Revenue Management is the application of disciplined analytics that predict consumer behaviour at the micro-market level and optimize product availability and price to maximize revenue growth. (www.wikipedia.org)
Revenue Management or Yield management is a branch of Operations Management which looks at improving the yield from operations by apportioning resources to different customer segments at different points of time at the right price.
Originally started in the Airline Industry in US by United Airlines to increase the yield per flight and reduce waste of unoccupied seats, it has now spread to many other areas like hotels, travel and tourism and brings in a new concept of dynamic pricing to achieve better yield from operations.
We played the game on Revenue Management in the class with the EMBA students of Alliance University in the subject of Revenue Management.
A brief note on the game is given here ..
Here is the link that gives the demand distribution of the different classes of passengers for the airline seats.
In the game which we played for each of the seven days for 4 weeks over a month, the highest preference for seats in an A320 flight of max 160 capacity, was given to the highest paying luxury segment, then to the medium paying segment and whatever was left out after being taken by these two classes were distributed for the lite or low paying customers.
In the theoritical setting, we find by the formula for the capacity for the higher paying segment customer, the critical fractile, (1 - P_l/P_h) and use the formula norminv(1-pl/ph),mhu,stdev).
In a practical setting, the demand changes daily but the critical fractile gives the capacity of the higher paying segment which in the long run would bring maximum revenue for the airlines.
After playing the game with the practical daily forecasted demand triggering class segmentation, the revenues are tabulated at the end of one month. The revenues by applying RM theory, marginal analysis of the revenues earned, we arrive at the different capacities for the different segments of customers and calculate the total monthly revenues (cross checking with the daily demand and seeing that it does not exceed the allocations or fall short).
Error is the difference between the total costs from practical demand and the analytical model .
The team that gives least error is the winner !