Integrated S&OP and S&OE
S&OP plans are quite attractive and look great with all kinds of helpful colorful charts. However, being at such a high level and intended for long term planning, their accuracy is far from reliable when it comes to committing delivery dates and financial projections., Furthermore, they need to be translated to plans that are executable, i.e. accurate short term plans. Accurate execution plans require detailed explosion of bill of materials, actual capacities of resources (instead of number of units per day), correct setting of inventory levels at each stage of the supply chain, prediction of risks due to breakdowns and supply shortages, possibility of batching, order-level pegging, alternative methods of production and routes, substitute parts, transportation alternatives and many other constraints that are needed to implement an accurate plan. Sales & Operation Execution (S&OE) provides such functions and more. S&OE addresses the supply and production issues in a realistic way knowing what the alternatives are and what to expect. In addition, whatever goes wrong, there needs to be a methodology by which the plan is put back on track, more or less, in real-time! If you are considering a S&OP solution, ask: How do I execute the plan? Almost all S&OP users require user intervention to make the plan executable which is unnecessary, time consuming and suboptimal.
In recent years, there has been a lot of discussion regarding bringing planning and execution closer to each other in a seamless environment. Having an integrated S&OP and S&OE environment seems to be the answer. We, at Adexa, accomplish this through a continuum. In other words, a system with a unified data model that generates plans at a high level and gradually converts them into lower and lower levels of detail for execution based on the granularity and frequency of data. Thus, from network planning and S&OP all the way down to factory planning and sequencing, having a consistent environment respecting both business and physical constraints at different levels. At Adexa, we deploy an AI search technique, called constraint propagation, that defines guide posts to limit the search space for the next level of detail so that very quickly the system arrives at an optimal solution. Much like finding a desired location, you start from country to city, then street, the street number and apartment number to find an individual. Constraint propagation, as described in this example, systematically eliminates infeasible solutions to quickly arrive at the right optimal and executable plan.
S&OE goes even further than just executable plans, it also provides invaluable insight and identifies root causes of issues. For example, why certain orders or customer deliveries are, or more likely to be, late, and suggest alternative methods to avoid lateness. When combined with attribute-based planning (ABP), S&OE can also ensure important customer specifications are met for every order. An example would be, a specific qualified supplier to be pegged to the customer order. Or ensuring certain range or attributes of intermediate inventory or an equipment meet and match the specifics of the customer requests. In the absence of such a feature, substitute SKUs must be generated which increase the size of master data exponentially, make its maintenance a nightmare and slow down the system performance drastically. S&OP and S&OE are not two disjointed processes and strongly depend on one another. Consider them as a continuum of planning and execution.
