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Handbook of Management Scales/Process management

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Process management (alpha = 0.82; composite reliability = 0.81)

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Description

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Eight quality management practices were identified by the authors: customer focus, employee relations, management leadership, process management, product/service design, quality data and reporting, supplier quality management, and training.

Items

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  • Extent to which inspection, review, or checking of work is automated. (0.64)
  • Stability of production schedule/work distribution. (0.68)
  • Degree of automation of the process. (0.62)
  • Extent to which process design is "foolproof" and minimizes the chances of employee errors. (0.81)
  • Extent to which statistical techniques are used in order to reduce variance in processes. (0.64)

Items 1–4 were adapted from Saraph et al. (1989); item 5 was adopted from Anderson et al. (1995).

Source

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Process management (composite reliability = 0.89)

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Description

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The authors identify improvement and innovation as two critical plant level capabilities. These capabilities are each conceptualized as a second-order factor and measured through a distinct bundle of routines. The following routines underlying improvement capabilities are identified: continuous improvement, process management, and leadership involvement in quality. The routines closely related to improvement capability are: search for new technologies, cross-functional product design, and processes and equipment development. The items to measure each routine were selected based on a review of the relevant literature. Items were included that have been used in prior studies. A panel of five academic researchers and managers with expertise in manufacturing operations reviewed each of the items.

Definition

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Process management is based on the view that an organization consists of systems of interrelated processes. It typically involves efforts to map, improve, and adhere to organizational processes.

Items

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  • A large percent of the processes on the shop floor are currently under statistical quality control.
  • We make extensive use of statistical techniques to reduce variance in processes.
  • We use charts to determine whether our manufacturing processes are in control.
  • We monitor our processes using statistical process control.

Source

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