Hostname: page-component-7479d7b7d-767nl Total loading time: 0 Render date: 2024-07-11T01:12:05.689Z Has data issue: false hasContentIssue false
  • English
  • Français

WORKING AGILE TO SPEED UP RESEARCH WITH INDUSTRY: FIVE INDEPENDENCE PRINCIPLES

Published online by Cambridge University Press:  19 June 2023

Massimo Panarotto ,
Ola Isaksson  and
Rikard Söderberg
Massimo Panarotto*
Affiliation:
Chalmers University of Technology
Ola Isaksson
Affiliation:
Chalmers University of Technology
Rikard Söderberg
Affiliation:
Chalmers University of Technology
*
Panarotto, Massimo, Chalmers University of Technology, Sweden, massimo.panarotto@chalmers.se

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

One of the obstacles to the ability of research to make an impact on industry resides on the research process itself. Today, there is a need to accelerate the means for research to support industrial transformation. At the same time, there is the need to maintain scientific rigorousness, which often requires time. To solve this trade-off, this paper evaluates existing research approaches through the lenses of agile development. The analysis is based on a simulation of research process architectures, and on observations made over several research projects with industry. The results of this analysis highlight five light-but-sufficient rules of research project behavior to keep momentum, motivation and trust when doing research with industry. The paper demonstrates the use of these five rules in a “research sprint” conducted iwith two automotive OEMs.

Keywords

Design methodsDesign methodologyResearch methodologies and methodsvalidationagile development
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 3919 - 3928
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), 2023. Published by Cambridge University Press

References

Aguinis, H., Pierce, C.A., Bosco, F.A. and Muslin, I.S., 2009. First decade of Organizational Research Methods: Trends in design, measurement, and data-analysis topics. Organizational Research Methods, 12(1), pp.69–112.CrossRefGoogle Scholar
Bajpai, S., Eppinger, S.D. and Joglekar, N.R., 2019. The structure of agile development under scaled planning and coordination. In DS 97: Proceedings of the 21st International DSM Conference (DSM 2019), Monterey, California, September 23rd-25th 2019 (pp. 1–10).CrossRefGoogle Scholar
Barth, A., Caillaud, E. and Rose, B., 2011. How to validate research in engineering design?. In DS 68-2: Proceedings of the 18th International Conference on Engineering Design (ICED 11), Impacting Society through Engineering Design, Vol. 2: Design Theory and Research Methodology, Lyngby/Copenhagen, Denmark, 15.-19.08. 2011 (pp. 41–50).Google Scholar
Beck, K., Beedle, M., Van Bennekum, A., Cockburn, A., Cunningham, W., Fowler, M., Grenning, J., Highsmith, J., Hunt, A., Jeffries, R. and Kern, J., 2001. Manifesto for agile software development.Google Scholar
Blessing, L.T. and Chakrabarti, A., 2009. DRM: A design reseach methodology (pp. 13–42). Springer London.CrossRefGoogle Scholar
Brown, T., 2008. Design thinking. Harvard business review, 86(6), p.84.Google ScholarPubMed
Browning, T.R. and Eppinger, S.D., 2002. Modeling impacts of process architecture on cost and schedule risk in product development. IEEE transactions on engineering management, 49(4), pp.428–442.CrossRefGoogle Scholar
Cantamessa, M., 2003. An empirical perspective upon design research. Journal of Engineering Design, 14(1), pp.1–15.CrossRefGoogle Scholar
Cash, P., Isaksson, O., Maier, A. and Summers, J., 2022. Sampling in design research: Eight key considerations. Design studies, 78, p.101077.CrossRefGoogle Scholar
Checkland, P. and Scholes, J., 1990. Soft systems methodology in action, John Wileys Sons Inc.Google Scholar
Cocchi, N., Dosi, C. and Vignoli, M., 2021. The Hybrid Model MatrixEnhancing Stage-Gate with Design Thinking, Lean Startup, and Agile: Managers can use the Hybrid Model Matrix to decide when to use design thinking, Lean Startup, or Agile with Stage-Gate to boost new product development. Research-Technology Management, 64(5), pp.18–30.Google Scholar
Cockburn, A., 2006. Agile software development: the cooperative game. Pearson Education.Google Scholar
Cross, N., 2018. Developing design as a discipline. Journal of Engineering Design, 29(12), pp.691–708.CrossRefGoogle Scholar
Da Silva, T.S., Martin, A., Maurer, F. and Silveira, M., 2011, August. User-centered design and agile methods: a systematic review. In 2011 AGILE conference (pp. 77–86). IEEE.Google Scholar
Dingsøyr, T., Nerur, S., Balijepally, V. and Moe, N.B., 2012. A decade of agile methodologies: Towards explaining agile software development. Journal of systems and software, 85(6), pp.1213–1221.CrossRefGoogle Scholar
Douglass, B.P., 2015. Agile systems engineering. Morgan Kaufmann.Google Scholar
Eckert, C., Stacey, M. and Clarkson, P.J., 2004. The lure of the measurable in design research. Design Society.Google Scholar
Eckert, C.M., Stacey, M.K. and Clarkson, P.J., 2003. The spiral of applied research: A methodological view on integrated design research.Google Scholar
Fernández, I.A., Panarotto, M. and Isaksson, O., 2020, May. Identification of technology integration challenges at two global automotive OEMs. In Proceedings of the Design Society: DESIGN Conference (Vol. 1, pp. 2245–2254). Cambridge University Press.Google Scholar
Gericke, K., Eckert, C., Campean, F., Clarkson, P.J., Flening, E., Isaksson, O., Kipouros, T., Kokkolaras, M., Köhler, C., Panarotto, M. and Wilmsen, M., 2020. Supporting designers: moving from method menagerie to method ecosystem. Design Science, 6, p.e21.CrossRefGoogle Scholar
Gericke, K., Kramer, J. and Roschuni, C., 2016. An exploratory study of the discovery and selection of design methods in practice. Journal of Mechanical Design, 138(10), p.101109.CrossRefGoogle Scholar
Guertler, M.R., Kriz, A. and Sick, N., 2020. Encouraging and enabling action research in innovation management. R&D Management, 50(3), pp.380–395.Google Scholar
Hernandez, R., Kreye, M. and Eppinger, S., 2019, June. Applicability of agile and scrum to product-service systems. In EurOMA Conference (pp. 1–10).Google Scholar
Isaksson, O., 2015. A Collaborative Engineering Design Research Model—An Aerospace Manufacturer's View. In Impact of Design Research on Industrial Practice: Tools, Technology, and Training (pp. 363–381). Cham: Springer International Publishing.CrossRefGoogle Scholar
Isaksson, O., Eckert, C., Panarotto, M. and Malmqvist, J., 2020, May. You need to focus to validate. In Proceedings of the Design Society: DESIGN Conference (Vol. 1, pp. 31–40). Cambridge University Press.Google Scholar
Jagtap, S., Warell, A., Hiort, V., Motte, D. and Larsson, A., 2014. Design methods and factors influencing their uptake in product development companies: a review. In DS 77: Proceedings of the DESIGN 2014 13th International Design Conference.Google Scholar
Kapurch, S.J. ed., 2010. NASA systems engineering handbook. Diane Publishing.Google Scholar
Keijzer-Broers, W.J. and de Reuver, M., 2016. Applying agile design sprint methods in action design research: prototyping a health and wellbeing platform. In Tackling Society's Grand Challenges with Design Science: 11th International Conference, DESRIST 2016, St. John's, NL, Canada, May 23-25, 2016, Proceedings 11 (pp. 68–80). Springer International Publishing.CrossRefGoogle Scholar
Lewin, K., 1946. Action research and minority problems. Journal of social issues, 2(4), pp.34–46.CrossRefGoogle Scholar
Lewin, K., 1947. Frontiers in group dynamics: II. Channels of group life; social planning and action research. Human relations, 1(2), pp.143–153.Google Scholar
Lindau, B., Lorin, S., Lindkvist, L. and Söderberg, R., 2016. Efficient contact modeling in nonrigid variation simulation. Journal of Computing and Information Science in Engineering, 16(1).CrossRefGoogle Scholar
Maier, J.F., Wynn, D.C., Biedermann, W., Lindemann, U. and Clarkson, P.J., 2014. Simulating progressive iteration, rework and change propagation to prioritise design tasks. Research in Engineering Design, 25, pp.283–307.CrossRefGoogle Scholar
Mårtensson, P., Fors, U., Wallin, S.B., Zander, U. and Nilsson, G.H., 2016. Evaluating research: A multidisciplinary approach to assessing research practice and quality. Research Policy, 45(3), pp.593–603.CrossRefGoogle Scholar
Martin, J.N., 2020. Systems engineering guidebook: A process for developing systems and products. CRC press.CrossRefGoogle Scholar
Mitsuyuki, T., Hiekata, K., Goto, T. and Moser, B., 2017. Evaluation of project architecture in software development mixing waterfall and agile by using process simulation. Journal of Industrial Integration and Management, 2(02), p.1750007.CrossRefGoogle Scholar
Mumford, E., 2001. Advice for an action researcher. Information Technology & People, 14(1), pp.12–27.CrossRefGoogle Scholar
Newton, P. and Burgess, D., 2016. Exploring types of educational action research: Implications for research validity. In The Best Available Evidence (pp. 33–46). Brill.CrossRefGoogle Scholar
Otto, K., Hölttä-Otto, K., Simpson, T.W., Krause, D., Ripperda, S. and Ki Moon, S., 2016. Global views on modular design research: linking alternative methods to support modular product family concept development. Journal of Mechanical Design, 138(7), p.071101.CrossRefGoogle Scholar
RD&T, 2011, RD&T Manual, Version 1.13, Gothenburg, Sweden. Retrieved online 2023-04-03: http://rdnt.se/software-tool/Google Scholar
Stylidis, K., Wickman, C. and Söderberg, R., 2020. Perceived quality of products: a framework and attributes ranking method. Journal of Engineering Design, 31(1), pp.37–67.CrossRefGoogle Scholar
Suh, N.P., 1995. Axiomatic design of mechanical systems.CrossRefGoogle Scholar
Vermaas, P.E., 2013. The coexistence of engineering meanings of function: four responses and their methodological implications. AI EDAM, 27(3), pp.191–202.Google Scholar
Wallin, J., Isaksson, O., Larsson, A. and Elfström, B.O., 2014. Bridging the gap between university and industry: Three mechanisms for innovation efficiency. International Journal of Innovation and Technology Management, 11(01), p.1440005.CrossRefGoogle Scholar
Wang, G.G., 2003. Adaptive response surface method using inherited latin hypercube design points. J. Mech. Des., 125(2), pp.210–220.CrossRefGoogle Scholar
Wassenaar, H.J. and Chen, W., 2003. An approach to decision-based design with discrete choice analysis for demand modeling. J. Mech. Des., 125(3), pp.490–497.CrossRefGoogle Scholar
Wynn, D.C. and Eckert, C.M., 2017. Perspectives on iteration in design and development. Research in Engineering Design, 28, pp. 153–184.CrossRefGoogle Scholar