Gaining IS Business Value through Big Data Analytics: A Case Study of the Energy Sector

Faculty/Professorship: Information Systems and Energy Efficient Systems  
Author(s): Sodenkamp, Mariya; Kozlovskiy, Ilya; Staake, Thorsten
Title of the compilation: ICIS 2015 Proceedings
Corporate Body: 35th International Conference on Information Systems (ICIS), Fort Worth, 2015
Publisher Information: AIS Electronic Library (AISeL)
Year of publication: 2015
Pages: 19
Language(s): English
Following decades of stability and comfortable margins, utility companies today face
strong pressure from regulatory bodies and competitors. As a response to the market
dynamics, many have initiated a transformation from a “provider” to a service
company, yet realize that their customer insights that would be necessary to
successfully develop and market new services are sparse. We argue that the required
information is contained in consumption data that is available to utility companies. We
demonstrate how data analytics and machine learning make sense out of such data and
add value to organizations. Using datasets containing annual electricity consumption
information of private households, we apply and test in field experiments a Support
Vector Machines algorithm that predicts probabilities of individual costumers to sign up
on an energy efficiency portal. We show that signup rates can be doubled and argue
that classification tools provide customer insights at low cost and at scale.
Keywords: Business value of IS/value of IS, Decision Support Systems (DSS), Data analysis, Green IT/IS
Type: Conferenceobject
Year of publication: 23. May 2016