@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}

}