Pricing and Revenue Management 12 Pricing and Revenue Management

Learning Objectives What is revenue management? Why do firms offer differential prices to different market segments? What are the conditions under which revenue management can be practised in an effective way? How do firms make optimal pricing decision in the context of revenue management? Why does the fashion industry offer markdown pricing during the end of the season?

Revenue Management The traditional approach involves hierarchical decision making Marketing function makes decisions on pricing and other marketing variables and supply chain function makes relevant supply chain decisions . In limited supply situation , it is important to make integrated decisions where pricing decisions in particular and overall marketing decisions in general should factor in limited supply availability. Supply is limited by the available capacity in perishable products or service situations. Since one can not store perishable products and services, the capacity of plane or a hotel or a truck restricts the supply position in these businesses. Supply is limited by available inventory in long lead time supply situations. The ability to handle demand is constrained by the fact that the supplier needs a long lead-time and, within that period the firm has to manage with the inventory available at hand. Under conditions of limited supply, the bulk of the capacity and supply-related costs have already been incurred and consequently revenue management attempts to make optimal pricing decision so that the firm can generate the highest possible revenue so as to generate the highest possible profit.

Optimal Pricing Decision: Single Customer segment Linear demand curve D= a- b p D= demand and p = price and a & b are parameters of demand curve Pricing : No capacity constraint , zero variable cost P* = a/2b & Revenue* = a 2/4b P* & Revenue* = optimal price & Revenue respectively Pricing under capacity constraint P* = (a – capacity)/b Pricing in a situation involving significant variable cost P* = ( a+bc) /2 b where c= variable cost

Demand and Revenue Curve Demand = 160- 20* price Revenue = 160* Price - 20 * Price 2

Revenue Management for Multiple Customer Segments Required conditions for Applicability of Revenue Management Capacity is perishable One can not store unused airline seat or unused hotel room The same unit of capacity can be used to deliver product or service to different submarkets having their own demand curves with differing price elasticity. Leisure and Business traveller would use identical seat/room Using appropriate booking rules firm can create a fence among the relevant submarkets. Leisure Traveller is willing to book early and does not mind no cancellation policy while Business traveller would book close to the travel date and would value flexibility of cancelling at last minute

Demand Curve for Multiple Customer Segments Demand = 160 -20 p if price > 4 Demand = 400- 80p if price ≤ 4

Impact of Different Price Schedule on Revenue Under Capacity Constraints How to determine optimal prices ? : Optimization model

Pricing Under Capacity Constraint for Multiple Segments: Demand Deterministic: Optimization Model Maximize Subject to ≤ Capacity ( ai - bi Pi ) ≥ 0 for i= 1.. n i= 1.. n represent n market segments

Revenue Management under Uncertain Demand and Limited-capacity Situations Capacity allocation under multiple segments Low price segment has unlimited demand ( at least more than capacity ) & High price segment has uncertain demand Low price segment demand/booking is observed before the High price segment demand is realised Capacity for price segment needs to be reserved by placing limit on low price booking. Illustrations Business segment versus leisure segment in travel and hotel industry: Prices are high in Leisure segment but demand is uncertain. Prices are low in leisure market but demand is high ( usually more than capacity) Forward versus spot market in business to business markets where capacity : Spot market is les price sensitive but demand is uncertain. Prices are low in Forward market but demand is high ( usually more than capacity)

Capacity Allocation Among Multiple Segments: Airlines and Hotels Let Pb be a price charged to the business traveller and Pl the price charged to the leisure traveller. Cost of understocking = Pb - Pl Cost of overstocking = Pl Optimal Service Level = (CU  100) / (CU + CO ) = (Pb - Pl )*100/( Pb - Pl + Pl ) = (Pb - Pl )*100/ Pb Optimum protection level for the high-price segment = Mean demand for the high-price segment+ k  Standard deviation of the demand for high price Where k = service factor for optimal service level

Capacity allocation among Multiple segments : Airline industry - Illustration Super Airlines case : The seating capacity of each aircraft is 180 seats. Super Airlines decided to charge Rs 2000 for leisure travellers (who are expected to book 14 days ahead of the scheduled flight day) and Rs 5000 for business travellers. With price of Rs 2000 for leisure travellers, demand is more than 180. At price of Rs 5000, demand for business travellers is likely to follow normal distribution with mean demand being 60 seats with standard deviation of demand being 20 seats. Optimal booking limit for low-price fares: CU = Pb - Pl = 5000- 2000= 3000 & CO = Pl = 2000 Optimal Service Level = 3000*100/ (3000+2000) = 60% service level of 60% means k ≈0.25  = 60 + 0.25*20 = 65 High-price protection level for business travelers = 65 seats Booking limit for low price fares = 180-65 = 115 seats.

Capacity Allocation Among Multiple Segments: Forward-versus-spot Market Forward price is Pf and spot price is Ps Cost of understocking = Ps - Pf Cost of overstocking = Pf Optimal Service Level = (CU  100) / (CU + CO ) = (Ps - Pf )*100/( Ps - Pf + Pf ) = (Ps - Pf)*100/ Ps Optimum protection level for the spot market segment = Mean demand for the spot market segment+ k  Standard deviation of the demand for spot market segment Where k = service factor for optimal service level

Capacity Allocation Among Multiple Segments: Forward-versus-spot Market Warehousing firm Case : Firm has a warehouse in Gurgaon and a the firm rents out capacity for a month as a unit of time. It has physical warehousing space for storing 50000 MT of goods and is trying to decide on how much capacity to reserve for spot market customers for a coming December month. Forward market : Unlimited demand , market prices are Rs. 150 per MT spot markets prices are 200 per MT. Demand for warehousing capacity in spot market in December follows normal distribution with mean demand being 10000 MT with standard deviation of demand being 3000 MT. Ps = 200 & Pf = 150 Cost of understocking = Ps - Pf = 50 & Cost of overstocking = Pf = 150 Optimal Service Level = 50*100/200 = 25% → k= - 0.7 Optimum reserve capacity for spot market = 10000 -0.7 * 3000 = 7900 MT

Overbooking : Revenue Management for Handling Booking Cancellations Overbooking is the practice of booking seats/rooms in excess of the actual seats available in flights or rooms available in hotel. Whenever there are chances of cancellations (at the last hour) or no-shows (customer not showing up), if airlines/hotels does not do overbooking, it will end up with a lot of unused capacit Optimum overbooking p= price for the unit of capacity sold b = net cost incurred in making backup arrangements in case the firm is not able to provide the booked unit of capacity to the customer. Cost of understocking* = p Cost of overstocking* = b Optimal Service Level = p*100/(p+b) Optimum number of over-bookings = Mean cancellations + k  Standard deviation of cancellations where k = service factor for optimum service level * Stocking refers to excess bookings ( Bookings above capacity )done by Airline/hotel

Overbooking: Illustration Bangalore Hotel has 100 deluxe rooms and has observed in the past that cancellations at the last minute (including no shows) follow a normal distribution with mean of 15 and standard deviation of 5. The hotel charges room rent of Rs. 2600 per day from all its customers. Because of overbooking policy, whenever Bangalore Hotel faces shortage of rooms it accommodates the customers in another hotel in the neighbourhood which charges Rs; 4000 to Bangalore Hotel for providing rooms at short notice. Optimum Overbookings: C u = P= 2600 and C o = b= 4000 -2600 = 1400. Optimal Service Level = 2600 *100/ (2600 +1400) = 65 % → k ≈ 0.4 Optimum number of over-bookings = Mean cancellations + k  Standard deviation of cancellations where k = service factor So optimum number of over-bookings = 15 + 0.4 * 5 = 17

Revenue Management for Inventory Assets In short life cycle product Demand over season is highly uncertain But usually order for entire season is placed before the start of season Standard Practice: If Seasonal demand < Order, excess stock is salvaged at the end of season Markdown Management: Forecast is updated based on demand observed during initial part of the season and if Updated Demand < Inventory, Prices are reduced ( marked down) so as to Maximise revenue over the Season .

Markdown Management: Illustration Season consist of Four periods and demand is updated at the end of period1 & entire requirement for the season is ordered in advance Updated Demand = 150 units per period Opening stock at the beginning of period 2 = 694 units, Base price= 500 Rs./Unit, Salvage Value at the end of season= Rs. 30/unit Possible Markdown options: Markdown Demand Increase 0% 0% 20% 30% 40% 70% Markup not allowed

Impact of Markdown Options on Revenue Markdown Management: Impact of Markdown Options on Revenue

Impact of Markdown on Sales and Revenue Markdown Management: Impact of Markdown on Sales and Revenue Markdown Sales(Units) Tot-Rev Option Period-2 Period-3 Period-4 1 150 232320 2 20 195 233970 3 40 255 230670 4 235620 5 6 229020 7 237270 8 9 244 227700 10 184 208200

Innovative Pricing Firm can offer differential prices to customers even in a situation where there are no capacity constraints. Use of Rebate coupons by P &G Use of Happy hours by Pubs & Restaurants Differential prices charged by Amazon.com Brand loyal customers ( customers who do not search over net for price comparisons) were charged prices Coca-cola experimented with idea of changing prices at smart kisoks based on season and temperature and based on location of Kiosk. Higher prices charged on hotter day, Kiosks located close to football field would charge higher prices on the day of the match Firm should ensure that differential pricing schemes are not perceived as unfair practices by customers Amazon.com and Coca Cola discontinued differential pricing schemes when they found that customers perceived theses practices as “unfair” Extreme case of differential pricing would involve customized pricing where each customer is charged different prices based on his utility and willingness to pay.

Summary-I In a situation where capacity is perishable, the bulk of the capacity and supply-related costs have already been incurred, revenue management attempts to make optimal pricing decision so that a firm can Maximize both the revenue, and by extension, the profit. Revenue management can be practiced where the same unit of capacity can be used to deliver product or service to different submarkets having their own demand curves with differing price elasticity. Firm should be able to come up with innovative way of separating different submarkets so that firm can offer differential pricing schemes. Using different booking conditions, firm should be able to create a fence between various submarkets.

Summary-II As different submarkets book capacity at different point in time, firm has to a priory allocate capacity to various submarkets. In uncertain demand situations firm faces a delicate decision regarding how much capacity to reserve for high fare paying customers who usually book capacity at later point in time. Given uncertainty in demand, while reserving capacity for high fare paying customers firm has to balance cost of over-reserving versus cost under- reserving. Firm can use ideas of revenue management in any industry ( not restricted to case of perishable capacity context) by applying innovative pricing scheme like customised pricing so as to increase revenues and profits.