More flights overbooked, but some things are changing

Airlines often sell more tickets on a particular flight than they have seats available. Not because they are mean, not because they can’t keep track of what they sell, but simply to protect them from passenger no-shows. If passengers, especially those with flexible tickets, change their travel plans at the last minute, the airline has to fly with empty seats. And, given the high fixed cost of operating a flight (fuel, labor, and landing fees), that is the airlines biggest fear.

The number of passengers that get bumped is publicly reported in the US by the Department of Transportation. This number is up, once again. About 1.16 passengers per 10,000 are bumped. Not a lot – until, of course, you are the one who gets bumped. 

Two things have changed recently. First, airlines are now better predicting how many passengers show up. Part of this is they just get smarter (using more sophisticated modeling tools), part of this is that the choice set of flights for most customers is shrinking (many airlines have cut the number of flights they offer). Second, planes are getting fuller. The load factor (the percentage of seats that are occupied in a plane) has increased some 10 percentage points in the last year.

How much to overbook remains an interesting problem for the airline. There are elegant analytical models available, that trade-off the cost of the empty seat with the cost of bumping a passenger.

Actors paid to line up for IPhone launch in Poland

Those of us with children know an interesting pattern in consumer (child) behavior. People want to have what is hard or impossible to get. It must be this insight that explains why French telecom giant Orange has hired actors to line up in front of their stores during the Poland launch of the IPhone.

Usually, firms try to REDUCE the length of waiting lines – very much in the spirit of “Matching supply with demand”. But – even we admit – there is more to business than operations alone. Creating a perception of scarcity and increasing the difficulty for a consumer to obtain a product can actually INCREASE demand. Consumers view long lines as indicators of good quality. In fact, recent research combining models of Operations Management and Marketing show what our children have long figured out: “If you can’t get it, it probably is really good”…

http://www.reuters.com/article/newsOne/idUSN215519020080821 

Also see the research by Professors Debo and Veeraraghavan(http://opim.wharton.upenn.edu/~senthilv/)

Adapting lean for customized bank processes

Lean Operations tools, initially developed for the manufacturing sector, have seen numerous successful applications in service operations. Examples range from healthcare to banking and from professional services to insurances. However, most financial service applications reported so far have been related to highly standardized, back-office processes. In contrast, high value-added services often were seen as not suitable for the lean tools.

Applying “lean” to a new domain has almost always triggered the outcry of “these tools don’t apply to OUR business”. We have heard this outcry all too often over the last decade and – once again – this outcry is currently proven wrong as far as customized bank processes are concerned.

A recent McKinsey Quarterly article reports how a commercial lending process could be redesigned using lean principles, leading to 70% faster decisions at 30% lower costs. To achieve these results, the bank leveraged a combination of operational and organizational tools. On the operational side, work-flows were redefined, and each loan was assigned to one of four tracks. On the organizational side, the bank created cross-functional teams that challenged the previous silo mentality separating lawyers, credit analysts, and product managers.  

This is a great example how a combination of Operations Management tools with organizational insights leads to successful lean implementations. 

McKinsey Quarterly, August 2008

Toyota has to idle its truck plant – but keeps workers on payroll

Toyota has long be the darling of us Operations Professors – and rightfully so. It has replaced GM has the largest (measured in vehicles produced) auto company in the world. And, its financial performance remains solid, even at times when many of its rivals struggle. Yet, the challenge of matching supply with demand exist for Toyota as much as for any producer. While customers wait to order the Prius, production workers at Toyota’s San Antonio plant wait for something useful to do – right now, they spend their time on training and community projects (not to say that these tasks are not useful). Remarkably, Toyota continues to keep the entire San Antonio workforce employed and hence operates with  two shifts – management chose to pay the excess capacity rather than going through lay-offs.

Source: Driving.ca, http://autos.canada.com/news/story.html?id=df54a901-2cfb-4740-9507-1cb647edaf8d

Further increase in emergency room waiting time

Recently, we commented in this blog on the tragic case of a patient’s death in a New York emergency room – a death, largely ignored by everyone else in the hospital, and a death following a 24h wait time. Unfortunately, emergency rooms continue to make head-lines.

As reported in the Wall Street Journal, the average wait time in the country’s emergency rooms continues to rise. The Journal reports the results of a recent survey of 362 ERs. The average patient wait time increased over the last decade from 38 minutes to almost 1 hour. Very much in the spirit of this blog, Dr Stephen Pitts, the lead author of the study that was published by the US Centers of Disease Control and Prevention, attributed this increase to recent changes in supply and demand.

The overall supply of emergency care continues to decrease in the US – the number of ERs is down from 4,900 to 4,600. At the same time, demand for emergency care is up: overall population growth, an increasing number of uninsured patients, and increasingly long wait times for appointments have contributed to this increase in demand.

There are no easy fixes to the US healthcare system. Yet, this example illustrates that whatever the next healthcare reform might look like, it has to: (a) make emergency care more attractive to hospitals, many of which pay for the treatment of patients out of their own pockets and (b) improve the access and the management of appointments for patients who want to see a doctor.

Wall Street Journal, Aug 8, 2008 – Average ER Waiting Time Jumps to Nearly an Hour

Supply chain coordination snags Airbus and Boeing

Although airlines in general are having a hard time turning a profit now, there remains brisk demand for new aircraft from Airbus and Boeing. (Possibly because new aircraft are more fuel efficient.)

With a full backlog and a price tag around $200 million per aircraft, these companies do not want to delay delivery of any new aircraft.  But apparently they have had to park nearly finished aircraft due to some missing parts. For example, Boeing couldn’t deliver several 777s to Emirates because they didn’t received customized galleys from Snell, a German producer. 

The problem is that Snell didn’t anticipate the increase in volume and consequently didn’t build enough capacity. This is a good example of how a supplier’s capacity decision can have significant financial consequences for a buyer.

Wall Street Journal, Aug 8, 2008 – Lack of Seats, Galleys Delays Boeing, Airbus

Environmental Kaizen

Kaizen, or “continuous improvement”, means constantly working towards improving processes, no matter how small the improvement.  The idea of kaizen has famously been applied at Toyota to their manufacturing process but the concept has also been applied by GM to make their manufacturing plants more environmentally friendly.

GM’s Lansing Delta assembly plant in the the world’s only to have received Gold Certification from the U.S. Green Building Council’s Leadership in Energy and Environmental Design (LEED) system. They achieved this goal by making many small (and some large) improvements to their processes. For example, they use bright lights were tasks are needed and dim or no lighting where light is not needed (such as where robots are working).  The restrooms use rainwater collected from the roof and the roof is painted white to reduce heat absorption. (Both the light and rainwater examples emphasize that an important resource should be used only where needed.) But more important than any single idea, the implementation of Kaizen changes how employees view their environment and motivates them to generate further ideas.

Automotive News, August 11, 2008 – GM Factory a Model of Sustainable Manufacturing

Improving a process – US Airways’ on-time performance

Believe it or not, US Airways is now a lot better with on-time performance, even better than all of the other airlines (and this is hard to believe if you live in Philly, one of their hubs).  Apparently they are doing this with some good old basic process improvement techniques. For example:

– They have created a “rallying cry” to emphasize the importance of on-time performance.
– They support their rallying cry with financial incentives when goals are met.
– They have installed electronic displays for the baggage handlers so that they can monitor flight status and prioritize effort. A good example of providing workers with the necessary information needed to achieve a goal.
– They have runners that move bags between connecting flights when necessary.  This can be controversial. On the one hand it creates another process, which adds to variability. On the other hand, it prioritizes service where most needed.
– Buffer times has been added to schedules. And instead of doing this haphazardly, they appear to be adding buffers where buffers are most needed – on routes that experience the most uncertainty. This makes for a more efficient use of buffers.

To summarize, they are applying behavioral techniques (goals, incentives) and process changes to demonstrate that good on-time performance can be achieved by anyone.

Wall Street Journal, July 22, 2008 – How US Airways Vaulted to First Place

How local will we become? – fuel costs and international sourcing

The cost of oil seems to be influencing everthing these days.  A recent report by CIBC World Markets, as reported in the NY Times, finds that the cost of shipping a container from China to the U.S. is now about $8000, up from $3000 earlier in the decade. In fact, the cost of transportation is now larger than the cost of tariffs.

What does this mean for supply chains – it is intuitive that higher transportation costs should lead to more localized production.  Instead of producing something in one location in a far off place, companies will start to choose to produce in multiple locations, closer to consumers.

Will this trend continue? One reason for international sourcing is wage rate differentials. If they continue to decrease (because wages in countries like India and China increase) and energy costs continue to decrease, then we may be looking at a long term trend to reverse globalization.

NY Times, Aug 3, 2008 – Shipping costs start to crimp globalization
http://www.nytimes.com/2008/08/03/business/worldbusiness/03global.html

More on Potty Parity

A recent post in our blog discussed NY City’s decision to require more restroom capacity for women than men. Several possible reasons were proposed, including that women may require more processing time on average. Turns out there is data on this. In one study women required nearly three minutes while men required on average 83 seconds (about 1/2 the time of women).  See …

http://www.csmonitor.com/2006/0119/p16s01-lihc.html

and a Feb 24, 1994, Wall Street Journal article titled “Potty Parity’ Lets Women Wash Hands Of Long Loo Lines — Several State Laws Give Jane As Many Johns as John”

The WSJ article is also interesting because it mentions that some architects are designing restrooms with movable walls. This allows them to adjust capacity depending on known demand fluctuations, i.e., flexible capacity for flushes. 

It would still be interesting to have some data on the variability of processing times across the sexes. With mean and variance data, one could get an estimate of how much more female capacity is needed to equate average waiting times. (Of course, other objectives are possible, such as equating the probability that each will be “served” within 5 minutes, or whatever threshold is deemed to be appropriate.)