Browsing by Author "Stander, Jacques B."

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    The modern asset: Big Data and Information Valuation
    (Stellenbosch : Stellenbosch University, 2015-12) Stander, Jacques B.; Vlok, P. J.; Jooste, J. L.; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.
    ENGLISH ABSTRACT: The volatile nature of business requires organizations to fully exploit all of their assets while always trying to gain the competitive edge. One of the key resources for improving efficiency, developing new technology and optimizing processes is data and information; with the arrival of Big Data, this has never been more true. However, even though data and information provide tangible and often indispensable value to organizations, they are not appropriately valued or controlled. This lack of valuation and control is directly related to the lack of a reliable and functional valuation method for them. This study takes a qualitative and inductive approach to developing Decision Based Valuation (DBV); a proof-of-concept information valuation method. DBV addresses the need to correctly value the data and information an organisation has and may require. Furthermore, DBV is presented with its valuation framework and value optimization and performance assessment tools. These tools address the issue of management and control of information, following in the footsteps of Physical Asset Management (PAM). By using complimentary valuation methods and attributes from PAM in combination with intangible asset valuation methods, DBV is able to capture what is essential to the value of information. Beginning with a background to Big Data and PAM, their value is made clear to reader. Furthermore, the difficulty and need for a valuation method catered towards information is presented. This will set the stage for the introduction of data and information principles as well as physical and intangible asset valuation methods. These methods are drawn upon for the development of DBV as well as the valuation framework it is based upon. The valuation framework acts as the foundation of DBV and addresses the core principle of information valuation. After detailing DBV in full, proposed value optimization and performance assessment tools are described. These tools are created to assist with the control and management of information. Concluding this study is the validation of both the method itself and the need for it. Combining depth interviews and case studies, the need and importance of a method such as DBV will become clearer to the reader. Furthermore, the success of DBV as a proof-of-concept is illustrated. The method presented in this study shows that it is possible to create a reliable and generic valuation method for Big Data and information. It sets a foundation for further research and development of the Decision Based Valuation method.