LECTURE - 2 YIELD MANAGEMENT

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LECTURE - 2 YIELD MANAGEMENT Learning objective To demonstrate the applicability of yield management in services

8.5 Yield Management or Revenue Management Yield management is applied by service organizations to maximize the revenue or yield from revenue generating, perishable and relatively fixed capacity. Yield management was originated in the airline industries in early 1980 s. The other industries where we can see the applications of yield management are Hotels, Freight transport, Rentals, Telecommunications. 8.5.1 Evolution of Revenue Management Revenue Management was introduced in the Airline industry following its deregulation in 1978. As per the deregulation, the airline industry was given freedom to develop marketing and pricing strategies. This deregulation came as rescue to the airline industry which was facing declining market demand and fierce competition. 8.5.2 Examples of Revenue Management Applications 1. We often encounter a situation while flying by air, where airlines offer discount fares and higher fares to the passengers on board in the same aircraft. 2. Airlines offer early bird bookings that charged lower fares to the passengers who book at least one month in advance of flight departure. 1. Airline & hotel industry offer cheaper fares during off peak season. We can see form online travel website that the cheapest air ticket from Chennai to Goa in Diwali week. i.e. November 13, 2012 costs around Rs.3700/- whereas there is 30% reduction in airfare just a fortnight late for the same route. (Source: - www.thehindubusinessline.com/features/investment-world/moneywise/article3412430.ece accessed on 17 May 2012) 2. Hotel and airline industries give discounts if the passengers opt for round trip rather than one way trip, booking online by using credit card, booking airline and hotel

accommodation in combo Source:- How to save your vacations, (The Times of India, April 23, 2012). 3. Various movie multiplexes in India offer discounted movie tickets for the morning shows on weekdays. This discount is given to sell the inventory that is empty seat in the multiplexes during morning time of weekdays 8.6 Applicability of Yield Management Yield Management is applicable in service industries exhibiting the characteristics shown in Figure 8.3. Relative fixed capacity Lower marginal cost of serving an additional customer Market or demand segmentation is possible Perishable service capacity Possibility of advance selling of service product FIGURE 8.3: CONDITIONS UNDER WHICH YIELD MANAGEMENT IS APPLICABLE 1) Relatively fixed capacity or fixed amounts of resources In airline industry, an airplane has fixed capacity in terms of number of seats. The number of rooms in a hotel is fixed. 2) Marginal cost of serving an additional customer is lower as compared to high marginal capacity change cost. - The short term fixed costs of airlines are higher but the variable costs per passenger are small. The variable cost per passenger can be there to serve meal and drinks, which is very less and will not impact much on the revenues. 3) The demand for the service can be segmented. The segmentation of market can be done on the basis of following:

a) Price sensitive consumers versus time sensitive consumers - Price sensitive consumers may like to adapt their schedules to take advantage of low prices whereas time sensitive consumers are less sensitive to price and emphasize on specific time at which they want the service. Example: Business travelers need to reach the meetings on a specific day and time whereas tourists can be price sensitive and explore for the lower fares regardless of the day and time. b) Market segmentation based on the customer s arrival at different times to purchase the service. - The price insensitive customers will arrive late and are willing to pay higher price to buy the service late like hotels. - The other case can be about the first customers who want to pay the highest prices for high fashion services like cellular services. 4) Service capacity is perishable Once the aircraft takes off, any unsold seats cannot be inventoried or utilized for next flight. The unsold seat does not generate revenues and hence it is perished forever. 5) Service product can be sold in advance or there is a provision of reservations and to charge different prices. Different pricing can be structured based on o The time interval between a customer making a reservation and the time of service delivery. o The level of customer commitment in terms of refundable or non-refundable deposit. 6) Service organization faces competition from a discount competitor. The non - discount service organization sometimes faces competition from low fare or discount service organization. This competition may force the non-discount service

organization to match the fares with low fare discount service organization. This can be achieved by imposing fences that is offering high fares to the customer segment which is price insensitive like business class for airline & hotel industry. Whereas, the non-discount service organizations can offer the low fare segment lower fares at par with discount competitor. In the way, the revenues can be retained or generated from high fare customers by the non-discount service organizations. 8.7 Different pricing strategies for revenue management The service organizations use variable pricing as a critical lever to maximize earnings from available assets. The pricing can be categorized as dynamic pricing or differential pricing. Example: Same product is sold at different prices on Dell s website based on whether purchased by Private consumer, small, medium and large business, federal government or a health care provider. Dynamic Pricing: Changing prices over time without necessarily distinguishing between different types of customers explicitly. Differential Pricing: Charge different customers different prices according to their price sensitivity. Different form of pricing can be offered different situations as mentioned in Table 8.3. TABLE 8.3: FORMS OF DYNAMIC PRICING AND DIFFERENTIAL PRICING Dynamic Pricing Differential Pricing Discounts during off-season Group pricing (giving discounts to Periodic sales (customers with specific groups) different reservation price) Channel pricing (different prices Adjusting aggregate demand from period to period through different channels) Regional pricing (exploit different

price sensitivities at different locations) Time based differentiation (different rates for different delivery times) Product versioning (Offer slightly different products) Coupons and rebates 8.7.1 Conditions under which dynamic pricing can be profitable Available capacity o smaller the capacity relative to demand, the larger the benefit from dynamic pricing Demand variability o Beneficial with increase in Coefficient of Variation (COV) Seasonality in demand pattern o beneficial as level of demand seasonality increases Length of the planning horizon o longer it is, the lesser the benefits from dynamic pricing 8.7.2 How to determine the best price? When demand is price sensitive and follows a relationship as given below: D= a-bp, Where D is the demand (downward sloping and decreasing linearly with increase in price) for service product, p is price, b is slope of the demand curve and a is the intercept. The revenues for selling product is = Dp Substitute value of D in Revenues and we get, Revenues = (a-bp)p or ap-bp 2 Find the best price of service product which will maximize the revenues.

Differentiate the revenues with respect to price p and equate with zero, we get optimal price, p *, as given below. p * =a/2b Example: Let s say Demand for a service product is price dependent and follows relationship as given below D = 1000 0.5p Revenues = p(1000-0.5 p) or 1000p-0.5p 2 Maximize revenues at optimal price, p* = a/2b = 1000/2*0.5 =1000 Maximum Revenues = a/2b (a-b*(a/2b)) = a 2 /4b=500000 8.8 Revenue Management Tools 1) Overbooking ( discussed in last lecture of module 7) 2) Booking limits and Protection level 8.8.1 Booking limits and Protection level We will use an example of XYZ hotel to understand this tool. XYZ hotel has 200 rooms. These rooms can be offered to leisure travelers and business travelers. XYZ Hotel Fixed capacity of 200 rooms and XYZ offer high fares to Business travelers (H) and offer discounted fares to leisure travelers (L) if they book in advance. Issues faced by XYZ How to plan booking for 30days after the current or today s date under the conditions presented in Figure 8.4 XYZ has 3 options to plan for booking of hotel rooms which are given below. Option 1:- If the demand is more for L fares. If XYZ reserves all rooms for L fares, there will be loss of revenues which XYZ could have generated from H type fares

Option 2:- Reserve rooms for H fares. The demand for H fares is likely to be lesser because of high price. There can be a significant loss due to having empty rooms. This opportunity loss will be lost forever. Option 3: Introduce some protection level for a fare, which is the number of rooms reserved for that fare or higher, and denote it with M. Set some booking limit for low fare rooms. The booking limit is the limit on the number of reservations allowed at that fare or lower. Protection level for M fares = Capacity Booking limit of L fares Option 3 may give good opportunity to generate more revenues. But here the major decision variable is how to set protection level? Service Capacity Of XYZ 200 Rooms Leisure travelers Business travelers Price sensitive Price Insensitive Supply of service Regular Fare Discount fare on weekday if Reservation / booking is done well in Advance (1 month) Demand for service Price sensitive: Book rooms well in advance Price insensitive: Book closest to the time of stay or trip Issues and challenges How many rooms to be reserved for regular fare? How many rooms to be reserved for discount fare? FIGURE 8.4: ROOM BOOKING CHALLENGES FACED BY XYZ HOTEL

8.8.2 Optimal Number of rooms reserved for M fare Or Optimal Protection level What if XYZ sets the protection level too high that is over protection? - XYZ over protects and on the day of traveler s arrival, there are many rooms unreserved or empty rooms. - The empty rooms might have been sold at low fares. - The cost of over protection. C o, is the opportunity lost of selling the room at low fare. i.e. C o = L. What if XYZ sets the protection level too low that is under protection? - XYZ protects few rooms and a business traveler asks for booking one day in advance. XYZ has to turn away the high fare customer because of under protection. - XYZ may loose revenue of difference between high fare and low fare which is represented as cost of protection, i.e. C u = H L. XYZ can implement Newsboy model to determine the optimal protection level. XYZ needs to forecast the demand. If XYZ forecast the demand, D, which follows normal distribution N~ (μ, σ 2 ). The optimal protection level Q can be determined as Cu H L FQ ( < q) = = = C + C H o Optimal Protection level, Example u Critical ratio Q * against = µ + z Critical σ ratio Superjet Airline is facing a decline is demand during off peak season. For a route from Mumbai to Trichy, Superjet Airline have been flying with more empty seats than usual. To stimulate demand, Superjet has decided to offer a special, non-refundable, 20-days advanced purchase fare for Rs 3000 one way based on round-trip ticket. The regular full fare or spot buying costs Rs 4500 one way.

Superjet has limited capacity for 100 Passengers in an airline. The management at Superjet wants to limit the number of seats that are sold at the discount fare in order to sell full fare tickets to passengers who have not made advance travel plans. As per the forecast, the demand for full fare tickets on the given route appears to follow a normal distribution, with a mean of 65 and a standard deviation of 15. How the management will decide the Protection level of full fare tickets? Solution Let s Say Q=Seats reserved for full fare passengers or the protection level D=Demand for full fare tickets C u =Under protection cost, lost revenue associated with reserving too few seats at full fare, i.e. H-L where, H is the full fare ticket cost and L is the discount fare ticket cost C o =Overprotection cost, cost of reserving too many seats for sale at full fare and when the empty full-fare seat could have been sold at the discount price of L C u =4500-3000 =1500 C o =3000 Cu 1500 PD ( < Q) = C + C 1500 + 3000 Critical fractile o u 1500 = = 0.333 4500 The demand is following Normal distribution with N (65, 15 2 ) Using Standard normal table, find the value of Z for a Cumulative probability of 0.33. Z value = -0.4307 The Protection level Q = µ + zσ =65+ (-0.4307) (15) =59 seats