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Forecasting Methods. Chapter 9. Forecasting. How Important Is Forecasting? Is Forecasting Only Financial? How Is It Done? Does Forecasting Help Be Successful? What Are Forecasting Limitations? Does Forecasting Differ From Planning?. Forecasting.

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Forecasting Methods


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forecasting
Forecasting
  • How Important Is Forecasting?
  • Is Forecasting Only Financial?
  • How Is It Done?
  • Does Forecasting Help Be Successful?
  • What Are Forecasting Limitations?
  • Does Forecasting Differ From Planning?
forecasting1
Forecasting
  • What Is the Difference Between Seasonal and Cyclical Patterns?
  • How Do Quantitative and Qualitative Forecasting Methods Differ?
forecasting2
Forecasting
  • How Is a Moving Average Calculated?
  • When Are Causal Forecasting Approaches Useful?
implicit versus explicit forecasts
Implicit versus Explicit Forecasts
  • Implicit - (Intuitive)

Unsystematic

Imprecise

Difficult to Evaluate

implicit versus explicit forecasts1
Implicit versus Explicit Forecasts
  • Explicit - (Analytical)

Systematic

Reasonably Reliable and Accurate

Rational Evaluation

the nature of forecasting
The Nature of Forecasting
  • Done by All Levels of Management
  • Looks at the Future
  • Involves Uncertainties
  • Based on Historical Data
  • Less Accurate Than Desired
  • Extensive Use of Naive Models
the nature of forecasting1
The Nature of Forecasting
  • Large Properties Need to Use More Sophisticated Models
  • Trend - Straight Line Projection
  • Seasonal - Fluctuate Over Time
  • Cyclical - Movements Over a Trend
  • Random Variations Create Uncertainty
forecasting methods1
Forecasting Methods
  • Naïve Method - Multiply current sales level (or sales price) by a percentage increase (or decrease); or add (or subtract) a fixed amount.
  • This method does not use any analytical or scientific method
forecasting method
Forecasting Method
  • Naïve Example
    • Current year sales level is 1,000 units
    • Current year sales price is $15.00
    • Next year levels increase 10%
    • Next year price decreases $0.50
    • Current Year Total Sales Equals

1,000 * $15.00 = $15,000

forecasting method1
Forecasting Method
  • Naïve Example - Continued
    • Next year sales level equals

1,000 * 1.10 = 1,100

    • Next year price equals

$15.00 - $0.50 = $14.50

    • Next year Total Sales equals

1,100 * $14.50 = $15,950

forecasting methods2
Forecasting Methods
  • Moving Averages - Sum of Activity in Previous N Periods Divided by N, Where N Is the Number of Periods
moving average
Moving Average
  • Page 408; Forecast week 13 using 3 week moving average

Thus use data in weeks 10, 11, 12 and divide by 3

(1025 + 1000 + 1050) / 3 = 1025

forecasting methods3
Forecasting Methods
  • Exponential Smoothing - Uses a Smoothing Constant and Recent Actual and Forecasted Activity to Estimate Future Activity
exponential smoothing
Exponential Smoothing
  • Forecast for Period 3:
  • Using Data below
  • Period 1 Forecast 1,025
  • Period 1 Actual 1,000
  • Period 2 Forecast 1,020
  • Period 2 Actual 1,050
exponential smoothing1
Exponential Smoothing
  • Forecast for Period 3:
  • Step 1 - Determine Smoothing Constant

Period 2 Forecast - Period 1 Forecast

Period 1 Actual - Period 1 Forecast

(1,020 - 1025 ) / (1,000 – 1,025 ) = 0.20

exponential smoothing2
Exponential Smoothing
  • Step 2
  • Forecast for Week 3
  • Wk 3 F = Wk 2 F + SC(WK2 Act – Wk2 F)
  • Wk 3 F = 1,020 + 0.2(1,050 - 1,020)
  • Wk 3 F = 1,020 + 0.2(30)
  • Wk 3 F = 1,026
forecasting methods4
Forecasting Methods
  • Causal - Regression Analysis Which Is Estimating an Activity (Dependent Variable) on the Basis of Other Activities (Independent Variables)…
  • How Closely Related Is Measured by Coefficient of Correlation and Coefficient of Determination
forecasting methods5
Forecasting Methods
  • Coefficient of Correlation ( r )– is the measure of the relationship between the dependent and independent variables. Closer to 1 the stronger the relationship.
  • Coefficient of Determination ( r2 ) – reflects the extent to which the change in the independent variable explains the change in the dependent variable
regression analysis
Regression Analysis
  • Formula

Y = A + BX

Y is the dependent variable

A is a constant

B is a multiplier

X is the independent variable

regression analysis1
Regression Analysis
  • Page 412

Y = 370 + 1.254x

If X = 3,000 rooms

Y = 370 + 1.254(3000)

Y = 6,013 meals

forecasting limitations
Forecasting Limitations
  • Scarcity of Data
  • Assumes Continuation of Trends
  • Unforseeable Occurrences
qualitative methods
Qualitative Methods
  • Based on human judgment
    • Market Research
    • Jury of Executive Opinion
    • Sales force estimates
    • Delphi Method
consideration in choosing a forecasting method
Consideration In Choosing a Forecasting Method
  • Effectiveness in Providing Information
  • Cost of Implementation
  • Frequency of Forecast Updates
  • Turnaround Time of Forecasting
consideration in choosing a forecasting method1
Consideration In Choosing a Forecasting Method
  • Size and Complexity of Operation
  • Forecasting Skills of Personnel
  • Purpose of Making Forecast