INCENTIVES AND PERFORMANCE IN LARGE-SCALE LEAN SOFTWARE DEVELOPMENT - An Agent-based Simulation Approach

Benjamin S. Blau, Tobias Hildenbrand, Matthias Armbruster, Martin G. Fassunge, Yongchun Xu, Rico Knapper

Abstract

The application of lean principles and agile project management techniques in the domain of large-scale software product development has gained tremendous momentum over the last decade. However, a simple transfer of good practices from the automotive industry combined with experiences from agile development on a team level is not possible due to fundamental differences stemming from the particular domain specifics – i.e. different types of products and components (material versus immaterial goods), knowledge work versus production systems as well as established business models. Especially team empowerment and the absence of a a hierarchical control on all levels impacts goal orientation and business optimization. In such settings, the design of adequate incentive schemes in order to align local optimization and opportunistic behavior with the overall strategy of the company is a crucial activity of central importance. Following an agent-based simulation approach with reinforcement learning, we (i) address the question of how information regarding backlog item dependencies is shared within and in between development teams on the product level subject to different incentive schemes. We (ii) compare different incentive schemes ranging from individual to team-based compensation. Based on our results, we are (iii) able to provide recommendations on how to design such incentives, what their effect is, and how to chose an adequate development structure to foster overall software product development flow by means of more economic decisions and thus resulting in a shorter time to market. For calibrating our simulation, we rely on practical experience from a very large software company piloting and implementing lean and agile for about three years.

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Paper Citation


in Bibtex Style

@conference{enase11,
author={Benjamin S. Blau and Tobias Hildenbrand and Matthias Armbruster and Martin G. Fassunge and Yongchun Xu and Rico Knapper},
title={INCENTIVES AND PERFORMANCE IN LARGE-SCALE LEAN SOFTWARE DEVELOPMENT - An Agent-based Simulation Approach},
booktitle={Proceedings of the 6th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,},
year={2011},
pages={26-37},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003418300260037},
isbn={978-989-8425-57-7},
}


in Harvard Style

S. Blau B., Hildenbrand T., Armbruster M., G. Fassunge M., Xu Y. and Knapper R. (2011). INCENTIVES AND PERFORMANCE IN LARGE-SCALE LEAN SOFTWARE DEVELOPMENT - An Agent-based Simulation Approach . In Proceedings of the 6th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE, ISBN 978-989-8425-57-7, pages 26-37. DOI: 10.5220/0003418300260037


in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,
TI - INCENTIVES AND PERFORMANCE IN LARGE-SCALE LEAN SOFTWARE DEVELOPMENT - An Agent-based Simulation Approach
SN - 978-989-8425-57-7
AU - S. Blau B.
AU - Hildenbrand T.
AU - Armbruster M.
AU - G. Fassunge M.
AU - Xu Y.
AU - Knapper R.
PY - 2011
SP - 26
EP - 37
DO - 10.5220/0003418300260037