Tuesday, 25 November 2008

Defining O.R.

The journal that I edit, International Abstracts in O.R. (IAOR), aims to index and abstract the worldwide academic literature of O.R. and Management Science. This means that I (and others) need to make binary decisions about papers; is this one "O.R/M.S." or not?

So what rules to follow? I have several. There are about 40 journals which are abstracted cover-to-cover. These are the journals published by one or more national O.R. societies, such as Operations Research, Management Science, Journal of the Operational Research Society, 4OR and ORiON. There are others which are clearly primary journals in O.R. such as Omega and Health Care Management Science Dealing with these is, so to speak, easy. Then there are about a hundred which regularly include O.R. related papers. Then, I have a long list of journals which have, at one time or another, provided one or more abstracts for IAOR. Some of these abstracts have been found by serendipity, others by researchers citing them in papers in the principal journals. But I need to decide that binary question in each case; is this O.R.? I look at the content (as described in the title and the abstract). As I do, I ask myself what the paper is about. If it is a paper about theory, is the theory directly concerned with a modelling tool (not, I stress, necessarily a mathematical tool) from the suite of techniques used in O.R.. If so, I say yes. If the theory is less directly relevant, I speculate about whether it is close to a technique that is used in O.R.. Practical papers are considered with the question: is this about a decision-making problem? Is there something that a decision-maker could learn from? Is this paper about a problem in practice where I would expect an O.R. person to be involved?

These may appear naive heuristics, but they work. And in my reading, I can add further questions. When I taught in a unit devoted to statistics and operational research, I often used the (crude) distinction that statistics was concerned with looking at what had happened, and O.R. with modelling what might happen, to answer the questions "What if?" and/or "What's best?"

There are still fuzzy edges, at the interfaces with other disciplines. Engineering problems, economic models, psychology of decision-making ... all pose classification uncertainties. But all of these point to the universality of O.R. in the world today.


For those of us involved with O.R., numeracy is practically second nature. Most O.R. people have above average number skills, however you measure them. So it is sometimes salutary, and even shocking to realise that others are numerically illiterate, even though they may be otherwise well-educated.

Two stories from my experience this week illustrate this:
(1) (and this is horrifying) A radio interview with a debt-counselling service in my home city of Exeter. The speaker described how a door-to-door salesman offered a loan "with 100% interest", which the borrower thought was a very good deal.
(2) My national newspaper headlined a column chart showing the "U.K. Government borrowing" for this year and the previous two. Each column was below the axis, and the amount was clearly marked as being negative, becoming increasingly negative as time progressed. Obviously nobody had realised that borrowing a negative amount meant the opposite of what was intended.

Those of us involved in education can take these as reminders that when we have numerical results to communicate, we need to explain them as clearly as possible.

To end on a lighter note, on the same theme. Another newspaper story concerned with the current credit crunch had obviously been hastily sent through a spell-checker. There were two references to £100bun loans.

Monday, 17 November 2008

Google and influenza (flu)

One of my email signatures uses the following quotation:
In the information age, somebody has to specialize in the development and presentation of really useful information. Doing that for management and decision-making applications is the core role of Operational Research scientists. (Randy Robinson, the first executive director of INFORMS)
Throughout my working life, I have worked alongside some excellent statisticians, and been part of some wonderful data collection exercises. Randy R's comment sums up an important aspect of the work of O.R. people -- taking data which has been collected and making sense of that data for other people to use intelligently.
Over the past week, Google's work on modelling influenza epidemics has been made public. Essentially, the company is monitoring the fraction of search queries that they judge to be related to flu, week by week, and region by region in the USA. The results so far show that the fraction of queries that are related to flu increases during an epidemic, and the change can be seen more quickly than is possible by conventional means of epidemiological monitoring. So here is "really useful information" for "management and decision-making". Google's work can be read here.

Monday, 10 November 2008

Wjat went wrong at T5?

Mention "Terminal 5" to an air traveller this year and you may well be greeted by a hollow laugh. The new terminal at Heathrow gummed up within a couple of hours of opening. The summary report states that:
"On the first day of operation alone, 36,584 passengers were frustrated by the 'Heathrow hassle' that Terminal 5 had been designed to eliminate." More than 600 flights were cancelled in the first 11 days, and "23,205 bags required manual sorting before being returned to their owners". The causes: "Insufficient communication between owner (BAA) and operator (British Airways, or BA), and poor staff training and system testing".
All this sounds strange, because the airline BA has one of the most efficient O.R. teams in the United Kingdom. (Yes I mean it, and am not hoping for freebies.) But the word "communication" is at the core of the problem, as a short extract from what Iggy Vaid (a shop steward for staff working on T5) said in an appraisal of the mess:
"I hate to say that about my own airline, but culturally the existing management structure is one where you cannot tell the emperor that he has no clothes; you have to say his clothes are beautiful. No supervisor or person can tell his or her boss that the system will not work. If you do you are not a team player; you are sidelined, so for that reason you say that it works and the emperor has beautiful clothes."
Even the most efficient O.R. work will not be successful if there is no way to communicate it.
Later in the report from which I am quoting (The Independent, Saturday 10th November 2008) another area of potential (inevitable) breakdown was highlighted:
"Should there be a failure in the system at any point it will not self-rectify."
Hidden in these words is a warning for every large O.R. project

Cost Benefit in New York

One of the few email newsletters that I really enjoy is the Internet Scout Report from the Computer Science Department, University of Wisconsin, even though it generally has little to do with O.R.. However, the phrase "weighing costs and benefits" leapt out at me this week, in relationship to the costs for tax-payers of a new sports stadium in New York, and the related benefits. The email gave links to news stories about the issue. Obviously this is an area for O.R. analysis (not just economics) and modelling. But perhaps the most telling comment is that in the Sabernomics blog, where it records:
There is little evidence of large increases in income or employment associated with the introduction of professional sports or the construction of new stadiums.

Monday, 3 November 2008

Placing a value on an experience

In my previous post I referred to the IFORS Newsletter and the account of the IFORS conference in Sandton, South Africa. Among the pictures, there is one of several people stroking a cheetah in a wildlife rescue centre, with the note that there was a fixed charge per photograph. The four people shared the expense. This raises the question -- which is OR related -- of what would be a fair price for that "experience". Someone has had to make the decision and fix a price, presumably to try and maximise the revenue. Costs must be more or less fixed, and extra stroking won't wear out the cheetah. So someone judges what the market will bear. How?
It contrasts with a visit that I paid to a similar rescue centre, where stroking selected animals was free as part of the overall "experience". Another model of costing?

More about IFORS 2008 conference

The IFORS Newsletter dated September 2008 has recently arrived on the web (HERE).
It is a colourful edition, with several accounts of the 2008 conference at Sandton in South Africa. My friend, former colleague, and predecessor as editor of IAOR (International Abstracts in Operations Research) has printed his diary and thoughts about the event. That is one of the worthwhile articles in the newsletter, even though Graham is described as one of the "stall warts" of IFORS, and his account is a "dairy account". Spell checkers are wonder full!