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.
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