Supply Chain Coordination Through Schedule Integration
Successful industry examples prove that tighter integration of information and physical flows in supply chains yield significant productivity improvements. Research suggests that the benefits range from 2.3% to 48% in system cost reductions depending on the degree of information sharing and coordination among the channel members. Despite the magnitude of the potential benefits and availability of enabling technologies, supply chain integration continues to be a challenging task and a critical issue for today's supply chain professionals. The difficulty arises from the conflicting objectives of the supply chain members and an inadequate understanding of how to integrate the supply chain processes.
Information sharing and coordination, which are requirements for successful supply chain integration, are of particular importance for make-to-order (MTO) supply chains. Consider the typical relationship between a manufacturer and a supplier of an MTO supply chain, where the manufacturer's production schedules drives the order fulfillment activities. Seeking to minimize his costs, the manufacturer optimizes his production schedule and releases his purchase orders to his supplier one at a time and as a result exports operational inefficiencies to his supplier. In return, the supplier is left with no option but to respond on a lot-for-lot basis, which compromises the schedule integration efforts. This is particularly the case when managing the master production schedule (MPS) that MTO planning systems often rely upon.
Establishing a stable MPS to facilitate manufacturer-supplier integration is an important issue in supply chains utilizing material requirements planning (MRP) based systems. Due to the many industry examples, researchers, for many years, have been emphasizing the need to examine supply chain integration in requirements planning environments.
In requirements planning environments, as a result of the limited visibility into the future, the manufacturers often plan their replenishment schedules on a rolling horizon basis. Using the currently available data, they determine their best replenishment quantities over a specified planning horizon and implement a subset of the earlier replenishment decisions. After rolling through time, the schedules are updated utilizing recently collected data.
Application of rolling schedules is common in industry; however, appropriate use of rolling schedules requires careful consideration as it poses many challenges for channel integration. First of all, one needs to be aware of the limitations of rolling schedules. Even if the best possible replenishment schedule is determined in each planning cycle, the long-term replenishment schedule may not necessarily represent the best possible schedule. This is usually the result of the length of each planning cycle. If each cycle is not long enough, it is not possible to determine the best replenishment schedule that would be found knowing demand beyond the end of the planning cycle.
Furthermore, periodic MPS updates can induce major changes in the detailed MRP replenishment schedules resulting in a phenomenon referred to as "schedule instability/nervousness." If not properly managed through the MPS design, this schedule nervousness can easily compromise the ability to effectively integrate manufacturer-supplier schedules leading to higher total system costs.
The use of advance order commitments (AOC) is a common method for facilitating integration. According to the policy, the manufacturer places multiple purchase orders in advance of the supplier's minimum replenishment lead-time, which gives the supplier visibility into future orders and allows for more efficient order fulfillment activities. The AOC policy serves as a major link between the manufacturer and supplier's replenishment schedules by defining the frequency and the length of the planning horizon during which the orders are released.
A stable MPS is a requirement for an effective AOC policy. However, the frequent changes brought by the rolling horizons make it difficult to establish a stable schedule. A common way of presenting a stable schedule is to freeze all or a portion of the MPS over the planning horizon. Freezing the schedule allows for no timing or quantity changes in the following planning iteration. The frozen orders are then shared with the supplier as AOCs. However, how much of the schedule should be frozen depends on the amount of flexibility the manufacturer is willing to give up since freezing the schedules reduces his flexibility in the next planning iteration that can increase his production and inventory costs.
Traditionally, these decisions are made myopically, where optimizing the manufacturer's schedule (with no regards to the impact on the supplier's scheduling) is of main concern. Supply chain integration, on the other hand, requires an effective MPS/AOC policy that considers the trade off between the manufacturer's desire for schedule flexibility and the supplier's need for a stable demand (manufacturer order) stream.
Based on our experience with industry and our research efforts, we found out that the supplier's order size flexibility is the major driver for the most effective MPS/AOC policy design and the total system costs. In case of high vendor flexibility with relatively low replenishment fixed costs, the supplier's economic benefit from the AOCs is relatively small since he can respond to manufacturer orders on a lot-for-lot basis. This maximizes the manufacturer's flexibility by allowing him to release purchase orders to the supplier as late as possible without adversely impacting the supplier's schedule or the system costs. When the supplier's flexibility is low, the best policy design requires a long frozen schedule to minimize the system costs. In this case, the supplier benefits from consolidating multiple AOCs when the manufacturer loses schedule flexibility in order to release more orders.
Results indicate that if a myopic approach is taken and the manufacturer's schedule flexibility drives the policy design, the system costs are 900% higher than the optimal system costs that should follow the supplier's schedule settings. This finding also provides guidance on supplier selection. If a manufacturer needs to operate under short planning horizons and shorter frozen schedules, efforts should be directed towards finding a highly flexible supplier that can respond effectively on a lot-for-lot basis. It is clear that MPS/AOC policy design in supply chains need to be carefully and jointly managed.
Funda Sahin, Ph.D., is Associate Professor of Logistics, Department of Marketing & Logistics, The University of Tennessee. For over 50 years, University of Tennessee (UT) faculty have played a major role in the supply chain/logistics arena -- conducting innovative research, publishing leading-edge findings, writing industry-standard textbooks, and creating benchmarks for successful corporate supply chain management. 2009 U.S. News and World Report ranked the University of Tennessee College of Business Administration a Top-25 school among top-tier public universities, up 12 positions from last year. The college's supply chain management/logistics program now ranks #5 among top-tier public universities. Certification is available. http://SupplyChain.utk.edu
Interested in information related to this topic? Subscribe to our weekly Value-chain eNewsletter.
