Let’s be specific and ask ourselves why a Retail company (for example) fails in what would seem such a simple task of selling products to willing buyers.
Firstly, as a company grows quickly the key to success is to always be stocked with everything, everywhere. The result: too much of everything is stored everywhere at considerable cost.
Secondly, as profits are eroded and growth slows down it becomes imperative not to have overstocking anywhere, and so stock limits are imposed across the board using guesswork. Sales are lost when these guesses are wrong.
Thirdly, with no way of predicting different sales figures in different stores, some stores sell out of certain items whilst others stay overstocked.
Fourthly, in some areas stocks are ‘optimised’ by individual managers talking over the phone, but no-one ever knows whether the increased sales gained are worth the cost of communications, wasted time, stock transportation (non-scheduled) etc.
Now of course this rather simple problem is actually caused by, amongst other things, the poor planning of IT deployment and data management. In the example there is no detailed understanding of different sales volumes by product by outlet, let alone how these sales are affected by weather or even simply the season. Sales data is not available at the ‘per item’ basis and is never collated to show sales by outlet. Purchase data is held in a separate database and never compared to sales data as an ongoing process, and payment data again stands alone. Product information is held in different data stores by category, and all predictive reporting is outsourced to a marketing bureau. Sound typical? Yes, that’s the way we manage information, this priceless asset, today!