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Financial forecasting & planning

methods of financial forecasting (including both qualitative & quantitative)

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Financial forecasting & planning

  2. 2. WHAT IS FINANCIAL FORECASTING?  It is a Part of Planning process.  They are inferences as to what the future may be.  One of the key aspects of organizational management and is critical to the success of all businesses  Based on: i. Economic assumptions (interest rate, inflation rate, growth rate and so on). ii. Sales forecast. iii. Pro forma statements of Income account and Balance sheet. iv. Asset requirements. v. Financing plan. vi. Cash Budget
  3. 3. TYPES OF FINANCIAL FORECASTING There are a number of methods that can be used to develop a financial forecast. These methods fall into two general categories i. Qualitative Methods ii. Quantitative Methods
  4. 4. QUALITATIVE METHODS 1. Executive Opinion: The expert opinions of key personnel of various departments are gathered to arrive at future predictions.  The management team makes revisions in the resulting forecast, based on their expectations. 2. Sales force Polling: Companies believe that salespersons have close contact with the consumers They could provide significant insights regarding customer behavior.  The estimates are derived based on the average of sales force polling.
  5. 5. QUALITITAVIE METHODS… 3. Delphi Method: A series of questionnaires are prepared and answered by a group of experts, who are kept separate from each other. On the basis of result of first questionnaire, a second questionnaire is prepared This second document is again presented to the experts, who are then asked to reevaluate their responses to the first questionnaire This process continues until the researchers have a narrow shortlist of opinions.
  6. 6. QUALITATIVE METHODS… 4. Scenario Writing: In this method, the forecaster generates different outcomes based on diverse starting criteria. The management team decides on the most likely outcome from the numerous scenarios presented
  7. 7. QUANTITATIVE METHODS 1. Regression Analysis Regression analysis is widely used for prediction and forecasting. It is analysis of average relationship between two or more variables. In this method basically there are two type of variables i. Dependent Variable ii. Independent Variable  Basically it helps one understand how the typical value of the dependent variable changes when any one of the independent variables is varied, while the other independent variables are held fixed
  8. 8. Regression analysis…  Let ‘x’ be the independent variable, then the line of regression can be given by, y = a+bx Now we have to find the best possible value of a & b.  Line of Regression of x on y (by regression coefficient method): 𝑥 − 𝑥= 𝑟 𝜕𝑦 𝜕𝑥 (𝑦 − 𝑦)
  9. 9. Regression analysis…. Co-efficient of line of regression: The slope of line of regression is called its ‘Co-efficient’, denoted by “b” Since there ere two line of regression ‘y on x’ and ‘x on y’, there are two co-efficient, denoted by, & 𝑏 𝑦𝑥=𝑟 𝜕𝑦 𝜕𝑥 𝑏 𝑥𝑦= 𝑟 𝜕𝑦 𝜕𝑥
  10. 10. 2. Time series analysis: It consist statistical data which are collected, recorded & observed over successive interval of time. More clearly it can be defined as successive observation of given phenomenon over a period of time. Components affect the result of time series are: i. Secular Trend (T): it shows the direction of the series in a long period of time. Effect of trend is gradual, but extends more or less consistently throughout the entire period of time. ii. Cyclic Fluctuation (C): these are the fluctuations as a result of business cycles and are generally referred to as long term movements that represent consistently recurring rises.
  11. 11. Components affecting time series…. iii. Seasonal Fluctuations (S): • these are of short duration occurring in a regular sequence at specific intervals of time. • These fluctuations are the result of changing season. iv. Irregular Fluctuations (I): • Also known as “Random Fluctuations” • These variations are take place in a completely unpredictable fashion
  12. 12. Time series analysis… • For analysis of the time series, we usually have two models, i. Multiplicative Model: ii. Additive Model: Y*= Observed values of time series Y*= T×C×S×I Y= T+C+S+I
  13. 13. 3. Proforma financial analysis: • Proforma statements use sales figures and costs from the previous two to three years after excluding certain one-time costs. • This method is mainly used in mergers and acquisitions. • Also in cases where a new company is forming and statements are needed to request capital from investors. • Pro forma Income Statement. (Represents the operational plan for the whole organization.)
  14. 14. PREPARATION OF PRO FORMA INCOME STATEMENTS Percent of Sales Method • Assumes that future relationship between various elements of cost to sales will be similar to their historical relationships. • These cost ratios are generally based on the average of previous two or three years. • For example, Cost of Goods sold may be expressed as a percentage of Sales.
  15. 15. 2. BUDGETED EXPENSE METHOD. • Estimate the value of each item on the basis of expected developments in the future period for which the pro forma P&L a/c is being prepared. • Calls for greater effort on the part of Management, since they have to define the likely happenings.
  16. 16. 3. COMBINATION METHOD • Neither the Percent of sales method nor the Budgeted expense method should be used in isolation. • A combination of both methods work best. • Items which have stable relationship to sales can be forecasted using the Percent of sales method. • For items where the future is likely to be very different from the past, budgeted expense method can be used.
  17. 17. PROFORMA INCOME STATEMENTActual figures for Quarter 31-3-2006 Assumptions Proforma for the qr ended 30-6-2006 1.No.of units sold 2.Net Sales 3.Cost of Goods sold: 4.Labour 5. Materials 6.Distribution cost 7. Overhead 8. Total 9. Ratio of CGS to Sales. 10. Gross Profit 11. GP Margin 14000 140000 100% 22960 25256 4592 61992 114800 82.0% 25200 18% Sales decline 30% due to low demand. No change in Product mix. 20% of Cost of good 22% of COG 4% of COG 54% of COG Increase by 1.5% 9800 98000 100% 16366 18002.6 3273.2 44188.2 81830 83.5% 16170 16.5%
  18. 18. CONTD. Actuals Assumption Proforma 12. Expenses: 13. Selling Expenses 14. Admin. Expense 15. Others 16.Total 17. Operating Profit 18. Interest 19. Depreciation 20.PBT 21. Tax @ 30% 22.Net Income 23.Dividends 24.Retained earnings. 25. Cash flow after dividends. 8250 4450 Nil 12700 12500 2500 2000 7000 2100 4900 900 4000 6000 A drop of Rs. 750 . A drop of Rs. 850 Rs.2000 only No dividends Carried to B/s. Retained earning + Depreciation 7500 3600 Nil 11100 5070 2000 2000 1070 321 749 0 749 2749