Mitra, A and Munir, K (2019) Influence of big data in managing cyber assets. Built Environment Project and Asset Management, 9(4), pp. 503-514. ISSN 2044-124X
Abstract
Purpose: Today, Big Data plays an imperative role in the creation, maintenance and loss of cyber assets of organisations. Research in connection to Big Data and cyber asset management is embryonic. Using evidence, the purpose of this paper is to argue that asset management in the context of Big Data is punctuated by a variety of vulnerabilities that can only be estimated when characteristics of such assets like being intangible are adequately accounted for. Design/methodology/approach: Evidence for the study has been drawn from interviews of leaders of digital transformation projects in three organisations that are within the insurance industry, natural gas and oil, and manufacturing industries. Findings: By examining the extant literature, the authors traced the type of influence that Big Data has over asset management within organisations. In a context defined by variability and volume of data, it is unlikely that the authors will be going back to restricting data flows. The focus now for asset managing organisations would be to improve semantic processors to deal with the vast array of data in variable formats. Research limitations/implications: Data used as evidence for the study are based on interviews, as well as desk research. The use of real-time data along with the use of quantitative analysis could lead to insights that have hitherto eluded the research community. Originality/value: There is a serious dearth of the research in the context of innovative leadership in dealing with a threatened asset management space. Interpreting creative initiatives to deal with a variety of risks to data assets has clear value for a variety of audiences.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | databases; estimation; forecasting; social media |
| Index terms: | methodology, insurance, social media, evidence, vulnerability, quantitative analysis, variability, interview, real-time data, forecasting, big data, manufacturing industry, asset management, estimation, transformation, database |
| Subjects: | evaluation and assessment methods, data collection methods, business, technology adoption, data analysis and analytics, financial and cost management, economic analysis, prediction and forecasting, research methods, industry analysis, information systems, environmental hazards, statistical analysis, data management, asset management |
| Topics: | Digital Applications, Sustainability, Research Practice, Business Strategy, Cost Management |
| Descriptive scope: | 5 PCTEA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here