I do love a model with curves
We are surrounded by data and lots of it, so the potential for conflict and confusion is growing. It is big data and quick data. We really are inundated – it is flowing freely just like a river that has burst its banks. Our decision-making ability is therefore being tested with all this data. It is fraught with risk at the best of times, but hopefully a calculated risk rather than being a gamble. Nevertheless, it could probably always tell us what we need to know.
“If you torture the data long enough, it will confess.” Ronald Coase (Nobel Laureate)
Such decisions may lead to a short-term pain for a long term gain. Examples of short-term pains in media could be a loss of audience after a change in programme presenter or a publication relaunch. We saw it when Virgin Radio changed to Absolute Radio in 2008 and audiences dipped after the re-branding before increasing steadily thereafter. Although we are perhaps yet to see it with ITV’s Daybreak!
It is a phenomenon seen throughout business and especially in finance. In economics they call this the J-curve and the all important variable here is the ‘timeframe of judgement’. When do we judge that a decision has been successful? It may be that some bespoke research is conducted or it may be a case of waiting for the next set of industry currency data, such as NRS, BARB or RAJAR.
In this age of big data and vey quick, continuous streams of data, I firmly believe that the timeframe of judgement is artificially shortening. Companies can get quick data to make quick decisions; but quick data does not necessarily make good data and therefore good decisions. It really is ‘more haste less speed’. The subject of big data will be debated at the MRG Conference in Monte Carlo next month. Ah – that famous old Grand Prix circuit has got me thinking about curves again…