Lead Time Calculation is Hard
What’s in a delivery date? Turns out a lot in today’s complex supply chains making lead time calculation very difficult! As discussed in our previous blog article Intersection of Price Product and Availability, customers want to know what product they’re getting, how much it costs, and when they can get it. Each of these questions are answered in increasingly complex ways as manufacturers, distributors, and retailers optimize their operations, supply chains, and diversify their customer touchpoints.
Specifically here, we’ll touch on delivery date or lead time calculation and available-to-promise (ATP). Delivery date comes into play before the order has been promised when a customer is trying to finalize an order. As supply chains optimize, there aren’t as many finished goods in the system so determining delivery dates is more complex than simply checking inventory. Also, in times of limited supply, goods may be tied up with contractual obligations on service levels and allocations. Throw in build to order or mix options, and the myriad of permutations is even harder to predict. Finally, there are transportation issues that could delay or complicate the answer.
When we previously did this for a computer manufacturer, the permutations were so complex, we simply took a statistical average for lead time and used that, then when they couldn’t deliver on time, they’d notify the customer and take the customer satisfaction hit or make them happy by delivering early. But when you’re a manufacturer selling to assemblers or selling through eTailers like Amazon or Ebay, they take delivery dates more seriously and if you miss your date there could be severe consequences.
Accurate Delivery Dates
So how do you limit your inventory exposure and also get an accurate delivery date back to customers? Here are some of the ways we approach it:
- Standard Lead Time – As mentioned above, a standard lead time is the easiest to simply put on a product. This is not always the most accurate or desirable method because it means you may have to keep more inventory than needed to maintain service levels. In this case, we typically estimate the lead time by looking at past deliveries and then tweak that on products that are quicker to deliver or take longer using rules.
- Available to Promise – Available to promise is a complex mix that combines current orders with delivery dates, service levels, on hand inventory, and future deliveries. Taking all these factors into consideration is difficult when you have a complex supply chain. There are a couple products we use including BlueYonder’s Order Promiser and SAP IBP (formerly APO) that can accurately model all these moving parts and provide a good date. With these systems, you also have the ability to move orders or delay them given service levels or a customer’s willingness to wait.
- Allocated Available to Promise – Building on ATP, in industries like semiconductor, there are also allocations to consider and limited supply. These commitments complicate the delivery date answer because you may have firm orders further out that you’ve reserved inventory for, but need to satisfy an order now. The AATP engines can see that you have replenishment orders pending and allow you to consume current inventory expecting that you will be able to satisfy the future orders with new inventory.
- Build to Order – Build to order needs a special mention because it complicates the process even more. With build to order or configure to order we typically model the most constrained parts and don’t worry about the other parts that have more availability. We have used the standard lead time method on the constrained parts in the past, such as processors for computer manufacturers, but have also used an ATP engine with the constrained parts. Both methods work and it depends on the situation as to what we would recommend.
Customer Service and Lead Time
In all cases, customers and customer service people need the ability to query the ATP engine for availability or delivery dates when either taking orders, changing orders, or checking order status. Customer service people also need the ability to make decisions like shifting availability when possible or pushing orders out when a customer allows it. In large enterprises, these decisions must also happen in real time so that customers can make their own decisions. As supply chains get more efficient and customers get more demanding, order promising quickly outgrows a customer service reps ability to simply check inventory and these ATP engines can fill that need.
If calculating lead time and delivery dates is a problem for you, we can help. Whether you are using SAP, Oracle, some other ERP, or planning tool, we can extract the data and model your supply chain. For more information or to discuss how we can help, please schedule a call!