Business value of in-memory technology – multiple-case study insights

Author:

Bärenfänger Rieke,Otto Boris,Österle Hubert

Abstract

Purpose – The purpose of this paper is to assess the business value of in-memory computing (IMC) technology by analyzing its organizational impact in different application scenarios. Design/methodology/approach – This research applies a multiple-case study methodology analyzing five cases of IMC application scenarios in five large European industrial and service-sector companies. Findings – Results show that IMC can deliver business value in various applications ranging from advanced analytic insights to support of real-time processes. This enables higher-level organizational advantages like data-driven decision making, superior transparency of operations, and experience with Big Data technology. The findings are summarized in a business value generation model which captures the business benefits along with preceding enabling changes in the organizational environment. Practical implications – Results aid managers in identifying different application scenarios where IMC technology may generate value for their organizations from business and IT management perspectives. The research also sheds light on the socio-technical factors that influence the likelihood of success or failure of IMC initiatives. Originality/value – This research is among the first to model the business value creation process of in-memory technology based on insights from multiple implemented applications in different industries.

Publisher

Emerald

Subject

Industrial and Manufacturing Engineering,Strategy and Management,Computer Science Applications,Industrial relations,Management Information Systems

Reference65 articles.

1. Acker, O. , Gröne, F. , Blockus, A. and Bange, C. (2011), “In-memory analytics – strategies for real-time CRM”, Journal of Database Marketing & Customer Strategy Management, Vol. 18 No. 2, pp. 129-136.

2. Baesens, B. , Leuven, K.U. and Vanthienen, J. (2013), “Call for papers misq special issue on transformational issues of big data and analytics in networked business”, available at: www.misq.org/skin/frontend/default/misq/pdf/CurrentCalls/BigDataCFP.pdf (accessed 16 May 2014).

3. Bakos, Y.J. (1987), “Dependent variables for the study of firm and industry-level impacts of information technology”, Working Paper (CISR WP No. 161), Center for Information Systems Research Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, August.

4. Barney, J. (1991), “Firm resources and sustained competitive advantage”, Journal of Management, Vol. 17 No. 1, pp. 99-120.

5. Barua, A. , Kriebel, C.H. and Mukhopadhyay, T. (1995), “Information technologies and business value: an analytic and empirical investigation”, Information Systems Research, Vol. 6 No. 1, pp. 21-23.

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