How to Integrate S&OP and Production Planning
Brian Hoey - May 19, 2020
Let’s say you’re a production planner, and you’re trying to generate planned production programs for the upcoming month: what would your ideal meeting look like if your goal was to come away with the necessary tools for creating the optimal plan? First of all, you’d probably want to know what the expected demand is for the upcoming week, month, or quarter (depending on your sales and production cycle times). You might also want to know what the confidence interval is on those expectations, i.e. how strongly the data that’s been collected supports those predictions. From there, you might want to learn more about capacity restraints and inventory plans, so that you can figure out how best to work within existing constraints to create the right amount of product.
No doubt, there’s some specifics you might want to know: What’s your current buffer stock? What are your suppliers’ upcoming lead times looking like? Plus, you’d want a more general overview of the company’s longer term goals and trajectory (up to, say, 18 months out). Once you had this information, you’d basically be all set to sit down with your production planning software and get to work, right? Right. The question is how best to make that happen.
How S&OP Connects Demand and Supply Planning
As it happens, the ideal meeting we described above is, in essence, a well-run S&OP (sales and operations planning) meeting. For those who might now know (or who might want a refresher), S&OP is a software-driven business function in which multiple functions align on demand and production expectations for a given period, say the next 6-18 months. You begin by collecting the necessary data to create a demand forecast from as many touchpoints on the value chain as possible, and then you start mapping out your capacity restrictions in order to create a supply plan. This is where the production planner comes in, since the production plan should act as the operationalization of this supply plan once you’ve determined the specific units and ratios you’re going to need to meet your expected demand.
In this way, you can see how S&OP supports not just better alignment between production plans and other departments, but more data-driven production runs that benefits from having visibility across the entire end-to-end value chain. The question is, how do you actually implement this process in such a way as yield more optimal production plans? Largely, this is a matter of getting buy-in from the appropriate stakeholders and committing to improved data collection, storage, and analysis across the board. This might involve updating your IT systems to allow more flexibility in terms of connecting the right datastreams and powering advanced analytics processes that can help you reach planning optimization more quickly.
Creating a Demand-Capacity Feedback Loop
So far, you might be getting the impression that S&OP and production planning are something of a one-way street, i.e. S&OP meetings furnish production planners with data and directives, and those planners then go forth and operationalize. While it’s true that that’s what happens, production planning processes are also critical sources of feedback for the larger S&OP paradigm. If, for instance, your last three production runs yielded less than you estimated (and thus less than enough to meet demand) because of a higher concentration than usual of dud parts from your supplier, you need to document those processes and present them to the assembled group at the next S&OP meeting (and enter the relevant data into the S&OP software solution). This provides feedback for related functions like inventory planning and sourcing, but it also gives an important picture of the existing demand-capacity planning situation to the larger planning function. With this picture established, you’re able to refine the S&OP process and its related functions to provide more and more value and run more and more smoothly over time.
When we talk about integration between S&OP and production planning, the above is more or less what we mean. And how do you make that happen, exactly? By powering operational and interpersonal workflows (e.g. monthly meetings with a real give-and-take) with technological workflows. The more effectively you’re able to gather digital data from production workflows (while your counterparts in inventory planning, logistics, etc. do the same) and share it intra-operationally, the more successfully you can effect this sort of integration. This might mean installing IoT devices or other trackers on the factory floor that transmit data to a central planning control tower, or it might mean training advanced analytics processes on those same datastreams to create even more valuable insights and thread the demand-capacity needle that much more efficiently.
Integrating Sales and Operations Execution (S&OE)
For S&OP planners, the goal is to make sure that your production and delivery meet demand without exceeding it by too much—and the goal of a planned production program is to do the same within its own purview. Because of the volatility of the modern global supply chain, however, this is easier said than done. That’s why, in recent years, some businesses have been complementing their S&OP workflows with S&OE workflows that operate on a much shorter timescale. These processes are fundamentally driven by data and analytics, which means they need a high level of end-to-end visibility (and thus a high level of technology integration) in order to thrive. Once this process is in place, it can make minute adjustments to inventory and transport levels on a weekly basis in order to keep plans on track as new demand realities emerge.
While S&OE doesn’t directly impact production planning, it’s connected to the production floor by way of inventory planning. This means that in a sophisticated, fully Industry 4.0-enabled factory, S&OE would act as a weekly reality-check for production planners, who might scale plans and product ratios up or down accordingly. Naturally, doing this at scale on a weekly basis requires you to optimize production plans with shorter lead-times than ever before. As such, it’s here that technology integration becomes increasingly important: if you have data analytics in-tow from up and down the value-stream, you can optimize and re-optimize as new conditions emerge. Without this level of integration, it will be difficult to remain responsive enough to truly capitalize on S&OP and S&OE workflows.