Most tools have too much complexity that planners give up on using them or the tools have given up on decent, time-tested models and play big brother black box approach so there is only one forecast available. There is no intuition or explanation to this forecast produced by the system.

The third angle to it - tools that have some decent algorithms suffer poor implementation by integrators who do not understand the difference between mean and median. At Valtitude, we have been rescuing SAP IBP implementations over the last few years. IBP has been continuously adding more models and functionality but jettisoned some good functionality that was found in APO.

Regardless, the consultants from the big integrators use their primary weapon - the "Best Fit" model that runs a hodge podge and ends up picking garbage as the final result. Also, the planners can do better using the crystal ball to get a better forecast as suggested by Philip Auinger in LinkedIn post.

At the end of the day, a forecast is about an uncertain future - tools that claim to give you a decent and most probable forecast will do better than tools or experts that claim to give you the most accurate forecast or the most accurate distribution of the future. They will end up costing you a whole lot of money and time with very little tangible results.

There are few good exceptions and one of them is ForecastPro - we have used this software for many of our small clients with great results. This set of software platforms do not make those lofty claims and practice humility in what they promise to the demand planner.

Finally a demand plan is driven by human judgement. All of Economics is about human behavior. Anyone that tells you this is a natural phenomenon that is perfectly forecastable is really conning you - you need to find out when the magician put the rabbit into his hat!!