(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.
