Tag: Ch.13

Teaching Tip: The Secret to the Airline Pricing Model

This will probably be the 1st blog we do that can save you and your students money!  The Wall Street Journal (Jan.27,2011) just reported  that whatever you do, don’t buy your next airline ticket on a weekend.

We all know that airlines use revenue management (Ch.13) to maximize seat revenue. But the airlines don’t manage their inventory as actively on weekends, so if cheap seats sell on some flights, prices automatically jump higher. When is the best time to buy? The answer is Tuesday and Wednesday—and to be exact, it is at 3 pm on a Tuesday. “That’s when the maximum number of cheapest seats are on the marketplace”, says the CEO of FareCompare.com.

Though prices fluctuate frequently and the ups and downs of air fares can frustrate and anger us, it turns out that pricing has  followed  the same cycle during the week for many years. Discounts of 15-25% for seats are typically launched on Monday nights. “There is a method to the madness… behind the moves for airlines”, adds Expedia’s strategy director. “But for consumers it does seem crazy”. A ticket can be $199 on certain days and $499 other days, even months ahead of a flight.

Two weeks ago, reports the Journal, a Chicago-Atlanta  round-trip ticket for April  (on both American and Delta) cost $209 on Tuesday and Wednesday, but then $301 for the next 4 days. When Tuesday rolled around one week ago, the fares went to $219 —then back up to $307 by Friday.

This is certainly a topic that will interest your students.

OM in the News: Matching Supply (of seats) with Demand at Delta Air Lines

Have you ever been bumped from a flight that was over capacity? It’s a drama that plays out at departure gates every day in airports around the world. Typically, gate agents on overbooked flights embark on last-minute negotiations with passengers who might be willing to take a later plane. The agents broadcast their offers– vouchers worth $200-$400–and keep ratcheting up the price until enough passengers accept. Customers involuntarily bumped get an $800 voucher ( which the Transportation Dept. is proposing to raise to $1,300).

With 541,000 US passengers bumped in the 1st 9 months of 2010 (53,000 involuntarily), there must be a better way to manage capacity (Supp.7) and manage revenue (Ch.13). According to today’s Wall Street Journal (Jan.14,2011),  Delta Air Lines thinks it has the answer.

Delta’s high-tech new system (opened last month) asks passengers who check in online or at kiosks before going through security, what dollar amount they would accept to be bumped from their (overbooked) flight. Delta can then accept the lowest bids, eliminating a lot of uncertainty early. Not only does this give Delta a negotiating edge–passengers won’t know how low others are willing to go. But, in addition, “saving 3 or 4 minutes at the gate has a big operational impact”, according to Delta.  Delta calls it a “win-win” for both consumers and the airline.

Is this good customer service–or do any one of us even expect customer service when we fly? The topic fits well when discussing capacity and yield management issues in both Supp.7 and Ch.13. Given that 8-10% of passengers with reservations do not show for their flights, what other suggestions do students have?

Discussion questions:

1. Which system is better–Delta’s or its competitors?

2. What options do airlines have for capacity and demand?

OM in the News: Robots vs. People for Holiday Staffing

On-line retailers staffing up for the holiday rush are testing a critical hiring decision this year: man vs. machine. Ch.13 lists the options open to firms facing capacity issues, but robots introduce a new wrinkle. The Wall Street Journal (Dec.20,2010) highlights 2 firms with totally different staffing approaches: Crate & Barrel and Amazon. Both firms face a similar holiday crunch and e-commerce sales are up 12% overall, now accounting for 8% of US retail sales.

At Crate & Barrel, which sees holiday sales quadruple, the warehouse gets by with just double the number of employees, thanks to a cadre of 35 robots from Kiva Systems, a firm we highlighted in a recent blog. The machines carry racks of company products (8,000 SKUs) to people who pick and pack—no walking around the building at all.

By contrast, Amazon takes a more human-oriented approach. There, employees walk 18-20 miles a day down aisles lined with shelves, filling shopping carts with orders and carrying them back to packing stations. Amazon also quadruples its holiday staff—hiring a massive force of 11,500 seasonal employees at $11/hour. The firm tries to remove waste from the  hand-picking process with weekly  “kaizen” sessions. Amazon believes that people, not robots, give flexibility to handle its wider variety of products. It also uses hand held computers to guide workers to walk the shortest distance for each order, as described in an article in London’s daily, The Telegraph (Dec.21,2010).

“Which approach is better is a matter of debate in the 15-year-old e-commerce industry”‘ concludes The Journal. But Amazon does point out that it can now take orders up to Dec.19 and still guarantee Christmas delivery, a full 2 days later than last year.

Discussion questions:

1. Discuss the advantages vs. disadvantages of the human vs. robots staffing decision.

2. Where else has Kiva make progress in the fullfillment industry?

OM in the News: Yield Management Turns to Sports

We discuss the subject of yield (revenue) management in detail in Chapter 13, Aggregate Planning. Examples are provided from the airlines(American), hotels (Marriott), car rental companies (Hertz), and even Disney’s theme parks. But the latest issue of Operations Management/Management Science (OR/MS) Today (Oct., 2010) turns to an interesting and relatively new application of revenue management that may interest your students, namely, major league baseball.

Ticket prices to sporting events have always been priced to depend on the seat’s location. But the San Francisco Giants have discovered that  dynamic pricing of game tickets has increased 2010 revenues 6%. Ticket costs now depend on the opposing teams,  pitching match-ups, day of the week,  and even the weather forecast.

For example, a ticket in the Field Club, behind home plate,  for the Oct. 1st game between the San Diego Padres and the host Giants cost $68 at the start of the season. It went to $92 on Aug. 1st,$121 a week later, $145 on Sept. 4th, and $175  just before the game!

Discussion questions:

1. Are other sports and teams replicating this concept of dynamic pricing ?

2. Will there be fan pushback to the idea?

3. How did the 2010 pennant race impact on the Giant’s decision to use yield management?