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In addition to your name, write down your section number & instructor’s name on the scantron sheet.

In addition to your name, write down your section number & instructor’s name on the scantron sheet.

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In addition to your name, write down your section number & instructor’s name on the scantron sheet.

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  1. In addition to your name,write down yoursection number & instructor’s nameon the scantron sheet. Business Game Quiz

  2. Sales Forecasting & Production Planning An Outline of the Analysis

  3. Excel Spreadsheet Templates: • Several templates will be provided: • Initial Data Worksheet • Sales Forecast Worksheet • Sales Order Worksheet • Production Schedule Worksheet • As indicated in Section 6 of the Lecture Notes, an Excel file containing these templates can be downloaded online at: http://www.calstatela.edu/faculty/klai/CL497.htm

  4. Data will come from both industry and company reports: • After opening the BPG program, you can view all the reports available on the company decision disk: • Report J(seep.210 of the Player’s Manualfor a sample) Consolidated Historical Data for Years 1 and 2 • Report D(seep.215 of the Player’s Manualfor a sample) Operating Information – Output, inventory, and sales • Report F(seep.217-8 of the Player’s Manualfor a sample) Industry Report – Real GDP, sales, product prices, and exchange rates.

  5. A top-down approach will be used for sales forecasting: • The method starts with sales forecasting at theindustrylevel for each market area: M1 (Merica 1) M2 (Merica 2) M3 (Merica 3) M4 (Nystok, Pandau, or Sereno) • From the industry sales forecast, the sales forecast for thecompanyin each market can be obtained as: Company Sales Forecast = Industry Sales Forecast × Expected Market Share

  6. Account for seasonal effects and obtain seasonally adjusted sales data: • See Section 1.A of the Lecture Notes. • Seasonal Indices(p.105 of the Player’s Manual) Q1 (Winter) 0.92 Q2 (Spring) 1.01 Q3 (Summer) 0.91 Q4 (Fall) 1.16 • To remove the seasonality from industry sales data: Seasonally Adjusted Industry Sales = Actual Industry Sales ÷ Seasonal Index

  7. Cyclical and Trend Components Seasonal Component Real GDP, Average Price, andTime Trend Seasonal Factors Regression Forecasting Model Seasonally Adjusted Industry Sales Forecasts Industry Sales Forecasts by Market Area Company Sales Forecasts by Market Area

  8. Use a regression model to forecast industry sales: • See Section 1.B of the Lecture Notes. • Dependent variable (YSA) • 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

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

  10. Step-by-step forecasting exercise: • Read Sections 2.A to 2.E of the Lecture Notes for more details: • 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).

  11. After obtaining company sales forecasts, determine how much to produce: • Read Sections 3.A, 3.B, and 3.C of the Lecture Notes. • TheSales Order Worksheet and the Production Schedule Worksheet can be used to perform production analysis in Excel. • Why do firms hold inventories? • To guard against demand uncertainty. • To guard against production uncertainty.

  12. Choose an inventory policy that balances between over- and under-stocking costs: • Select your desiredinventory-to-sales ratio. • Under normal situations, a ratio from20% to 40%may be used 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. • Carrying too little inventory may lead to costly stockouts. • Stockouts are very costly because they result in not only a loss of present sales but also a loss of some future sales. • Carrying too much inventory can be costly too. • Warehouse Storage Cost • Financing Cost: It tied up working capital.

  13. How should production be scheduled?Should production capacity be expanded? • See Chapters 7 & 8 of the BPG Player’s Manual. • Read also Section 4 of the Lecture Notes. • Normal operation: 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)

  14. Company Sales Forecasts by Market Area Desired Inventory Ratio Estimated Sales Office Orders 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

  15. Prepare sales forecasts, production plans, and cost estimates for the Two-Year Plan: • Read the course outline for specific requirements. • When you are ready to prepare the Two-Year Plan, read theAppendixof the Lecture Notes.

  16. Hope you will enjoy the Business Policy Game!