- Data, Statistics and AI for Well-Being of People and Organisations
- A cura di Luigi Fabbris, Alberto Franci, Pietro Renzi
Evaluating M2M data as a potential alternative for official business statistics through an experimental approach
- Giovanni Gualberto Di Paolo
- Paola Bosso
- Diego Distefano
- Pasquale Papa
- © 2026 Author(s) |
- CC BY 4.0
- DOI: 10.36253/979-12-215-1062-1.36
Amid the digital transformation of production and increasing data availability, finding alternatives to traditional enterprise surveys is crucial for official statistics. A multi-source approach leveraging emerging Industry 5.0 technologies is being explored to improve data integration and statistical production. An experimental study was launched, focusing on industrial production volume within a specific sector. The first phase involved interviews with ERP system developers to assess data structure and compliance with statistical requirements. The second phase engages enterprises using these ERP platforms to evaluate the feasibility of producing statistics aligned with European standards, while also assessing data usability and enterprise acceptance. The experiment aims to test the quality, feasibility, and efficiency of ERP-generated data for statistics, emphasizing automated machine-to-machine (M2M) data transmission per Industry 5.0 principles. It also documents methodology and preliminary results to support scalable solutions. Digitalizing business processes can reduce data collection costs and burdens, enhancing timeliness and accuracy. Supported by public digital transition incentives, statistical institutes seek to integrate alternative data sources for more efficient and sustainable official statistics. Challenges remain, including high setup costs, limited ERP use among SMEs, software heterogeneity, and semantic misalignments between ERP taxonomies and Istat classifications. Therefore, enterprise cooperation, data standardization, and interoperability are essential. Preliminary findings highlight benefits and challenges, providing a basis for replicable methods and future integration of innovative data sources in official statistics.
- Keywords:
- Industry 5.0,
- Machine-to-Machine (M2M),
- official statistics,
- multi-source data collection,
- ERP systems,
- businesses,
- experimental approach,
ISTAT, Italian National Institute of Statistics, Italy
ISTAT, Italian National Institute of Statistics, Italy
ISTAT, Italian National Institute of Statistics, Italy
ISTAT, Italian National Institute of Statistics, Italy
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Informazioni sul capitolo
Titolo del capitolo
Evaluating M2M data as a potential alternative for official business statistics through an experimental approach
Autori
Giovanni Gualberto Di Paolo, Paola Bosso, Diego Distefano, Pasquale Papa
Lingua
Inglese
DOI
10.36253/979-12-215-1062-1.36
Opera sottoposta a peer review
Anno di pubblicazione
2026
Copyright
© 2026 Author(s)
Licenza d'uso
Licenza dei metadati
Informazioni bibliografiche
Titolo del libro
Data, Statistics and AI for Well-Being of People and Organisations
Curatori
Luigi Fabbris, Alberto Franci, Pietro Renzi
Opera sottoposta a peer review
Numero di pagine
420
Anno di pubblicazione
2026
Copyright
© 2026 Author(s)
Licenza d'uso
Licenza dei metadati
Editore
Firenze University Press
DOI
10.36253/979-12-215-1062-1
ISBN Print
979-12-215-1061-4
eISBN (pdf)
979-12-215-1062-1
eISBN (xml)
979-12-215-1063-8
Collana
Applied Statistics Series