This paper proposes a methodology that helps understanding and modeling the relationship between business and technical benchmarking in BDT (Big Data Technology) use cases. Technical benchmarks are aimed to help IT managers in making technical decisions by measuring key performance metrics of the underlying BDT infrastructure. Business benchmarks are aimed to associate BDT use cases with measurable business benefits. In principle, making the right technical choices is key to deliver business benefits. However, the relationship between technical and business benchmarking is rarely addressed in previous research, which mostly focuses on either side of benchmarking. This methodology takes a first step towards bridging the gap between technical and business benchmarking. The paper illustrates the methodology and discusses providing pre-liminary evidence gained from a desk analysis.

Bridging the Gap Between Technical and Business Benchmarking

Francalanci Chiara;Giacomazzi Paolo;Pernici Barbara
2019-01-01

Abstract

This paper proposes a methodology that helps understanding and modeling the relationship between business and technical benchmarking in BDT (Big Data Technology) use cases. Technical benchmarks are aimed to help IT managers in making technical decisions by measuring key performance metrics of the underlying BDT infrastructure. Business benchmarks are aimed to associate BDT use cases with measurable business benefits. In principle, making the right technical choices is key to deliver business benefits. However, the relationship between technical and business benchmarking is rarely addressed in previous research, which mostly focuses on either side of benchmarking. This methodology takes a first step towards bridging the gap between technical and business benchmarking. The paper illustrates the methodology and discusses providing pre-liminary evidence gained from a desk analysis.
2019
The 13th Mediterranean Conference on Information Systems (MCIS), Naples, Italy, 2019
Business KPI, technical benchmark, performance metric, Big Data, Big Data Technology, BDT
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1159989
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