While processes are often continually monitored to see how they can be made more efficient to save on costs, it is has been shown that re-orienting processes to be more customer-centric can transform entire companies. The concept of a Demand-Driven Supply Network (DDSN) (O'Marah, 2004) specifically focuses on this level and focus of interprocess integration and re-orientation. As with the Toyota Production System (TPS) the concept of a DDSN in the context of any organization is to create higher levels of transparency and trust through shared process ownership. From this context both the Toyota Production System and DDSN model share the attribute of collaborative workflows that ensure higher levels of adoption and higher levels of accuracy as well (O'Marah, 2004).
Like the Toyota Production System, DDSNs are capable of becoming learning ecosystems (Dyer, Nobeoka, 2000) due to the intensive level of interprocess and system integration that is prevalent in these approaches to managing collaboration often on a global scope. The use of DDSN as a strategy for ensuring customer-centric processes gain the highest priority and also attain the highest levels of performance over time are critical. In fact the combining of the TPS concept for supply chain integration to the process level with the DDSN concept for demand management and customer-facing processes could be used for defining entire value chains in an organization.
Quantifying the extent of interprocess integration on the financial performance of an organization is a concept mentioned in the Introduction of this analysis. The Perfect Order (Novack, Thomas, 2004) is a key performance indicator companies rely on to verify and measure over time the extent of interprocess and system -- level linkages over time. Quantifying the performance of supply chains and their ability to stay focused on the goal of being demand driven is also captured in this metric. Ultimately The Perfect order metric is useful for measuring the accuracy, stability, transparency and trust generated throughout a supply chain (Columbus, 2008).
Measuring Interprocess Integration and Management Linkages in Supply Chains
Organizations have created process-based linkages in the form of connections that are rapidly becoming knowledge sharing networks (Dyer, Nobeoka, 2000). The corresponding growth in measuring the accuracy and performance of these networks on transaction accuracy and velocity is how The Perfect Order metric of performance (Columbus, 2008) has gained in prominence. In essence The Perfect Order measures the extent to which the process linkages throughout a supply chain are delivering consistently accurate and consistent performance (Novack, Thomas, 2004). One of the key factors in the growing popularity of this metric is the ability to quickly assess the impact of internal and external factors on the entire supply chain networks' performance. It is in effect a measure of the performance of a supply chain taking into account the key premises and concepts of Chaturvedi (2005).
For any company to attain excellent performance on the Perfect Order there are many other supply chain metrics that need to also be synchronized. The true objective of completing any level of supply chain interprocess synchronization is to ensure the highest level of responsiveness to customers. This is consistent with the core concepts of the DDSN model as mentioned earlier (O'Marah, 2004), yet seeks to extend this concept by including order velocity as a function of interprocess integration. Table 1, Measures of Supply Chain Performance, provide a summary of the most often used series of metrics by manufacturing and services companies alike in their pursuit of attaining high levels of performance on The Perfect Order measure of performance.
The Perfect Order is a measure of how effectively an organization has also been able to align its internal processes to their strategic plans. Not only does this measure of performance indicate the level of interprocess linkages and their correlation to management strategies, it actually measures how effectively the connections work. Inherent in any supply chain there is the need for close synchronization of processes across multiple, independent businesses (O'Marah, 2004). The Perfect Order is used as a means to share ownership of these key process areas and give each supplier in a supply chain network an opportunity to evaluate their performance. Each of the cycle times shown in Table 1 are often used as predictive indicators of how effective an entire network of suppliers are managing customer-facing processes (Columbus, 2008). This metric also shows the increase in accuracy based on interprocess transparency as well.
Table 1: Measures of Supply Chain Performance
Measure of Performance
What It Measures
Perfect Order
An order that is complete, accurate, on time, and in perfect condition
Demand Forecast Accuracy (DFA)
The difference between forecasted and actual demand
Quote-to-Cash Cycle Time
The time between when a quote is accepted by a prospect to when their first invoice is paid
Cash-to-Cash Cycle Time
The length of time between when a company spends cash to buy raw materials to the time cash flows back into the company from its cus-tomers. Includes the following metrics:
Ship to Customer Delivery -- Time taken from shipment of finished goods to delivery at customer's address Raw Materials
Receipt...
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