Further to an Informatica blog by http://blogs.informatica.com/perspectives/2014/10/29/if-data-projects-weather-why-not-corporate-revenue/#fbid=syxgmrw49EV drawing parallels between weather forecasting & the business forecast by corporates – my sequel suggests it’s not just about the data:-
Forecasters of weather crunch data in a model that is constantly refined both in terms of the quality, volume & accuracy of the data used but more importantly they make significant efforts to refine & improve the granularity of the model itself.
That can’t be said of (m)any corporates trying to forecast revenue – Excel has it’s limitations!
Predicting weather is based largely on measurable scientific & logical parameters, the same can’t be said about forecasting revenue, the most influential ‘weighting factors’ are biased much more towards the emotional – such as “loyalty”, “preferred supplier” & “budget allocation” which depend on people with allegencies, egos & political constraints that do not fit into any spreadsheet and remember this equation has two sides: internal & external so it’s doubly volatile & exponentially unstable. As a result there is usually no connection between the folks that do the revenue generation & those that count the results, this mismatch correlates directly to a flawed model – it’s a very rare animal that can combine any permutation of hard skills (technology, accounting, product development) with soft skills (HR, sales, management) so no doubt this syndrome is only set to proliferate.
There are clearly some vague analogies with the weather but the comparison ends at a point that companies should easily recognise but fail to modify their approach – that is: each time they get their forecast wrong they end up firing a whole lot of valuable FTE’s (are they considered as real people?) OR panic hire a bunch of rookies ready to ride the next chunder from development (aka sows’ ear turned into silk purse for FYXX kick-off) or the next wave of IT rhetoric around Data (white) Elephants or whatever – they do not analyse where mistakes were made, assumptions need to be narrowed & the model needs to have critical components added.
If they did, they would find that most such errors emanate from the soft squishy bits loosely called management that dictate the flawed guidelines & inadequate spreadsheets that occupy their introverted daily lives with a focus on margin & utilisation rather than more relevant “feelgood” or “creativity” factors. If they would just focus on ‘generation’ rather than ‘inspection’ the results would take care of themselves then who would care about the forecast only that it’s going up!
Given good leadership that is firmly in touch with what the company is all about at it’s customer facing sharp end, most of these ailments would give way to innovation, expansion & a healthy self-generating work ethos.
In summary, I’ll wager that every listed company will “forecast less business more accurately” towards the end of each & every quarter until they go broke profitably…it doesn’t take a rocket scientist to work out what they should have done instead given the right tools.
Peter
A not at all cynical businessman having worked for the likes of Steve Jobs & witnessed what it takes to do good things
"Evolutionary MDM" 