Yield Management (OM) Introduction Ing.J.Skorkovský, CSc, Department of Corporate Economy FACULTY OF ECONOMICS AND ADMINISTRATION Masaryk University Brno Czech Republic Some OM methods (part of OM and ERP course) •Theory of Constraints •Critical chain •Balanced Scorecard •Project Management methods (Critical Chain, SCRUM,…) •Material Requirement Planning and Just-in-Time – part of MS Dynamics NAV •CONWIP (in case of gaining free capacity in the course schedule) •Boston, SWOT and Magic Quadrant Matrices •Little ´s Law (relations between WIP, Throughput and Cycle time) (will be dicussed on 15.11.) •Linear programming (will be discussed on 22.11.) •Yield Management (will be discussed on 15.11.) •Kepner-Tregoe-support of decision making (was discussed on 8.11.) •Drum-Buffer-Rope (will be discussed on 22.11.) • • • Project management Theory of constraints Production Critical chain Drum –Buffer-Rope MRP-MRP-II,JIT,APS Linear programming Cutting, blending Total quality management Pareto, ishikawa Product postitioning Little´s law Boston Matrix Gartner QM Workflow CONWIP Logistics EOQ and BEP analysis Decision Making Kepner-Tregoe Hurwitz Business Intelligence Yield management Prospect Theory Another point of view (plan-do-check-act) ABC Pareto, Ishikawa Six Sigma Product Life Cycle LEAN Function block Logistic more in detail will be presented later in this show SCRUM Used abbreviations : QM– Quadrant Matrix; CONWIP – Constant Work in Progress; EOQ – Economic Order Quantity ; MRP - Material Requirement Planning This will be modified in following South African project show (use of Balanced Score Card) Yield Management (YM)-definition I. •YM seeks to maximize yield or profit from time-sensitive products and services •Used in industries with flexible and expensive capacities, perishable products (fresh fish, flowers, bakery products) and uncertain demand. It is part of revenue management •Type of problems: – overbooking (airlines, hotel industry,..) – partitioning demand into fare classes – single order quantities – YIELD: to produce or furnish (payment, profit, or interest): a trust fund that yields ten percent interest annually; that investment will yield a handsome return. •Simply put, the purpose of Yield Management is to achieve maximum revenue/profit. •To get Max Revenue/Profit, a yield management strategy needs to be both reflective and forward-looking. Yield managers should attain a clear and detailed understanding of what has happened before and what is happening now. •The most efficient way to do this is to draw from historical data to predict what may happen in the future. So, the process of effective yield management involves understanding, anticipating, and reacting to consumer behavior (to maximize revenue ultimately). • • • Yield Management (YM)-definition II. Single Order Quantity Newsboy problem – see next slide and slide number 11 as well !!! Economic Order Interval: period between orders that minimizes the total inventory cost under the given assumptions. EOI is estimated by comparing the cost of placing an order with the cost of holding inventory. EPQ =Economic production quantity model (also known as the EPQ model) determines the quantity a company or retailer should order to minimize the total inventory costs by balancing the inventory holding cost and average fixed ordering cost. Newsboy problem Often managers have to make decisions about inventory level over a very limited period. This is the case, for example with seasonal goods such as Christmas cards that should satisfy all demand in December, but any cards left in January have almost no value. These single-period decision models are phrased as the Newsboy Problem. For a newsboy who sells papers on a street corner, the demand is uncertain, and the newsboy must decide how many papers to buy from his supplier. If he buys too many papers, he is left with unsold papers that have no value at the end of the day. If he buys too few papers, he has lost the opportunity of making a higher profit. Prices and demand •Prices can be determined by: –Service –Group of services –Market (consumer type or geographical area) or –A combination of the above • •And the demand side is characterized with: – Variability of demand – Variability of value (time, area, type of client, type of service) • Overbooking (hotels, airlines,..) - example Výsledek obrázku pro airbus a380 seats plan 10%-30 % of a no-show (traveler who reserved ticket, but canceled it at the last minute). Therefore, airline companies overbook their capacities. The no-show ratio is sometimes lower than the overbooking ratio, so „bumped“ client will be compensated by providing the free of charge service at another time or place. They are so-called „offloaded“ to other routes. Example: 311 economy seats, estimation of 10 % no-show-> 31 places would be lost (only 280 seats occupied). If overbooked by 10 % (31 more tickets offered) and no-show ratio on reality is only 7 %->only 22 clients cancelled - > 311-22=289 seats occupied ->289 + 31=320->320-311=9 clients have to be „bumped“ (or 31-22=9) and provided by free air tickets, which is better than the loss of not sold 31 places. You have to calculate the loss of 31 places -22 sold tickets =amount which must cover expenses for 9 bumped clients 7 % out of 311=22 Basic calculations - example •Air ticket in economy class =10000 •31 no-show = loss = 310 000= 31*10000 •9 bumped travellers – granted business class instead of economy class ->one air ticket =30000 •Cost of bumping = 270 000 =9*30000 •Difference = 310000-270000 = 40000 profit How to Make the Most of Emirates Economy Class - NerdWallet První třída versus business class. Jaký je mezi nimi ve skutečnosti rozdíl? Overbooking<->No-Show Full Aircraft No-show NS OB Overbooked No-show Overbooked B = bumped passeners Planned Planned Reality Final status NS = no-show passengers Overbooked OB B B OB = overbooked passengers Cost of B < Cost of No-show Overbooking - claims •Do not settle! Do not worry about it! Instead get up to €600 + luxury hotel + meals + additional expenses + new ticket! • Delta Air Lines has increased the amounts passengers can be offered to give up their seats to up to almost US$10,000 in extreme cases — something passengers can take advantage of if they act in collusion (secret deal). Single order quantities •Newspapers •Magazines •Florists •Bakeries •Fresh fishes Single order quantities •N = number of items that can be sold (expected optimum) •X = number of items ordered by salesman •C0 = Cost of over-estimating demand (cost of remaining faded flowers and are not sold) •Cu = Cost of under-estimating demand (customers like to buy more roses and you do not have enough of them ) •Cu >= C0 •P(N= P(N P(X<=N) = 1-P(N= P(N OPTIMUM PROBABILITY • • Cu • P(N=pCo • Cu+pCu >=pCo • Cu>=>p(Cu+Co) Final formula for over-estimating demand Example 1 ->Single Order Quantity -hotel industry •Manager Simon Stein of the Best Western in Las Vegas is tired of customers who make •reservation and do not show up. Rooms rent is 100 USD per night and cost 25 USD to maintain •per day. Overflow („bumped“) customers can be sent to Motel 7 for only 70 USD per night. •Simon´s records of no-show over past six months are given below. Should Best Western start overbooking? If so, how many rooms should be overbooked? No-Show Probability 0 0,15 1 0,25 2 0,30 3 0,30 Solution : C0 = 70 USD - cost of overestimating demand Cu = 100 USD-25 USD =75 USD - cost of underestimating demand Cu P(N0,517 Optimal probability of no-show falls between 0,40 and 0,70. So if we take less of equal to 0,517, so next lower value is 0,40. So two rooms have to be overbooked !!! 0,15+0,25=0,40 and 0,40+0,30=0,70… Simon Stein statistics Example 2 ->Single Order Quantity - Airlines (home study) •FlyUS Airlines is unhappy with the number of empty seats (same with hotel rooms) on its NY-Miami flights. To remedy the problem, the airline is offering a special discounted rate of 89 USD instead of standard full fare 169 USD, but only for 7-days advance purchases and for a limited number of seats per flight. The aircraft flown from NY to Miami holds max 100 passengers. Last month´s distribution of full-fare passengers is shown below. How many seats FlyUS reserve for full–fare passengers ? • • Aircraft capacity 100 Full fare No-Show Frequency Probability P(N