McDonald’s medicine

February 5, 2011

Americans want instant gratification – that is true for fast food as much as it is for healthcare. Consequently, the traditional model of general practitioner in which you make appointments and then (a week later – if you are lucky) see a doctor is getting increasingly challenged. Patients have found the McDonald’s of healthcare. It is called the ER. You go there when you want and they will get you what you want. One stop shopping for all your healthcare needs.
In the following article, two ER doctors describe their view of the problem – and make us think if we have to invent the way we deliver care:,8599,2044392,00.html


Taxi capacity in NYC – the 4 O’Clock Blip

January 12, 2011

Apparently it is hard to find a taxi between 4 and 5pm in Manhattan. Why? Because that is the time when many taxis switch drivers. This turns out to be a fascinating capacity management issue.

The first surprise is that a substantial number of taxis are used around the clock in two 12-hour shifts. I guess NYC really does never sleep.

So, given that you have two 12-hour shifts, and clearly one driver can do only one of those shifts, you need to decide a time and place to switch drivers. The place turns out to be, in all likelihood, a garage in Queens. (The use to do it in Manhattan, but real estate became too expensive, so they moved to Queens.) The time, you would think, would be chosen at a relatively light period. Or, it would be chosen so that earning potential of the two shifts are equated in some sense (accounting for the fact, I would assume, that the day shift is more pleasant than the night shift).  Take those factors into account and apparently 4 pm is a good time to swap drivers – one person gets the morning rush hour, one the evening rush hour. The result, according to NY Times 1/11/11 is a 4 O’Clock Blip of empty taxis:

What is really interesting about this is that the spike is so pronounced. If 20% of the taxis are taken out of service 4-5pm, then you would think that there would be a noticeable drop in competition. Wouldn’t more taxis want to make the switch at 3pm or 6pm to take advantage of this? In other words, why isn’t the blip smoother? Given that it is spiky, it must be that it is too costly to switch at the other times relative to the 4-5 pm slot.

One explanation has to do with coordination. If some cab drivers make the switch at 3, others at 4, others at 5 and yet others at 6, a cab driver needs to know when he will make his switch – when to drive the taxi back if he is doing the day shift and when to show up at the garage if he is doing the night shift. Keeping track of those times might lead to the inevitable late cabby, which will lead to idle taxis. Having everyone show up at 4-5 is a simple rule that is easy to remember – you show up at 4-5. When do you show up? 4-5.  But this seems like it could be fixable with technology. A computer keeps track of the schedule and sends reminders to cabbys as to when they will show up. Or, it could be fixed with some consistent scheduling – for a given month a given cabby will have the same drop off/pick up time but the times are staggered to smooth the spike.

An alternative explanation could be due to demand. Maybe demand drops significantly at 4-5, so being a taxi at that time is not as advantageous as the lower supply would make it seem. This strikes me as unlikely, but what do I know about taxi demand in Manhattan between 4 and 5pm?

The Bloomberg administration is looking into this issue, being a data-driven type of administration. To their credit, they don’t plan to do anything until they identify the root causes. And even then, they say they are hesitant to tell businesses how to do their business – maybe the taxis know something that we don’t know. “Fixing” this issue (if it should be fixed) will not change the world much, but it is a fun capacity management exercise.



What Disney does to reduce wait times

January 5, 2011

Understanding (and reducing) waiting lines (Queues) is central to Operations Management. Waiting in line is often one of the most memorable experiences when visiting theme parks such as Disneyland. The long wait times limit the number of rides a visitor can experience per day. Disney research shows that the average visitor only can enjoy nine rides per day. From a “value-add” perspective, this is a rather poor performance.  A ride might take five minutes. So we are looking at 45 minutes of value add (ride) time relative to an eight hour day. What can be done to improve this? Improvement actions in this environment can be categorized into three groups: (a) Increase capacity: in some cases, it is possible to increase capacities at the attraction. In the Pirates of the Caribbean attraction, Disney is able to increase the launch frequency of boats as demand increases. (b) Make the waiting more pleasant: Disney dispatches greeters and entertainers to reduce the perceived waiting times when it is not possible to reduce the actual waiting time. Simple video games are now added to Space Mountain as a way to turn unproductive (and not amusing) wait time into something fun. (c) Divert demand to less crowded areas: if you can’t increase capacity, try to reduce demand. There are 40 rides / attractions in a typical park. But demand tends to focus on some high visibility attractions as those are perceived as being the most fun. When wait times in those areas grow long, Disney tries to create some “buzz” in other areas of the park, trying to divert demand and thus balance capacity utilization.

For a more detailed story, see:

Actors paid to line up for IPhone launch in Poland

August 22, 2008

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”… 

Also see the research by Professors Debo and Veeraraghavan(

More on Potty Parity

August 4, 2008

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 …

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.)

Women need more capacity – potty parity laws

July 19, 2008

When it comes to potties, “separate but equal” may not be equal enough – NY’s City Council decided that public venues like arenas, nightclubs and theaters must provide a female-to-male restroom ratio of two to one. This provides an entertaining context to discuss queuing theory.

We all know that women often have to queue to use the restroom while men usually do not. To devise the appropriate solution, it is important to know why. Queuing theory provides useful guidance.

In short, a queue will form when the load on the system exceeds its capacity, where the load is the arrival rate multiplied by the time to process each request. Think of load as the desired number of flushes per minute and the capacity as the feasible number of flushes per minute. This raises several possibilities for why the queue in the women’s room is longer:

(1) The arrival rate of women is higher, either because there are more women than men at a particular venue (doubtful at Madison Square Garden’s Monster Truck Smash) or because women need to use the restroom more often (absolutely true in some families);
(2) The arrival rate of women is more variable. Hard to imagine this is so unless the women’s basketball team bus arrives or women have a greater tendency to use the restroom in packs.
(3) Women have a longer processing time. Data could in theory be collected on this, though discretion would be appropriate;
(4) Women have a more variable processing time. Again, many theories, little hard evidence;
(5) Less capacity per restroom – How many people can flush simulataneously in a restroom? On a per square meter basis, urinals are very efficient.

When it comes to restrooms we probably do not want to consider options that would either strive to (i) decrease the mean or variance of their arrival rate or (ii) change their restroom behavior to decrease the mean or variance of their “processing times”. That leaves cause (5) above as the solution – increase capacity. 

A simple solution to increase capacity is to pool capacity – unisex restrooms.  This, of course, is a non-starter in some cultures. The obvious alternative is to add more women’s restrooms (i.e., more possible flushes per unit time),  which is exactly what NY City has legislated.

This leaves open two questions – why do we need legislation to fix this? (i.e., why doesn’t the market work here) and how do we get men to leave the seat down?

NY Times, July 18, 2008
A ‘Women Only’ Restroom Renovation Tips the Balance at Grand Central

24h wait in the ER / video of a patient collapsing while waiting

July 10, 2008

Long waiting times and crowded ERs have unfortunately become rather common in the US – sadly enough, the country has gotten so much used to this fact that a crowded ER or a diverted ambulance is not news any more. The tragic story of a NY woman collapsing in the ER of a psychiatric ward, however, made it into the national news. Her collapse and subsequent death were captured by the video system installed in the waiting room and the video made it onto YouTube. When the patient collapsed (after having waited for 24h), nobody (neither patients nor hospital employees) noticed or cared. A sad reminder about the importance of service operations management (including the management of waiting times) and quality management. For more details, see:

NYT July 2, 2008: Video of Dying Mental Patient Being Ignored Spurs Changes at Brooklyn Hospital

How to reduce congestion?

July 3, 2008

Fewer drivers are using Manhattan’s bridges and tunnels, which should mean that there is less congestion in the city. One obvious explanation is the increase in fuel prices. Another is the increase in tolls that went into effect March 2008. Either way, economics seems to work – raise the cost of something and people do less of it. But this raises an interesting question – what is the best way to reduce congestion within the city?

Mayor Bloomberg had proposed a congestion tax of $8 for entering a certain portion of Manhattan during peak times. That is a fee targeted at usage when the system is most highly congested, which, according to queuing theory, should be a more efficient approach than raising the cost of fuel, which applies for travel at any time. However, the increase in fuel costs may be equally effective if consumers are only able to choose alternative means of transportation at peak times. For example, consider two trips – a visit to a friend’s house for a dinner party or a commute to the office. The train may bring the person to the office, but not to the friend’s house. Hence, as fuel prices increase, the first trip to be dropped is the car drive to the office. Hence, it is an open question as to how much more effective a targeted congestion tax would be. However, it is clear that an increase in the cost of fuel funds oil producers whereas a congestion tax funds the city’s efforts to improve transportation – they may have similar effects on congestion, but not on the allocation of resources.

Politics Failed, but Fuel Prices Reduce Congestion
NY Times July 3, 2008