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On the relationship between advanced analytics and business value

Type and Duration

PhD-Thesis, since September 2015

Coordinator

Hilti Chair of Business Process Management

Main Research

Business Process Management

Field of Research

Business Process Management

Description

The emergence of big data has stimulated large investments into advanced analytics solutions while companies are still striving to determine whether those investments generate measurable business value. Although multiple case studies and vendor reports have highlighted the importance and strategic value of advanced analytics, large-scale and reliable empirical evidence about the payoff of advanced analytics investments remains scarce.

This dissertation focuses on disentangling relationship between advanced analytics and business value. It aims to provide robust empirical evidence for the effects of advanced analytics adoption on firm productivity and performance, and to determine boundary conditions that could constrain or increase firm's ability to benefit from advanced analytics adoption.

By achieving those goals this research will contribute to the body of knowledge in the areas of IT value and investment, on the one hand, and the business side of advanced analytics, on the other hand. Futhermore, estimations and timeframes for expected payoffs from advanced analytics in various industries with consideration of company characteristics and other context parameters would support organizations in deriving business value from advanced analytics investments.

Keywords

Big Data Analytics, Advanced analytics, Firm Performance, Productivity, Econometric Analysis Analysis, IT Geschäftswert