This article is the second part of our three-part series on how S&OP leaders can empower their processes with Simulation Digital Twins. Here we look at how by modeling in finite granular detail, the digital twin simulates cascading effects to determine optimal outcomes to overcome disruptions. If you missed our Series Introduction article, make sure to check it out.
A challenge in traditional S&OP planning is controlling all supply chain steps while at the same time focusing on what’s critical for the business in a continually volatile environment. Often S&OP planning tools cannot identify and model critical resources at a granular level to guarantee the (S&OP) process viability. And thus, they do not provide the insight and foresight needed to ensure the S&OP plan can be executed when faced with changes of critical resources.
An example of this is in manufacturing, where most S&OP planning tools and processes consider only plant or production lines aggregated capacities and do not model each operation’s cycle time. Moreover, they do not model the difference of cycle times according to the product which is processed and do not give the possibility to represent an evolution in time (dynamic).
Another example is a tier-1 supplier in the aeronautics industry that focused its efforts on establishing a very detailed production plan in its S&OP process. At the same time, the bottleneck in its plant is in the quality control lab, which was not considered in the production resources of the S&OP plan.
In addition, as the tier-1 supplier took three weeks to retrieve, validate and communicate the data, the S&OP manager doesn’t have adequate time to develop a contingency plan before meeting with management for a decision.
To ensure an S&OP plan that can be executed in the best possible conditions, especially in terms of its alignment with the Master Production Schedule (MPS), entails the following:
By implementing a simulation digital twin, the S&OP team can take into account
the above critical areas while providing the following added value:
As we’ve seen, the next generation of Simulation Digital Twins provides the modeling capabilities required by today’s S&OP leaders in both manufacturing and distribution. Continual market uncertainty and volatility in the months (or years) ahead means that companies will need modeling tools that provide end-to-end process management and controlled complexity.
In the next article, we will explore soon how Simulation Digital Twins ensure faster risk assessment for better decision making. And if you missed our first article, we look at how digital twins provide better visibility of key business indicators and cascading effects on the entire organization.
To learn more about how your S&OP organization can leverage Simulation Digital Twins, watch a replay of our webinar with Agilea Overcoming uncertainties with prescriptive S&OP. Philippe Bornert, CEO at Agilea, and Romain Ropitault, Senior Product Manager at Cosmo Tech, discuss how organizations can deploy a mature S&OP process to improve responsiveness and mitigate risks.