From Big Data to Smart Data: Application to performance management

Amel Souifi (1, 2) , Zohra Cherfi-Boulanger (3) , Zolghadri Marc (1, 2, 4) , Maher Barkallah (5, 6) , Mohamed Haddar (5, 6)

1 QUARTZ - Laboratoire QUARTZ
2 ISAE-Supméca - ISAE-Supméca Institut Supérieur de Mécanique de Paris
3 Roberval - Roberval
4 LAAS-ISI - Équipe Ingénierie Système et Intégration
5 LA2MP - Laboratoire de recherche de Mécanique, Modélisation et Production
6 ENIS - École Nationale d'Ingénieurs de Sfax | National School of Engineers of Sfax

In the context of digitalization, some companies are considering a transition to Industry 4.0 to ensure greater flexibility, productivity and responsiveness. The implementation of a relevant performance management system is then a real necessity to measure the degree of achievement of these objectives. In the era of Industry 4.0, the potential access to large amounts of data, i.e. Big Data, poses new challenges to the design and implementation of these systems. With the exponential growth of data generated from different sources, there is a need for extensive exploitation of data for performance management. Given the large volume of data, the speed at which it is generated and the variety of data sources, the manufacturing sector is facing with the challenge of creating value from large data sets. This paper introduces some potential benefits of Big Data for business and in particular its role in performance management systems. However, the key idea is that Big Data are not always neither available nor necessary. Authors focus on the concept of smart data, the result of the transformation of Big Data, and define a set of necessary and sufficient conditions the data should satisfy to be considered as Smart. The paper presents some methods of smart data extraction. Such smart data will be used to feed the performance management system in order to obtain more accurate, timely and representative key performance indicators.

Mots clés: Big Data; Smart Data; Performance Management

Domaines: Sciences de l'ingénieur [physics]

Amel Souifi, Zohra Cherfi-Boulanger, Zolghadri Marc, Maher Barkallah, Mohamed Haddar. From Big Data to Smart Data: Application to performance management. IFAC-PapersOnLine, 2021, 54 (1), pp.857-862. ⟨10.1016/j.ifacol.2021.08.100⟩. ⟨hal-03837160⟩