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A Prussian general once said "no plan ever survived contact with the enemy", some people seem to translate that into "it is pointless to plan" (or to be even more aggressive they talk about "paralysis by analysis"). I was reminded about this anti-planning bias recently when I listened to a report about an Australian couple attempting to organise a wedding⊗, they were to be married in Melbourne but currently live in London and they wanted to send out enough invitations to friends in Australia, the UK, the US and round the world to get between 100 and 110 people accept (to match the venue they had already booked). Their approach was analytical, they classified potential invitees according to their physical distance and estimated firmness of friendship, in order to guess the probability of accepting the invitation. In the end they mailed out 139 invitations and had 105 people turn up at the wedding. You might think this demonstrates a suspiciously accurate model of their friend's preferences, however as the presenter of the piece gleefully explained only 97 of the original guests showed up, the others were "new partners we didn't know about and people who our parents accidently invited". The presenter concludes "if you can't be right, then be lucky" which is a good motto to live by, but I draw a slightly different conclusion. My suspicion is that their error estimating the chances that guests would turn up turned out to be unimportant, the fact that they ended up with exactly the result they wanted shows that their analysis was useful (even though it was actually wrong). I suspect that as replies started to come back they quickly identified the mistake, knew well in advance that their numbers were going to be low and so could be relaxed about allowing additional "accidental" guests.
My experience has been that when you are dealing with other people's behaviour the first guess is almost always wrong (just as the elder von Moltke suggested). But, time spent planning is rarely wasted effort: it gives you some insight into the "bigger picture"; it alerts you to your mistakes while there is still time to address them; and it lets you test scenarios so when something fails you are familiar with the options that are available. Of course those with no experience have trouble planning, suppose for example that you are a geologist with no awareness of computer science theory suddenly put in charge of your company's data handling group, planning would be impossible. In such a situation surely anyone's first task would be to bring in expertise and start learning, but I would say their second task should be to start analysing.
There is such a thing as too much analysis, personally I don't think I've ever seen that occur when oil company management are discussing data systems. Less than optimal decisions reached because some manager doesn't understand even the most fundamental aspects of data handling, and is not prepared to pay for someone that does, that I've seen lots of times.
⊗ Reported for example at http://www.bbc.co.uk/news/magazine-25980076
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