The importance of experience

Three lessons were drummed into us as students of O.R., and I have tried to pass them on to my students.

(1) do not analyse numerical data by machine before you have looked at that data by hand; the analyst needs to have a "feel" for the numbers.
(2) do not assume that the decision-maker who is identified for you by the management is actually the decision-maker; somebody on the spot may actually take decisions which the management do not know about.
(3) observe as much of the system as possible, first hand. Walk the line!

On our trip last week to South Wales, the importance of number (3) became clear. But I doubt if the organisation actually has an O.R. team, but they needed O.R. advice.

We went out to an inn for our evening meal. Like most inns serving food, there was one queue for ordering food, and another for drinks. Food orders were passed to the kitchens and waiting staff, and drinks, of course, were served at once. However, on Wednesday evenings, it was Curry Night. If you ordered a curry at the food counter, then you could have a drink included in the price. This meant that the young lady at the food counter had to leave her place and collect the drink that you had ordered from her. Hence she had to do an increased workload on an evening when there was increased demand at the food queue. Customers for food had long queues, while there were no queues for drinks. Service time could be speeded up in various ways ... passing a token to the drinks bar ... having an extra person to serve at the food queue, all or some of the time. It could also be reduced by having a printed list of what "free drinks" were available, rather than for the staff to have to recite them. All of this could have been noticed if someone with authority had actually observed the queue process, rather than assume that the normal system could cope on the Curry Night.

Result: two very nice curries, reasonable drinks, but lost profits because we didn't go back to the long queue for a sweet.

Marketing Crisps and Operational Research

Having mentioned crisps, my mind wandered to a recent news story about marketing with an O.R. twist. The UK crisp brand Walkers called on consumers to come up with new ideas for flavours of crisps, with the slogan "Do us a flavour". Six were identified as potentially usable: chilli and chocolate, onion bhaji, Cajun squirrel, fish and chips, crispy duck and hoi sin, and builder's breakfast. There is a public vote to determine the winning flavour which will then remain on sale.

The competition has generated a considerable amount of public interest. Walkers had originally expected about 250,000 entries into the competition, however, it actually received about 1.2m flavour suggestions.

And there is the O.R. twist. Who made the forecast? Has anyone stood up, put their hand on their heart, and admitted "Our forecast model was wrong. We were 80% below."? In the circumstances, I suspect that the forecast was more of a guess than a mathematical model, and the success, both in consumer response and free publicity, will mean that the forecasters will live to forecast for another campaign.

Marketing and Operational Research

My impressions are that in the United Kingdom, surprisingly few O.R. scientists have published papers relating to marketing. The U.S. O.R. society, INFORMS, publishes a journal devoted to quantitative marketing, but there is no comparable interest in the U.K.. Over the years, I have had one or two encounters with projects relating to some aspect of marketing, but have never got a sense that marketing departments use O.R. advice very much. Some of the projects have started with the adage "Half the money spent on advertising is wasted -- but nobody knows which half; if you knew which half, you would make a fortune."

In my postgraduate course we came across a problem which I have never seen written up, perhaps because the problem was trying to build a model to explain some anomalous data and the parameters would have been a commercial secret. So here, nearly forty years after it happened, is a summary.

For many years, the dominant company in the U.K. market for potato crisps was "Smith's". They held over half the market. Then a new brand was launched, called Golden Wonder. Over the subsequent few months, surveys were carried out to try to measure brand awareness. The problem was that the percentage answering the question "What was the brand of crisps that you last bought?" with "GW" was far lower than the percentage market share for GW. Why?

The answer was inertia and lack of awareness of the brand. Purchasers would ask for a "packet of crisps" and since most shops (and especially bars) only stocked one brand of an item that occupied a lot of storage space, the purchasers accepted what they were given and did not associate their purchase with a brand -- and Smith's had been the leading brand for so long that the association was "Smithscrisps" as one word.

So, as students, we were asked to re-work what the consultants had done, and build a model to link the growth over time of the sales and the growth over time of the awareness. It taught us about building and fitting nonlinear models, and a little about the vagaries of our fellow humans. But it could never have been written up as a paper!