In search of a better investment metric, researchers began to study Economic Value Added, or EVA, which was introduced in 1991 by Stern Stewart & Co in their book, "The Quest for Value" (Turvey, 2000). Stern Stewart & Co devised EVA as a better alternative to evaluate investment projects within the corporate finance field, later to be considered for use as a performance metric for investor use. A wide array of multinational corporations, such as Coca-Cola, Briggs and Stratton, and AT&T adopted the EVA method, which led to EVA's worldwide acclaim. Several points in the study reveal that EVA does not offer less risk, higher returns, and more adaptability for an investor. In fact, EVA underperformed the traditional portfolio performance metrics in key measurements including mean returns, and confidence intervals. EVA is a difficult performance metric to calculate, with several complex components that can be calculated in several different ways such as NOPAT, cost of equity, and cost of debt. Any information that is inaccurate or lacking can significantly impact the outcomes. Traditional performance metrics, on the other hand, such as ROA, ROE, and E/P are simple to calculate with few components, and only one way to calculate them.

Productivity and efficiency are the tools used in managing performance. This study researches and implements best practices that lead to best performance. A customer quality defined standard has to be created by benchmarking the Information Technology Service Regions which may be used to help decision-makers or management make informed decisions about (1) the effectiveness of service systems, (2) managing the performance of Information Technology Service Regions. Waiting lines or queues are an everyday occurrence and may take the form of customers waiting in a restaurant to be serviced or telephone calls waiting to be answered. The model of waiting lines is used to help managers evaluate the effectiveness of service systems. It determines precisely the optimal number of employees that must work at the centralised service desk. A Data Envelopment Analysis (DEA) methodology is used as a benchmarking tool to locate a frontier which is then used to evaluate the efficiency of each of the organizational units responsible for observed output and input quantities. The inefficient units can learn from the best practice frontier situated along the frontier line. / Thesis (M.Sc. (Computer Science))--North-West University, Vaal Triangle Campus, 2009.

Productivity and efficiency are the tools used in managing performance. This study researches and implements best practices that lead to best performance. A customer quality defined standard has to be created by benchmarking the Information Technology Service Regions which may be used to help decision-makers or management make informed decisions about (1) the effectiveness of service systems, (2) managing the performance of Information Technology Service Regions. Waiting lines or queues are an everyday occurrence and may take the form of customers waiting in a restaurant to be serviced or telephone calls waiting to be answered. The model of waiting lines is used to help managers evaluate the effectiveness of service systems. It determines precisely the optimal number of employees that must work at the centralised service desk. A Data Envelopment Analysis (DEA) methodology is used as a benchmarking tool to locate a frontier which is then used to evaluate the efficiency of each of the organizational units responsible for observed output and input quantities. The inefficient units can learn from the best practice frontier situated along the frontier line. / Thesis (M.Sc. (Computer Science))--North-West University, Vaal Triangle Campus, 2009.

Productivity and efficiency are the tools used in managing performance. This study researches and implements best practices that lead to best performance. A customer quality defined standard has to be created by benchmarking the Information Technology Service Regions which may be used to help decision-makers or management make informed decisions about (1) the effectiveness of service systems, (2) managing the performance of Information Technology Service Regions. Waiting lines or queues are an everyday occurrence and may take the form of customers waiting in a restaurant to be serviced or telephone calls waiting to be answered. The model of waiting lines is used to help managers evaluate the effectiveness of service systems. It determines precisely the optimal number of employees that must work at the centralised service desk. A Data Envelopment Analysis (DEA) methodology is used as a benchmarking tool to locate a frontier which is then used to evaluate the efficiency of each of the organizational units responsible for observed output and input quantities. The inefficient units can learn from the best practice frontier situated along the frontier line. / Thesis (M.Sc. (Computer Science))--North-West University, Vaal Triangle Campus, 2009.