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A Systems Thinking Approach to Data-Driven Product Development

Published online by Cambridge University Press:  26 May 2022

T. Langen ,
K. Falk  and
M. Mansouri
T. Langen*
Affiliation:
University of South-Eastern Norway, Norway
K. Falk
Affiliation:
University of South-Eastern Norway, Norway
M. Mansouri
Affiliation:
University of South-Eastern Norway, Norway
*
tommy.langen@usn.no

Abstract

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The amount of information in our society and its opportunities have given rise to Big Data research. The systems supplier industry needs suitable tools and methods to ensure the harvest and utilization of Big Data in their product development. This paper used Systems Thinking to analyze the current state in the industry and suggested leverage points for further research direction. The findings suggest that the research project should emphasize the industry cases, the collaboration between the companies and academia, develop a Big Data systems architecture, and maintain a socio-technical view.

Keywords

product developmentsocio-technical systemsbig data analysissystems thinkingsystemigram
Type
Article
Information
Proceedings of the Design Society , Volume 2: DESIGN2022 , May 2022 , pp. 1915 - 1924
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2022.

References

Arnold, R. and Wade, J. (2015), “A Definition of Systems Thinking: A Systems Approach”, Procedia Computer Science, Vol. 44, pp. 669–678, 10.1016/j.procs.2015.03.050.Google Scholar
Boardman, J. and Sauser, B. (2008), Systems Thinking: Coping with 21st Century Problems, CRC Press.Google Scholar
Checkland, P. (1999), Systems Thinking, Systems Practice: Includes a 30-Year Retrospective, Wiley.Google Scholar
De Mauro, A., Greco, M. and Grimaldi, M. (2016), “A formal definition of Big Data based on its essential features”, Library Review, Emerald Group Publishing Limited, Vol. 65 No. 3, pp. 122–135, 10.1108/LR-06-2015-0061.Google Scholar
Gharajedaghi, J. (2011), Systems Thinking: Managing Chaos and Complexity: A Platform for Designing Business Architecture, Elsevier.Google Scholar
Majava, J., Harkonen, J. and Haapasalo, H. (2015), “The relations between stakeholders and product development drivers: practitioners’ perspectives,”, International Journal of Innovation and Learning Inderscience Publishers, Vol. 17 No. 1, pp. 59–78, 10.1504/IJIL.2015.066064.CrossRefGoogle Scholar
Müller, S.D. and Jensen, P. (2017), “Big data in the Danish industry: application and value creation”, Business Process Management Journal, Emerald Publishing Limited, Vol. 23 No. 3, pp. 645–670, 10.1108/BPMJ-01-2016-0017.CrossRefGoogle Scholar
Eigbe, Patrick, Sauser, A., and Boardman, B.J., J. (2010), “Soft systems analysis of the unification of test and evaluation and program management: A study of a Federal Aviation Administration's strategy”, Systems Engineering, Vol. 13 No. 3, pp. 298–310, 10.1002/sys.20150.Google Scholar
Pretorius, L., Benade, S. and Scribante, N.P. (2019), “The design of a research tool for conducting research in a complex socio-technical system”, South African Journal of Industrial Engineering, South African Institute of Industrial Engineers (SAIIE), Vol. 30 No. 4, pp. 143–155, 10.7166/30-4-2191.Google Scholar
Provost, F. and Fawcett, T. (2013), “Data Science and its Relationship to Big Data and Data-Driven Decision Making”, Big Data, Mary Ann Liebert, Inc., publishers, Vol. 1 No. 1, pp. 51–59, 10.1089/big.2013.1508.Google ScholarPubMed
Richmond, B. (1994), “Systems thinking/system dynamics: Let's just get on with it”, System Dynamics Review, Vol. 10 No. 2–3, pp. 135–157, 10.1002/sdr.4260100204.Google Scholar
Salado, A. and Nilchiani, R. (2013), “Contextual- and Behavioral-Centric Stakeholder Identification”, Procedia Computer Science, Vol. 16, pp. 908–917, 10.1016/j.procs.2013.01.095.Google Scholar
Smyth, D.S. and Checkland, P.B. (1976), “Using a systems approach: the structure of root definitions”, Journal of Applied Systems Analysis, Vol. 5 No. 1, pp. 75–83.Google Scholar
Staack, I., Amadori, K. and Jouannet, C. (2019), “A holistic engineering approach to aeronautical product development”, The Aeronautical Journal, Cambridge University Press, Vol. 123 No. 1268, pp. 1545–1560, 10.1017/aer.2019.51.CrossRefGoogle Scholar
Tao, F., Sui, F., Liu, A., Qi, Q., Zhang, M., Song, B., Guo, Z., et al. . (2019), “Digital twin-driven product design framework”, International Journal of Production Research, Taylor & Francis, Vol. 57 No. 12, pp. 3935–3953, 10.1080/00207543.2018.1443229.CrossRefGoogle Scholar
Trabucchi, D. and Buganza, T. (2018), “Data-driven innovation: switching the perspective on Big Data”, European Journal of Innovation Management, Emerald Publishing Limited, Vol. 22 No. 1, pp. 23–40, 10.1108/EJIM-01-2018-0017.Google Scholar
Urbinati, A., Bogers, M., Chiesa, V. and Frattini, F. (2019), “Creating and capturing value from Big Data: A multiple-case study analysis of provider companies”, Technovation, Vol. 84–85, pp. 21–36, 10.1016/j.technovation.2018.07.004.CrossRefGoogle Scholar
Zhan, Y., Tan, K.H., Li, Y. and Tse, Y.K. (2018), “Unlocking the power of big data in new product development”, Annals of Operations Research, Vol. 270 No. 1, pp. 577–595, 10.1007/s10479-016-2379-x.CrossRefGoogle Scholar