Deep modeling and dynamic constraints

The results of any planning engine are only as good as how the system models the environment. Almost all current S&OP solutions use spreadsheet logic for capacity representation with a bucket! This inaccuracy leads to an unnecessary and painstaking adjustment of plans by the planners. It also leads to a fallacy of fixed lead-times. But the latter heavily depend on the product mix.

Furthermore, the product mix and quantity define bottlenecks. Sadly S&OP solutions make a pre-determined assumption regarding the bottleneck resources! All of this leads unreliable commit dates, and erroneous financial projections.

Plans and execution of the plan are a continuum. By separating S&OP from S&OE, one creates disjointed models that do not represent the same assumptions. This means not having a true supply chain digital twin resulting in two incoherent processes.

We believe S&OP and S&OE are a continuum. One evolves from the other by simply adding to the granularity and frequency of the data and vice versa.


Digital blueprint to digitalization of your supply chain

View video

Get in touch

Need more information?