Sales orders identify actual demands. Actual demands may drive all supply chain activities when the sales orders with future ship dates exceed the cumulative lead-time to obtain and ship a product. However, actual demands must be anticipated when selling a product from inventory. One approach to stocking products in advance of sales orders involves a sales forecast, and the combination of sales forecast and sales orders defines demand for the saleable item. A second approach involves an order-point replenishment method, where the reorder point represents forecasted demand over the item s lead-time .
A make-to-order manufactured item may be built from stocked components. One approach to stocking components in advance of sales orders involves a component forecast, and the combination of component forecast and dependent demand defines demand for the component. A second approach involves an order-point replenishment method.
A sales order line defines an actual demand for an item, expressed as a quantity, date, and ship-from location. A blanket sales order line also defines an actual demand for an item and location. Sales orders linked to the blanket order line consume the blanket order quantity. In this sense, a blanket sales order represents a forecast by customer.
A sales forecast defines an estimated demand for a stocked item, expressed as a quantity, date, and ship-from location. Each sales forecast represents the desired inventory level on the specified date. Planning logic considers the combination of sales orders and forecasts in calculating requirements. Sales orders consume the sales forecast to avoid doubled -up requirements. This is termed forecast consumption logic. Forecast consumption logic reflects an implied forecast period defined by the sales forecast dates. An example may help. When an item s sales forecasts are defined on the first of each month, for example, a sales order consumes forecast within a given month based on the ship date. Unconsumed forecast rolls forward throughout the implied forecast period of a month, and gets ignored when the system work date matches or exceeds the next forecast date. The same logic applies to other implied forecast periods, such as sales forecasts entered with weekly or intermittent dates.
Multiple sets of sales forecast data can be defined, where each set is uniquely identified by a user -defined name . Each set may contain sales forecast data and component forecast data (described below) by location, so that each set is termed a production forecast. Planning calculations only use the set of forecast data identified on the manufacturing setup screen. Multiple sets of forecast data often reflect various scenarios for simulation purposes, or forecast revisions based on changing market conditions. A set of forecast data can be copied to a new set and subsequently revised. This approach supports comparison of actual demand to a selected set of forecasted demand.
Forecasted demands can be based on many factors, such as management intuition, the current pipeline of prospects and quotes, and sales history. An item s sales history ”typically reflecting posted shipments or item ledger entries about shipments ”provides the basis for generating a statistical forecast in weekly or monthly increments . A sales forecast by location can be based on the best fit of various forecasting techniques. Projected quantities can be optionally overridden, and then used to automatically update a set of sales forecast data for use by planning calculations.
A component forecast defines an estimated demand for a stocked component, expressed as a quantity, date, and location. A component forecast is different from a sales forecast. A sales order for an end-item does not consume component forecast, so that a different type of forecast consumption logic must be used to avoid doubled-up requirements. In this case, the creation of a purchase order, production order, transfer order, or system-suggested order for the item consumes an item s component forecast. The system uses an implied forecast period defined by the component forecast dates. The order s scheduled receipt date acts as the basis for consuming component forecast. The unconsumed component forecast rolls forward throughout the implied forecast period, and is ignored when the system work date matches or exceeds the next forecast date.
An order-point replenishment method provides an alternative to forecasts when anticipating demand for a location s stocked material. Time-phased order-point logic suggests replenishment when an SKU s projected available balance falls below its reorder point. The reorder point quantity represents estimated demand over the SKU s lead-time. This means planning calculations suggest an SKU s replenishment orders based on sales orders with future shipment dates. A time-phased order point approach does not require forecasted demand, but forecasts, if entered, will be considered by planning calculations.
Many firms carry additional inventory to anticipate variations in customer demand and meet customer service objectives regarding stockouts, partial shipments, and delivery lead-times. The additional inventory is termed an inventory plan . An inventory plan is typically expressed for SKUs at the highest possible stocking level, such as saleable end-items that are purchased or manufactured to stock. A make-to-order manufacturer, on the other hand, typically expresses an inventory plan for stocked components.
An inventory plan can be explicitly expressed as an SKU s safety stock quantity or as a safety lead-time. The safety lead-time represents a buffer against delayed receipts, but it also represents a type of inventory plan.
An implicit inventory plan can be expressed in several different ways. With an order-point replenishment method, the extent to which a reorder point exceeds typical demand over lead-time represents an implicit inventory plan. Suggested order quantities represent an implicit inventory plan when they exceed typical demand over the reorder cycle, or when inflated by order modifiers. The order modifiers and reorder cycle provide a similar implicit inventory plan for a replenishment method based on MRP logic.
Visibility of all demands is critical to formulating an effective S&OP game plan. Surprise demands can cause shortages that impact customer service or production and result in expediting. Some sources of demand may need interpretation or alternative ways to express the demand, as illustrated in the following examples.
Customer Schedules Customer schedules represent a combination of sales orders (in the near term) and forecasts (in the longer term ), and often require time-frame policies for proper interpretation. A blanket sales order provides one approach for defining a customer schedule, with sales orders representing releases within the customer schedule.
Internal Sales Orders An internal sales order may be required to initiate production and/or procurement activities prior to obtaining the customer s purchase order. Once obtained, the designated customer can be changed on the sales order.
Customer Service Demands Customer service may require material for loaners, exhibition items, donations, replacement items, and repairs .
Field Service Demands Field service may require spare parts for selling to customers, and for repair and field service projects.
Engineering Prototypes Prototypes may be built for internal or external customers, with requirements for material and production capacity. Procurement and production activity may also be initiated on new products with partially defined bills.
Quality Quality often requires validation lots or first articles, especially during ramp-up to production lot sizes. Other quality- related demands can be embedded in planned manufacturing scrap, so that planning calculations identify the additional requirements for material and capacity.