A news item at the weekend told that one of the big four UK supermarkets has opened a small city centre store for the first time. Morrisons were joining others (Tesco & Sainsbury and Co-operative) who have both large out-of-town stores and basic outlets in city centres.
The story claimed that the decision had been taken because of the recession, affecting the number of people who shop out-of-town. But the other stores know that there are different clienteles for different types of shop, so there is almost certainly an underlying decision to try and reach the clientele who shop regularly in their city centres. Maybe the recession drew the management's attention to the need to do this?
I don't know how many O.R. scientists work at Morrisons. But I hope that any who are there have read about a study that one of the others commissioned, which led to a change in the way that it handled distribution to its city-centre shops. The study showed that the principles of distribution were significantly different to such stores, compared with the model that was used for out-of-town stores. The O.R. person involved spent three months travelling in the cabs to observe what actually happened, which was not what the staff in head office thought happened. And as numerous O.R. studies have shown, it is always important for the O.R. staff to get involved on the front line, or sharp end.
Showing posts with label operational research at the supermarket. Show all posts
Showing posts with label operational research at the supermarket. Show all posts
Monday, 11 July 2011
What's in that truck?
Last week Tina and I drove from Exeter to South Wales for a two day break (it rained a lot!). On the motorway (M5) we started to pass the time by looking at the articulated lorries coming on the other carriageway. The first "game" was to look out for those labelled with the major British supermarkets. We decided that the rules were to see how long it took before we had a hand of five: Asda, Morrison, Sainsbury and Tesco, plus one wild card from Waitrose, Co-operative, Somerfield etc. We weren't sure whether or not to count M&S, as their lorries might be carrying clothes ... but decided that the big supermarkets also deal in clothes and much else. (Yes, British readers will know that Somerfield doesn't exist as an entity these days, but the Co-operative which has taken it over has not completed the conversion of its fleet. We even spotted a truck whose trailer read Somerfield, pulled by a tractor labelled Co-operative.)
In the first hour, we completed three hands of five, an indication of how much traffic there is into the south-west of England. But we were also interested in the other labelled food trucks. Once, when I was consulting for a major confectionery company, I remarked that you never saw lorries with their name on the side. I was told that when the company started in the UK, they linked to a local haulage company in the same town, and that haulage company continued to carry all the confectionery; the two companies had grown together. So there are many household names which never appear on the sides of articulated lorries in the UK.
But there were two companies we commented on, one selling yoghurts and dairy products, the other selling pasties and pies. How many yoghurts fit into a 40-ton trailer? Allowing for packaging and pallets, we suggested about 30,000 (assuming about 1kg each). And about the same time for the pies, possibly a few more. How many of these products would be sold in one day in a major supermarket? We estimated at least 10 and at most 1000, for both "large" and packages of four. So by the rules of guesstimation, we plumped for 100 per day (geometric mean). With two products, that meant each lorry carried enough for about 150 supermarkets. And with thousands of supermarkets across the country, one could see why it was economical for these companies to haul such large quantities of their products from factory to distribution centre in large trucks.
Next time we use the motorway, we'll be looking out for other named products on the move, and wondering whether the owners have made the decision to run their own fleets for commercial reasons or because it has "just happened".
In the first hour, we completed three hands of five, an indication of how much traffic there is into the south-west of England. But we were also interested in the other labelled food trucks. Once, when I was consulting for a major confectionery company, I remarked that you never saw lorries with their name on the side. I was told that when the company started in the UK, they linked to a local haulage company in the same town, and that haulage company continued to carry all the confectionery; the two companies had grown together. So there are many household names which never appear on the sides of articulated lorries in the UK.
But there were two companies we commented on, one selling yoghurts and dairy products, the other selling pasties and pies. How many yoghurts fit into a 40-ton trailer? Allowing for packaging and pallets, we suggested about 30,000 (assuming about 1kg each). And about the same time for the pies, possibly a few more. How many of these products would be sold in one day in a major supermarket? We estimated at least 10 and at most 1000, for both "large" and packages of four. So by the rules of guesstimation, we plumped for 100 per day (geometric mean). With two products, that meant each lorry carried enough for about 150 supermarkets. And with thousands of supermarkets across the country, one could see why it was economical for these companies to haul such large quantities of their products from factory to distribution centre in large trucks.
Next time we use the motorway, we'll be looking out for other named products on the move, and wondering whether the owners have made the decision to run their own fleets for commercial reasons or because it has "just happened".
Thursday, 9 December 2010
Queues, psychology, and collapsing websites
One of the problems of queues which involve people is to forecast when and at what rate the customers will arrive. Recently, the UK supermarket giant, Tesco, made a spectacular mistake in the run up to the Christmas rush and the holidays. Here's the story:
---------------
The Tesco Big Christmas Exchange
Back in November 2010, Tesco announced it was launching a Big Clubcard Voucher Exchange. Lasting four weeks, it gave collectors of Clubcard points the opportunity to double the value of their vouchers on a large range of non-food items, ranging from wine and computers to Christmas decorations.
A similar scheme was launched earlier in the year. However, Tesco trumpeted the fact that this time the scheme had been revamped, so now customers would be able to exchange their vouchers online.
But it went wrong
The scheme was launched around the time that most customers received their November points statement, early in November. If you wanted to double up your vouchers, the closing date was Sunday 5 December.
Clearly Tesco expected the bulk of interested shoppers to take part once they got their statement through, rather than leave it to the last minute. This was very much a mistake, as news reports and Internet message boards are awash with tales of shoppers facing enormous queues to exchange their vouchers, only to give up and try and do it online. With predictable results, the Tesco website collapsed under the weight of so many users.
------------------
Yes, it was bad understanding of psychology, leading to not enough provision of servers for the customers. There is a great deal of literature about call centres and the behaviour of customers, so someone should have been aware of the likely rush at the end. And, I suspect, there should have been some monitoring of the rate of redemption of the vouchers, which might have given advance warning of the changing rate of redemption. If only 10% of the customers redeemed their points in the first half of the offer, then it might be foreseen that there would be a great demand in the second half.
---------------
The Tesco Big Christmas Exchange
Back in November 2010, Tesco announced it was launching a Big Clubcard Voucher Exchange. Lasting four weeks, it gave collectors of Clubcard points the opportunity to double the value of their vouchers on a large range of non-food items, ranging from wine and computers to Christmas decorations.
A similar scheme was launched earlier in the year. However, Tesco trumpeted the fact that this time the scheme had been revamped, so now customers would be able to exchange their vouchers online.
But it went wrong
The scheme was launched around the time that most customers received their November points statement, early in November. If you wanted to double up your vouchers, the closing date was Sunday 5 December.
Clearly Tesco expected the bulk of interested shoppers to take part once they got their statement through, rather than leave it to the last minute. This was very much a mistake, as news reports and Internet message boards are awash with tales of shoppers facing enormous queues to exchange their vouchers, only to give up and try and do it online. With predictable results, the Tesco website collapsed under the weight of so many users.
------------------
Yes, it was bad understanding of psychology, leading to not enough provision of servers for the customers. There is a great deal of literature about call centres and the behaviour of customers, so someone should have been aware of the likely rush at the end. And, I suspect, there should have been some monitoring of the rate of redemption of the vouchers, which might have given advance warning of the changing rate of redemption. If only 10% of the customers redeemed their points in the first half of the offer, then it might be foreseen that there would be a great demand in the second half.
Tuesday, 14 July 2009
Two sides of the "Diet Problem"
Yesterday I contributed a comment to Laura McLay's blog about Operations Research in the USA. She was considering the way that food manufacturers mark the nutritional content of their products. Here are her comments.
I wrote:
There is a similar debate going on in the UK. Our Food Standards Agency has proposed a “traffic light” system showing that certain ingredients are low, medium or high. Some manufacturers have adopted the FSA system, others have refused to use it. Some supermarkets (and in the UK, the food retailing sector is dominated by a few large supermarket chains) have chosen their own systems.
It doesn’t look as if the FSA has used any OR in their research; I would have thought that OR could have helped answer the question that doesn’t really get tackled “What information will people use, and how will they use it?”.
It is possible to see some of the research reports that led to the FSA recommendations at http://www.food.gov.uk/foodlabelling/signposting/siognpostlabelresearch/alt
I was surprised at one response that said 25% of consumers always read nutritional labels. The question which led to this response was badly phrased and it looks as if the response was badly understood. Just watch the shoppers in your local shop; do 25% of them read every label?
Historians of O.R. reckon that Stigler's diet problem was one of the catalysts of the development of linear programming at the end of the 1940's ane early 1950's. I, like many academics, have used nutrition as a simple example of a medium-sized linear programming problem in my classes. Nutrition is additive, and there are one or two interesting constraints on maxima and minima of nutrients in the human diet. Some of them are straightforward, others are expressed as percentages of other nutrients. Many people (myself included) have used data from McDonald's to see if one can find a minimal cost, "Healthy" diet from that chain. [If you have never encountered this problem, then there are two twists in the modelling. The first is the obvious one that the problem really is an integer programming problem. The second is that sachets of sauce are free and contain nutrients; without constraining the number of sachets that you use in a day, the LP solution uses over 40.] The model has a variety of extensions and lessons for the class, for example, concerning shadow prices. [Apologies to those who do not know what a shadow price is; in this case, I used it as a tool to tell you what the maximum price should be for an item that is not in the diet.]
My former colleague, Alan Munford created an integrated database and optimisation tool for mixing feed for animals, who are less choosy about their diets than humans.(Incidentally, Munford's theorem states that for any random variable X, with mean \mu and variance \sigma^2, then for any value k
Probabilty (abs(X-\mu) \ge k^2\sigma^2) \le minimum of((1/k^2),1) [footnote])
My title was "Two sides of the ...". The second side is the one I alluded to in my comment on Laura's blog. People need information. There is an immense amount that you could list about any item of food. What ought to be put on the packaging of processed food? Those with the commonest allergies need to have simple, clear warnings. That is almost straightforward, though there are numerous unusual allergies whose sufferers need to peruse the whole list of ingredients. So those observations give the essentials: common allergies, list of everything. But what about the extra, general information? As I said, the FSA does not appear to have really though this one through, and there is a case for using some O.R. in answering it.
[footnote] Munford's theorem is a joke. Alan introduced it when he was teaching a class of probability, and proved Chebyshev's theorem, which has the inequality
\le (1/k^2). However all probabilities must be less than 1. A few years after this spoof was introduced, a firstyear student told Alan how excited he was to be taught by someone who had a theorem named after them; this student had been taught by one of our graduates who had swallowed the story that this result carried Alan's name.
I wrote:
There is a similar debate going on in the UK. Our Food Standards Agency has proposed a “traffic light” system showing that certain ingredients are low, medium or high. Some manufacturers have adopted the FSA system, others have refused to use it. Some supermarkets (and in the UK, the food retailing sector is dominated by a few large supermarket chains) have chosen their own systems.
It doesn’t look as if the FSA has used any OR in their research; I would have thought that OR could have helped answer the question that doesn’t really get tackled “What information will people use, and how will they use it?”.
It is possible to see some of the research reports that led to the FSA recommendations at http://www.food.gov.uk/foodlabelling/signposting/siognpostlabelresearch/alt
I was surprised at one response that said 25% of consumers always read nutritional labels. The question which led to this response was badly phrased and it looks as if the response was badly understood. Just watch the shoppers in your local shop; do 25% of them read every label?
Historians of O.R. reckon that Stigler's diet problem was one of the catalysts of the development of linear programming at the end of the 1940's ane early 1950's. I, like many academics, have used nutrition as a simple example of a medium-sized linear programming problem in my classes. Nutrition is additive, and there are one or two interesting constraints on maxima and minima of nutrients in the human diet. Some of them are straightforward, others are expressed as percentages of other nutrients. Many people (myself included) have used data from McDonald's to see if one can find a minimal cost, "Healthy" diet from that chain. [If you have never encountered this problem, then there are two twists in the modelling. The first is the obvious one that the problem really is an integer programming problem. The second is that sachets of sauce are free and contain nutrients; without constraining the number of sachets that you use in a day, the LP solution uses over 40.] The model has a variety of extensions and lessons for the class, for example, concerning shadow prices. [Apologies to those who do not know what a shadow price is; in this case, I used it as a tool to tell you what the maximum price should be for an item that is not in the diet.]
My former colleague, Alan Munford created an integrated database and optimisation tool for mixing feed for animals, who are less choosy about their diets than humans.(Incidentally, Munford's theorem states that for any random variable X, with mean \mu and variance \sigma^2, then for any value k
Probabilty (abs(X-\mu) \ge k^2\sigma^2) \le minimum of((1/k^2),1) [footnote])
My title was "Two sides of the ...". The second side is the one I alluded to in my comment on Laura's blog. People need information. There is an immense amount that you could list about any item of food. What ought to be put on the packaging of processed food? Those with the commonest allergies need to have simple, clear warnings. That is almost straightforward, though there are numerous unusual allergies whose sufferers need to peruse the whole list of ingredients. So those observations give the essentials: common allergies, list of everything. But what about the extra, general information? As I said, the FSA does not appear to have really though this one through, and there is a case for using some O.R. in answering it.
[footnote] Munford's theorem is a joke. Alan introduced it when he was teaching a class of probability, and proved Chebyshev's theorem, which has the inequality
\le (1/k^2). However all probabilities must be less than 1. A few years after this spoof was introduced, a firstyear student told Alan how excited he was to be taught by someone who had a theorem named after them; this student had been taught by one of our graduates who had swallowed the story that this result carried Alan's name.
Friday, 27 March 2009
The coin machine problem
Yesterday I saw inside a new machine and realised that its designers had solved an interesting multicriteria problem.
Many British supermarkets have introduced self-service checkouts; the shopper brings their basket to the machine, scans the items one by one without the need for a cashier, and pays by card or by cash at the end. I use one such supermarket regularly when buying a few items, because it is generally quicker than queueing for a cashier. As I have used it, I have been interested in the algorithm it follows for giving change for cash purchases. The first part of the algorithm is straightforward; if your bill is for P pence, then as soon as you have inserted any sum greater than P, the machine gives change. (So if you want to get rid of small change, then you must put that small change in before the larger coins.) But the second part concerns the coins that are dispensed as change.
British coins have values 1, 2, 5, 10, 20, 50, 100 and 200 (pence). My change has never included coins of value 2, 50 or 200. 9 pence in change is dispensed as four 1s and one 5. 90 pence in change is dispensed as one 10 and four 20s. So when I found staff maintaining one of the machines, I stopped to look (probably being labelled by the CCTV operators as a suspicious character). There were six storage receptacles for coins to be given as change, labelled 1, 5, 10, 20, 100, 100. So there is no way that I could be given a 2, a 50 or a 200.
The designers needed a design that worked with an algorithm. Have a stock of coins to give change in a logical way, and keep that stock inside a small volume. So they eliminated three coins from inclusion. So, objective 1: Be able to give change; objective 2: keep the number of storage bins to a logical minimum. But there was a subtle objective 3: use coins of small volume, to maximise the number of coins in the machine.
2 pence coins are larger in volume than those of value 1, 5, 10 and 20. 50 pence coins are larger than 2 pence. 200 pence (2 pound) coins are very large. So these were the coins to remove from the machine's design.
Now, was this design a multicriteria O.R. problem, or not? I think it was -- even if it has a solution that will not shake the world! But it does make the world a little better.
Many British supermarkets have introduced self-service checkouts; the shopper brings their basket to the machine, scans the items one by one without the need for a cashier, and pays by card or by cash at the end. I use one such supermarket regularly when buying a few items, because it is generally quicker than queueing for a cashier. As I have used it, I have been interested in the algorithm it follows for giving change for cash purchases. The first part of the algorithm is straightforward; if your bill is for P pence, then as soon as you have inserted any sum greater than P, the machine gives change. (So if you want to get rid of small change, then you must put that small change in before the larger coins.) But the second part concerns the coins that are dispensed as change.
British coins have values 1, 2, 5, 10, 20, 50, 100 and 200 (pence). My change has never included coins of value 2, 50 or 200. 9 pence in change is dispensed as four 1s and one 5. 90 pence in change is dispensed as one 10 and four 20s. So when I found staff maintaining one of the machines, I stopped to look (probably being labelled by the CCTV operators as a suspicious character). There were six storage receptacles for coins to be given as change, labelled 1, 5, 10, 20, 100, 100. So there is no way that I could be given a 2, a 50 or a 200.
The designers needed a design that worked with an algorithm. Have a stock of coins to give change in a logical way, and keep that stock inside a small volume. So they eliminated three coins from inclusion. So, objective 1: Be able to give change; objective 2: keep the number of storage bins to a logical minimum. But there was a subtle objective 3: use coins of small volume, to maximise the number of coins in the machine.
2 pence coins are larger in volume than those of value 1, 5, 10 and 20. 50 pence coins are larger than 2 pence. 200 pence (2 pound) coins are very large. So these were the coins to remove from the machine's design.
Now, was this design a multicriteria O.R. problem, or not? I think it was -- even if it has a solution that will not shake the world! But it does make the world a little better.
Tuesday, 27 May 2008
Introducing myself and OR
This is the first item in the Blog of the IAOR editor. So it is a place to do some introductions. I am David Smith and one of my responsibilities is to edit IAOR, the International Abstracts in Operations Research. As I shall often refer to OR, I'd better explain. OR is the abbreviation for Operations Research or Operational Research, depending on where in the world you live. There are many places which define OR, so I will not waste space describing the subject in detail, but simply give one illustration.
From time to time, people ask me what I do.
First answer: "I work at the university".
Some people change the subject; others ask: "What subject?"
Second answer: "I teach a branch of mathematics."
More people change the subject, or admit that they did not get on with mathematics; however, some ask a little more.
So I explain that OR is not really a branch of mathematics, but a subject in its own right, which uses mathematics and other ideas to answer questions for business and commerce, either "What's best?" or "What happens if ...?" And my standard, simple illustration is the local supermarket, and the number of cashiers on duty. The best number is somewhere between too small and too many; too few, and the queues get big, and the customers start to go to another store; too many, and there are no queues, but the cashiers are not working fully. So there must be a "Right number" -- the problem is mathematical. But the number depends on the time of day, day of the week, month of the year. So you need to forecast the number of customers who will shop on different days at different times. More mathematics. And you need to devise a shift system for the staff of the store so that the full-time and part-time employees have regular work patterns. More mathematics (or OR!) So what started as a simple question, "How many?", has become a much larger problem for the company.
Having explained that, my audience starts to realise that OR is useful in their world, and I can recount other applications that often surprise and fascinate them.
I meant to introduce myself, but it has turned into an introduction to explaining OR to my dinner guests.
From time to time, people ask me what I do.
First answer: "I work at the university".
Some people change the subject; others ask: "What subject?"
Second answer: "I teach a branch of mathematics."
More people change the subject, or admit that they did not get on with mathematics; however, some ask a little more.
So I explain that OR is not really a branch of mathematics, but a subject in its own right, which uses mathematics and other ideas to answer questions for business and commerce, either "What's best?" or "What happens if ...?" And my standard, simple illustration is the local supermarket, and the number of cashiers on duty. The best number is somewhere between too small and too many; too few, and the queues get big, and the customers start to go to another store; too many, and there are no queues, but the cashiers are not working fully. So there must be a "Right number" -- the problem is mathematical. But the number depends on the time of day, day of the week, month of the year. So you need to forecast the number of customers who will shop on different days at different times. More mathematics. And you need to devise a shift system for the staff of the store so that the full-time and part-time employees have regular work patterns. More mathematics (or OR!) So what started as a simple question, "How many?", has become a much larger problem for the company.
Having explained that, my audience starts to realise that OR is useful in their world, and I can recount other applications that often surprise and fascinate them.
I meant to introduce myself, but it has turned into an introduction to explaining OR to my dinner guests.
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