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Product Portfolio Models

Product Portfolio Models. Group 8 Zaid Azmi 01 Pratik Malde 20 Nisha Pancholi 31 Sneha Sahani 39 Dhaval Shah 41. Why product portfolio management?. Allocate Resources amongst various businesses/products Maximizing product portfolio value Project Prioritization

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Product Portfolio Models

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  1. Product Portfolio Models Group 8 Zaid Azmi 01 Pratik Malde 20 Nisha Pancholi 31 Sneha Sahani 39 Dhaval Shah 41

  2. Why product portfolio management? • Allocate Resources amongst various businesses/products • Maximizing product portfolio value • Project Prioritization • Aligning product portfolio to overall business strategy

  3. Classification of Product Portfolio Models

  4. Standardized Models Standardized Models assume that the value of market position or market share depends on: • Structure of Competition • Stage in PLC

  5. A.D.Littles Business Profile Matrix • Arthur D Little's method is based on PLC • Uses dimensions of Environmental Assessment and Business Strength Assessment • Environmental measure is the Industry’s life cycle.

  6. ADL Matrix

  7. Calculating Competitive Position Illustration

  8. ADL Matrix • Competitive position: • Dominant: Rare. Results from near monopoly, protected leadership. • Strong: Not too many rivals • Favorable: Fragmented, No clear leader. • Tenable: Business has a niche • Weak: Business too small to be profitable or survive over long term. • Limitations: • Difficult to identify the current phase of industry life cycle. • There is no standard life cycle

  9. Shell’s Directional Policy Matrix • Similar to GE Matrix • X- Axis is Sector Prospects • Y-Axis is Company’s Competitive Capability

  10. Sample Calculation • Competitive Advantage

  11. Sample Calculation • Sector Prospects

  12. Placing the SBU on the matrix

  13. The 9 Cells Explained • Leader - major resources to be focused upon the SBU. • Try harder - could be vulnerable over a longer period of time, but fine for now. • Double or quit - gamble on potential major SBU's for the future. • Growth - grow the market by focusing just enough resources here. • Custodial– Maximize Cash Flow, do not commit any more resources. Almost like Cash Cow • Cash Generator– Exactly like a cash cow, milk here for expansion elsewhere. • Phased withdrawal - move cash to SBU's with greater potential. • Divest - liquidate or move these assets on as fast as you can.

  14. Limitations • No fixed factors • Subjective

  15. Customized Models • Product – Performance Matrix • Conjoint Analysis • Analytic Hierarchy Process

  16. Product – Performance Matrix • Allows management flexibility to choose customized dimensions • E.g. in the below matrix, 4 dimensions – Industry Sales, Product Sales, Market Share & Profitability are chosen

  17. Conjoint Analysis • Overall utility for a product can be decomposed into the utilities of the individual attributes of the product. • Rankings or ratings of the product profiles in terms of preference, purchase probability, etc. • Pairwise comparisons of product profiles in terms of preference, purchase probability, etc. • Choice of a product from a set of product profiles

  18. Example: Laptop Profiles

  19. Uses of conjoint analysis • Market segmentation • New product design • Trade-off analysis (esp. in pricing decisions)

  20. Financial Models • Risk – Return Model

  21. Expected Return • The expected rate of return on a SBU represents the mean of a probability distribution of possible future returns on the SBU. • Given a probability distribution of returns, the expected return can be calculated using the following equation: N E[R] = S (piRi) i=1 Where: • E[R] = the expected return on the stock • N = the number of states • pi = the probability of state i • Ri = the return on the SBU in state i.

  22. Expected Return • The table below provides a probability distribution for the returns on SBU A and SBU B Scenario Probability Return On Return On SBU A SBU B 1 20% 5% 50% 2 30% 10% 30% 3 30% 15% 10% 4 20% 20% -10% • The probability reflects how likely it is that the state will occur. This is management assumption. • The last two columns present the returns or outcomes for SBU A and SBU B that will occur in each of the four states. Again this is management assumption.

  23. Expected Return • In this example, the expected return for SBU A & B would be calculated as follows: E[R]A = .2(5%) + .3(10%) + .3(15%) + .2(20%) = 12.5% E[R]B = .2(50%) + .3(30%) + .3(10%) + .2(-10%) = 20% • SBU B offers a higher expected return than SBU A. • However, we haven't considered risk.

  24. Measures of Risk • Risk reflects the chance that the actual return on an investment may be different than the expected return. • Way to measure risk is to calculate the variance and standard deviation of the distribution of returns. • Variance is calculated as N Var(R) = s2 = S pi(Ri – E[R])2 i=1 Where: • N = the number of states • pi = the probability of state i • Ri = the return on the stock in state i • E[R] = the expected return on the stock • SD is root of Variance

  25. Measures of Risk The variance and standard deviation for SBU A is s2A = .2(.05 -.125)2 + .3(.1 -.125)2 + .3(.15 -.125)2 + .2(.2 -.125)2 = .002625 sA = (.002625)0.5 = .0512 = 5.12% Similarly for SBU B s2B = 0.042 and sB = 20.49% • Although SBU B offers a higher expected return than SBU A, it also is riskier since its variance and standard deviation are greater than SBU A's.

  26. Portfolio Risk and Return • Most companies do not hold SBUs in isolation. • Instead, they choose to hold a portfolio of several SBUs. • Aportion of an individual SBU’s risk can be eliminated, i.e., diversified away. • From our previous calculations: • the expected return on SBU A is 12.5% • the expected return on SBU B is 20% • the variance on SBU A is .00263 • the variance on SBU B is .04200 • the standard deviation on SBU A is 5.12% • the standard deviation on SBU B is 20.49%

  27. Portfolio Risk and Return • The Expected Return on a Portfolio is computed as the weighted average of the expected returns on the SBUs which comprise the portfolio. • The weights reflect the proportion of the portfolio invested in the SBU. • This can be expressed as follows: N E[Rp] = SwiE[Ri] i=1 • Where: • E[Rp] = the expected return on the portfolio • N = the number of SBUs in the portfolio • wi = the proportion of the portfolio invested in SBU i • E[Ri] = the expected return on SBU i

  28. Portfolio Risk and Return • If we have an equally weighted portfolio of SBUA and SBU B then the expected return of the portfolio is: E[Rp] = .50(.125) + .50(.20) = 16.25% • The risk on the entire portfolio can also be calculated using Variance and Standard Deviation for the entire portfolio • The purpose of diversification is that by forming portfolios, some of the risk inherent in the individual SBU’s can be minimized.

  29. THANK YOU

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