A lifetime forecasting, and never getting it right

Dominic is the process man in the company. He’s a pillar of the organization. He is accurate, precise. Well dressed. On his spreadsheets you can easily find the column “Workflow Generators”. He means the customers. Dominic is also responsible for forecasting, and has been for as long as anyone can remember. Never once have we gotten the products we needed to sell.

You would think that Cloud Management —that’s Cloud, with a big “C”. Nothing to do with the internet, it’s just the level of management that lives in the clouds— would have taken severe steps long time ago. Well, no. How come? The short answer is that Dominic has systematically proven, beyond any reasonable doubt, that his forecast being wrong is everyone else’s fault. In fact, that both the factories upstream and, especially, the sales teams downstream are engaged in a sort of sick conspiracy to feed him bullshit data. Marketing, in the meantime, draws nice pictures.

It gets more complicated: Dominic does receive poor numbers. We spent weeks convincing people to order what was available while they were getting what they needed from someone else, so now we just don’t know what’s next. Customers complain. Posh-chic customers with bosses who also live high above the ozone layer complain directly to Cloud Management and then every other customer complains twice as much to everyone else. Factories begin taking matters into their own hands; they cherish an elusive concept called “efficiency”, by which they will get any investment approved in order to better produce what they are already best at producing. Digital speaks up and suggests to let AI do forecasting. Nobody is sure why we should pay seven figures to ask Siri or Alexa what we’ve been asking Dominic all this time, but he smiles, satisfied that next year he’ll have a new victim to blame. Marketing is almost done with the pictures.

Is there light at the end of this tunnel? Maybe, with an innovative approach. Digital technology now allows for strategies that were simply unrealistic not long ago. Forecasting the future is inevitably going to remain a gamble, but we can pre-cast it. By creating a platform where end users can easily let us know how and how much they use the products they already bought, we can make sure to deliver them the ones they are about to need. Might this be something for you? What would it require?

Let’s check it together.