Introduction to Forecasting techniques.pptx

This is a presentation on forecasting

1. Mechanical Engineering Dept. HITEC Univ. Forecasting

2. Mechanical Engineering Dept. HITEC Univ. Forecasting An estimate of sales in physical units (or monetary value) for a specified future period under proposed marketing plan or program and under the assumed set of economic and other forces outside the organization for which the forecast is made.

3. Mechanical Engineering Dept. HITEC Univ. Forecasting and Prediction Prediction is an estimate of future event through subjective considerations other than just the past data. Forecasting is a n estimate of future event achieved by systematically combining and casting forward in a predetermined way data about the past. Forecasting helps in planning the system and in planning the use of the system

4. Mechanical Engineering Dept. HITEC Univ. Need for Demand Forecasting Activities of industries usually depend on future sales Assists in decision making with respect to investment Scheduling of production activities for optimum utilization of resources To prepare material plans for steady supply of material To obtain a balanced product mix. Future trend for product design and development

5. Mechanical Engineering Dept. HITEC Univ. Steps in Forecasting Determine the purpose of the forecast Establish a time horizon Select a forecasting technique Gather and analyze the appropriate data Prepare the forecast Monitor the forecast

6. Mechanical Engineering Dept. HITEC Univ. Forecasting Trends

7. Mechanical Engineering Dept. HITEC Univ. Forecasting Trends

8. Mechanical Engineering Dept. HITEC Univ. Classification of Forecasting Methods Judgmental techniques Time Series methods Causal methods (Econometric forecasting)

9. Mechanical Engineering Dept. HITEC Univ. Judgmental techniques Opinion survey method Executive opinion method Customer and distributor surveys Marketing trials Market research Delphi technique

10. Mechanical Engineering Dept. HITEC Univ. Opinion survey method Simple and practicable for new products Opinions are collected from the prospective buyers regarding a product The sampling technique is used to survey the customers.

11. Mechanical Engineering Dept. HITEC Univ. Executive opinion method Experts opinion is sought on the future of demand for the product It is biased and subjective Accuracy of the predicted demand depends upon the skill, expertise and experience of the decision maker

12. Mechanical Engineering Dept. HITEC Univ. Customer and distributor surveys The individuals or companies who bought a product can be asked the reasons for making the purchase Estimates of expected sales can be requested from retail outlets and company’s sales force.

13. Mechanical Engineering Dept. HITEC Univ. Marketing trials Applicable to new products A controlled experiment in which the market area and the method of presentation are carefully selected and controlled. Cost is high

14. Mechanical Engineering Dept. HITEC Univ. Market research Best if extensive data is needed Collection of information regarding the nature of consumption. Factors influencing demand like location, price, quality, quantity etc. are observed and used to forecast sales

15. Mechanical Engineering Dept. HITEC Univ. Delphi technique An expert panel is used A sequential questionnaire is used The responses of these experts are made available to other and are then deliberated Iterative process

16. Mechanical Engineering Dept. HITEC Univ. Time Series Analysis It refers to the past data arranged in a chronological order as a dependent variable and time as an independent variable Moving average Weighted moving average Exponential smoothing Seasonal forecasting Trend analysis

17. Mechanical Engineering Dept. HITEC Univ. Moving Averages The moving average (MA) method supplies a forecast of future values based on recent past history. MA is also called simple MA method. The latest n consecutive values, which are observations of actual events such as daily, weekly, monthly, or yearly demand, are used in making a forecast. These data are recorded and must be updated to maintain the most recent n values.

18. Mechanical Engineering Dept. HITEC Univ. Example Consider the demand (sales) data given in Table for 12 periods The forecast for months 4–12 are calculated.

19. Mechanical Engineering Dept. HITEC Univ. Weighted Moving Average A way to make forecasts more responsive to the most recent actual occurrences (demand) is to use the weighted moving average (WMA) method. Just like the MA method, the most recent n period are used in forecasting. However, each period is assigned a weight between 0 and 1. The total of all weights adds up to 1. The highest weight is assigned to the most recent period and then the weights are assigned to the previous periods in the descending order of magnitude.

20. Mechanical Engineering Dept. HITEC Univ. Example Consider the data given in Table. Suppose the number of periods used in forecasting n = 3 and the weights are 0.2, 0.3, and 0.5.

21. Mechanical Engineering Dept. HITEC Univ. Exponential Smoothing The exponential smoothing (ES) method calculates an average demand (forecast). ES methodology remembers the last estimate of the average value of demand and combines it with the most recent observed, actual value to form a new estimated average. ES forecasts the demand for a given period t by combining the forecast of the previous period ( t − 1) and the actual demand of the previous period ( t − 1). The actual demand for the previous period is given a weight of α and the forecast of the prior period is given a weight of (1 − α), where α is a smoothing constant whose value lies between 0 and 1.

22. Mechanical Engineering Dept. HITEC Univ. Exponential Smoothing

23. Mechanical Engineering Dept. HITEC Univ. Example Consider the data given in Table. Using the ES method makes a forecast starting from period 2.

24. Mechanical Engineering Dept. HITEC Univ. Problem

25. Mechanical Engineering Dept. HITEC Univ. Forecasting with Seasonal Cycle Forecasting when seasonality is present can be done by assuming that what happened last year (or last month, etc.) will happen again This method works if a stable pattern (which is often seasonal) exists. This is termed as historical forecasting. If the time-series pattern remains fixed, but the demand level has increased overall, then a base series modification can be used.

26. Mechanical Engineering Dept. HITEC Univ. Forecasting with Seasonal Cycle Assume that last year the quarterly demands were 10, 30, 20, and 40. This gives a yearly demand of 100 units. Assuming that this year the yearly demand is expected to increase to 120 units. What would be the adjusted quarterly forecasts ?

27. Mechanical Engineering Dept. HITEC Univ. Problem Consider the data in the table on next slide that gives the quarterly demand for last 4 years. Based on these data, forecast the demand for the four quarters of year 5. Assume that the annual demand is expected to be, 2800, in year 5.

28. Mechanical Engineering Dept. HITEC Univ. Demand Table

29. Mechanical Engineering Dept. HITEC Univ. Solution- Step 1 Find average quarterly demand for each year.

30. Mechanical Engineering Dept. HITEC Univ. Step 2 Compute seasonal index (SI) for each quarter for each year. The seasonal index for a quarter for a given year is obtained by dividing the demand in that quarter by the average quarterly demand for that year .

31. Mechanical Engineering Dept. HITEC Univ. Step 3 Calculate the average SI for each quarter.

32. Mechanical Engineering Dept. HITEC Univ. Step 4 Calculate the average quarterly demand for next year.

33. Mechanical Engineering Dept. HITEC Univ. Step 5 Forecast demand for quarters of next year.

34. Mechanical Engineering Dept. HITEC Univ. Trend Analysis If the time series exhibits an increasing or decreasing trend, then the techniques discussed above (MA, WMA, and ES) may not be appropriate for making a forecast. We perform a trend analysis to make a forecast in this case. The trend analysis will fit a trend line through data to make forecast. The equation of the trend line is, Y = a + bX , where Y is the demand forecast and X is the time period. X is the independent variable and Y is the dependent variable since the demand depends on the time period.

35. Mechanical Engineering Dept. HITEC Univ. Trend Analysis

36. Mechanical Engineering Dept. HITEC Univ. Problem Using trend analysis predict the forecast for the 11 th and 12 th term

37. Least Square Method