Data analytics in product development: Implications from expert interviews | IEEE Conference Publication | IEEE Xplore

Data analytics in product development: Implications from expert interviews


Abstract:

An increasing number of technical products are being equipped with connectivity components, which enables the collection of use phase data. Such data helps to better desi...Show More

Abstract:

An increasing number of technical products are being equipped with connectivity components, which enables the collection of use phase data. Such data helps to better design products or understand customer needs. Available studies only take a cross-industry perspective on data analytics. Due to longer development and product life cycles, engineering companies work under special circumstances. The authors therefore conducted expert interviews to better understand the needs and current practices in engineering companies. Experts highlighted the potential of data analytics for instance in requirements engineering. Experts also mentioned the various problems that occur when identifying and implementing use cases. Besides support for technical issues, experts raised the need for additional support during the initial planning phase.
Date of Conference: 10-13 December 2017
Date Added to IEEE Xplore: 12 February 2018
ISBN Information:
Electronic ISSN: 2157-362X
Conference Location: Singapore
Citations are not available for this document.

I. Introduction

Digitalization is progressing fast and changes products, companies, business models, and competition. Technical products no longer consist only of physical parts but also of sensors, microprocessors and additional parts for the connectivity [1]. Studies indicate that the number of connected products will vastly increase in the future [2]. The rise of connected products is one reason for the large amount of available data worldwide, often referred to as Big Data [3]. The term Big Data comprises not only data, but also analytical methods (data analytics), processes and technologies [4]. Five characteristics describe Big Data: volume, variety, veracity, velocity, and value [5].

Cites in Papers - |

Cites in Papers - IEEE (5)

Select All
1.
Kunxiong Ling, Jan Thiele, Thomas Setzer, "Loss-Aware Histogram Binning and Principal Component Analysis for Customer Fleet Analytics", IEEE Open Journal of Intelligent Transportation Systems, vol.5, pp.160-173, 2024.
2.
Kunxiong Ling, "Digital Twinning From Vehicle Usage Statistics for Customer-Centric Automotive Systems Engineering", IEEE Open Journal of Intelligent Transportation Systems, vol.4, pp.966-978, 2023.
3.
Timm Fichtler, Khoren Grigoryan, Christian Koldewey, Roman Dumitrescu, "Towards a Data-Driven Product Management – Concepts, Advantages, and Future Research", 2023 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD), pp.1-6, 2023.
4.
Suman De, Ivy Baroi, "Evolution of Analytics in Product Management for Data-driven Feature Prioritization", 2022 Seventh International Conference on Parallel, Distributed and Grid Computing (PDGC), pp.588-593, 2022.
5.
Julian Wilberg, Tobias Kalla, Manuel Fetscher, Franz Rimböck, Christoph Hollauer, Mayada Omer, "Development of a Use Phase Data Strategy for Connected Products: A Case Study in Industry", 2018 Portland International Conference on Management of Engineering and Technology (PICMET), pp.1-12, 2018.

Cites in Papers - Other Publishers (3)

1.
Maurice Meyer, Melina Panzner, Christian Koldewey, Roman Dumitrescu, "17 Use Cases for Analyzing Use Phase Data in Product Planning of Manufacturing Companies", Procedia CIRP, vol.107, pp.1053, 2022.
2.
Maurice Meyer, Melina Panzner, Christian Koldewey, Roman Dumitrescu, "Towards Identifying Data Analytics Use Cases in Product Planning", Procedia CIRP, vol.104, pp.1179, 2021.
3.
Maurice Meyer, Ingrid Wiederkehr, Christian Koldewey, Roman Dumitrescu, "UNDERSTANDING USAGE DATA-DRIVEN PRODUCT PLANNING: A SYSTEMATIC LITERATURE REVIEW", Proceedings of the Design Society, vol.1, pp.3289, 2021.

References

References is not available for this document.