Predictive Analytics Applications for Small and Medium-Sized Enterprises (SMEs) - A Mini Survey and Real-World Use Cases

Simon Bøgh; Daniel S. Hain; Emil Blixt Hansen; Simon Buus Jensen; Torben Tvedebrink; Roman Jurowetzki

doi:10.1007/978-3-031-15428-7_22

Predictive Analytics Applications for Small and Medium-Sized Enterprises (SMEs) - A Mini Survey and Real-World Use Cases

Simon Bøgh^*, Daniel S. Hain, Emil Blixt Hansen, Simon Buus Jensen, Torben Tvedebrink, Roman Jurowetzki

^*Corresponding author for this work

Research output: Contribution to book/anthology/report/conference proceeding › Book chapter › Research › peer-review

6 Citations (Scopus)

Abstract

Predictive analytics is becoming more mature and is gaining traction in smart manufacturing around the world. Over the past decade, predictive analytics has hence reached a plateau of productivity while techniques and tools became more robust and accessible. Small- and medium-sized enterprises have to seize these new opportunities in order to optimize and embed analytics in high-value business scenarios and improve their competitiveness. However, getting started with predictive modeling can seem like an insurmountable feat for SMEs, why inspiration and pointers to real-world applications can be valuable. In this paper, we first introduce current trends in predictive analytics followed by a mini survey showcasing interesting real-world use cases in SMEs. Finally, we present common algorithms and models, followed by two recent real-world applications in Danish SMEs.

Original language	English
Title of host publication	The Future of Smart Production for SME : A Methodological and Practical Approach Towards Digitalization in SMEs
Editors	Ole Madsen, Ulrich Berger, Charles Møller, Astrid Heidemann Lassen, Brian Vejrum Waehrens, Casper Schou
Number of pages	17
Publisher	Springer
Publication date	2022
Pages	263-279
ISBN (Print)	978-3-031-15427-0, 978-3-031-15430-0
ISBN (Electronic)	978-3-031-15428-7
DOIs	https://doi.org/10.1007/978-3-031-15428-7_22
Publication status	Published - 2022

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023. All rights reserved.

Keywords

Predictive analytics
Artificial Intelligence (AI)
Internet of Things (IoT)
Small- and medium-sized enterprises
Small and medium-sized enterprises (SMEs)
Use cases
Survey

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10.1007/978-3-031-15428-7_22

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Bøgh, S., Hain, D. S., Hansen, E. B., Jensen, S. B., Tvedebrink, T., & Jurowetzki, R. (2022). Predictive Analytics Applications for Small and Medium-Sized Enterprises (SMEs) - A Mini Survey and Real-World Use Cases. In O. Madsen, U. Berger, C. Møller, A. Heidemann Lassen, B. V. Waehrens, & C. Schou (Eds.), The Future of Smart Production for SME: A Methodological and Practical Approach Towards Digitalization in SMEs (pp. 263-279). Springer. https://doi.org/10.1007/978-3-031-15428-7_22

Bøgh, Simon ; Hain, Daniel S. ; Hansen, Emil Blixt et al. / Predictive Analytics Applications for Small and Medium-Sized Enterprises (SMEs) - A Mini Survey and Real-World Use Cases. The Future of Smart Production for SME: A Methodological and Practical Approach Towards Digitalization in SMEs. editor / Ole Madsen ; Ulrich Berger ; Charles Møller ; Astrid Heidemann Lassen ; Brian Vejrum Waehrens ; Casper Schou. Springer, 2022. pp. 263-279

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Bøgh, S , Hain, DS, Hansen, EB, Jensen, SB, Tvedebrink, T & Jurowetzki, R 2022, Predictive Analytics Applications for Small and Medium-Sized Enterprises (SMEs) - A Mini Survey and Real-World Use Cases. in O Madsen, U Berger, C Møller, A Heidemann Lassen, BV Waehrens & C Schou (eds), The Future of Smart Production for SME: A Methodological and Practical Approach Towards Digitalization in SMEs. Springer, pp. 263-279. https://doi.org/10.1007/978-3-031-15428-7_22

Predictive Analytics Applications for Small and Medium-Sized Enterprises (SMEs) - A Mini Survey and Real-World Use Cases. / Bøgh, Simon ; Hain, Daniel S.; Hansen, Emil Blixt et al.
The Future of Smart Production for SME: A Methodological and Practical Approach Towards Digitalization in SMEs. ed. / Ole Madsen; Ulrich Berger; Charles Møller; Astrid Heidemann Lassen; Brian Vejrum Waehrens; Casper Schou. Springer, 2022. p. 263-279.

Research output: Contribution to book/anthology/report/conference proceeding › Book chapter › Research › peer-review

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Bøgh S , Hain DS, Hansen EB, Jensen SB, Tvedebrink T, Jurowetzki R. Predictive Analytics Applications for Small and Medium-Sized Enterprises (SMEs) - A Mini Survey and Real-World Use Cases. In Madsen O, Berger U, Møller C, Heidemann Lassen A, Waehrens BV, Schou C, editors, The Future of Smart Production for SME: A Methodological and Practical Approach Towards Digitalization in SMEs. Springer. 2022. p. 263-279 doi: 10.1007/978-3-031-15428-7_22

Predictive Analytics Applications for Small and Medium-Sized Enterprises (SMEs) - A Mini Survey and Real-World Use Cases

Abstract

Bibliographical note

Keywords

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