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Operations management Session 17: Introduction to Revenue Management and Decision Trees.

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Presentation on theme: "Operations management Session 17: Introduction to Revenue Management and Decision Trees."— Presentation transcript:

1 Operations management Session 17: Introduction to Revenue Management and Decision Trees

2 Session 17 Operations Management2 Previous Class

3 Session 17 Operations Management3 Today’s Class  Introduction to Revenue Management  Decision-making under uncertainty Decision Trees  Simulation Game Explanation

4 Session 17 Operations Management4 RM: A Basic Business Need  What are the basic ways to improve profits? Profits $ $ Reducing Cost Increasing Revenue Revenue Management

5 Session 17 Operations Management5 Revenue Management forecasting capacity control overbooking optimization market segmentation pricing

6 Session 17 Operations Management6 ‘Selling the right seats to the right customers at the right prices and the right time.’ (American Airlines 1987) Revenue Management Definitions (Squeezing as many dollars as possible out of the customers) ‘Integrated control and management of price and capacity (availability) in a way that maximizes company profitability.’

7 Session 17 Operations Management7 Revenue Management History  RM was ‘invented’ by major US carriers after airline deregulation in the late 1970’s to compete with new low cost carriers  Matching of low prices was not an alternative because of higher cost structure  American Airline’s ‘super saver fares’ (1975) have been first capacity controlled discounted fares  RM allowed the carriers to protect their high-yield sector while simultaneously competing with new airlines in the low-yield sector  From art to science: By now, there are sophisticated RM tools and no airline can survive without some form of RM  Other industries followed - hotel, car rental, cruise lines etc.

8 Session 17 Operations Management8 Revenue Management  How the optimization in Revenue Management might differ from what we have already learned (like linear programming)?

9 Session 17 Operations Management9 Capacity Investment-1  New-Fashion buys dyed yarns and makes fashionable dress. The company knows with certainty that red will be the color of the year and the demand for a red gown is 2,000 units per month for the next 5 months.  The company can invest in a new production line with advanced technology. The capacity of the new line is 2,000 units per month. The cost of this line is $1,000,000. The production cost per unit is $130.

10 Session 17 Operations Management10 Capacity Investment-1  Alternative: The company can also convert an obsolete line with traditional technology. The capacity of the production line is also 2,000 units per month. The cost of this conversion is $500,000. The production cost per unit is $200.  Each red gowns are sold for $300 each.

11 Session 17 Operations Management11 Capacity Investment-1  Which technology should the company chose?  Clearly the new technology is preferable. New -1,000,000+5*2,000*170=0.7M Traditional -500,000+5*2,000*100=0.5M

12 Session 17 Operations Management12 Capacity Investment-2  New-Fashion company is concerned that orange instead of red being the color of year.  The CEO of the company prefers to assume that the demand for the red gowns will be: 2,000 per month (probability 0.6) 0 (probability 0.4, market will demand 2000 orange gowns)  Given this information…

13 Session 17 Operations Management13 Capacity Investment-2 New Traditional red orange red orange -1,000,000+5*2,000*170=0.7M -1,000,000+0=-1M -500,000+5*2,000*100=0.5M -500,000+0=-0.5M

14 Session 17 Operations Management14 Capacity Investment-2  The optimal decision is to invest in the traditional technology.  Intuitively, the traditional technology is preferred when the demand is uncertain because it has a lower upfront cost, but higher variable cost of production. Lesson: Lower upfront costs are preferred when there is more variability.

15 Session 17 Operations Management15 Decision Tree  A tool to come up strategy under uncertain environments Decision Scenario

16 Session 17 Operations Management16 Capacity Investment-3  A smart consultant realized that a technology can delay the dye process and enable the company dye finished gowns after they know the color of the year.  The technology introduces an additional $30 cost of dyeing for each unit produced.  What should the company do?

17 Session 17 Operations Management17 Capacity Investment-3 w/o dye delayed with dye delayed

18 Session 17 Operations Management18 Observations  We observe that delay dyeing to collect more information is beneficial.

19 Session 17 Operations Management19 More Observations  We also observe that if the company delays dyeing it is optimal to invest in the new technology. While if it decides to not wait, it is optimal for the company to invest in the traditional technology. Why? The new technology costs more, but has lower production costs. Therefore, once we know demand is high, we prefer to make a higher initial upfront investment but have a lower marginal production cost.  Postpone differentiation and flexibility is desirable  Sometime, waiting and collecting information is worthwhile

20 Session 17 Operations Management20 What did we learn?  How to use a decision tree to evaluate alternatives.  Let’s see another example in a different context.

21 Session 17 Operations Management21 Decision Trees  A new drug must pass through three stages of clinical trials before it can be brought to market. Phase 1: Safety is evaluated on a small group. Phase 2: The effectiveness of the drug is evaluated on a large group. Phase 3: Randomized controlled trials are performed on even larger groups. Comparison is against a “gold standard” treatment. (Phase 4: Post-launch safety surveillance.) When should we contract for production capacity?

22 Session 17 Operations Management22 Decision Trees  Suppose we desire to introduce a new hypertension drug to market.  We have completed phase 1 and 2 trials successfully.  We assess a 90% probability of completing phase 3 successfully (and therefore gaining FDA approval).  We assume demand for the drug will be 5 million people in the next year.  A one-year drug supply for a single person should net us a $50 profit.

23 Session 17 Operations Management23 Decision Trees  We have the option of contracting for manufacturing capacity now for $150 million.  We expect the cost of manufacturing capacity to increase if we wait until we know the results of our Phase 3 trial.  What is the minimum expected cost of delaying manufacturing such that it is beneficial for us to wait to contract for manufacturing capacity?

24 Session 17 Operations Management24 Decision Trees contract now contract later approved not approved 0.9 0.1 $50×5-$150 =$100 million -$150 million 0.9× (50×5-P) million 0.9×100-0.1×150=75>0.9× (50×5-P), 83.33 > 250-P or P>166.67 in order that contracting now is more profitable.

25 Session 17 Operations Management25 Decision Trees We valued the flexibility of being able to wait until there is no more uncertainty.

26 Session 17 Operations Management26 Decision Trees  Now suppose we have only completed Phase 1, and that we assess the probability of completing phase 2 to be 50%.  We still assess the probability of completing Phase 3 to be 90%.  We again have the option to contract now at $150 million or to contract later (after either completing phase 2 or 3).

27 Session 17 Operations Management27 Decision Trees later now pass phase 2 do not pass pass phase 3 do not pass $100 million -$150 million 0.9 0.1 0.5 $75 million -37.5 million It does not make sense to contract now.

28 Session 17 Operations Management28 What did we learn?  Decision trees  How to value the option of delaying decisions to collect information  Next class, we will study revenue management tools based on decision trees  Still upcoming … simulation game explanation.

29 Session 17 Operations Management29 Next Session  Homework 4 due.  Game report 1 due.

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