The opening line of Spike Milligan’s humorous novel Puckoon said that the town was located several and a half metric miles north east of Sligo. Milligan knew that such spurious accuracy would draw a whimsical smile from the reader who appreciates the absurdity of registering the half mile in a measurement where one did not know the total mileage.
Yet many organisations replicate this absurdity every day in their management reports. They are not deliberately setting out to deceive or to be humorous. However, it derives from a belief that the reality of a situation is best seen in numbers and the more the better. People will even make up numbers to add weight to their arguments as in “We have a better than 50-50 chance…” or “I am 90% certain that we will win the case”.
There is a danger that measures are chosen based on availability rather than significance.
The classic example of spurious accuracy is the story of the tour guide who described a castle as being 1006 years old because he was told that it was 1000 years old when he started his job six years earlier.
Again, the example is given to show a point in a humorous way. It is difficult not to be amused at the naivety of the guide. However, what happens when that approach occurs in so-called well managed organisations. Take for example the banks prior to the collapse. Their financial reports were capable of measuring accounts to the nearest thousand but the errors in their valuations ran into the hundreds of millions.
There are three main problems with spurious accuracy. Firstly, it is misleading in the sense that it suggests a level of accuracy and control which does not exist. Employment costs are notoriously difficult to measure. A recent change in accounting standards requires that accruals should be made for annual leave outstanding at the end of a year. The same calculation should be made in respect of the accumulated redundancy entitlements for existing employees.
Data should be presented at the highest level appropriate to the level of management handling it to avoid senior management being bogged down in detail and different levels of management handling the same issues.
Secondly, spurious levels of accuracy draw the eye away from the real numbers. For instance, tracking the cost of medicines against budget has great face validity. For this reason, it is measured and reported on monthly. However, it is not clear that that it is the best or the most useful measure. Would it not be better to measure efficacy, wastage or obsolescence unless your priority was only to focus on budgetary performance. There is a danger that measures are chosen based on availability rather than significance.
The third problem is the most serious and it has to do with management focus. It is best summed up in the maxim of being unable to see the wood for the trees. Take for example a report to the Board containing a sum for expenditure such as €1,713,346 (compared to €1,691,764 in the previous year). It is not immediately obvious whether or not there is a problem. The Board member has to do a number of calculations, any of which could result in a miscalculation, to derive meaning from that data.
In fact, there is a possibility that the Board member is deliberately being given too much data so that it is impossible for him or her to easily decipher what is going on. As a general rule, from a management pint of view, accuracy levels that go beyond four digits involve a level of precision which they are incapable of addressing. Given that a cup of rice contains up to 10,000 grains, levels of accuracy in excess of four digits is equivalent to an extra grain of rice in a cup and is meaningless.
Management controls, whether headcount, budget, infection rates etc. should be based on four criteria. Relevance: whether or not it is necessary for the performance of duties. Accuracy: the data should only be presented at the level at which there can be confidence in its accuracy. Relativity: absolute numbers are fairly meaningless unless compared to appropriate benchmarks such as annual targets, last year’s data, other departments etc. Significance: Data should be presented at the highest level appropriate to the level of management handling it to avoid senior management being bogged down in detail and different levels of management handling the same issues.