falling into a functional rut. This is exemplified in the approach Kuiper Leda also takes with regard to optimizing lead times throughout the productions scheduling and fulfillment processes as well.
In summary, Kuiper Leda has many of the foundational processes, systems and roles in place to enable an efficient demand-driven supply chain network (Barrett, 2007), including the ability to synchronize suppliers, inbound quality management and inspection, production scheduling, manufacturing, and fulfillment. The maturation from MRP to ERP is evident in the same factors which illustrate how the company is becoming more adept at accomplishing its lean manufacturing objectives, beginning with attainment of JIT. Outsourcing excess demand for the ECUs also indicates a relatively high level of process maturity, knowledge management (Ferdows, 2006) and quality management expertise as well (Yamazaki, 2003). Kuiper Leda shows the potential to scale into more collaborative processes with their suppliers, opening up the opportunity to create even greater cost reductions, more accuracy in their measurement and reporting of supply chain performance, and as a result create even more profitable operations as a result.
Kuiper Leda Measures and Metrics
It is common to find manufacturers measuring a limited set of processes that are often siloed or only in a specific area of their companies -- often the ones that have the highest levels of performance over time that are not dependent on any other departments' cooperation. Myopic and mis-guided as this strategy is, it often happens in companies with extensive supply chains that rival Kuiper Leda's. What this manufacturer of Electronic Control Units (ECUs) and Radio Frequency identification (RFIO) tags for automotive manufacturers and OEMs must concentrate on is more of a quantifying of the performance of bringing more collaborative processes into their supply chains. The ability of manufacturers in OEM-centric industries to create more collaborative process workflows through these of key performance indicators (KPIs) and metrics of performance has been shown to enable greater shared accomplishment over time (Chatterjee, Satpathy, Ganguli, Kumaresh, 2002). Kuiper Leda needs to re-evaluate the processes that are in place with suppliers and revise them to be more collaboratively-based so that both risk and more accurate knowledge is shared. As Dr. Kasra Ferdows (2006) has commented in his analysis of the variations in the roles and knowledge generated by factories and the supplier relationships that support them, the greatest differentiator over time is the ability to capture and transform knowledge into a competitive advantage. Measuring collaboration throughout their supply chain and rewarding it can set in motion the dynamics to turn knowledge generation and use as a competitive advantage. The Toyota Production System (TPS) is often held up as an example of this type of strategy, where knowledge has become the greatest competitive asset and the ability to manage costs to lower levels through shared collaboration and trust has been shown. Measuring shared, collaborative processes is going to be the most efficient strategy for Kuiper Leda to accomplish this level of competitive performance.
Specifically looking at measuring and improving the extent to which Kuiper Leda can increase their supply chain performance through more effective collaboration, the use of the framework of Collaborative, Planning, and Forecasting & Replenishment (CPFR) needs to be considered (Truss, Wu, Saroop, Sehgal, 2006). Figure 1 provides a graphical representation of this framework, which has been used extensively in auto components manufacturers globally.
Collaborative Planning Forecasting & Replenishment (CPFR)
Applied to the Automotive Components Business
Source: (Truss, Wu, Saroop, Sehgal, 2006)
Putting into place a CPFR framework will give Kuiper Leda the ability to more effectively manage inventory levels and through more effective collaboration, be able to manage variation in demand as well. The CPFR framework can also serve as the basis for quantifying shared processes throughout the supply chain and creating measures of shared performance. The use of the AMR Research hierarchy of supply chain metrics (Hofman, 2004) where functional measures of shared process performance serve as the foundation for transaction-based metrics of order accuracy lead to the development of measures of order accuracy...
The use of the AMR Research hierarchy of supply chain metrics to define when the right order is delivered to the right customer, at the right price, in essence the perfect order (Hofman, 2004) needs to guide the use of metrics to measure collaboration as it relates to streamlining the Kuiper Leda's supply chains' use of metrics.
Second, the use of JIT in the context of broader supply chain collaboration and synchronization metrics needs to be put into the context of process and system integration, not measured by itself. The reliance on JIT as a means to reduce costs of capital and increase inventory turns while meeting customer delivery dates and expectations needs to become much more of a process based on shared ownership throughout the supply chain. Instead of being centered only within Kuiper Leda, JIT needs to have implications in Service Level Agreements (SLAs) and contracts with suppliers, partners, and support partners. Increasing the accuracy, accountability and auditability of JIT will result from this broader integration of the metric, in addition to discovering as to what creates causality of its values over time. JIT can also be used as a metric to evaluate how mature and therefore teachable upstream processes in their suppliers' supply chains are standardized enough, and therefore capable of being outsourced as well. For Kuiper Leda to gain knowledge, not price, as their greatest differentiator over time they need to transform the role of JIT away from being purely for measuring lean manufacturing and re-architect its structure to also encompass supplier management, supplier learning and knowledge transfer throughout a supply chain (Ferdows, 2006).
Third, Kuiper Leda needs to better measure, monitor and manage demand from it customers, automotive manufacturers and OEMs, concentrating on those metrics of performance that capture and quantify collaboration throughout their supply chains using Balanced Scorecards (Bhagwat, Sharma, 2007). The use of the CPFR framework can initially define these shared process workflows, yet taxonomies or organizations of metrics is required to ensure end-to-end processes are accurately measured. With Balanced Scorecards, Kuiper Leda will be able to also more open, and succinctly share information with their suppliers, creating more trust in the process. In addition to the transparency of this process, the real-time sharing of production schedules by Kuiper Leda and forecasts on the part of their suppliers will do much to alleviate the spikes in demand that the company has no visibility of today. All of these factors together, when synchronized, will enable a far more effective level of knowledge generation, and competitive advantage by process synchronization and speed in the Kuiper Leda supply chain.
Kuiper Leda needs to aggressively pursue more collaboratively-based processes throughout its supply chain, inclusive of Balanced Scorecards to CPFR and including SLAs that tie JIT inventory performance to suppliers as well. Not only does this spread the risk of supply chain performance, it serves to internalize the shared goals and priorities of the company with its suppliers as well. In conjunction with these initiatives, the company's reliance on MPR for production scheduling and sequencing needs to be re-evaluated in light of the more integrative nature of the processes they are relying on. Data in the case study suggests that order management is a crucial system and process workflow. By definition, Enterprise Resource Planning (ERP) systems concentrate on distributed order management workflows and also are adept at production scheduling, pricing, and supply chain management. Modules are often added to ERP systems to make them capable of integrated into supply chain planning, management and optimization workflows as well. These technological capabilities are secondary to the need on the part of Kuiper Leda to create more shared ownership of supply chain performance in the near-term, and shared knowledge in the long-term. Ultimately the many strategies that encompass their pursuit of lean manufacturing objectives within their supply chains, from JIT-based workflows, through forecasting, production scheduling and pricing, all must be focused on how to create a more demand-driven supply network.
Appendix A: Progression of Lean Manufacturing from JIT
Source: (Holweg, 2007)
Jane Barrett. (2007, November). Demand-Driven is an Operational Strategy. Industrial Management, 49(6), 14-19,5.
R Bhagwat, MK Sharma. (2007). Performance measurement of supply chain management using the analytical hierarchy process. Production Planning & Control, 18(8), 666.
Anjan Chatterjee, Aurobind Satpathy, Neal Ganguli, TV Kumaresh. (2002). Collaboration: Key to world class quality. Quality, 41(6), 50-53.
Debra Hofman. (2004, September). The Hierarchy of Supply Chain Metrics, Supply Chain Management Review, 8(6), 28-37.
Kasra Ferdows. (2006). Transfer of Changing Production Know-How. Production and Operations Management, 15(1), 1-9.
Matthias Holweg. (2007). The genealogy of lean production. Journal of Operations Management, 25(2), 420. Accessed from the Internet June 5, 2009 from location: http://www.lean.org/Community/Registered/ArticleDocuments/Holweg_Genealogy%20of%20Lean%20Production_JOM_2007.pdf
John F. Kros, Mauro Falasca, S Scott Nadler. (2006). Impact of just-in-time inventory systems on OEM suppliers. Industrial Management + Data Systems, 106(1/2), 224-241.
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