

de Recherche et d’Innovation
en Cybersécurité et Société
Barrad, S.; Gagnon, S.; Valverde, R.
An analytics architecture for procurement Journal Article
In: International Journal of Information Technologies and Systems Approach, vol. 13, no. 2, pp. 73–98, 2020, ISSN: 1935570X (ISSN), (Publisher: IGI Global).
Abstract | Links | BibTeX | Tags: Big data, Business process management, Complex event processing, Complex event processing (CEP), Computer science, Cost reduction, Digital transformation, Emerging technologies, Enterprise Architecture, Information technology, Machine learning, Predictive analytics, Procurement, Procurement organizations, Proposed architectures, Rules based systems, Skill shortage, Supply chain management, Technology limitations
@article{barrad_analytics_2020,
title = {An analytics architecture for procurement},
author = {S. Barrad and S. Gagnon and R. Valverde},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083561161&doi=10.4018%2fIJITSA.2020070104&partnerID=40&md5=79790ea0afaa8174f59e639d7c9ce917},
doi = {10.4018/IJITSA.2020070104},
issn = {1935570X (ISSN)},
year = {2020},
date = {2020-01-01},
journal = {International Journal of Information Technologies and Systems Approach},
volume = {13},
number = {2},
pages = {73–98},
abstract = {Procurement transformation and pure cost reduction are no longer a novelty in today's modern business world. Procurement, as a core business function, plays a key role given its ability to generate value for the firm. From maximizing supplier value to minimizing contract leakage, challenges seldomly lack in this department. In fact, both resource and skill shortages and technology limitations are typically "top-of-mind" for Procurement Executives. Many research articles around the concept of cost reduction however, limited literature has been published in the areas of Artificial Intelligence, analytics and Rules-Based Systems and their specific application in Procurement. This article proposes a new enterprise architecture, leveraging emerging technologies to guide procurement organizations in their digital transformation. Our intent is to discuss how analytics, business rules and complex event processing (CEP) can be explored and adapted to the world of procurement to help reduce costs. This article concludes by suggesting an approach to implement the proposed architecture. Copyright © 2020, IGI Global.},
note = {Publisher: IGI Global},
keywords = {Big data, Business process management, Complex event processing, Complex event processing (CEP), Computer science, Cost reduction, Digital transformation, Emerging technologies, Enterprise Architecture, Information technology, Machine learning, Predictive analytics, Procurement, Procurement organizations, Proposed architectures, Rules based systems, Skill shortage, Supply chain management, Technology limitations},
pubstate = {published},
tppubtype = {article}
}
Nabelsi, V.; Gagnon, S.
Information technology strategy for a patient-oriented, lean, and agile integration of hospital pharmacy and medical equipment supply chains Journal Article
In: International Journal of Production Research, vol. 55, no. 14, pp. 3929–3945, 2017, ISSN: 00207543, (Publisher: Taylor and Francis Ltd.).
Abstract | Links | BibTeX | Tags: Administrative data processing, Agile manufacturing systems, Artificial intelligence, Biomedical equipment, Budget control, Business process management, Decision support system (dss), Decision support systems, Enterprise resource management, Hospitals, Infusion pump, Patient-oriented, pharmacy inventory, Pumps, Radio frequency identification (RFID), Reengineering, Supply chain management, Supply chain managements (SCM)
@article{nabelsi_information_2017,
title = {Information technology strategy for a patient-oriented, lean, and agile integration of hospital pharmacy and medical equipment supply chains},
author = {V. Nabelsi and S. Gagnon},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84981229289&doi=10.1080%2f00207543.2016.1218082&partnerID=40&md5=7b476ebaef87d06a411d3c3c683a0362},
doi = {10.1080/00207543.2016.1218082},
issn = {00207543},
year = {2017},
date = {2017-01-01},
journal = {International Journal of Production Research},
volume = {55},
number = {14},
pages = {3929–3945},
abstract = {Both public and private hospitals are increasingly under pressure to reduce costs while improving patient care across all medical disciplines and departments. Hospitals must become patient-oriented, lean, and agile in order to properly realign and integrate health care processes, helping to reconcile efficiency imperatives with patient needs and hospital mission. One of the highest potential for improvement can be found in supply chain management (SCM) practices for medical supplies, which often represent more than 40% of a hospital’s operating budget. We report on 3 case studies of business process management and reengineering projects, relying on advanced information technology, focused on the supply chains of two major urban hospitals, involving $2 million in minimum stocks for drug inventory. Case study 1 deals with an in-depth analysis of SCM practices around a key medical asset in pharmaceutical supply, i.e. infusion pumps. Case study 2 builds upon the findings of case 1, and proposes an radio-frequency identification solution to support a new hospital-wide asset location process and system, aiming for just-in-time availability of infusion pumps for critical drugs administration. Case study 3 complements cases 1 and 2 by analysing the feasibility of integrating the various components of the hospital pharmacy inventories, which in turn could be integrated to asset location systems. Our 3 case studies lead us to a number of conclusions on how hospitals can develop a patient-oriented, agile, and lean perspectives and practices, as well as ensure the proper integration of patient needs within optimised supply chains. © 2016 Informa UK Limited, trading as Taylor & Francis Group.},
note = {Publisher: Taylor and Francis Ltd.},
keywords = {Administrative data processing, Agile manufacturing systems, Artificial intelligence, Biomedical equipment, Budget control, Business process management, Decision support system (dss), Decision support systems, Enterprise resource management, Hospitals, Infusion pump, Patient-oriented, pharmacy inventory, Pumps, Radio frequency identification (RFID), Reengineering, Supply chain management, Supply chain managements (SCM)},
pubstate = {published},
tppubtype = {article}
}
Nabelsi, V.; Gagnon, S.
Detecting constraints in supply chain reengineering projects: Case study of data and process integration in a hospital pharmacy Proceedings Article
In: A., Zaremba M. Sasiadek J. Dolgui (Ed.): IFAC-PapersOnLine, pp. 106–111, 2015, ISBN: 24058963 (ISSN), (Issue: 3 Journal Abbreviation: IFAC-PapersOnLine).
Abstract | Links | BibTeX | Tags: Administrative data processing, Artificial intelligence, Business Process, Business process management, Business process management (BPM), Business process re-engineering, Case-studies, Data integration, Data mining, Data models, Data structures, Data warehouses, Decision support system, Decision support system (dss), Decision support systems, Enterprise resource management, Extract transform and load, Extract Transform and Load (ETL), Hospitals, Information management, Integration, Process management, Project case, Re-engineering projects, Reengineering, Supply chain management, Supply Chain Management (SCM), Supply chain managements (SCM), System architectures, Verification method, Verification of information system
@inproceedings{nabelsi_detecting_2015,
title = {Detecting constraints in supply chain reengineering projects: Case study of data and process integration in a hospital pharmacy},
author = {V. Nabelsi and S. Gagnon},
editor = {Zaremba M. Sasiadek J. Dolgui A.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84953887968&doi=10.1016%2fj.ifacol.2015.06.066&partnerID=40&md5=ce9be2cbe2fdcfc4872793c13f4228a2},
doi = {10.1016/j.ifacol.2015.06.066},
isbn = {24058963 (ISSN)},
year = {2015},
date = {2015-01-01},
booktitle = {IFAC-PapersOnLine},
volume = {28},
pages = {106–111},
abstract = {This paper discusses how messy data may be a hidden failure factor that Business Process Reengineering (BPR) projects typically cannot detect during the planning phase. Our case study deals with Supply Chain Management (SCM) within two major urban hospitals, involving $2 million in minimum stocks for drug inventory. Our project addresses the feasibility of the hospital's data warehousing integration, especially at the stage of Extract, Transform, and Load (ETL). We conclude with a proposed system architecture audit and verification method that may serve to guide reengineering project planning and execution. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.},
note = {Issue: 3
Journal Abbreviation: IFAC-PapersOnLine},
keywords = {Administrative data processing, Artificial intelligence, Business Process, Business process management, Business process management (BPM), Business process re-engineering, Case-studies, Data integration, Data mining, Data models, Data structures, Data warehouses, Decision support system, Decision support system (dss), Decision support systems, Enterprise resource management, Extract transform and load, Extract Transform and Load (ETL), Hospitals, Information management, Integration, Process management, Project case, Re-engineering projects, Reengineering, Supply chain management, Supply Chain Management (SCM), Supply chain managements (SCM), System architectures, Verification method, Verification of information system},
pubstate = {published},
tppubtype = {inproceedings}
}