Healthcare system improvement project management: how not to manage projects

Lately, I am finding it difficult to not do the work myself in the projects I'm leading/managing. The excuse I've been using is "well, it's just easier to do it myself than asking someone else for it". However, I end up paying for it with way too many late nights working around the clock. I'll be the first to admit: this is the wrong way to manage projects. I end up feeling burned out and tired doing work that should have been done by others in the team, leaving me without enough energy or time to actually 'manage' the projects. Ultimately, if I continued this way, it would be both bad for me and the projects.


However, I used to lead projects like this before, and it worked charmingly. What changed?

Well...

Here I talked about the Master of Management in Operations Research program that trained me as an OR professional (great program by the way). During this master's program, each student is a project lead on a 4-6 months project with a real company doing real projects. The students are fully capable of carrying out all tasks within the project, but have data analysts to help out, because there is just too much analysis work for one person usually. A project lead in this scenario is both the leader and largely the doer - what I'm used to do at work both before and after the master's program.

Why isn't it working now? In my humble opinion, leading 2 projects with relatively large project teams is quite a busy job. One simply doesn't have the time to both lead and do. I did, so I paid for it. Then I learn. I guess in this case, it would probably be overall easier to ask someone else to do it than doing it myself.

Got any tips to share with me? Comment here or email me at dawen [at] thinkor [dot] org

Healthcare system improvement project management: what's the right balance?

I now live in London, UK, and work for a rather famous hospital, renowned for its medical reputation internationally. My role is a project manager on 2 system improvement projects. Such projects are also labeled as "transformation" or "modernisation" projects, depending on where you work. The idea is to work with doctors, nurses, managers, clerical and administrative staff, as well as patient families, who live and breathe the hospital, so that this group of people take ownership of the problems and solutions. We meet one day a week for a full day, and project managers like me and lean improvement facilitators are thrown into the mix to try to help the projects move along. The key is all about implementation, which may make some external management consultants jealous, since they almost never get to implementation. It is a luxury as one can see one's work flourish.

Great idea, isn't it?

Is the team too big?

• 20% of 8-12 people's time is huge! On paper, the staff are 'back filled' for that 20% of work, but in reality, finding the right people with the right skill mix to do 1 day's work is quite difficult. Therefore, these people often end up working 120%. Commitment to the team starts high but then lacks off a bit.
• With the amount of time invested, people outside the group have very high expectations. They want to see things getting churned out from the team quickly, and often ask "when are you going to deliver what". When in reality, such projects have a research nature to them. There may be the best of project plans, but research will always take as long as it does until you can move onto solutions.
• Keeping 8-12 people 'entertained' and interested in the same topic is challenging. Some people are very detailed. Some want to talk big concepts. Some just want to start getting into the issues and start tearing it apart. Keeping everybody happy is never easy.
  
• Big groups also suffer from democracy. It takes time for everybody to have their say, and one person can dominate the whole discussion and shut others up. The good facilitators will still find this difficult.

But is the team too big? I've definitely experienced the same group, but with fewer people, and we were very productive for the small group days. True, everybody in the team should be there because of their functions within the hospital, but perhaps they don't need to all be there every week.

Ideas on how to tackle the big group:

• We are now trying to break the team into smaller groups to be efficient, and to break the group dynamic. Each sub group also has a sub lead, so more people can feel true ownership within the team. We then reconvene after half a day to update each other on progress. It seems to be working so far.
• Send team members out to the hospital to observe, collect information, shadow someone else, and then update. It breaks the 'classroom' feeling when in a meeting room.
• Of course there are many facilitative ways to deal with it as well when they are all doing this: :)
  

I find these projects are shaping like way more people talking than actually doing the work. It is especially frustrating for the ones who actually joined up for doing the work. I've definitely done successful projects in the past that didn't involve such an elaborate set up. This way of working should make implementation easier. I am waiting and seeing.

Introducing variability, flow and processes in a funny video to anyone

I'm leading on two variability & flow management projects at the hospital right now, and the terms "variability" and "flow" are certainly not something the medics hear much about. I needed a quick way of explaining what the projects are about, what these terms mean, and what kind of problems we are trying to resolve. A colleague suggested this video from the ever popular "I Love Lucy" TV series, episode "Chocolate Factory". It does a wonderful job of making people laugh, as well as acting out some strong parallels to a process, and the variability and flow within the process. Take a look at the video (it's a funny one!) and read on for the parallels to the operation of a hospital. The doctors, nurses and patients on my team all found the video not only hilarious but also made it clear to them what we are trying to do in the variability & flow management project.



The parallels:

• Process: the chocolates can be patients coming into the hospital 'conveyor belt'. Lucy and her friend Ethel can be the nurses, for example, (or the various clerks, doctors, pharmacists, radiographers, etc.) handling the patients, 'dressing' them up or giving them care to make them better so they can go on to the next hospital professionals, i.e. the pharmacists to receive medications in the next room down the conveyor belt. The patient traveling through the conveyor belt is a process. Similarly, Lucy and Ethel picking up the chocolate from the conveyor belt, taking the wrapping paper, wrapping up the chocolate nicely, placing the wrapped chocolate back onto the conveyor belt, and returning to the position to be ready for the next chocolate, is a process. Lucy and Ethel are the 'servers' within the process. The things they do to the chocolate are 'steps' within the process. The girls feeding the chocolate onto the conveyor belt for Lucy & Ethel in the previous room are the servers of the upstream process to Lucy & Ethel's wrapping process. Similarly, the girls boxing the chocolates in the next room, perhaps, are the servers of the downstream process.
  
• Flow: The chocolates going through the Lucy & Ethel's wrapping process is a flow.
• Variability: The speed the chocolates are placed onto the conveyor belt is a source of variability, because the speed changes, and so is the speed that Lucy & Ethel wraps the chocolate, as they have very different styles of wrapping. This results in the variable speed of the wrapped chocolates flowing out of the Lucy & Ethel wrapping process.
• Queuing & waits - When Lucy & Ethel were running behind and when they started to collect the chocolates in front of them and in their hats, so that they can wrap them later, that's queuing the chocolates, and those chocolates are experiencing 'waits'.
  
• Mis-communication: When the supervisor meanie lady shouted to the upstream girls to "let it roll" and nothing happened so she had to go to the previous room to sort it out, that's mis-communication or signal failure. :)

The video also shows some classic examples of problems around processes:

• Isolated processes and working in silos – what is going on 'upstream' and 'downstream' is absolutely unknown to Lucy & Ethel.
  
• Lack of issue escalation procedure - when the chocolates are coming too fast for Lucy & Ethel to handle, they had no way of letting the upstream or the manager know (but of course, the meanie supervisor lady didn't allow them to leave one chocolate behind).
  
• Performance management - the meanie supervisor lady did not have realistic expectations on Lucy & Ethel's performance, or maybe she simply didn't have any clue about the variability of the sometimes very high demand placed on Lucy & Ethel from the upstream.
  
• Reactionary management - When the supervisor lady came into the room and saw that Lucy & Ethel had no chocolates on the belt and therefore ordered the upstream to feed faster is very reactionary. She simply made the decision based on one observation / data point, and did not ask any questions about why it is that way.

Hope you find the video useful in your work as well. I'm sure you can draw parallels to other industries aside from health care. Please feel free to share it with me. Things are often best explained by humour.

"Doing good with good OR" - it's not just academic

ThinkOR reader, Tina asks:

I recently graduated from college and am considering going to graduate school to study Operations Research because it is a subject I really like. There's something strangely satisfying about improving the real world with mathematical models. However, I am conflicted about what kind of career path a masters in OR would put me on. In an admittedly naive way, I want to use my education to improve our society. I think that OR can be better applied to many social services to improve efficiency. However, are there currently opportunities like this available? It seems like most of the job market (at least in the US) is for market analysis...something I don't know I'd want to devote my life to, not that there's anything wrong with that.

There is an issue of Interfaces coming out about the sort of thing I'd be interested in doing--"Doing good with good OR", but the contributors so far are all academic. Is this the main option for this kind of research? I would hate to spend two more years getting a masters degree, only to find out that the kind of job I'm looking for doesn't really exist.

ThinkOR's reply to Tina's concerns on non-academic careers in Operations Research that would do good in our society (outside of finance):

True that OR can be applied to many social (or non-social) services to improve efficiency, because as long as there is a process in place, OR can be applied to it. The question is to what degree it would help - is the ROI worthwhile? You are right that some of the "Doing Good with Good OR" seems research oriented. However, I would disagree that market analysis is the only 'career' for OR graduates out there. In fact, health care is the biggest employer for my graduating class in Vancouver, Canada. It is my understanding that health care is employing OR folks more and more in North America, so there you go, a very valid social/public service that is using OR to improve our society.

Also, in this website, they have listed quite a few other real world examples of using OR to do good, some of them are certainly for the good of our society:

• evacuation planning
• cancer therapy
• acquisition prioritization
• dispatching service vehicles
• delay management in public transportation
• design of a house for disabled persons
• hub location in cargo applications
• production resetting optimization
• optimization of the collection and disposal of recyclable waste

See this website "24 Hours Operations Research - operations research clock" for more details on the above projects.

Simple Hostel Yield Management Example

Continuing on from my thoughts in Yield Management in Hostels?, in this article I present a simplified example of how a Hostel might use simple Yield Management principles to increase its profitability.

Yield Management or Revenue Management or Revenue Optimization is a set of theories and practices that help companies, typically in the transportation and hospitality industry, gain the most revenue possible by selling a limited product where short-term costs are, for the most part, fixed. Simply put, this is why the prices of plane tickets change every time you check and why you can save on hotel rooms by booking in advance.

Consider a simplified hostel. Another time I will discuss some of these simplifications. This hostel takes only single-person bookings for a maximum of a 1-day stay. This hostel has the following rooms: 6 private single rooms and one 6 person dorm. The beds in the single rooms go for £20 and beds in the dorm go for £10. The hostel has entirely fixed costs, meaning they would rather fill a bed at 1p than have it be empty.

Our simplified hostel realizes demand in two streams. The cheapskate travelers desire the cheap dorm rooms, and the wealtheir backpackers are willing to splurge on a single room. The cheapskates would choose the single rooms if they were the same price, and this is the key to my example.

Our hostel is considering bookings for July 1. Currently 1 of the 6 single rooms are booked and the dorm room is full with 6 of 6 beds taken. Currently revenue for this day is £80. This is low compared to the maximum potential of £180, but we're not concerned yet because there are still several days left to take bookings for the single rooms. However, during this time we may also have to turn away some cheapskates, as our dorm is full. Now we ask the question: What would happen to our revenue if we gave one of our cheapskates a free upgrade to a single room, freeing up a dorm bed for more bookings? Let us consider the scenarios in the following table:

New Single Room Booking Requests	New Dorm Room Booking Requests	Resulting Occupancy With Upgrade	Resulting Revenue With Upgrade	Resulting Occupancy Without Upgrade	Resulting Revenue Without Upgrade
5+	0	6/6 Single, 5/6 Dorm	£160	6/6 Single, 6/6 Dorm	£180
5+	1+	6/6 Single, 6/6 Dorm	£170	6/6 Single, 6/6 Dorm	£180
x<=4	0	(2+x)/6 Single, 5/6 Dorm	£80+£20x	(1+x)/6 single, 6/6 Dorm	£80+£20x
x<=4	1+	(2+x)/6 Single, 6/6 Dorm	£90+£20x	(1+x)/6 Single, 6/6 Dorm	£80+£20x

I've colour coded the scenarios above so we can see when we would benefit from upgrading a guest, when we would suffer, and when we are indifferent. In the first two scenarios we receive enough single room booking requests that we could have filled our single rooms at £20, and thus putting a cheapskate in there for £10 hurts our total revenue. In the third scenario we do not receive enough booking requests to have to turn anyone away, so we are indifferent between the upgrade and not. Finally, in the last scenario, if we offer an upgrade, a cheapskate sleeps in as single room for £10 that would otherwise have gone empty and the dorm remains full.

Evaluating the decisions is then a matter of estimating the likelihood of each scenario and calculating the expected revenue for each choice. We evaluate the decision in the same way you would evaluate the following game: I flip a fair coin. If it lands heads I give you £2 and if it lands tails you give me £1. Naturally you would calculate that 0.5*£2 - 0.5*£1 = £0.50 and thus the game is worth playing. The expected value of the decision to play is £0.50.

In order to carry this example through, suppose the probability of there being 5 or more single booking requests is 20% and 4 or fewer is 80%. Suppose the probability that 1 or more dorm booking requests is 75% and 0 is 25%. All probabilities are independent.

Expected value of offering an upgrade = 20%*25%*£160 + 20%*75%*£170 + 80%*25%*(£80+£20x) + 80%*75%*(£90+£20x) = £103.5 + £20x
Expected value of not offering an upgrade = 20%*25%*£180 + 20%*75%*£180 + 80%*25%*(£80+£20x) + 80%*75%*(£80+£20x) = £100 + £20x

As we can see, in the example that I have just constructed, we can expect to make £3.50 by giving a guest an upgrade in the same manner that we expect to gain £0.50 by playing the coin tossing game. Now £3.50 may not sound like a lot, but scale this up to a multi-hundred bed hostel and we're talking about more money.

What made this a winning decision? The £10 we might gain by replacing our upgradee with another guest in the dorms outweighs the £20 we might lose if we have to turn someone away from the single rooms.

So what? Just how likely is this scenario? Consider Smart Russel Square, a large hostel in central London, UK. As of 9:00 pm local time on Sunday, the current bookings* for Tuesday are as follows:

• Large Dorms (10 person and above) 159/160 booked
• Small Dorms (9 person and below) 135/276 booked.

*data gleaned from Hostelworld.com, reliability uncertain.

Based on your gut feeling, what are the odds that they could realize an expected benefit from upgrading some of their large dorm guests to small dorms? 10 guests? 20 guests? If the large dorm beds were filled this could represent £100-£300 in additional revenue. Minus the marginal costs of the guest including their free breakfast of course. Food for thought.

Later I would like to generalize this simple scenario, discuss the simplifications, assumptions, limitations and extensions. That's all for now, though.

Edit:
The way I've set this up might seem strange. Why go to the trouble of upgrading someone from the dorm when you could simply sell a single room as a dorm room? This is because I'm already looking forward to implementation. I don't anticipate hostel management IT systems to have the ability to do this. Instead I envision hostel management IT systems linking bed inventory directly to what is offered online, and thus for us to offer beds at the dorm rate, there must be beds available in the dorms on our system. Additionally, rather than being handled directly by the IT systems, I envision a clerk/manager manually intervening in the system and upgrading a booking. This person might follow a simple set of decision rules compiled from analysis of past data in order to make their decisions. If this strategy proved to be profitable, then it's integration into IT systems might occur.

Yield Management in Hostels?

In my recent travels in Europe I have again had significant exposure to the Hosteling Industry. As readers of this blog will know, we can't help but seeing Operations Research or opportunities in our daily lives. Sure enough we find ourselves analyzing our surroundings and considering the pricing structures of our hostels. In this article I hope to begin an exploration of pricing strategies in the hostel industry that I will continue after I have collected some of your thoughts and more of my own.

The Hostel industry has been rapidly developing throughout the world. According to Wikipedia, youth hostels had their humble origins in German Jugendherberge (1912), non-profit hostels for youths by youths. Fast forward to today and you can witness the evolution to profit-maximizing corporate hostels sometimes exceeding 500 beds.

That said, sophistication in the industry seems to be developing more slowly. In particular, possibly due to it's origins, there is significant resistance to profit-maximizing activity like yield management. I also believe that there is a growing suite of hostel management IT systems with some direct interfacing with booking websites. I can't claim to be an inside expert in the industry, though we did have a nice informal chat with the manager of a small-to-medium-sized non-profit hostel over beers in Munich.

Youth hostels face a problem that is similar in some ways, but different in others to that faced by traditional hotels. Apart from the obvious similarity of product, the primary similarity is that both face an expiring good that is booked ahead of time and cannot be stored.

Hostels, however, do not have business customers. Traditional revenue optimization approaches for hotels centre around price discrimination. With leisure customers and business customers that can be separated by booking time, hotels can sell rooms early at a discount to money-saving leisure customers and sell the remainder later to late-booking, price-insensitive business customers. Hotels can sell some rooms to leisure customers who would otherwise have gone to the competition had they been charged full price, and hotels can then later sell the remaining rooms at a higher price to business customers who would otherwise have only paid the flat rate that leisure customers pay. Hostels on the other hand face an exclusive stream of budget-sensitive travellers. The differentiation achieved by time of booking is thus only a question of how far the customer plans ahead and may say little about their willingness to pay.

Hostels have a wider range of product. I'm not an expert in the hospitality industry, so maybe I can ask our readers to confirm this, but I believe your typical hotel offers simply twin, triple, double, queen, and king rooms. The Meininger City Hostel and Hotel in Munich, Germany for example offers 9 distinct products on hostelworld.com: Single Private Ensuite, Twin Private Ensuite, 3 Bed Private Ensuite, 4 Bed Private Ensuite, 5 Bed Private Ensuite, 6 Bed Private Ensuite, 6 Bed Mixed Dorm Ensuite, 6 Bed Female Dorm Ensuite, 14 Bed Mixed Dorm Ensuite. Something that bears noting is that for the most part these products can be ranked such that any customer will unconditionally prefer one over those below it. For the most part, no customer would prefer to sleep in a 14 Bed Mixed Dorm when they could be in a 6 Bed.

Other factors relevant to the question of YM in hostels: I estimate that the majority of hostel stays are booked through internet booking websites, with the majority of those coming from hostelworld.com. The majority of these bookings are thus made after some moderate price comparison making the market fairly competitive. Many of these bookings will also be made factoring in reviews of the hostel. Sometimes hundreds of website users will have given the hostel a rating for things like security and cleanliness.

The lack of business customers does not mean that hostel customers cannot be segmented. I propose that hostels face two main types of customers. One group comprises the shoestring customers, willing to do anything to save a dollar (or a euro or a pound, etc.). The other group is more differentiating, willing to pay slightly more for a smaller dorm. I'm still working out the significance of this for myself.

I believe there is an opportunity there. Some initial research based on my own experience and some creative use of hostelworld shows that hostels often fill from the bottom up. That is that the largest dorms with the cheapest beds are the first to fill up, and the smaller rooms frequently go empty during the week. This may be a sign that the supply of hostel beds does not match demand. This may show that there are more small dorms in the market than desired and fewer large dorms.

I welcome any comments on the topic. Is there a business opportunity here, or is it just academic? Is the current state of IT and sophistication in hosteling sufficient to work on elementary yield management? Most hostels have a Friday-Saturday price, and everyone in Munich has a low season, high season, and Oktoberfest price, but could we go further?

Starting up in Operational Research: Should I be a generalist or a specialist?

This is the part 2 of 3 of the mini-series on "Starting up in Operational Research".

Question 1: What programming languages should I learn?

Question 2: Should I be a generalist or a specialist as an Operational Research professional?
"As an Operational Research professional, are you usually viewed as a "jack of all trades" or do you usually have to specialize in one area like marketing, government, military, logistics, etc.?"

The short answer is:
First of all, there are two different types of "specializations" in Operational Research: industry specialization, and OR technique specialization. When you are a student at the master's level, you cannot afford to specialize in either industry or technique, because there is so much to learn, and it is all somewhat important. However, once you start working as an OR professional, because of the nature of your work / organization, you will almost be forced to specialize in an industry, such as marketing, healthcare, defense, logistics, mining, energy, etc. However, personally, I would not corner myself into specializing in an OR technique, such as optimization, forecasting, simulation, etc., unless I were an academia. This is because of 'what-if' scenarios for your career. As an OR professional, if you specialize in a technique, you may pigeon-hole yourself into one type of job, which will be difficult to change from if you ever want to. For example, what if you wanted a change from doing simulation models? Personally, specializing in one OR technique could quickly get boring, but that may not be the case for everybody.

Now, let me elaborate a bit more on the above:
As a student of Operational Research (a.k.a. "Operations Research" in North America), there simply isn't time enough to specialize in one field of OR during the studies. At least that was the case for me. My program, Master of Management in Operations Research, run by the Centre for Operations Excellence in the Sauder School of Business, University of British Columbia, is 15 months long. It included 8 months of intensive, mandatory, foundational courses to build up the skills and tools necessary for an Operational Research professional, including but not limited to: optimization, simulation, forecasting, statistical methodology, stochastic processes, decision analysis, operations management and logistics, consulting practices, as well as operations research and management sciences best practices. These are our tools to be a "jack of all trades", and must not be neglected. Then the program included a crucial 4-month (typically) hands-on project, where the student acts as the main consultant on behalf of the school to work with a private or public organization on a relatively high importance OR project, charged with real deliverables to the client. This makes it a "professional degree", instead of a M.Sc. (Master of Science) where the student is expected to do research and produce an academic thesis paper. After the project, the entire program wraps up with another 4 months of courses, but to be chosen by the student. This is the opportunity to specialize if you wish. However, I don't believe 4 months of studies can make anyone a "specialist" in anything. It is the future work that you do that will shape you into whatever specialist you may choose to be.

As a professional working in OR, one will be forced into specializing in an industry or a field of business, such as healthcare, unless you go with a large consulting firm that deals with more than just one type of industry. With the big consulting firms, you may get the chance to be exposed to different industries, but you may have to insist. That experience could be invaluable. From my current job hunting experience in the UK, many industries are rather incestuous, such as energy, finance, insurance, and healthcare. Many jobs will require you to have experience in an industry before they would consider you a worthy candidate. I do not agree with it entirely. Even though there is much to be said about prior industry experience, a good management consultant can transcend industries, because his/her expertise is in the problem solving aspect. Industry knowledge can be picked up quickly by a good consultant, not to be an expert, but enough to solve the problem efficiently. Not mentioning, if an industry keeps hiring from within, not to be cliche, but it just doesn't have the new blood or the out-of-the-box fresh thinking to approach problems from a different angle. I understand if the hiring manager prefers a candidate with prior industry experience over one that does not, but to list it as an essential criteria is over the top and short-sighted.

To learn more about the fields that Operational Research plays a major role in, check this out.

Starting up in Operational Research: What Programming Languages Should I Learn?

A ThinkOR blog reader asked me some questions about getting started as an Operational Research professional. The reader is in his final year studying Mathematical Statistics, and is preparing to get into an OR master's degree upon graduation. I think these might be some common questions about starting up in OR, so I'm publishing my answers here as a mini-series on "Starting up in Operational Research".

Question 1: What programming languages should I learn?
"I'm a bit interested in what programs and programming languages you would recommend to learn? May seem like a silly question, but since we use a few different programs in university, I'd like to focus on the programming languages which are most widely used/accepted. Our main tool at the moment is R, with some Matlab thrown in for Econometrics and larger matrix calculations. Would you consider R a well used tool in OR or is it mainly used in academics but not in real life?"

I think it is not so important as to what language to learn, but to learn the basics of programming well, so that you can pick up any language easily in the future.

The reason I say that is because:

1. The OR application and software world is very fragmented. There are many different applications, and they seem to like having their own proprietary languages. However, most of them are developing a Graphical User Interface (GUI) for non-programmers, since they are often aimed at business users (that's where the money is). That said, if you want to fully utilize a software's potential, especially in the case of simulation software, you'd better learn its own language, which is usually proprietary. This would require you to pick up a new language.
2. Most of these proprietary languages are quite low level languages. Therefore, it is important to have a solid foundation in programming. It will help you understand the language and learn it fast.

My undergraduate degree was in Computer Science (CS). I learned quite a few different languages, but did not really get to use them in Operational Research. However, my CS education helped me to pick up the programming languages needed in OR very quickly. Here I will list the main languages that I encountered in OR:

• VBA
• SAS
• R

VBA is the number one, since a lot of models are done in Excel. SAS is probably the most used in business and a required skill by many employers. Matlab is more for researchers, I believe. I haven't seen it used in any commercial setting so far. I do believe R is used in some commercial settings though.

Note: needless to say, these are only my thoughts on the topic. Please feel free to chime in.

London King's Cross train station platform utilization

In a previous article, Maximizing airport runway & boarding gates utilization at London Heathrow, I talked about the assignment of boarding gates at London Heathrow Terminal 5. They are not assigned until about 40 minutes before departure. I suppose it would only be logical to find the similar approach used on train station platform assignments in London's King's Cross rail station.



As can be seen on the picture above, platforms are assigned only about 15-20 minutes before the train's departure time. They appear to be using a hot platforming system similar to the gates at T5. This has it's advantages and disadvantages though.

It creates a commotion in front of the information board once the platform is finally assigned. Streams of people start to pour away from the information board, which is in the centre of the rail station, making foot traffic rather chaotic. For one train we took, it was so chaotic that the train narrowly managed to depart on time, and it seems likely that delays are sometimes caused. Also, there is always a huge crowd of people waiting in front of the info board at any time, with their pieces of luggage, which again makes foot traffic congested.

Then again, as the crowd of Friday-afternoon-bank-holiday-Monday-weekend travelers pushed to board the KGX to Leeds train, we were met by a team of 8+ ticket checkers who processed us efficiently. These resources only had to be assigned for the 15 minute window between platform announcement and departure. Another possible advantage might be the ability to allow travelers to depart incoming trains before being crowded by outgoing passengers. This suggests the possibility that the platform is known but not announced in order to manage foot traffic, though they are having mixed results given the disadvantages listed above.

Lean Airport with Clear Measurement at London Heathrow

The London Heathrow Terminal 5, which cost 4.3 billion pounds to construct, was described to be a "national embarrassment" for the UK due to its chaotic and "mayhem"-like opening on March 27th, 2008. Blames were put on the problematic computer system behind the luggage belts. On the opening day, 34 flights were cancelled, passenger check-in's were suspended, 20,000+ bags were stranded due to the inefficient system, and passengers waited for hours because of it.

Less than one year later, the London Heathrow Terminal 5 is doing very well. Going through the London Heathrow airport recently, I noticed the following sign just past the Terminal 5's security check point, which screamed "lean operations" to me. It measures and reports on the terminal's various wait time, service availability, overall ease and accuracy, as well as cleanliness.

In particular, the measurement of "Flight information" in the following photo is related to the last article on Maximizing airport runway & boarding gates utilization at London Heathrow, where I talked about the flight information board of gate assignment. It seems like all targets were achieved and some were exceeded. Well done.

Also, the reporting on "Security waiting time for transfer passengers" reminded me of a project done in 2003 by the Centre for Operations Excellence at the Sauder School of Business in the University of British Columbia with the Vancouver International Airport (YVR). The project team created a simulation model to form optimal staffing requirement for the security check point to meet the target of "90% of customers pass through the security check point in 10 minutes or less".

I guess when people pay attention, things can be done properly. "The general consensus at the moment is that Terminal Five has put its initial problems firmly behind it. British Airways believes that the terminal now provides the 'best customer experience Heathrow has known' for several years. Furthermore, the airline holds frequent meetings with BAA in order to review the airport’s performance." (source: Heathrow Airport Guide)

Maximizing airport runway & boarding gates utilization at London Heathrow

Have you transferred at or departed from the London Heathrow airport lately? Did you notice how the boarding gates remain unassigned until approximately 40 minutes before departure for the inter-European flights?  See picture below. I noticed them doing this at least 2 years ago, but now as an Operational Research professional, I can appreciate some of the intuition behind it.

It allows the runway and boarding gate planners a lot of flexibility so that if a flight is late, the planner can easily swap gates and runways if needed with minimum communication to the parties involved. In terms of communication, it is less hassle and less mistake-prone. In terms of an optimization problem, this flexibility means fewer constraints, and therefore better solutions potentially.

Interesting note: see how there are 4 flights scheduled at 19:05 for departure? My flight was the 19:05 to Prague, and I was able to see that there were basically 2 runways for the group of gates in my area, and several planes (about 4) were lined up like ducks in a row waiting for their turns to take off one by one. However, the individual take off is quite fast. Therefore, even though the 19:05 departure time is somewhat approximate for the 4 flights, my flight to Prague certainly arrived on time nonetheless.

As a passenger, it was slightly annoying that when I arrived at Heathrow, I did not know which gate to sit at to wait for my departing flight. However, I was quickly assured that this would not be a problem, because another information board tells me how long it would take to get from where I am to another gate, so I did not need to worry about being late for boarding. See picture below.

I suppose this could also be applied to the domestic flights in other parts of the world, such as the USA and Canada.

ThinkOR's Operational Research traveling tidbits

As previously mentioned, ThinkOR's authors, Aleksey and Dawen, have moved to Europe and are now looking for Operational Research type of jobs in western Europe in countries like Germany, the Netherlands, Belgium, Denmark, UK, etc. Aleksey and Dawen are now on the road a lot, evaluating potential cities to live and work in, while checking out the local OR employment opportunities. On these trips, you will see notes by us about interesting applications or references to OR topics, such as the 2 articles before by Aleksey:

• Lean Prison Management - Alcatraz, San Francisco, California, USA
• Keynesian Economics in 1360 - "the hungry wall", Prague, Czech Republic

Look out for more fun articles on operations research tidbits that we encounter on our trips.

Ciao!

Keynesian Economics in 1360?

I recently tripped across this in Prague. Originally built by Emperor Charles IV, this old city wall was built to protect Prague and some of it still stands today. Two local students who were touring us around the city told me that Charles IV had it commissioned in order to provide work for Prague's people who were suffering from a famine at the time. "Keynesian Economics!" I said.

I found this interesting in a time where the media, public opinion, and politicians suddenly all seem to believe and support Keynesian Economics completely.

Unfortunately the Prague city website reports that this is all a myth and that the wall was already under construction when the famine struck. This cannot be called stimulus money after all. For anyone who has been following the recent stimulus efforts, you could say that this wall was "shovel-ready."

Lean Prison Management

Two weeks ago, Dawen and I were in San Francisco. A mandatory tourist stop is the Alcatraz tour/cruise. Despite the poor weather, we elected to take the cruise and enjoyed an interesting visit to the island, including the award winning audio tour. While on this tour, we noticed an application of the lean principle of poka-yoke or mistakeproofing.

Alcatraz was a super-ultra-max security prison lasting 29 years from 1934 to 1963. High profile and extremely dangerous prisoners were sent here and security was tight. Guns and knives, naturally, were kept secure, but food still had to be prepared in the kitchen. Thus was born the knife board. This was a piece of wood in which each knife had it's shape cut out as a home so that it could be easily determined if a knife was missing.

Lean or Lean manufacturing has an interesting relationship with Operations Research. While Lean is not a component of Operations Research, many of the same principles are at play in its execution. They also typically share the same goals and the same field of play. Lean approaches can be excellent tools for implementing changes recommended by OR analyses. The focus of Lean is the elimination of wasted time and resources in business processes. The key to lean is the grass-roots approach it takes, involving process owners and front-line workers in the problem identification, and solution process.

The audio tour is a largely solitary endeavour, so we did not discuss it immediately. Being the sort of people that we are, though, Dawen and I both noticed this and spoke with each other about it immediately afterwards. It would be interesting to look for more applications of Lean to prison management. Perhaps one that minimizes inventory?

ThinkOR's authors looking for Operational Research positions in Europe

ThinkOR's authors are looking for exciting Operational Research and Operations Management work opportunities in western Europe. Aleksey and Dawen are moving from Canada to Europe to further and broaden their work and life experiences.

We are flexible in the cities we reside in and the industries we work in, so long as the problems are interesting and that we can contribute to the development of an exciting organization. If you or someone you know are looking to hire English-speaking OR consultants, please contact Dawen at dawen[dot]peng[at]gmail[dot]com and/or Aleksey at aleksey[dot]nozdrynplotnicki[at]gmail[dot]com. Our high-level resumes are available on LinkedIn (Aleksey and Dawen). Detailed resumes and references are available upon request. Your help is greatly appreciated. Advices are also welcomed on OR job hunting in Europe.

Since we will be in Europe, if you'd like to meet and chat, we'd certainly be glad to meet more fellow Operational Research professionals. Just shoot over an email to connect.

Breakfast optimization :)

At the end of his course on mathematical methods in optimization, the professor sternly looks at his students and says: "There is one final piece of advice I'm going to give you now: Whatever you have learned in my course - never ever try to apply it to your personal lives!"

"Why?" the students ask.

"Well, some years ago, I observed my wife preparing breakfast, and I noticed that she wasted a lot of time walking back and forth in the kitchen. So, I went to work, optimized the whole procedure, and told my wife about it."

"And what happened?!"

"Before I applied my expert knowledge, my wife needed about half an hour to prepare breakfast for the two of us. And now, it takes me less than fifteen minutes..." 

VBA: Alive and... Well?

The future of Visual Basic for Applications (VBA) has been recently called into question. In March 2008, Microsoft dropped their extended support for VB6 and the Microsoft Office 2008 for Mac did not include any VBA functionality.

This is a cause for concern in the applied OR community. In my recent post about the use of Excel for modeling, all four examples relied heavily on VBA. The ability to rapidly develop models using both cell formulas and VBA scripting is invaluable. Taking that a step further, the interface components and widely available platform of Excel are useful when developing end-user tools for clients.

Luckily our fears can be generally put to rest. An MSDN blog article: The Reports of VBA's Demise Have Been Greatly Exaggerated has assured us that:

"[T]he next generation of the Microsoft Office system will definitely contain all of the functionality that developers and power users expect from VBA."

None of this is breaking news if you're on the lookout for it, but if you're an academic director paying close attention to the relevance of your course/project work it's certainly a current issue.

Personally I'm more interested in the questions that all of this raises rather than answers. With Visual Basic (.NET) 9 and C# as viable options for interoperability between general purpose programming and Microsoft Excel, I find the more interesting question to be: Should we be coding tools with VBA?

Ease of development is one thing, but are we really asking too little of ourselves? Sure someone from a non-software development background can develop a subroutine for Excel, but is that really optimal? Personally I think anyone practicing OR should have at some point learned to code in a modern Object Oriented programming language. It's not that difficult and it really maximizes your efficacy. What it takes to teach someone to code pales in comparison to the sheer educational investment necessary to get someone from high school mathematics to Markov Decisions Processes.

With a little effort C# inter-operating with Excel could produce a much "better" solution than VBA. With a modern IDE and a little experience C# can be coded with relative speed. Indeed I did just this when producing a prototype tool for my Masters project. I must admit, though, that deployment did not happen completely without a hitch. Just because I know how to code does not mean I can comfortably shrug off all of the benefits of VBA/Excel including deployment-by-mailed-attachment.

Philosophically matching the weight of the task to the weight of the approach is difficult. It would be irresponsible to code a truely complex application in VBA. Then again, it might be dishonest to dress up a hatchet job of a solution in the guise of an industrial application.

To sum the above three paragraphs up, the part of me that almost took Computer Science as an undergradutae degree fails to find VBA as an acceptably elegant solution. That said the (clearly much louder) part of me that DID take a Business graduate degree sees the silver lining:

• I read an article by Simon Murphy defending VBA and much of it rang true.
• Some would promote OpenOffice Calc as an alternative to Excel because it's free and non-proprietary. I would disagree. Excel/VBA solutions are good because their platform is free at the margin. Every organization has, has had and will have Excel, making its continuing use essentially free.

What can I say? The debate will continue to rage on. I find it hard to draw a conclusion for this article, but I will leave our OR readers with a thought: Recall the Simplex algorith. Something doesn't have to be perfect in theory for it to be excellent in practice.

Love it or hate it VBA is here to stay. With its inclusion in current and future MSOffice products (with the exception of Mac 2008, but who cares anyway? ;)) we can safely continue to use it where appropriate. We can continue to teach it to our Masters students as a gold standard of business programming.

Use of Excel Spreadsheets in Masters Program Projects

I've been involved with the Centre for Operations Excellence for nearly 2.5 years now. First as a masters student and later as an employee. Each masters student completes an applied Operations Research industry project in the summer as part of the 16-month professional degree in the Sauder School of Business at the University of British Columbia*. This industry project is the highlight of the program and is a consulting-style engagement. A great deal of the modeling done at the COE involves Excel spreadsheets and Visual Basic for Applications. Today I will go through the 4 industry projects from this summer that used Excel for modeling.

In two instances Excel was used as an interface for an ARENA model. ARENA is an excellent discrete event simulation platform and when developing complex scenarios for it, it's ability to interface with Excel is a powerful feature. In An Evaluation of Alternative Designs for the Surgical Suite at BC Children's Hospital, an Excel VBA-based tool was developed to configure surgery block schedule scenarios for the simulation model. In Complex Care & Assisted Living Resource Forecasting an Excel VBA interface was developed for inputs and outputs to an ARENA model for forecasting needs and queuing in an extended care system.

In Optimizing the Supply Chain for a Beverage Manufacturing and Distribution Company a spreadsheet was used to model the supply chain. This model allowed for what-if scenarios testing production schedules, delivery methods, order processing, and inventory levels.

In Evaluating Operational Capital Investments at an International Mining and Metals Company an Excel-based stochastic model was developed of the processing operation.

Obviously I haven't gone into great detail here, but there are confidentiality issues at play. Even without the details, I think the importance of the role of Excel spreadsheets here can be appreciated. All 9 of the projects that year used Excel for data analysis and I would say that 4/9 using Excel for modeling is remarkably few when compared to previous years. If you surveyed the students ahead of time, I don't imagine they would say they pursued a career in OR in order to work with spreadsheets, but in a project where the problem leads the solution, the rapid development environment and widespread platform of the spreadsheet is hard to argue with.


* also the Robert H. Lee Graduate School, but I think we're all getting a little tired of naming all the components of our post secondary institutions.

Operational Researchers and Industrial Engineers - Top 10 Happiest Professionals

As an Operational Research professional, the kind of work we do is pretty exhilarating. Don't you agree?

Recently at work (a major health care authority), my team did some analysis of the emergency department visits trend. We presented our findings and communicated our recommendations to the senior management based on thorough quantitative analysis. I left the boardroom thinking "geeze, who knows when the recommendations will be taken seriously, but if only they would". Then a week later (a week only, can you imagine?!), to my surprise, we hear about the ED changing the physician coverage based on our suggestions and analysis. To take it one step further, they have voluntarily asked for continuous measurement and report to see how this has impacted the ED operations. It made my day! However, I should emphasize that we are lucky to be working with progressive clinical staff who are open to quickly try new suggestions. Cooperative clients make a very happy OR consultant.

It feels good to be useful. I'm sure this is a feeling shared by many other OR professionals. Naturally, we enjoy our line of work, and we are one (or two) of America's top 10 happiest professionals.

At number 7:

Science technicians
Job Description: Use principles and theories of science and mathematics to solve problems in research and development, and to help invent and improve products and processes.

Very happy: 51.0%
Median salary (research scientists): $72,435

At number 9:

Industrial engineers
Job Description: Design, develop, test, and evaluate integrated systems for managing industrial production processes.

Very happy: 48.4%
Median salary: $61,729

So we have some frustrating moments (a lot of them, actually), but when it works according to design, it puts a big smile on my face. :)

Operations Research blogger meet up at INFORMS 2008 Conference

Back in October, 2008 at the INFORMS annual conference in Washington, DC, attending as the official daily e-news reporter for the conference, I also had the opportunity to meet up with a few other operations research bloggers at one of the evening receptions. Here is a photo of us. From left to right:

• Dawen Peng of ThinkOR - Think Operations Research
• Mike Trick from Michael Trick's Operations Research Blog
• Aurelie Thiele from Thoughts on business, engineering and higher education
• Laura McLay from Punk Rock Operations Research

It was great to meet the other operational research bloggers. I got to hang out with Laura at another reception during the conference. It was interesting to learn about other blogger's reasons for starting an OR blog. Mine was to publicize operational research, because I believe in it, and I think more people should know about it. Laura's reason was to attract more high quality operational research students (she is an OR professor). I guess it is a long way to go still, but we are all making small steps in trying to make OR more known.

If you are an OR blogger, make sure to drop me a line and say hi, so we can start building up an OR network. I'd also be happy to link to your operational research blog on ThinkOR.org.