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Statistical process control

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1. What is statistical process control?

2. How can Statistical Process Control methods help to minimize errors?

3. What are the potential benefits of this control process.

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Unisys Corp's Costly Experiment in Health Care Services

When Unisys Corp. expanded into the computerized health care service business thing looked rosy. It had just beat out Blue Cross/Blue Shield of Florida for an $86-million contract to serve Florida's state employee health-insurance services. Its job was to handle the 215,000 Florida employee's claims processing- a seemingly simple and lucrative growth area for an old-line computer company like Unisys.

But 1 year later the contract was not only torn up, Unisys was fined over $500,000 for not meeting quality standards. Here are two of the measures of quality, both attributes ( either defective or not defective) on which the firm was out of control:

1. Percent of claims processed with errors.

An audit over a 3-month period, by Coopers & Lybrand, found that Unisys made errors in 8.5% of claims processed. The industry standard is 3.5% defectives.

2. Percent of claims processed within 30 days.

For this attribute measure, a "defect" is a processing time longer than the contract's time allowance. In one month's sample, 13% of the claims exceeded the 30 day limit, far above the 5% allowed by the State of Florida.

The Florida contract was a migraine for Unisys, which underestimated the labor-intensiveness of health claims. CEO James Unruh pulled the plug on future ambitions in health care. Meanwhile, the State of Florida's Ron Poppel says, "we really need somebody that is in the insurance business.

Souces: Kight Ridder Tribune Business News (2/7/2002)

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Solution Summary

Statistical process control is examined. The potential benefits of this control process is determined.

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Introduction:

For a company to be able to meet effectively the needs of the customers, they need to continually improve quality standards of their services and products. Through effective quality control only then can quality problems be identifies right from their sources and effective steps of resolving these problems be undertaken. As noted by the quality problem that Unisys Corporation faced in not being able to meet client specification and quality standards of services provided, ineffective control of quality in a company can result to bad relations between the business and client and even demise of the business unit that has defects (Ridder, 2002). There are a number of tools that help in identifying quality control problems first and developing strategies to ensure that quality standards is not high as required but is continually improved. This paper analyses one of the tools of quality control and management: Statistical Process Control (SPC), and also looks at how such tool helps in minimizing errors and the potential benefits that accrue to a company using this control process

Statistical Process Control:

Statistical Process control is a quality improvement and control tool that statistically analyses various processes in order to determine whether they are performing properly or not. This tool analyses variations in processes to understand whether the variation is natural and falls within
the range of performance required or whether it is extreme and requires correction (Wisner, 2010; Reid, 2009).

Statistical process control method of total quality management was developed by Walter Shewhart in the 1920's and furthered by Edward Deming who noted that most variations in a ...

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