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From the article: Though organizations are increasingly aware that the huge amounts of digital data that are being generated, both inside and outside the organization, offer many opportunities for service innovation, realizing the promise of big data is often not straightforward. Organizations are faced with many challenges, such as regulatory requirements, data collection issues, data analysis issues, and even ideation. In practice, many approaches can be used to develop new datadriven services. In this paper we present a first step in defining a process for assembling
data-driven service development methods and techniques that are tuned to the context in which the service is developed. Our approach is based on the situational method engineering approach, tuning it to the context of datadriven service development.

Published in: Reinhartz-Berger I., Zdravkovic J., Gulden J., Schmidt R. (eds)
Enterprise, Business-Process and Information Systems Modeling. BPMDS 2019, EMMSAD
2019. Lecture Notes in Business Information Processing, vol 352. Springer. The final authenticated
version of this paper is available online at https://doi.org/10.1007/978-3-030-20618-5_11.

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OrganisatieHogeschool Utrecht
AfdelingKenniscentrum Leren en Innoveren
LectoraatBetekenisvol Digitaal Innoveren
Gepubliceerd inEnterprise, Business-Process and Information Systems Modeling Uitgave: 352, Pagina's: 156-168
Datum2019-05-10
TypeConferentiebijdrage
DOI10.1007/978-3-030-20618-5_11
TaalEngels

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