1. Sales Forecasting & Production Planning
Presented by
Dr. Kern Kwong

2. Decision Form:

3. Excel Spreadsheet Templates:
Several templates will be provided:
Historical Data Worksheet
Sales Forecast Worksheet
Shipment Orders Worksheet
Production Schedule Worksheet
An Excel file containing these templates can be downloaded online at:
Additional lecture notes, along with some flow charts, can also be downloaded from there.
Also from our class Moodle site, with updated historical data

4. Use your own data from both industry and company reports:
After opening the BPG program, you can view all the reports:
Report J (see p.210 of the Player’s Manual for a sample) Historical Data for Years 1 and 2 – GDP, CPI, product sales, and product prices.
Report D (see p.215 of the Player’s Manual for a sample)
Company’s Current Operating Information – Output, inventory, and product sales
Report F (see pp of the Player’s Manual for a sample)
Recent Industry Information – Real GDP, exchange rates, product sales, and product prices.

5. View reports:

6. A top-down approach will be used for sales forecasting:
Industry Level
The method starts with sales forecasting at the industry level for each market area:
M1 (Merica 1)
M2 (Merica 2)
M3 (Merica 3)
M4 (Nystok, Pandau, or Sereno)
Company Level
From industry sales forecasts, company sales forecasts for the corresponding market areas can then be obtained as:
Company Sales Forecast
= Industry Sales Forecast × Expected Market Share

7. Need to account for seasonal effects on sales:
See Section 1.A of the Lecture Notes on Forecasting.
Seasonal Indices (p.105 of the Player’s Manual)
Q1 (Winter) 0.92
Q2 (Spring) 1.01
Q3 (Summer) 0.91
Q4 (Fall)

8. Use a regression model to forecast industry sales:
See Section 1.B of the Lecture Notes on Forecasting.
Dependent variable (Y)
SA Sales: Seasonally Adjusted Industry Sales
Independent variables – Predictors (X)
Real GDP: Real Gross Domestic Product
Avg Price: Industry Average Price
Time: Time Trend Index
Note: Real GDP is an often used indicator for the general demand and business conditions. The Time variable can capture demand changes generated by demographic trends.

9. Try a few different forecasting equations and identify the best one:
Model #1:
SA Sales = 0 + 1  Time
Model #2:
SA Sales = 0 + 1  Real GDP
Model #3:
SA Sales = 0 + 1  Avg Price
Model #4:
SA Sales = 0 + 1  Time + 2  Real GDP
All these forecasting equations are to be estimated using Excel on the Sales Forecast Worksheet.

10. Try a few different forecasting equations and identify the best one:
Model #5:
SA Sales = 0 + 1  Real GDP + 2  Avg Price
Model #6:
SA Sales = 0 + 1  Avg Price + 2  Time
Model #7:
SA Sales = 0 + 1  Time + 2  Real GDP + 3  Avg Price
Best Model: highest Adjusted R-square with Correct Sign
(e.g. Coefficient of Avg Price should be negative, SA Sales decrease when Avg Price increases)

11. Best Model – M1, Y3Q1 Model Adj. R-Square Correct Sign 1 Time .545 Yes
2 Real GDP
.530
3 Avg Price
.023
4 Time + Real GDP
.454
No-GDP
5 Real GDP + Avg Price
.437
No-Price
6 Avg Price + Time
.474
7 Time + Real GDP + Avg Price
.394
No-Price, GDP

12. Best Model – M2, Y3Q1 Model Adj. R-Square Correct Sign 1 Time
2 Real GDP
3 Avg Price
4 Time + Real GDP
5 Real GDP + Avg Price
6 Avg Price + Time
7 Time + Real GDP + Avg Price

13. Best Model – M3, Y3Q1 Model Adj. R-Square Correct Sign 1 Time
2 Real GDP
3 Avg Price
4 Time + Real GDP
5 Real GDP + Avg Price
6 Avg Price + Time
7 Time + Real GDP + Avg Price

14. Best Model – M4, Y3Q1 Model Adj. R-Square Correct Sign 1 Time
2 Real GDP
3 Avg Price
4 Time + Real GDP
5 Real GDP + Avg Price
6 Avg Price + Time
7 Time + Real GDP + Avg Price

15. Best Model – M1, Y3Q1 Model Adj. R-Square Correct Sign 1 Time
2 Real GDP
3 Avg Price
4 Time + Real GDP
5 Real GDP + Avg Price
6 Avg Price + Time
7 Time + Real GDP + Avg Price

16. Step-by-step forecasting exercise:
When using the Excel template for forecasting, you should read Sections 2.A to 2.E of the Lecture Notes on Forecasting for step-by-step instructions.
We will go through all the steps when looking at the template later:
To start, prepare initial data on regression variables using available historical data (see Section 2.A).
After setting up the data, estimate the forecasting regression equation using Excel (see Section 2.B).
Try different models and select the model that fits the data best (see Section 2.C).
Enter additional assumptions and your market share projection (see Section 2.D).
Repeat the forecasting exercise – steps 2 to 4 – after adding new data every quarter (see Section 2.E).

17. After obtaining company sales forecasts, we next determine how much to produce:
Read Lecture Notes on Production Planning (download it from OR from Moodle.
For our production analysis, we will use the following two Excel templates together:
Shipment Orders Worksheet
Production Schedule Worksheet

18. To determine a production target, we need to think about inventory management:
How much inventory to hold in each market area?
Carrying too little inventory may lead to costly stockouts:
Stockouts can result in not only a loss of present sales but also a loss of some future sales. Some dissatisfied customers may not come back.
Carrying too much inventory can be costly too:
Warehouse storage cost;
Financing cost for tying up working capital;
Product obsolescence.

19. Choose an inventory ratio that balances between over- and under-stocking costs.
Choose an inventory-to-sales ratio for each market area (when using the Shipment Orders Worksheet):
Under normal situations, a ratio from 25% to 45% should be sufficient for the game.
An example: Suppose the ratio is chosen to be 25%. If the sales demand is forecasted to be 100,000 units, then
Desired Inventory = 100,000 × 25% = 25,000 units.
The choice of inventory-to-sales ratios will affect how many product units to be shipped to different market areas.

20. How should production be scheduled
How should production be scheduled? Should production capacity be expanded?
See Chapters 7 & 8 of the BPG Player’s Manual (read also Section 3 of the Lecture Notes on Production Planning):
Normal operations: 40 hours per line each week
Schedule overtime: Up to 8 hours per line
Add second work shifts (Take 1 quarter to complete)
Create new production lines (Take 1 quarter)
Reactivate some idle lines (Take 1 quarter)
Add more space to a plant (Take 2 quarters)
Build a new plant (Take 3 quarters)

21. Overall: Keys to Successful Production Management
A number of factors are crucial for a company’s success in production management:
Reasonably accurate sales forecasts;
Excellent inventory control to cope with demand and production uncertainties;
Proper allocation of product shipments to regional sales offices and thereby to customers;
Efficient production scheduling to meet current production targets;
Timely production capacity adjustment (including plant expansion or construction) to meet future product demand.

22. Company Sales Forecasts by Market Area Desired Inventory Ratio
Estimated Shipment Orders to Sales Offices by Market Area
Planned Production Target
Production Scheduling:
Lines, Overtime, and Second Shifts
Production Capacity Expansion:
New Lines or Plants?
Production Cost Analysis
Capital Budgeting Analysis

24. mgmt49701@gmail.com every quarter
Screen print of your
decision screen and
research report order (if your ordered)

26. Hope you will enjoy the Business Policy Game!