In part one of this series, we looked at the challenges of economically and profitably providing rapid fulfillment, with unique personalized requirements by sector, channel, and customer. We looked at automation of mass customization as part of the answer. Here in part two, we look at several other strategies for profitable fulfillment in various scenarios.
Fulfillment Segmentation and Orchestration
A common strategy to control complexity and cost is consolidating spend to fewer suppliers and service providers (e.g. carriers, 3PLs, installers, and repair services), thereby gaining economies of scale and volume discounts with more business per supplier. However, supplier consolidation can make it harder to meet the increasingly diverse fulfillment requirements that companies are facing across the globe, such as a much broader mix of order sizes, product diversity, needs for specialized processing, handling, and installation skills and equipment, and expanding globalization with significant differences by regions (even within a country). The diversity of requirements drives the need to segment fulfillment, with capabilities to handle the unique requirements of each segment differently. It can be hard or impossible to find a supplier that can do it all. Often specialized or regional service providers are much better able to fulfill these diverse unique requirements — sometimes at a lower cost.
Unfortunately, using many specialized suppliers introduces complexities. Different products are handled by different partners, e.g. temperature sensitive carriers or storage facilities, heavy equipment haulers and riggers, extremely fragile instruments, and so forth. Advanced companies are using technology to provide the coordination and orchestration that lets them ‘have their cake and eat it too’ — that is to take advantage of the abilities of a diverse and scattered set of suppliers and service provider partners, while controlling costs and performance.
One example of fulfillment segmentation and orchestration is a major automotive OEM that has an online ‘Upfit Configurator’ that allows general contractors, plumbers, caterers, people transporters, electricians, and HVAC contractors to configure customized vans and wagons.1 The customizations are typically not done by the OEM, but rather by its network of upfit or port processing partners, at an ‘upfit center,’ often located near the origin or destination port. This is just one specialized step in a multi-step logistics process from the factory to the dealer (see Figure 2 below) that can include the OEM, their Origin Service Provider, rail carriers, the trading company, upfit centers and port processors, ocean carriers, car haulers, and more. By using a common networked platform across this network of fulfillment partners, the OEM is able to give the upfit centers much more precise estimated times of arrival, allowing the centers to better plan their labor and capacity. The upfit center receives a complete set of instructions for the operation.
The same system gives the OEM precise visibility into progress at the upfit center, for early alerts when things are falling behind with the potential to miss the sailing. The system provides a set of KPIs and dashboards to measure and continually improve the performance of the upfit centers. This is one example of how fulfillment can be highly segmented, performed by many parties, yet tightly coordinated, with the activities of all of the parties being monitored and orchestrated by a common end-to-end platform.
Optimized Postponement with Outsourced Partners
While supply chain postponement strategies2 have been implemented by manufacturers for years, they can be a lot harder to accomplish, due to the loss of visibility and control resulting from the tremendous growth in outsourced manufacturing and fulfillment partners. The challenges are compounded when multiple tiers and multiple enterprises are involved. To enable well-managed postponement execution with outsourced manufacturers, one of the world’s largest sporting footwear brand owners has implemented the ability to monitor the progress, step-by-step, at each of its suppliers’ factories. This granular, near-real-time visibility into factory progress against milestones is foundational to the OEM’s postponement strategy. Another large apparel manufacturer/OEM has taken a similar approach.
Precise factory milestone visibility enables these OEMs to have multiple points of postponement and maintain an accurate estimate of the time they have before they need to make each of the key postponement decisions. For example, the apparel OEM sends an order which specifies the number of shirts to make, but not yet the colors or sizes. The outsourced factory buys the undyed gray fabric. The OEM knows exactly when the material is ordered, arrives, and is scheduled to be dyed. It knows exactly when it has to make the color decisions, based on what is actually happening on the ground at the outsourced factory, not some average estimated schedule. Later in the process, it knows when the size decisions must be made, based on when the cutting and sewing will start. At the end, it knows by when they must tell the contract manufacturer how many of each size, color, and style to ship and where. In fact, the decision on final destination can be postponed further until the shipment arrives at the deconsolidator at the destination port. This allows key decisions to be postponed until location-specific demand is much better understood.
Postponement is also used for duty and tariff engineering, where an item’s components are assembled at the point in the supply chain that creates the lowest total cost. One large equipment manufacturer makes enormous mining trucks, which are assembled at different stages and points in the supply chain, both to optimize duties and tariffs as well as due to logistical constraints of moving very large machinery across roads, on or under bridges, and by rail. In many cases, the final assembly is at the mine.
The flexibility to design a global fulfillment and delivery process with postponement done at the optimal stage by various outsourced partners is made feasible by using a shared network platform that orchestrates the activities of the various partners. The network platform must provide highly granular, near-real-time visibility into what is happening on the ground at all of the various manufacturing and fulfillment partners, and provide a single shared system that drives the execution, with precise instructions for each activity at each partner at each step. With a single networked platform, there are no delays in these instructions or status information getting from one system to another or mistakes introduced by manual data re-entry or translation errors between different systems.
Multi-Party Inventory Pooling
The demands of omni-channel fulfillment have given rise to Distributed Order Management, whereby a retailer (or wholesaler or manufacturer) has a system that can see inventory across all locations and make optimal decisions about where to fulfill each order from. However, these systems are often constrained in their visibility to see inventory outside of the company. It is not uncommon to have inventory spread across multiple tiers of fulfillment, not only a company’s own inventory locations (DCs, stores, plants) but also at out-sourced manufacturers’ plants and DCs, and at other supply chain participants, such as wholesalers, distributors, installation and repair partners, accessory suppliers, and other players in the channel. In addition, there is often a lot of inventory in transit between these various locations, especially when shipped across an ocean. Network-wide visibility to available inventory, both at rest and in motion, provides major advantages of wider inventory pooling, often allowing much quicker and/or lower cost of servicing customer needs as they arise. In some percentage of cases, pooling consumes inventory that is not in demand in the location it is currently at and therefore might not be consumed for months or at all.
In addition to finished goods inventory, multi-party pooling can add a lot of value in spare parts inventory management, where it can be quite challenging to achieve desired service levels with the optimal mix of inventory at each location, in large part due to the long tail3 of slow movers that is common in spare parts. A frequently used approach, particularly where fulfillment response time is critical (e.g. auto parts, where a car is up on the lift waiting for a part), is to simply throw a lot of inventory at the problem, especially at or near the end nodes. This adds a lot of inventory and cost to the system. This can be further complicated when parts distribution centers (PDC) hold a mix of parts built by the OEM and by suppliers. In addition, there is inventory at dealers that becomes invisible to other dealers. Providing unified visibility across dealers’ inventory, suppliers’ inventory, parts retail store inventory, and PDC inventory creates opportunities for higher service levels at less cost across the network.
In part three, the final article in this series, we look at enablers of these profitable fulfillment strategies, including ‘Operationally Precise Visibility’ and ‘Dynamic Orchestration.’
1 Customizations include adding various interior racks, shelving, workbenches, seating, wire spool holders, partitions to separate and secure the cargo, protective window mesh, exterior ladder racks, strapping systems, and so forth. — Return to article text above
2 Postponement of differentiation is where certain decisions or steps in production (or fulfillment decisions such as where to ship to) are postponed until a clearer picture of demand emerges (such as having received firm orders or measured actual demand). A classic example is designing a platform with interchangeable components, building the components based on the forecast, but postponing assembly until each order arrives and then doing assemble-to-order. — Return to article text above
3 Complex machinery has a long tail of parts, many of which may see only a couple of turns per year at a given location. — Return to article text above
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