This lead time will allow an increase of price or the capture of additional business through either existing or new customer channels. Determining this lead time takes the active involvement of sales and customer service. Be aware that there could be different stratifications of market potential lead time. For example, a one-week reduction in lead time may only result in an increase in orders, whereas a two-week reduction in lead time could result in both an increase in orders and a potential price increase on some of those orders. Properly segmenting the market will maximize the possible revenue potential for the company and provide excellent revenue growth control. This is a consideration in Demand Driven Sales and Operations Planning, covered in Chapter 13.
Sales Order Visibility Horizon
The sales order visibility horizon is the time frame in which we typically become aware of sales orders or actual dependent demand. In retail situations, customers do not issue a sales order to a shop in advance of going to the shop. Thus the sales order visibility horizon in this situation is zero. In most manufacturing scenarios, however, there are sales orders conveyed in advance of expecting receipt of the item. Often the sales order visibility either matches or exceeds customer tolerance time. The longer the visibility to sales orders, the better the capability of the environment to see potential spikes and derive relevant demand signal information. In many cases relevant requirements are obscured from planners because all demand (including planned orders based on forecast and safety stock requirements) is aggregated together for aggregate planning purposes.
External variability considers both demand and supply variability.
Variable Rate of Demand
This refers to the potential for swings and spikes in demand that could overwhelm resources (capacity, stock, cash, etc.). This variability can be calculated by a variety of equations or determined heuristically by experienced planning personnel. As noted in the APICS Dictionary,
“Mathematically, demand variability or uncertainty can be calculated through standard deviation, mean absolute deviation (MAD) or variance of forecast errors.” If the data required for mathematical calculation do not exist, companies can also use the following criteria:
Variable Rate of Supply
This is the potential for and severity of disruptions in sources of supply or specific suppliers. This can also be referred to as supply continuity variability. It can be calculated by examining the variance of promise dates versus actual receipt dates. When first considering the variable rate of supply, the initial variances can be caused by critical inherent flaws in the MRP system. Additionally, those dates often shift due to other shortcomings associated with the way MRP is employed rather than because of the supplier capability. Any critical supplier of a major manufacturer will know exactly which day its customer regenerates its MRP. These suppliers will see a flurry of additional orders, canceled orders, and changes to orders (quantity, specification, and request date).
If the data required for mathematical calculation do not exist, the following heuristics can be used:
Inventory Leverage and Flexibility
There are places in the integrated bill of material (BOM) structure (matrix bill of material) or the distribution network that provide a company with the most available options as well as the best lead time compression to meet the business needs. Within manufacturing, these places are typically represented by key purchased materials, subassemblies, and intermediate components. This becomes more critical in environments with BOMs that are deeper and more complex (broader) and have more shared components and materials. This concept will be explored in detail later in this chapter.
Similar to how variability can impact a bill of material, the longer and more complex the routing structure and dependent chain of events (including interplant transfers), the more important it can be to protect identified key areas. These types of operations include areas where there is limited capacity, or where quality can be compromised by disruptions, or where variability tends to be accumulated or amplified. In Lean, these areas might be referred to as pacesetters. In the Theory of Constraints, they can be referred to as drums. Whatever manufacturing or operational methodology a company ascribes to, these resources typically represent control points that have a huge impact on the total flow or velocity that a particular plant, resource, or area can maintain or achieve.
The preceding six factors must be applied systematically across the entire BOM, routing structure, manufacturing facilities, and supply-demand network to determine the best decoupling positions for purchased, manufactured, and finished items (including service parts) in order to protect and promote the flow of relevant information and drive return on investment performance.
Applying the Positioning Criteria
As an example, let us apply these six factors to a relatively simple environment. In our example, only two finished products are made. Figure 6-1 shows the bill of material for the two products: FPE and FPF.
The numbers in the circles represent the manufacturing or purchasing lead time in days for each discrete part number. For instance, FPE takes 2 days to make when all components are available, and 204P has a purchasing lead time of 20 days.
For each part number in this example, there are three relevant lead times. These are described in the APICS Dictionary as:
Manufacturing lead time (MLT): The total time required to manufacture an item, exclusive of lower level purchasing lead time. For make-to-order products, it is the length of time between the release of an order to the production process and shipment to the final customer. For make-to-stock products, it is the length of time between the release of an order to the production process and receipt into inventory. Included here are order preparation time, queue time, setup time, run time, move time, inspection time, and put-away time. (p. 98)