Remember the classic TV game show ‘Play Your Cards Right’? (Showing my age now). If not, then the basic premise was to predict whether each card in a row was higher or lower than the previous one. If the contestant successfully guessed correctly all the way to the end of the row they won a toaster or a speedboat, or whatever. This is the sort of thing you’d be faced with:
Go on, have a guess at what comes next – Higher or lower?
Lower! Easy isn’t it?
And one more…
Oh look – it’s lower again! Who’d have thought? Bet you’d have guessed ‘higher’ (if you couldn’t already see what was coming).
Anyway, the reason for the card game is because I’ve used this sort of thing to kick off a couple of conferences I’ve spoken at recently. It’s a good laugh, but I’ve never seen anyone predict all the cards correctly in sequence. And why is this?
Well, the data pertaining to any process or system fall within a predictable range determined by its operating conditions. This range reflects the capability of that process or system. In the case of the cards, the range is between the Ace and the King (assuming the Ace is ‘low’). Every data value that falls in this range is therefore normal.
So… if you are looking at police performance data for detected crimes, public satisfaction rates or response times, unless a special cause (i.e. an unusual event, outside of the normal operating conditions of the process) occurs, the data will continue to populate your performance pages within the same range. A ‘two’ is as normal as a ‘nine’. Therefore, it is pointless getting worked up about the fluctuations that occur within this range. Furthermore, it is impossible to reliably predict whether the next ‘card’ will be higher or lower than the previous one. By relying on this method to judge performance, or making operational decisions based on whether the last data point was ‘high’ or ‘low’, we stray once more into the misleading world of the binary comparison.
Save yourself the pain of knee-jerking to that previous ‘card’, by understanding your performance data in context. If you want to positively affect the range within which the data fall (e.g. to detect more crime or get to incidents faster), then it is management’s responsibility to act on the system. Don’t just issue an edict that ‘twos’ and ‘threes’ are unacceptably low – take them out of the deck. Likewise, simply setting a numerical target outside of the system’s capability (e.g. demanding to see a Fifteen of Diamonds when you turn the next card) is pointless. Targets do not enhance the actual capability of the system, and are also likely to initiate dysfunctional behaviour, such as gaming.
Look – I had to cheat to meet the target! (Although only an expert could tell this card is a fake, I know).
Finally, a quote frequently attributed to Albert Einstein is:
“The definition of insanity is to do the same thing over and over and expect different results”.
(It is difficult to be absolutely certain that Einstein definitely said this – as Abraham Lincoln warned, “The source of many quotations found on the internet cannot be verified”).
In any case, whoever said it had a point. Playing guessing games with playing cards is not a viable method for judging performance or initiating operational activity – and it won’t suddenly start producing different results, regardless of how many times it is repeated.