Artificial Intelligence (AI) is a field of computer science that is concerned with making computers intelligent by mimicking the cognitive features of the human brain. Today, AI is part of our everyday lives; Netflix suggesting the next show to watch, Banks approving loan applications and Telecommunications companies predicting when customers will unsubscribe.

As we shall see, the key to successful AI is very much down to data. Obtaining good quality data is more than half the battle (more on that later). Something else that very much depends on good quality data is successful procurement. For procurement functions, information is power. Without data you cannot track spending on goods and services and it is difficult to effectively manage supplier relationships.

It is therefore no great surprise that the impact of successfully integrating AI into data-rich procurement processes can be huge. The era of AI and procurement has truly begun, with AI already being successfully deployed in procurement functions across the globe.

*According to Deloitte 2019 Global Chief Procurement Officer Survey*

How is AI Affecting Procurement?

So, what’s all the fuss about? AI is benefitting procurement in many different ways, but at its simplest it is doing one (or both!) of the following:

Enabling smarter procurement, e.g. identifying supply chain disruption, providing early warning of compliance issues, detecting fraudulent activities;
Relieving administrative burden, e.g. automation of routine and repetitive tasks like invoice processing, purchase approvals, recordkeeping and transcription.

The first point is a big one; with smarter procurement, we can start to identify more lucrative buying prospects. AI-enabled procurement tools are able to leverage vast amounts of data in unfathomably short timescales to locate unique and profitable opportunities, and then make sensible buying decisions that turn those opportunities into a deliverable bottom-line impact.

As AI starts to become fully integrated into the end-to-end procurement process, it will be able to deliver benefits across the whole procurement lifecycle. Three main areas of change are:

Sourcing. AI-tools will make current sourcing processes such as ‘request for proposal’ (RFP) and ‘invitation to tender’ (ITT) faster and more efficient, determining exactly which suppliers should be selected to participate in which process and why evidencing all decisions with knowledge of past events and relevant documents. As AI becomes more widely integrated, it has the potential to move beyond current sourcing processes entirely and enable new ways of awarding contracts.
Purchase to Pay. These processes are already automated to a greater or lesser degree, however, AI will take this to a new level. Chatbots are able to help purchasing teams through the buying process without the need for human procurement experts in what’s been termed ‘guided buying’, invoice processing can be fully automated and for the first time systems can learn for themselves how to detect fraud and handle non-standard invoices.
Contract management. AI is already utilised to scrape through existing contracts and flag up any terms and conditions that may pose a risk to the buyer. The next step is for it to actively help in the creation of new contracts, suggesting appropriate conditions and clauses, and ensure all ongoing contract management activities are correctly captured and reported.

What Does this Mean for Procurement?

A lot of things. The breadth and depth of AI capabilities are vast, but in terms of its impact on procurement it can:

Save money. On average, organisations waste between 3-4% of their external spend on avoidable transaction costs, regulatory noncompliance and other inefficiencies [1]. Assuming that the introduction of AI tools can – at the very least – stem this flow, a company with an annual procurement spend of £1bn is looking at savings of £35m per year. And as we know, AI goes beyond correcting wasteful spending to being able to unlock extra value, with spend analytics solutions delivering as much as 15-25% savings on addressable spend [2].
Save time. Higher efficiency means more time saved, allowing procurement teams to move away from data cleansing and analysis to focusing on maximising savings capture and executing procurement activities quicker, with 3-6 months faster savings capture being typical [2].
Ease supplier negotiation. Conversations with suppliers can now be fully data-driven, which allows the movement away from bargaining and depending on personal relationships to having an evidence-based, objective discussion with both parties aware of external rates and volumes, performance metrics and any other numbers that might affect the decision.

The benefits can be reaped by the procurement function as a whole too. As successful procurement begins to rely less on prior relationships with suppliers and subjective assessments of buying prospects and more on a solid foundation of data, the strategic importance of the procurement function will undoubtedly increase. Procurement will enjoy a more prominent and calculated role in driving business decisions and may start to play a bigger role in the C-suite.

Data, Data, Data

As with many things, the first step is the most important. The strength of any AI algorithm is limited by one thing and one thing only: the quality of its input data. Much of the AI that is used in procurement depends on machine learning techniques. Machine learning is the statistical branch of AI; it teaches the computer to solve problems by providing it with many examples from which to learn, the computer then uses these experiences to solve the same problem in new situations.

Building a strong data foundation is more than half the battle. In many organisations, spend data is often unreliable with it being manually inputted to clunky systems with a high probability of human error; and even if inputted correctly, the data is usually spread between several isolated systems, each with their own naming conventions, formats and rules with many fields left blank due to missing information. Collating this data into a central repository is essential to being able to leverage it for future insights and benchmarking purposes, let alone unlocking the plethora of benefits that AI can eventually bring.

At Deecon, we understand the importance of creating a robust and reliable data foundation. That’s why we have developed our bespoke in-house data consolidation engine – Deecon Core. So far, it’s revolutionised our ability to process and analyse tendering data for our clients during the procurement process (read more here) and we look forward to seeing what else it can achieve in the future.

The outlook of AI in procurement is bright indeed; but its success is wholly reliant on companies taking proactive steps to ensure their spend data is consolidated, robust and accessible.

Get in touch to find out how Deecon Core can support the data needs of your organisation today.

Words by Will Blacklock

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