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A number of writers in the service management literature have observed that because service quality is difficult to measure there is a danger that service organisations will neglect to measure it, despite the fact that service quality is often critical to their competitive business success.
The results of an empirical research project investigating the quality measurement systems of six multi‐site UK service organisations, all of which consider themselves to differentiate on the basis of service quality, are described. Two of the organisations were found to have very few quality measures and recognised that this was a major gap in their performance measurement systems. Two had developed a range of customer‐based measures of service quality which were reported regularly and widely in the organisations.
The other two companies had developed a wide range of internal and external, hard and soft quality measures. These companies used managers as well as customers to measure both tangible and intangible aspects of service. Internal measures were used to corroborate the perceptual measures drawn from customers and, conversely, the external measures were used to support service design and the setting of internal quality targets.
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To ensure that the learning continued to provide ongoing value, we supplemented the workshop with an Industrial Predictive Analytics and Machine Learning Planning Guide. This guide provided baseline information about the industrial analytics market, vendor profiles, and recommendations for considering analytics projects.
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Finding information on industries will require reviewing reports from multiple sources in order to get a complete picture of the industry. Key characteristics of the industry include geographic scope of the industry, the boundaries of the industry, and the dominant economic characteristics of the industry.