We live in a culture where so much business activity has a numeric target attached.
Targets are everywhere today. Not just in business, they have even spread into the public sector services where targets for appointments in the NHS for example are seen as measures of how well health services are being delivered – not do patients get better. The thing is people who have to achieve these targets often invest more effort and imagination in finding ways around the target than in focussing on the work task itself. A few decades ago companies seemed to be driven by doing what they did, well. Whether it was designing better products or providing ‘old fashioned’ superior service it was more guided by a shared work ethic than a numeric goal. Then the accountants moved up from the back office to board and CEO level and brought with them the language they understood best – reducing everything to a set of numbers. It was a compelling idea which politicians adopted to mange public sector services as well.
Think about banks. At one time banking was a profession that carefully managed funds and ensured loans were made to people able to repay them and with collateral that could be called in the event of a default. Then the terminology changed to talk about retail banking and selling financial products. They developed a sales target culture and hired sales people rather than bankers. Meanwhile the investment arms developed a casino culture. Targets were met or exceeded and motivated by generous bonuses. And look what happened. Even my milk bill left by the doorstep deliveryman starts, “ Please can you help me reach my targets by making payment this week.” Yes there are targets everywhere and marketing has not escaped either. My big question is, do they work?
“I know that half of my advertising dollars are wasted … I just don’t know which half.” This quote is still occasionally rolled out. Whether half is wasted is not the point. What is worth thinking about is that successful marketing campaigns use several different communications methods, so when enquirers are asked, “where did you hear about us?” quite often they don’t actually know. But just the same systems demand that they should know, so they offer an answer anyway that contributes to statistics. Instead of looking at the net result, such as “did the company make a profit?” individual elements of campaigns are scrutinized and costs per lead determined. Another quite different example is in justifying new product development by producing return on investment analysis. Anything less than 18% was a non-starter in one large organization I worked for. And guess what - every application reached this magic figure because sales targets were revised upwards until the numbers worked. Then there was the five year plan which took year 1 as the current budget year because it couldn’t be different. But partly because it was written last year it was probably already off target, but years 2 through 5 merrily forecast as rising year on year starting from that already off target benchmark. Nobody ever forecast a downturn. Huge effort went into developing these plans including competitor market shares to 2 decimal places – an implied precision based completely on guesses and a figure the competitors themselves would not recognise. Then all this questionable data was used to produce targets. Experience suggests that the data itself, assumptions and forecasts upon which targets are set lack the credibility that a numeric target implies. What then of the data used to measure achieving targets?
Thanks to web statistics Internet activities give rise to a new mass of data. Once more the implication is that this is precise and accurate. It is data collected on our behalf and provided free. Although companies can set rules, they do not collect or evaluate how the data is collected. Another example is email delivery and open rates. Sometimes non-delivery messages are received when in fact they did arrive, some seen in a viewing pane without registering as open. The reality is that marketing targets are being set based on dubious data and measured by data nobody in the company actually controls. Targets are useful but they shouldn’t become the objectives themselves.