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AI Procurement Analytics for Value Enhancement

The growth of Artificial Intelligence (AI) Procurement Analytics studies in data science, machine learning, and AI enables data-driven companies to reach the next level of excellence. These new technologies and techniques allow a brand-new manner of extracting patterns from data and deriving data insights. Insights that assist data-driven companies to better understand what is happening and why it happened. Insights that permit procurement to predict what will happen, anticipate and prescribe actions, make use of ever more advanced analytics combined with AI’s power. This article focuses on how AI Procurement Analytics can further enhance the value chain across the procurement arena.

The Power of Triple-A

According to the 2020 HFS Top 10 “Triple-A Trifecta Services” research paper, Automation, Analytics, and Artificial Intelligence are the three digital transformation change agents that work along to deliver positive business outcomes. These change agents are each powerful, however once combined, they provide exponential value potential. The research paper highlights two vital points.

The first vital point is that these change agents intersect with each other. While each agent has a distinct value proposition (automation drives efficiency, smart analytics improves decision-making, and AI solves business problems), there is increasing convergence between the three agents. For example, smart analytics are increasingly dependent on AI tools such as natural language processing (NLP) to search-driven analytics, neural networks for data exploration, and learning algorithms to make predictive models.

The second vital point is that these change agents are nonlinear and also without a definite starting point. Transformation is not a linear progression, and companies can start anywhere across these three agents. It is not necessary to begin with, basic automation and then advance to AI-based automation. However, it is vital to appreciate the business problem that you are attempting to solve and then apply the relevant value lever or a mix of value levers.

Procurement Analytics for Managing Contracts

Contracting is an everyday activity in companies, but few companies do it efficiently or effectively. A tedious process and common challenges are consistency in contracts’ clauses, organizing and updating data in an orderly and fast manner. AI overcomes these challenges by changing the tools, influences, and affects the processes by which companies contract.

Firstly, AI offers effective contract management by identifying contract types, regardless of languages. The software is trained on an algorithm on a set of contracts, recognizes patterns, and extracts critical variables. It offers simple prediction, which has implications for due diligence by quickly sorting a large volume of contracts and individual flag contracts based on company-specified criteria.

Secondly, AI provides consistency of terms and usage in all contracts. Any changes required to the definition will be incorporated quickly and accurately by the software. Hence, omitting variation can be damaging to the company. AI allows efficient execution of contracts with data organized, key data points extracted, non-compliance identified, and prompt response to contracts’ unfavourable provisions. AI reduces the risk of human error by quickly identifying terms and clauses that are suboptimal in contracts.Thirdly, AI shifts the contract professionals’ focus from routine activities to high-value work such as shaping strategies and navigating complex legal problems. 


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Clifford Chua, ADPSM
Clifford Chua is a procurement professional with extensive experiences in EMS, contract manufacturing, semiconductors and the Oil & Gas sectors. Clifford holds a Bachelor of Engineering degree from the University of Wolverhampton, and is a member of the Singapore Institute of Purchasing and Materials Management (SIPMM). Clifford completed the Advanced Diploma in Procurement and Supply Management (ADPSM) course on April 2021 at SIPMM Institute.
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