Quality and reliability through common business environment

1995 ◽  
Vol 7 (5) ◽  
pp. 7-15 ◽  
Author(s):  
Charles Tennant

Rover Group is the UK’s largest automotive manufacturer employing 35,000 people which designs, develops and manufactures vehicles in the small, medium, executive and specialist four‐wheel‐drive sectors. Describes the processes deployed at Rover to ensure that quality and reliability are designed into the product through the new product introduction process, in order to achieve the company quality strategy milestones. The quality and reliability processes have been developed as a project management framework, known internally as “common business environment”. Describes the product programme milestone philosophy and supporting processes such as design methodology, reliability management, cost management and programme timing synthetics. The processes are deployed into all project teams at Rover Group through a learning methodology called focused learning. Measurement of common business environment implementation is carried out at project Q&R reviews, which are based on the European Foundation for Quality Management self‐assessment criteria.

2003 ◽  
Vol 7 (3) ◽  
pp. 105-115 ◽  
Author(s):  
P.M. Herder ◽  
W.W. Veeneman ◽  
M.D.J. Buitenhuis ◽  
A. Schaller

2000 ◽  
Vol 19 (3) ◽  
pp. 169-180
Author(s):  
Pirkko Walden ◽  
Christer Carlsson ◽  
Shuhua Liu

Modern time managers have access to many more data sources than managers of earlier times, and better instruments and resources to deal with large amounts of data. In principle, this means that they have a better command of facts and should be able to work out better assessments of their business environment. In reality, however, information overflow and problems with the quality and reliability of information complicate the picture. We have a support system with intelligent agents to help managers conduct constantly active scanning and interpretation activities with hundreds of data sources. The system was built on a Java platform and has been enhanced and developed in several versions. The first implementation was at the Alko Group (the producers of the Finlandia vodka). The system is expected to provide mangers with a broad and comprehensive first approximation of environmental trends and events as needed, and will help them extract useful information from large volumes of data. (Originally presented at the ISDSS’99 Conference, Melbourne, July 19–22, 1999.)


Author(s):  
Irina Wedel ◽  
Michael Palk ◽  
Stefan Voß

AbstractSocial media enable companies to assess consumers’ opinions, complaints and needs. The systematic and data-driven analysis of social media to generate business value is summarized under the term Social Media Analytics which includes statistical, network-based and language-based approaches. We focus on textual data and investigate which conversation topics arise during the time of a new product introduction on Twitter and how the overall sentiment is during and after the event. The analysis via Natural Language Processing tools is conducted in two languages and four different countries, such that cultural differences in the tonality and customer needs can be identified for the product. Different methods of sentiment analysis and topic modeling are compared to identify the usability in social media and in the respective languages English and German. Furthermore, we illustrate the importance of preprocessing steps when applying these methods and identify relevant product insights.


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