Using Visual Analytics to Diagnose Productivity and Quality Issues on IT Service Pools

Using Visual Analytics to Diagnose Productivity and Quality Issues on IT Service Pools

Victor Cavalcante (IBM Research, Brazil), Heloisa Candello (IBM Research, Brazil), Claudio Pinhanez (IBM Research, Brazil), Alan Braz (IBM Research, Brazil), Franklin Amorin (IBM Research, Brazil) and Nelson Nauata (IBM Research, Brazil)
DOI: 10.4018/978-1-4666-8496-6.ch008
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This chapter describes and validates the applicability of a visual analytics tool, named Workload Profile Analytics (WPA), in the context of incident management (IM) inside a large IT services provider. The WPA tool implements a method to evaluate the performance and quality of IM systems that uses temporal information from incident records (tickets). The method is based on a graphical representation, called Workload Profile Chart (WPC), which consists of a log-log chart obtained by computing and plotting the spreading of ticket data. Then, using the chart, a visual inspection is done to examine the concentration of tickets over the various areas of interest of the WPC and a diagnosis of potential issues is suggested. To illustrate how powerful WPA can be, two real world scenarios are depicted and used to validate the use of WPA in a large service delivery organization. Finally, some discussions about further improvements on the tool and research directions are done.
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IT outsourcing services has become a large global industry. Usually, the delivery of IT outsourcing services is often made through very large IT service organizations (IT service providers) whose operations involve a huge variety of support teams (IT analysts). Typically, those teams take care, simultaneously, of networks of thousands of servers, routers, storage devices and systems, and firewalls, among other IT equipment from multiple companies. (Rouse, 2009) offers a good review of the state of academic knowledge on IT outsourcing.

Although in recent years the IT-related services industry has demonstrated an increasing interest in science, design, and management of service systems (Maglio, Kieliszzewski, & Spohrer, 2010), the progress in the development and establishment of methods, best practices, and tools applicable to the complexity and scale of the modern IT service provider is limited. Some recent research work described in (Rouse & Basole, 2010), (Qiu, 2009), and (Banavar, Hartman, Ramaswamy, & Zherebtsov, 2010) have suggested models for IT service delivery systems but have not proposed systematic methods of performance evaluation and characterization of problems and issues.

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