We are at a point to deploy planning systems that are accurate and intelligent enough to more or less run the supply chain autonomously. Just like an autonomous vehicle, user intervention may be needed from time to time, but rarely. Autonomous vehicles may show you how to get there but cannot tell you the destination. Nor can they tell you what your priorities are, what your values are and how your habits are going to grow and change over time. This is the case with any organization. Your priorities, business processes, methods of interaction with customers and suppliers, technological trends, availability of data are all changing and expanding. To this end, the systems need to adapt and be guided to know where they need to take the organization.
Systems are far better than humans in optimizing millions of variables in allocating resources to demand and equipment to jobs. Using a digital and accurate model, optimization of operations can be done in a very short amount of time by advanced supply chain planning systems. To this end, planners are now in a position to perform higher level functions. For example, examine the previously undetected, trends in the supply chain that are being highlighted by the system. They can see how the supply chain design and configuration can be altered in order to avoid unwanted patterns and causes of lateness and cost increases.
Planners can also decide what relevant data is needed to find root causes of disruptions. For example, if certain suppliers, resources or materials are causing more than 30% of late orders or cost increases during months of winter, exogenous data can be included for the system to identify the main causes. Similarly, given the current advances in technology for Big Data, planners are no longer limited to planning data, they can also see the relationship between planning data and data collected from systems such as ERP, MES, CRM and PLM. An example of the latter is relationship between maintenance schedules and late orders or cost increases. Equipment breakdowns due to lack of maintenance can be a cause of late orders or use of substitute parts causing increases in cost.
Finally, systems can now perform continuous planning in real-time. This does not mean running planning engines 24×7. An intelligent system can decide when to revise the plan, at different levels of supply chain, responding to events in an event-driven manner. Responding to shop floor issues in real-time requires a different skill set than responding to changes in demand at the supply chain level. Having this kind of capability can have a significant impact on the way the business process is designed and increase the velocity of doing business considerably.
Above are only a few examples of how intelligent supply chain planning systems can enhance the roles of the users, business processes and velocity of doing business. As much as S&OP systems have helped but they are only an extension of traditional planning with manual intervention and rough modeling, far from a digital twin. A digital model with S&OE is truly a shift in paradigm enabling organizations to take a quantum leap ahead of their competition. For more on the above topics and other aspects of intelligent systems click Here.