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How is measurement data used to reduce decision risk?

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A decision maker uses analysis of pertinent measurements as an objective foundation upon which to make a decision that carries minimal risk. A business decision influenced by measurements, for example, involves reducing the amount of overtime allowed to eight hours per week, since data over a six-month period indicates that a majority of workplace accidents occur during periods of overtime in excess of 10 hours per week.

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Measurement systems typically contain multiple measures and involve comparing a measurement to itself over time, against a preset goal or in relation to other measurements. Measurements sometimes serve to diagnose a problem, which then leads to a decision on the appropriate corrective action. In a manufacturing process, measurements reflecting descending production rates on a certain machine can form the basis for diagnosing the need to replace worn out equipment, or an increased number of complaints about excessive waiting times at a medical practice can diagnose over-scheduling or poor time management of a particular medical assistant.

While measurements as a means of reducing risk increasingly drive decision-making in business and personal affairs, the measurements themselves or the manner in which a business or individual understands or applies the measurements may actually increase the risks of making a poor decision. These risks to decision-making include selecting the wrong measurements, improper collection of data or inconsistency in the entering of data for analysis. Measurements can also lead to poor decisions on the part of those who lack the ability to properly comprehend the information provided. This is especially true in terms of health care information and the expectation that consumers make health care decisions based on a variety of sometimes complex and contradictory measurements. The presentation of numerical information is especially critical when it provides a decision-making foundation for less-numerate consumers.

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