Forecasting is the process of making statements about events whose actual outcomes have not yet been observed. Example might be estimation of some variable of interest at some specified future date. Prediction is a similar, but more general term. The data must be up to date in order for the forecast to be as accurate as possible

1. THE PROCESS OF
BUSINESS FORECASTING

2. BUSINESS FORECASTING
• Forecasting is the process of making statements about events
whose actual outcomes have not yet been observed.
• Example might be estimation of some variable of interest at
some specified future date.
• Prediction is a similar, but more general term. The data must be
up to date in order for the forecast to be as accurate as possible

3. NEED OF FORECASTING
• Forecasting is the process by which companies ponder and
prepare for the future.
• It involves predicting the future outcome of various business
decisions.
• It also helps the organization make plans that will lead to
becoming a financially successful business.

4. NEED OF FORECASTING
• Businesses must understand and use forecasting in order to answer these
important questions. This helps the company prepare for the future.
Forecasting is used to answer important questions, such as:
• How much profit will the business make?
• How much demand will there be for a product or service?
• How much will it cost to produce the product or offer the service?
• How much money will the company need to borrow?

5. VARIOUS TYPES OF FORECASTING
• There are a number of different methods by which a business
forecast can be made.
• There are many quantitative methods:- for example Time Series
Forecasting, Regression Forecasting, etc.
• Then there are many qualitative methods :- (judgmental
methods) such as Delphi Method, Expert Decision.

6. THE FORECASTING PROCESS
1. • Fix the forecasting objectives
2. • Decide what to forecast ?
3. • Determine the time frame
4. • Collect data for forecasting
5. • Select the forecasting model
6. • Build and test the forecasting model
7. • Prepare the forecasts
8. • Present the forecasts
9. • Compare events with the forecasts

7. TIME SERIES ANALYSIS?
• A time series is a collection of observations of well-defined
data items obtained through repeated measurements over time.
For example, measuring the value of retail sales each month of
the year would comprise a time series. This is because sales
revenue is well defined, and consistently measured at equally
spaced intervals.
• Data collected irregularly or only once are not time series.

8. TIME SERIES – EXAMPLES
• Stock price, Sensex
• Exchange rate, interest rate, inflation rate, national GDP
• Retail sales
• Electric power consumption
• Number of accident fatalities

9. IMPORTANCE OF TIME SERIES
ANALYSIS
• A very popular tool for Business Forecasting.
• Basis for understanding past behavior.
• Can forecast future activities/planning for future operations
• Evaluate current accomplishments/evaluation of performance.
• The basis of Time series Analysis businessman can predict about the
changes in economy.
• Safety from future
• Sales Forecasting

10. IMPORTANCE OF TIME SERIES
ANALYSIS
• Budgetary Analysis
• Stock Market Analysis
• Risk Analysis & Evaluation of changes.
• Census Analysis