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Software // Information Management

The Collaborative Effect

New business strategies and processes are putting pressure on IT to produce real-time information. Some of the most valuable stuff is held in manufacturing execution and plant processing systems. Integrating these resources is hard -- but competitive business value is the reward.

Investments made in production process and value chain systems are playing a larger role and gaining in value as companies move toward collaborative uses of data to support core business processes. Originally, companies acquired these systems to support narrow functional requirements such as production order tracking, quality assurance, warehouse management, or maintenance management. However, in the new environment of collaboration, information sharing, real-time business, and broader compliance requirements, their place and value in the corporate IT portfolio hierarchy is increasingly significant.

Gaining Attention

Manufacturing systems have long been largely ignored and taken for granted. Compared to the enterprise resource planning (ERP) systems, customer relationship (or requirements) management (CRM) applications, or even supply chain management (SCM) systems, companies have often treated production support needs such as manufacturing execution systems (MESs) or warehouse management applications as unwanted stepchildren. Although needed, loved, and protected by departmental managers, most plant systems have been difficult to justify on the basis of reduced costs and usually fall below the radar screens of most corporate IT managers.

Times are changing. Now, organizations are placing a much higher value on the information detail generated and used by events and processes within production and logistics worlds. This is where the value-adding action is — especially within manufacturing organizations but increasingly in many concerns where operating in near real time is critical. Reports about yesterday's events are coming too late or lack the detail necessary to support daily business decisions. In the "sense and respond" environment of many modern businesses, data generated by events as they're occurring offers the best basis for management decisions and actions.

The Manufacturing System

It's difficult to easily identify or define the full range of applications that are used to accomplish production because industries are different and vendors have never hesitated to add to the confusion by using labeling to suggest differences. The broad definition begins with a holistic view that includes the complete production system infrastructure, the collection of business processes that provide the event-by-event real-time management, and the execution of the planned production requirements. But even that isn't an adequate definition until we include each enterprise in the value chain on both the supplier and demand sides.

In an individual plant there could easily be 40 or more applications generating information or controlling manufacturing processes. Figure 1, which I used in an earlier article (see Resources), shows many of the typical plant processes. Although the term has wide meanings, for purposes of this article I'll describe the collection of these applications as the MES and/or the enterprise production system.

Figure 1
Figure 1: Manufacturing execution system.

Life would be easy if the plant processes were as simple as Figure 1's illustration suggests. Unfortunately, reality is a bit messier, with plants typically running 20 to 40 different applications that have been installed over the past decade or more. Within a multi-plant company or within a supply chain, the number of applications can grow to hundreds of disparate data generators and information sources. The value of these applications has been typically based on each system as a standalone answer to a particular set of operation conditions. Considering the aggregate value of the manufacturing execution system doesn't happen because business tends to think of these applications within the confines of a data-centric view.

Because the data-centric view is narrow and focuses on the original requirements to support a specific process, organizations tend to design and build functionality with a very inward sense. As an example, consider an application designed to support the quality assurance department. Although important quality management issues (including statistical process control, nonconformance measurement and statistics, corrective action support, in-process test, and more) are usually included, rarely will the package address or have any connection to equally important issues, such as work-in-progress tracking, cost variance, and scheduling, for example.

Early material requirements planning (MRP) systems were often described as closed-loop systems. The operator entered data; the software did the calculation; and clear truths emerged. It was indeed a closed loop that focused on internal mechanisms (pure logic unadulterated by outside forces) to deliver answers. This inward focus toward a narrowly identified list of departmental functions drives the frequent reference to many plant systems as "islands of information." We can envision a much greater value for these systems when we alter our thinking away from the data-centric to a process-centric view.

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