Basic of forecasting chapter number 1 for understanding

Basic of forecasting

1. INTRODUCTION TO FORECASTING Business Forecasting by A. Reza Hoshmand , Second Edition Publisher: Taytor & Francis Group, 2010

2. Introduction Importance of Forecasting

3. Introduction The aim of a business forecast is to combine statistical analyses and domain knowledge (not judgment) to develop acceptable forecasts . Advances in technology have revolutionized the way we process information and prepare business and economic forecasts . Forecasting methodologies have been in existence since the nineteenth century . They range from intuitive forecasting to highly sophisticated quantitative methods .

4. Objective of Forecasting The objective of forecasting is to provide managers with information that will facilitate decision making .

5. Who use Business Forecasting? Changes in economy influence enterprises Marketing (such as market share, trends in prices, sources of competition, and the demographics of the market) Finance and accounting (estimate its future levels of receivables, inventory, payables, and other corporate accounts).

6. 4. HR: decisions regarding the total number of employees a firm needs. number of workers in functional areas , nature of the workforce (part -time or full -time ) trends in absenteeism and lateness, and productivity 5. Government uses these forecasts to guide monetary and fiscal policy of the country.

7. What Is Forecasting? It is the process of predicting a future event which underlying as the basis of all business decisions such as: Production Inventory Facilities Personnel ….

8. The Art and Science of Forecasting wide range of forecasting methodologies: from intuitive forecasting to highly sophisticated quantitative methods. The more complex the model, the more the assumptions have to be made in the model.

9. Eight Steps to Forecasting 1. Determine the use of the forecast—what objective are we trying to obtain? 2. Select the items or quantities that are to be forecasted 3. Determine the time horizon of the forecast 4. Select the forecasting model or models 5. Gather the data needed to make the forecast 6. Validate the forecasting model 7. Make the forecast 8. Implement the results

10. Forecasting Methods

11. Qualitative Models Qualitative models incorporate judgmental or subjective factors Useful when subjective factors are thought to be important or when accurate quantitative data is difficult to obtain Common qualitative techniques are Delphi method Jury of executive opinion Sales force composite Consumer market surveys

12. Time-Series Models Time-series models attempt to predict the future based on the past Common time-series models are Moving average Exponential smoothing Trend projections Decomposition Regression analysis is used in trend projections and one type of decomposition model

13. Causal Models Causal models use variables or factors that might influence the quantity being forecasted The objective is to build a model with the best statistical relationship between the variable being forecast and the independent variables Regression analysis is the most common technique used in causal modeling