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CONCEPT FOR A PERSONA DRIVEN RECOMMENDATION TOOL FOR PROCESS MODELLING APPROACHES

Published online by Cambridge University Press:  27 July 2021

Katharina Helten ,
Claudia Eckert ,
Kilian Gericke  and
Pieter Vermaas
Katharina Helten*
Affiliation:
Vitesco Technologies GmbH
Claudia Eckert
Affiliation:
The Open University
Kilian Gericke
Affiliation:
University of Rostock
Pieter Vermaas
Affiliation:
Delft University of Technology
*
Helten, Katharina, Vitesco Technologies GmbH, BU Sensing & Actuation, Thermal Management Actuation, Germany, katharina.helten@vitesco.com

Abstract

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In order to ensure successful product development processes, manifold modelling approaches have been developed, which cover a wide range of aspects such as responsibilities, duration of activities and dependencies. Still, an industry standard does not exist. Users of process modelling approaches are driven by different targets depending on the respective role. Currently, practitioners need to evaluate strengths and weaknesses of each approach by themselves and find little guidance for the selection.

As a consequence, users might select unsuitable approaches and do not get the expected result. Thus, the intended applications of the model such as analyses or an optimization of the process are hampered. This could heavily affect companies´ success by product or project failures.

The paper shows the concept of a recommendation tool that enables a suitable and effective selection of process modelling approaches. Key element is the description of relevant use cases and personas that represent the various needs of both different company types as well as different roles within such as process modellers and users. By identifying the most relevant case, each practitioner will be successfully guided to the most suitable modelling approach.

Keywords

Design processProcess modellingDesign practiceRecommendation toolPersonas
Type
Article
Information
Proceedings of the Design Society , Volume 1: ICED21 , August 2021 , pp. 711 - 720
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), 2021. Published by Cambridge University Press

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