From Qualitative to Quantitative Data Valuation in Manufacturing Companies
- Since data becomes more and more important in industrial context, the question arises on how data-driven added value can be measured consistently and comprehensively by manufacturing companies. Currently, attempts on data valuation are primarily taking place on internal company level and qualitative scale. This leads to inconclusive results and unused opportunities in data monetization. Existing approaches in theory to determine quantitative data value are seldom used and less sophisticated. Although quantitative valuation frameworks could enable entities to transfer data valuation from an internal to an external level to take account of progress in digital transformation into external reporting. This paper contributes to data value assessment by presenting a four-part valuation framework that specifies how to transfer internal, qualitative to external, quantitative data valuation. The proposed framework builds on insights derived from practice-oriented action research. The framework is finally tested with a machine tool manufacturer using a single case study approach. Placing value on data will contribute to management’s capability to manage data as well as to realize data-driven benefits and revenue. [https://link.springer.com/chapter/10.1007/978-3-030-85902-2_19]
| Author: | Hannah Stein, Lennard HolstGND, Volker StichORCiDGND, Wolfgang Maass |
|---|---|
| URL: | https://link.springer.com/chapter/10.1007/978-3-030-85902-2_19 |
| DOI: | https://doi.org/10.1007/978-3-030-85902-2_19 |
| ISBN: | 978-3-030-85901-5 |
| ISBN: | 978-3-030-85902-2 |
| Parent Title (English): | Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems. IFIP WG 5.7 International Conference, APMS 2021, Nantes, France, September 5–9, 2021, Proceedings, Part II |
| Series (Serial Number): | IFIP advances in information and communication technology (631) |
| Publisher: | Springer |
| Place of publication: | Cham [u. a.] |
| Editor: | Alexandre Dolgui, Alain Bernard, David Lemoine, Gregor von Cieminski, David Romero |
| Document Type: | Conference Proceeding |
| Language: | English |
| Date of Publication (online): | 2023/08/21 |
| Date of first Publication: | 2021/08/31 |
| Release Date: | 2023/08/21 |
| Tag: | Industrie 4.0 case study research; data valuation framework; data value; industry 4.0; intangible assets |
| First Page: | 172 |
| Last Page: | 180 |
| FIR-Number: | SV7752 |
| Name of the conference: | IFIP WG 5.7 International Conference (APMS 2021) |
| place of the conference: | Nantes |
| Date of the conference: | 05.09.2021-09.09.2021 |
| Institute / Department: | FIR e. V. an der RWTH Aachen |
| Dienstleistungsmanagement | |
| Dewey Decimal Classification: | 6 Technik, Medizin, angewandte Wissenschaften / 62 Ingenieurwissenschaften |
