MRP may seem simple enough in its logic and it is easy to follow for one or two items. However, imagine doing that math for 1000's of finished good SKUs each having a three or four level BOM with numerous components and sub-assemblies. Then consider what happens if a planned receipt is early or late? What if actual demand is different from planned demand? And, remember the importance of inventory accuracy . . . What if we only had 39 Leg Assemblies in stock instead of the 40 we thought we had? This is why MRP is performed and managed by computers and typically cycles or refreshes itself once a week or even once a day. Everything is dynamic and the actions that need to be taken can and often will change from the original planning iteration.

These frequent changes however can also create havoc in the factories and with the supplier base. Too much change, especially in the short term creates what is called system nervousness, which, if left unchecked, can drive too many messages calling for production supervisors and buyers alike to make this, stop that, buy those, cancel these, and expedite some more of them. This is where the operations team must intercede, applying sensibility over the unmanaged output of the computer driven MRP logic. Much like time fences are used to dampen the near term changes allowed in the MPS process, they are also used with MRP to provide some stability in the short-term. By placing a frozen zone on some portion of the schedule, no changes are allowed which in turn negates the impact of short-term demand and supply variation.

There is also a tool called pegging, which is a method for tracing items from component to parent back through the BOM structure. With this capability, a planner can determine where the requirement for something is originating from and then can make informed decisions regarding the true necessity for that change. For example, if a series of actions are required as a result of falling below safety stock, the planner may accept the risk of having less safety stock inventory in lieu of allowing the changes to disrupt the factory and/or supplier schedules.

Lastly, MRP has limitations, as it is a planning system as opposed to a scheduling system. MRP assumes unlimited capacity that we know is not practical. This infinite scheduling approach with MRP must be further bound through the development of finite schedules, which limit the amount of work to be scheduled based on a finite level of capacity across work-centers, labor skills, and suppliers.

Before concluding this chapter, here are a few discussion points for your consideration.

What advantages can you see from having suppliers with shorter lead times?