It is presentation slide about introduction of forecasting and it's different models or techniques.

1. FORECASTING
पूर्वानुमवन
Bikram Adhikari
MBA II Semester

2. DEFINITION
• Science of predicting future event based on the historical data.
• Forecasts are possible only when past data exist.
• Used for business operations as well as by economist and social scientists.
• Based on time horizon, forecasts are classified in three categories:
• Short range forecast: less than 3 months. Used for job assignments and production levels.
• Medium range forecast: time period up to 3 years. Used in sales, production planning and
budgeting.
• Long range forecast: more than 3 years. Used in planning for new products, research and
development.

3. QUALITIES OF GOOD FORECASTING
• Timely
• Reliable
• Accurate
• Meaningful
• Written
• Easy to use and understand

4. FORECASTING MODELS OR TECHNIQUES
Qualitative Models Quantitative Models
Used where the forecasting time horizon is very
large and precise numerical description of
forecasting variables could be not formulated.
Used when the data representing the forecast
are available.
Favors the personal and work experience.
Avoids the personal judgements, instead use the
data.
Examples: production of novel etc. Examples: sales forecast for coming year etc.

5. TYPES
Qualitative Models Quantitative Models
• Delphi Technique
• Nominal Group Technique
• Historical Data Analysis
1. Time Series Methods
• Naive Approach
• Moving Average Method
• Exponential Smoothing Method
• Trend Projection
2. Causal Method
• Regression Analysis
• Economic Modeling

6. QUALITATIVE MODELS : DELPHI TECHNIQUE
• Group Process
• Panel of experts within or without the organization provides written comments
on the points in questions.
• Steps:
• Choose variety of knowledgeable people of different areas.
• Through a questionnaire, obtain forecast (opinions) from all participants.
• Summarize the results and redistribute among the participants along with new
questions.
• Summarize again, refining forecasts and conditions, and again develop new questions.
• Distribute the final results to all participants.

7. HISTORICAL DATA ANALYSIS
• Based on historical data
• Takes account pervious growth or decline rate for determining demand of new product.

8. SELECTION CRITERIA OF FORECASTING MODELS
1. Cost
2. Accuracy
• High Cost of implementation and maintenance, provides more accurate forecasts, resulting
lower operating cost.

9. THANK YOU !