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7 September 2010

Machiavelli and the birthday question

By Andrew Clifford

Management information systems provide a critical management function despite being deeply flawed.

There is a question that everyone involved in the provision of management information systems (MIS) ought to be able to answer.

The question is "How many people do there need to be in a room before it is more likely than not that two of them have the same birthday?"

Why is this question so important? The question is about probability, and probability is fundamental to understanding variability and statistics. If you do not understand probability, how do you know that the figures from your MIS are anything more than random chance?

Most people answer "about 180" to the question, but the answer is actually 23 (see calculation spreadsheet). If you did not know that, you are not really qualified to be in the MIS business. I did not know the answer the first time I saw it.

It is not just our understanding of statistics that is poor. We have inadequate data definitions. We make basic reasoning mistakes, such as selecting data that supports our position, rather than looking for data that could disprove it. There are all kinds of systematic bias in the data we collect. From what I have seen, very little of commercial MIS would stand up to rigorous scrutiny.

How should we do to respond to this dark side of MIS?

The best answer is to employ statisticians, to define and calculate data better, and distinguish real information from artefacts and noise.

Sadly, few MIS projects stretch to employing professional statisticians. We therefore need to tread carefully when we present MIS solutions. We need to:

  • Encourage users to be critical of the data. We need to train them to be especially critical of anything that supports their position. Putting poor data into a posh system with pretty graphs does not make the data better.
  • Do not lose additional narrative. So often management look at the pretty graphs and headline figures. However, any complicated analysis will have all sorts of caveats and definitions. Make sure that figures are accompanied by explanation.
  • Check definitions and derivations. If you do not understand the meaning of the base data, or how the calculations work, chances are nobody else does and any outputs are pretty much worthless.
  • Do not over-centralise. Once MIS is centralised, the context and narrative get lost, and we pay too much attention to over-simplified figures. MIS is not just there to help the centre judge the rest, it is there to help the rest do their work too.

Most importantly, we have to recognise that the purpose of MIS is to build certainty in order to define, justify and motivate management action. Even though some MIS is little more than ritual divination, it still helps cut through management indecision and set a direction.

We should recognise the Machiavellian nature of MIS. The true purpose of MIS is to build certainty of action, not necessarily to provide good data.

Next: 9 to 5 is dead, long live 9 to 5


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