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Assessing the value of data. An approach to evaluate the technology driven benefits of smart product data

 
: Schuh, Günther; Kreutzer, Ramon; Patzwald, Marc

:

Kocaoglu, Dundar F. (Ed.) ; Portland International Center for Management of Engineering and Technology -PICMET-:
Portland International Conference on Management of Engineering and Technology, PICMET 2017. Proceedings : Technology Management for Interconnected World; July 9 - 13, 2017, Portland, Oregon, USA
Portland/Or.: Portland State University, 2017
ISBN: 978-1-890843-36-6
10 pp.
Portland International Conference on Management of Engineering and Technology (PICMET) <2017, Portland/Or.>
English
Conference Paper
Fraunhofer IPT ()
Innovationsmanagement; Technologiemanagement

Abstract
Data-centered and customer-oriented business models shape the digitalization to be the central social, economic and technological development of current knowledge societies. A great share of these new business models is enabled by smart product field data, which is generated during the product´s phase of utilization. To capture the diluting value and commodification of mechanical products, companies within the manufacturing industry as the provider of smart products have to position themselves strategically against new competitors, e.g. from the IT sector, to avoid being victim to the "digital Darwinism". A growing number of manufacturing companies already starts to see the revenue and differentiation potential of smart product data as a competitive advantage. Similar to other intangible assets, a comprehensive understanding of the quality, scope and value of smart product field data is a basic prerequisite for its monetization. However, so far the majority of companies are lacking this basic understanding for the value of their smart product data, thus not being able to lever its potentials. Hence, this paper develops a model, which supports manufacturing companies in assessing, if a generic set of field data generated by a smart product is able to provide value added for the user. In the model itself, field data of smart products as well as "digitally enabled functionalities" will be examined extensively. Subsequently, generic sets of field data as carrier of information will be mapped regarding their suitability for enabling functionalities, which represent a demand of information.

: http://publica.fraunhofer.de/documents/N-469946.html