied from month to month, the production organization needs for you to break the final forecasted annual demand down into monthly values so that they can begin scheduling resources and making appropriate purchases of materials from the company’s suppliers.

 

You have demand and weather data for the last 10 years. Weather forecasters are predicting 198 days of sunshine in the relevant region for 2015.  Their weather forecasts have been accurate to plus or minus 10 percent in years past.  According to industry experts there is about a 25% chance that the patterns of global consumer demand for 2014 will hold in the future. However there is a 10% chance that demand will be much less (at least 30%) than predicted from previous patterns because of continuing low levels of consumer confidence. And there is a 65% possibility that demand will recover to pre 2014 trends.  This information is provided to help you with your executive summary and analysis.

Aggregate Demand Data 2005 – 2014

 

 

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

JAN

1393

1613

1615

1777

1920

2032

1912

2070

1901

1668

FEB

1551

1920

2107

1779

2220

2559

2627

2997

2529

1948

MAR

4572

5705

7204

7667

8159

8380

8742

11631

9671

8447

APR

9792

11301

12452

14938

13491

14064

16282

17966

18089

16799

MAY

9412

10000

9876

11023

13216

13500

15842

16587

16954

16500

JUN

2622

3243

3234

3513

3954

4479

4683

4641

4107

4745

JUL

1722

1910

2309

2400

2727

3021

2600

2730

2664

3224

AUG

1888

2272

2604

2736

3412

4101

4875

5182

4416

4905

SEP

3711

4464

4972

5633

6774

7191

9488

9795

8762

10602

OCT

1036

1016

1316

1485

1693

1943

2340

2487

2211

2589

NOV

2056

2600

2893

3297

3889

4014

4149

4364

4223

4671

DEC

1872

2123

2354

2076

2157

2592

3357

3938

3432

3920

Note that the copy of the tables are presented as text tables so you can copy and use them with Excel spreadsheet software without having to re-enter the data values.

 

 

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

Annual Days of Sunshine

249

245

261

264

269

278

285

186

245

250

 

 

Requirements (60 points total):

§  An executive summary (5 points) that tells what forecast you are recommending, and why. Your justification should include qualitative and quantitative evidence to support your choice. The text content of this summary text is not to take more than a half sheet of paper.  The summary is to be accompanied below by a table containing the monthly forecast values and total annual demand forecasted by the method you are recommending.
Use the executive summary as your cover sheet – the first sheet of your assignment upload.  

 

§  Five separate forecasts (8 points each) for 2015 using:

ü  A simple moving average. (You will choose the number of periods (years) to use.)

ü  A weighted moving average.   (Use the same number of periods as you SMA forecast and choose the weighting values for each period.)

ü  the linear regression analysis method using the causal factor (Days of Sunshine.)

ü  the exponential smoothing method (Choose a value for a)

ü  Trend Projection with Regression (Choose the best number of periods to use)

ü  Error Analysis should be included with each of your forecasts, at a minimum CFE, MAD and MAPE values.

§  For each method you should show:

ü  The method/formula you are using, including any constants/parameters used

ü  The spreadsheet used for the calculations.

 

§  Error Analysis (5 points)  One page in your spreadsheet should combine error values for all 5 forecast methods.

§  Seasonality (10 points) Choose one annual forecast to recommend and break the annual total into monthly forecast amounts using the multiplicative seasonality method.

 

 

 

Submission Requirements:

§  Your Excel submission file is to be in the following order:

o   Executive summary with the table of recommended forecast values on top. This summary is to include your name.

o   Spreadsheet for simple moving average

o   Spreadsheet for weighted moving average

o   Spreadsheet for the linear regression forecast of annual demand (Causal.)

o   Spreadsheet for exponential smoothing forecast of annual demand.

o   Spreadsheet for Trend Projection with Regression.

o   Spreadsheet for Error comparison

o   Spreadsheet showing results for seasonal distribution of your one, recommended forecast.

§  Each page must be clearly labeled as to its content (with the exception of the executive summary page whose template is provided.

§  Do not make the reader guess what you are doing – include appropriate explanations on each page (additional comment functions, titles, notes, graphs etc.).

 

Upload your completed Excel file in Blackboard by 11:59 pm PDT on Sunday, July 26th.  Assignments will be accepted up to one week late at a penalty of 25% (prior to grading.)

 

 

Suggestions and Tips:

 

 

  1. Start by copying the table of demand data into one page in the template, than calculate yearly totals and monthly averages for each year.
  2. Work in annual numbers where ever you are able.
  3. Use Excel functions such as average, sum, slope and intercept, to help you do your calculations.
  4. Build formulae so that you can easily change values to optimize your forecast.
  5. Make sure to mention both quantitative and qualitative analysis in your executive summary.
  6. Ask questions in the Assignment 1 discussion board.
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