ARMS — application of AI and OR methods to resource management

This paper documents work on automating resource management in BT Retail. BT Retail manages BT's access network and provides telecommunications services to its customers. BT Retail's field engineers are allocated jobs via an information system known as Work Manager. In order to proactively...

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Bibliographic Details
Published inBT technology journal Vol. 25; no. 3-4; pp. 249 - 253
Main Authors Owusu, G., Voudouris, C., Dorne, R., Ladde, C., Anim-Ansah, G., Gasson, K., Connolly, G.
Format Journal Article
LanguageEnglish
Published Ipswich British Telecommunications PLC 01.07.2007
Subjects
Artificial intelligence
Automation
Carriers
Costs
Customer services
Employment
Forecasting
Management
Planning
Quality of service
Rain
Resource management
Scheduling
Skills
Studies
Workloads
United Kingdom > UK
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Summary:This paper documents work on automating resource management in BT Retail. BT Retail manages BT's access network and provides telecommunications services to its customers. BT Retail's field engineers are allocated jobs via an information system known as Work Manager. In order to proactively position the engineers (i.e. resources) so as to service jobs in an optimal manner, resource managers are involved in analysing the profiles of engineers in the light of incoming jobs and 'selecting' those profiles that will yield best quality of service and reduce operational costs. A profile is a set of attributes that define a resource's capabilities (i.e. skills), capacity (i.e. availability), and location (i.e. area). Resource planning involves identifying an 'optimal' set of resource profiles. Accurate workload forecasting is sine qua non for optimal resource planning. To this end we have developed ARMS, Automated Resource Management System, a suite of components for workload forecasting and resource planning. [PUBLICATION ABSTRACT]
ISSN:1358-3948
1573-1995
DOI:10.1007/s10550-007-0081-x