A common challenge in Sales & Operations Planning (S&OP) is understanding how to break down your product family into a level of granularity that allows you to apply the right demand planning method in the right situations. With the right approach, you can significantly improve forecast accuracy. To do this, it's important to recognize that there are four distinct types of demand, each requiring its own unique method of forecasting. These are: Flow Demand, Dependent Demand, Intelligent Demand, and Abnormal Demand.
Let’s take a closer look at each one.
1. Flow Demand
Flow demand is often what comes to mind when most people think of forecasting. The basic concept behind flow demand is that history is the best indicator of future demand. This type of demand is usually spread across many customers, with individual orders being small and frequent. It’s most often seen in products with a history of consistent demand, standard specifications, and are typically make-to-stock (MTS) items.
For these types of products, we rely on historical data to create our forecasts. Statistical methods, such as time-series forecasting, can help predict future demand patterns. You might adjust these forecasts using a seasonal index or account for future growth plans. But at its core, flow demand is about leveraging historical trends to predict future needs.
2. Dependent Demand
Dependent demand is a bit different. This type of demand is derived directly from a customer’s forecast or build plan. For example, if you’re supplying components to a sister plant or large OEM, their forecast and production schedule will drive your demand.
In industries like automotive, where tier-one suppliers receive demand from OEMs via EDI (electronic data interchange), the demand can be calculated based on the flow rate of the OEM. In these cases, it doesn’t make sense to create a separate forecast on top of this, instead, you need to treat the demand as dependent.
The key here is collaboration. By working closely with your customer to validate actual demand against the forecast, you can improve the demand plan over time, without the need for constant re-forecasting or second-guessing.
3. Intelligent Demand
Intelligent demand is about using real-time, actionable data to make better decisions. This applies when you have a significant customer, like a retailer or distributor, that stocks your products for resale. Think of major players like Walmart or Home Depot.
With intelligent demand, you have access to a large quantity of data: sales in and out, point-of-sale (POS) data, and inventory levels at the retailer. This allows you to forecast demand with much greater accuracy. Instead of relying on traditional statistical forecasts, you can use the consumption model to calculate the demand based on the actual sales and inventory data you have access to. This approach ensures that you’re not just guessing, but rather using the most up-to-date information to guide your planning.
4. Abnormal Demand
Finally, there’s abnormal demand, which is also known as lumpy demand or project demand. This type of demand doesn’t follow the regular, predictable patterns of flow or dependent demand. It tends to be driven by fewer transactions, but with larger quantities, think engineer-to-order (ETO) projects or configure-to-order (CTO) items.
Abnormal demand is more unpredictable and often involves longer lead times and sales cycles. In these cases, traditional statistical forecasting doesn’t work very well. Instead, you need to manage your demand plan. This means pulling in opportunity data from your CRM and assigning probabilities to potential sales. You also need to determine which projects are “in” or “out” of the plan.
If you're just getting started, it's a good idea to separate flow demand from abnormal demand. This is often the simplest starting point. By excluding the larger, lumpier demand from your statistical forecast, you’ll end up with more accurate predictions for the flow demand. Once you have a solid handle on flow demand, you can focus on managing the larger projects separately.
Getting Started: The Importance of Segmentation
So, how do you get started with breaking down your S&OP family? It’s important to begin by segmenting your demand into the appropriate types: flow, dependent, intelligent, and abnormal. This allows you to apply the right forecasting methods to each type and improve accuracy.
When developing your demand plans, be sure to collect all the necessary data: bookings, shipments, and backlog. You also need to assign clear accountability within your team and track the performance of each demand stream. Over time, this segmentation will help you identify the biggest challenges and refine your demand plans to improve accuracy.
Conclusion
A successful S&OP process requires not only accurate data but also the ability to segment demand correctly and apply the appropriate forecasting methods to each segment. By breaking your product family down into flow demand, dependent demand, intelligent demand, and abnormal demand, you can ensure that your demand planning process is both efficient and effective.
For companies just starting out, I recommend focusing first on distinguishing between flow demand and abnormal demand. From there, you can expand your segmentation approach as you get more comfortable.
For more insights on how to transform your S&OP process and create better demand plans, check out our video here. It’s a great way to dive deeper into these concepts and see how they can benefit your business.
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