Measuring = reducing uncertainty

A lot of what we do in Monitoring and Evaluation is related to measuring. And that’s the problem: Many of us think of measuring as something precise. But that’s not necessarily the case in M&E. What we need to be is roughly right. Those of us in Monitoring and Evaluation should carefully consider this advice from John Maynard Keynes, a British economist.

“It is better to be roughly right than precisely wrong.”

Measurements are not always exact – but can be more or less precise. But after any measurement, we know more after measuring than we did before. Even an imprecise measurement will reduce our uncertainty to some degree. And depending on what we need, such an imprecise measure may just be good enough for a specific purpose.

For example: If you want to get yourselves new shoes, it is sufficient to know your shoe size. You don’t need to precisely measure your feet.

In Monitoring and Evaluation, this is how we need to look at measuring: as a set of observations that reduce uncertainty where the result is expressed as a number. In most cases in Monitoring and Evaluation, we are not interested in scientifically precise measurement. Instead, we aim for information that is sufficiently accurate to tell us what is going on – and to give us an indication of how it changes over time.

Bertram Russel, the British mathematician and philosopher, has formulated that well (apart from the gender insensitive ‘man’):

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Measuring = reducing uncertainty

by Thomas Winderl time to read: 1 min