SIGNIFICANT STATISTICS

Apparently, the average adult produces one pint of flatulence a day.  Why they have to produce it all in one go when crushed up against me on the Piccadilly Line is something the boffins have yet to come up with an answer to.  

And anyway, how on earth did they arrive at this statistic in the first place?  I am frequently accosted on the street by researchers asking what I think about the packaging of chocolate bars, CDs or Charles Kennedy.  If instead of making my excuses and leaving I allowed the interview to run its course, maybe somewhere towards the tail end they would produce a measuring jug and a jar of pickled eggs, their voice would drop conspiratorially and whisper “Could I ask you to do something for me….?”

Here’s another one:  I read in a magazine that if you collected all the leaves that fall in the British Isles in one autumn and filled railway carriages with them, you’d get a train long enough to stretch from here to India. Presumably they arrived at this statistic through complex computer modelling (using Microsoft Train Simulator perhaps) since I reckon I’d have noticed on the News had they really done it.  But why not try it for yourself?  It’s more satisfying than grafittiing the carriages.  Maybe the commuters of Kent could try it next autumn as a form of nemesis for their rail operator’s inability to deal with ‘leaves on the line’.

It’s interesting that when something is presented as statistically valid we inevitably treat it as significant and portentous, even when it’s either blindingly obvious or highly spurious.  Organisations in particular love objective scientific verification.  The runaway success of Emotional Intelligence as a concept is a wonderful example of this.  In 1995 Daniel Goleman, a scholarly and respected behavioural scientist, published a book in which he demonstrated, logically and objectively, that people who can empathise and who can work positively with feelings are at an advantage.  (Der! Had you been wondering when someone might notice that?).  Suddenly, organisations fell over themselves to help people develop their personal warmth.  If you can measure it objectively, then it must be worth spending money on.

Ah yes, objective measurement.  When it comes to training and development, this heuristic battle between head and heart really hots up.  Organisations typically – and with justification – expect training and development activities to deliver an objective, measurable benefit, and would like that to be quantified.  This is not impossible to do; but when you explain to the organisation that it would involve isolating those behaviours which the programme is designed to improve, then conducting detailed observations to establish the extent to which participants are actually demonstrating them – and give them a fee quote for what that would cost – they suddenly decide that an end-of-workshop ‘happy sheet’ will do the job nicely.  

Because objectivity doesn’t come cheap, especially where human beings are involved.  One global consulting firm spent several years and an awful lot of money developing a tool which would quantify in financial terms the value of HR to the business.  Given that it quietly passed away unnoticed, I imagine they found they’d met their match.  But when you consider that for many participants, the true value of training lies not in developing oneself (which after all involves quite a lot of effort) but in getting away from the office and enjoying a bit of peace and quiet, then I suppose a measure of how good they feel at the end of the workshop is the best way of establishing whether it delivered on that key objective.

But even true statistical measurement is, as we are all aware, not immune to a bit of massaging from a self-interest point of view.  The front page of The Times a week or so ago trumpeted that over two-thirds of the high profile doctors who publicly backed Labour in 1997 would not do so now.  Quite impressive – as long as you didn’t read the article and discover that the statistic was imputed from the proportion who said they definitely would still support Labour. The remaining two thirds (of quite a small sample) included several doctors who weren’t actually there when the paper rang them, and two who are dead (although, technically, I suppose we can take it they won’t be voting Labour).

When it comes to producing training stats, with a little imagination you can perform a similar illusion. I’ll leave the final word to a T&D manager, who sidled up to me during a workshop recently and said: “We’re hiring an independent consultancy to do an objective evaluation of this programme and they want to interview a few of your participants at random – can you volunteer a few that you know will say good things about it?”

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