Demand analysis and break even point: An entrepreneurial perspective


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A presentation for upcoming entrepreneurs who found difficult to calculate market and effective demand and analyzing break even point.

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Demand analysis and break even point: An entrepreneurial perspective

  1. 1. DEMAND ANALYSIS BREAK EVEN POINT Dr. Rahul Pratap Singh Kaurav © Entrepreneurship Development Camp, PIM, Gwalior
  2. 2. DEMAND  The process to satisfy human wants/ needs/desires.  Want: having a strong desire for something  Need: lack of means of subsistence  Desire: an aspiration to acquire something  Demand: effective desire  Demand is that desire which backed by willingness and ability to buy a particular commodity.  Things necessary for demand:  Time  Price of the commodity  Amount (or quantity) of the commodity consumers are willing to purchase 2 at the price
  3. 3. TYPES OF DEMAND Consumer Direct Capital Derived Goods Consumable Recurring Durable Replacement 3
  4. 4. DETERMINANTS OF DEMAND  Price of the product  Single most important determinant  Negative effect on demand  Income of the consumer  Normal goods: demand increases with increase in consumer’s income  Inferior goods: demand falls as income rises  Price of related goods  Substitutes  If the price of a commodity increases, demand for its substitute rises.  Complements  If the price of a commodity increases, quantity demanded of its complement falls. 4
  5. 5. DETERMINANTS OF DEMAND Contd…  Tastes and preferences  Very significant in case of consumer goods  Expectation of future price changes  Gives rise to tendency of hoarding of durable goods  Population  Size, composition and distribution of population will influence demand  Advertising  Very important in case of competitive markets 5
  6. 6. DEMAND FUNCTION  Interdependence between demand for a product and its determinants can be shown in a mathematical functional form Dx = f(Px, Y, Py, T, A, N) …….. [Multivariate fx]  Independent variables: Px, Y, Py, T, A, N  Dependent variable: Dx  Px: Price of x  Y: Income of consumer  Py: Price of other commodity  T: Taste and preference of consumer  A: Advertisement  N: Macro variable like inflation, population growth, economic 6 growth
  7. 7. XCEPTIONS TO THE LAW OF DEMAND Law of demand may not operate due to the following reasons:  Giffen Goods: Sir Robert Giffen, Ireland  Snob Appeal: Veblen Goods, Thorstein Veblen  Demonstration Effect: Fashion  Future Expectation of Prices (Panic buying)  Addiction  Neutral goods  Life saving drugs  Salt  Goods with no substitute  Amount of income spent  Match box 7
  8. 8. TECHNIQUES OF DEMAND FORECASTING • Subjective (Qualitative) methods: rely on human judgment and opinion. • Buyers’ Opinion • Sales Force Composite • Market Simulation • Test Marketing • Experts’ Opinion • Group Discussion • Delphi Method  Quantitative methods: use mathematical or simulation models based on historical demand or relationships between variables.  Trend Projection  Smoothing Techniques  Barometric techniques  Econometric techniques
  9. 9. SUBJECTIVE METHODS OF DEMAND FORECASTING Consumers’ Opinion Survey • Buyers are asked about future buying intentions of products, brand preferences and quantities of purchase, response to an increase in the price, or an implied comparison with competitor’s products. • Census Method: Involves contacting each and every buyer • Sample Method: Involves only representative sample of buyers • Merits • Simple to administer and comprehend. • Suitable when no past data available. • Suitable for short term decisions regarding product and promotion. • Demerits • Expensive both in terms of resources and time. • Buyers may give incorrect responses.
  10. 10. Sales Force Composite • Salespersons are in direct contact with the customers. Salespersons are asked about estimated sales targets in their respective sales territories in a given period of time. • Merits • Cost effective as no additional cost is incurred on collection of data. • Estimated figures are more reliable, as they are based on the notions of salespersons in direct contact with their customers. • Demerits • Results may be conditioned by the bias of optimism (or pessimism) of salespersons. • Salespersons may be unaware of the economic environment of the business and may make wrong estimates. • This method is ideal for short term and not for long term forecasting
  11. 11. Experts’ Opinion Method i) Group Discussion: (developed by Osborn in 1953) Decisions may be taken with the help of brainstorming sessions or by structured discussions. ii) Delphi Technique: developed by the Rand Corporation at the beginning of the Cold War, to forecast impact of technology on warfare. • Merits • Decisions are enriched with the experience of competent experts. • Firm need not spend time, resources in collection of data by survey. • Very useful when product is absolutely new to all the markets. • Demerits • Experts’ may involve some amount of bias. • With external experts, risk of loss of confidential information to rival firms.
  12. 12. Market Simulation • Firms create “artificial market”, consumers are instructed to shop with some money. “Laboratory experiment” ascertains consumers’ reactions to changes in price, packaging, and even location of the product in the shop. • Grabor-Granger test (1960s) Merits • Market experiments provide information on consumer behaviour regarding a change in any of the determinants of demand. • Experiments are very useful in case of an absolutely new product. • Demerits • People behave differently when they are being observed.
  13. 13. QUANTITATIVE METHODS OF DEMAND FORECASTING Trend Projection Statistical tool to predict future values of a variable on the basis of time series data. • Time series data are composed of: • Secular trend (T): change occurring consistently over a long time and is relatively smooth in its path. • Seasonal trend (S): seasonal variations of the data within a year • Cyclical trend (C): cyclical movement in the demand for a product that may have a tendency to recur in a few years • Random events (R): have no trend of occurrence hence they create random variation in the series.
  14. 14. • Graphical method • Past values of the variable on vertical axis and time on horizontal axis and line is plotted. • Movement of the series is assessed and future values of the variable are forecasted • simple but provides a general indication and fails to predict future value of demand Demand for mobiles (in lakhs) 200 180 160 140 120 100 80 60 40 20 0 2001 2002 2003 Year 2004 2005
  15. 15. LIMITATIONS OF DEMAND FORECASTING • Change in Fashion • Consumers’ Psychology • Lack of Experienced Experts • Lack of Past Data • Accurate • Reliable
  16. 16. BREAK EVEN ANALYSIS •Breakeven point is the point where total cost just equals the total revenue, in other words it is the no profit no loss point.
  17. 17. BREAK EVEN OUTPUT • Fixed Cost/Contribution • 200000 / 40 = 5000 units
  18. 18. BREAK EVEN SALES • BE Units X Sales price per unit • 5000 X 100 = 5,00,000
  19. 19. MARGIN OF SAFETY • Total output – BE output • 8000 – 5000 = 3000
  20. 20. PROFIT • MOS X Contribution • 3000 X 40 = INR. 1,20,000