Integration of procure-to-pay (P2P) processes with end-to-end automation and decision-making workflows positions procurement at the crossroads of massive data flows. The adoption of advanced analytics, AI, and ML technologies is gaining significant momentum across procurement and sourcing platforms, including contract management, strategic sourcing, procure-to-pay, and supplier risk & performance management domains.
According to the SPARK Matrix Procure-to-pay, 2021 report ‘’Many organisations are looking at deploying advanced analytics to gain critical information for assessing issues and opportunities. P2P vendors are enhancing their advanced analytics capabilities to enable organisations to gain comprehensive insights into suppliers, purchases, spend, procurement process metrics, and cash flow. Several P2P vendors, like ELCOM, are offering AI-driven P2P capabilities for improved product classification and mapping, spend classification and mitigating third-party supplier risks with real-time insights.’’
At ELCOM, artificial Intelligence plays a significant role in advanced data analytics. Our analytics business intelligence tool utilises AI/ML and helps take advantage of large datasets that we generate for our customers. Our BI tool captures good quality information by slicing and dicing large chunks of data captured in our systems to create 2 different types of reports for our customers:
- Strategic dashboards that give an overview to the management in the form of a heat map and enhance decision making
- Tactical reports that are to be used by the end-users like contract managers to run their own jobs daily
Advancements in data visualisation allow our customers to gain more detailed insights into spend profiles and opportunities for cost savings and real-time performance monitoring with advanced reporting and KPI monitoring capabilities.
ELCOM is working in partnership with The University of Strathclyde.
The project focuses on the economic, social, and environmental impact of procurement at the local level i.e., demonstrating the direct and indirect benefits of public sector procurement. Data Analytics and AI-driven data play a crucial role in the project. ELCOM exploits AI as the optimal solution for data deduplication. Our database has hundreds of thousands of supplier records and deduplication is a common problem. Deduplication refers to a method of eliminating a dataset’s redundant data. In a secure data deduplication process, an algorithm identifies extra copies of data and deletes them, so that a single record can then be stored. Data deduplication allows users to reduce redundant data and more effectively manage backup activity, as well as ensuring cost savings, and load balancing benefits.
Multiple new generation algorithms using artificial-intelligence (AI) scan our PECOS & EVOLVE databases containing thousands of supplier records in a fraction of time to radically improve the supplier-identification process. Data analytics powered by AI thus helps in improving efficiency by reducing man-hours and turnaround time as 80% of the matches are done correctly using our intelligent algorithm in a quicker and efficient way.
Machine learning and artificial intelligence can significantly improve an organisations’ end-to-end procurement performance by providing robust data collection to data cleansing and transformation, predictive analytics to provide granular insights on spending, robust data discovery from contract repository, automated execution of various e-sourcing and procure-to-pay processes, and such other features. As per the Quadrant Knowledge Solutions’ analysis of the overall market, procurement technologies are becoming collaborated, automated, and intelligent.
