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Your improvement efforts will encounter major delays and budget overruns if your supply chain architecture doesn t have integrity in the form of integrated applications, accurate data, and documented processes. You can t introduce new supply chain practices without a solid foundation. During the IT investment boom of the late 1990s, many companies added new best-in-breed applications such as advanced planning and scheduling, customer relationship management (CRM), and supplier relationship management (SRM) to their portfolios of systems. These applications often were added without fully reworking the underlying business processes and
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data. Despite the advent of enterprise application integration tools, the skills needed to create bulletproof integration were not available, and software vendors were slow to provide off-the-shelf integration for common ERP packages. Advances such as portal technology, which can connect multiple locations with multiple applications, are helping to resolve these integration challenges, but many companies still have applications islands (see Figure 2-5) stand-alone applications that support only one piece of the end-to-end process. The best supply chains have an integrated flow of information. Unfortunately, too many companies use nonintegrated applications that require manual data reentry, changes in data formats, and multiple quality checks. Missing links between processes and information systems result in fragile supply chains that depend on specific individuals, manual handoffs, and work-arounds. The result is a high risk of error, longer cycle times, and added costs.
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Application islands do not support process integration.
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CHAPTER 2 Core Discipline 2: Develop an End-to-End Process Architecture
For example, one of our clients was implementing new demand/ supply planning processes, supported by a supply chain planning application. As part of the new process, the company wanted to track forecast consumption over time to ensure that demand and supply were balanced on an ongoing basis. This required gathering data from two separate sources an existing CRM application, which held data related to customer orders, and the new supply chain planning application, which contained information about incoming supply. Unfortunately, the ordering information described products one way, whereas the planning application used different data to describe products for the purpose of planning. The chief information officer was concerned that resolving this disconnect would require restructuring the entire data model, a major undertaking. In the end, an answer was found that integrated the flow of information between the two applications. A translation table was developed that took the elements of a customer s order and translated them into planning items. Data quality and availability are as important as integration between applications. The typical company orchestrates hundreds, if not thousands, of supply chain activities and decisions every day, each depending on a wide range of data: master data (supplier lead times, material masters, prices, terms and conditions), transaction data (sales orders, inventory data, purchase orders, etc.), and analytics (which compare actual performance with target performance to ensure process management). Despite the importance of accurate data, one study estimates that between 15 and 20 percent of a typical organization s data are wrong or unusable.8 Inaccurate or missing data lead to errors and ineffective execution. Consider the example of a procurement system that captures quantities ordered and confirmed by suppliers but doesn t capture backorders quantities ordered but not confirmed. Backorder management must be done either manually, at the risk of error, or not at all, which could easily lead to overordering and excess inventory. Inaccurate or unusable data also create manual work, reducing speed and efficiency and adding costs to the supply chain. In the worst case, inaccurate data can drive poor performance. As an example, we had a client that felt the repercussions of inaccurate data for almost a year after it first implemented a supply chain planning solution. When preparing for the cutover to the new system, it had entered standard defaults for supply lead times, with every intention of updating the data before the go live date. Unfortunately, day-to-day tasks took precedence, and no one got around to updating the supplier lead-time data resulting in an increase in materials inventory (lead times too short) for some materials and inventory shortages (lead times too long) for others.
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