The purpose of system and sub-system integration is not to get rid of our silos, but to integrate them together. The second issue in this integration has to do with individual system capacity and total system throughput.

As organizations grow, there is constant pressure on efficiency (lean, six sigma, MUDA), but as the internal systems multiply, efficient as they are, they begin to get in each other’s way. It is not enough to have a collection of perfectly efficient systems, the organization now has to look at total system throughput. Capacity output and constraints of each system come into play.

Is it possible for Sales to write so many orders, that it outstrips the capacity of Operations to complete those orders? Unfilled sales orders become back-orders. Unfilled back-orders become cancelled orders. Customers go to competitors. What’s the problem? Both Sales and Operations are running full-tilt within the constraints of their function, but one function is outstripping the capacity of the other.

Let’s flip this around. Our Operations function has the latest, greatest state-of-the-art equipment, a cracker-jack operations team and the capacity to crank out finished goods like there is no tomorrow. Yet, if our Sales function is somewhat anemic, not that they are writing no sales orders, but certainly not selling everything that gets produced, what happens to the unsold finished goods? Into inventory they go, stacked in the warehouse. Until the warehouse gets full, then what do we do? We get another warehouse. What is happening to the cost-of-goods-sold?

This second issue of system integration is optimizing the capacity of each function as it sits next to its neighboring functions. There are dependencies, inter-dependencies, constraints, contingencies and bottlenecks that govern total system throughput. It does no good to write sales orders for products and services that cannot be filled.