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 Data dump

 

Techniques > Resisting persuasion > Data dump

Method | Example | Discussion | See also

 

Method

Cover them in information, so much so that they’ll spend forever trying to wade through this endless detail. It helps to give them good quality information, but if in doubt, you can put low-grade rubbish at the bottom to fill out the pile.

If they ask you how you are, tell them, in great detail.

If they ask you what you want, give them a pile of differing and conflicting needs.

If they ask you how things happen, describe the process in great detail.

Example

Well, as you ask, Jennifer wants something to go and visit her mother, who lives a long way out in the countryside and up some rutted tracks so I guess something rather sturdy is needed, but on the other hand I want something to look good about town -- no mud there, eh? -- but I also need to go between cities so cruising comfortably is important, yet on the weekend we both like to get sporty and zip around the place.

You ask how we buy here? Well that is a good question. First, someone who wants to get something has to fill in form P122 and take it down to Purchasing. Jennifer Wagston there is very good you know at helping you fill it in as they ask for all kinds of information -- goodness knows why --  then when you've got the initial signature you have to go to your manager or even higher ...

Discussion

People have bounded rationality and can only process so much information at once, after which they get confused.

By using the 'data dump', you can appear very collaborative whilst severely muddying their waters by giving them more information than they can easily process.

The data dump can also be used to hide the needle in the haystack, giving them the information that they do need, but surrounding it with lots of other extraneous data that cloaks the real information. This also allows you to truthfully tell others that you have given the person the requisite information, whilst minimizing the chance that they will find it.

Note the difference between data and information: data is raw stuff that needs interpretation. Information informs intelligently, providing useful meaning.

See also

Confusion

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