Artificial Intelligence in Procurement & Supply Chain


August 14, 2019

Overcoming challenges, leveraging efficiencies, insights and more.

Oleksii Kharkovyna
Aug 15 · 8 min read

I’m sure a lot of you would agree, it is really hard to pick out at least one area where Artificial intelligence is not effective. Being a significant driver for everything nowadays, AI is also a perfect solution for procurement and supply chains, along with the wealth of data they generate.

But, does it mean AI is a magic new solution to any problems? Of course, it is not. We hear a lot of talks about future potential instead of business reality and tangible results. Today, I will go the opposite way and focus on the latter aspect, which is more important. So what is AI for procurement and supply chains?

Let’s then make a little investigation, cut through the hype and identify the real business opportunity in AI today. As far as I included enough definitions and examples, this post is friendly to professionals without prior knowledge of the topic.

What’s the Problem with the Current State of Procurement?

Procurement is automating more of its repetitive tasks, which allows it to move the focus away from transactions and toward strategy. When deciding on the rationalization of financial flows, attention is paid specifically to procurement — an area where there are the greatest reserves to improve the efficiency of the entire business.

A competitive procurement system leads to the fact that the company receives the best price for the products it needs of a certain quality. And it is clear that without automation of this process it will be impossible to achieve success in the current market conditions.

To be more precise, several common procurement challenges haunt businesses of all sizes:

  • Risk management: Delivery risk / Counterparty risk — Market risks, potential frauds, cost, quality, and delivery risks constitute the most common type of risks.
  • Inaccurate data — Making purchases based on inaccurate procurement data can lead to inventory shortages, excess inventory, and other additional procurement challenges that have the potential to impact an organization’s bottom line directly.
  • High costs — the cost avoidance initiatives, albeit valuable, aren’t typically recognized as “real” savings. Therefore, the natural inclination of the category owner is to execute a competitive bid.

What about the supply chain? There is also enough challenges ad here are some of them:

  • Fast-changing market conditions — Consumer behavior changes according to many cultural, social, personal, and psychological factors. Enterprises feel the pressure to make their products attractive and relevant, and to introduce new, trendy products.
  • Cost control — Operating costs are under extreme pressure by rising energy/fuel and freight costs, the greater number of global customers, technology, increasing labor rates and new regulations and rising commodity prices.
  • Risk management and security — In today’s world, there are numerous security and reputation risks to supply chains from anticipated and unanticipated events.

So, let’s move to the ways for overcoming all of those challenges.

Cutting-Edge Solutions: AI, ML & Data Mining


Let’s take a closer look at one thing at a time:

Artificial Intelligence — the ability of an application to mimic human intelligence to the level at which it is difficult to distinguish between human and machine.

What is artificial intelligence in Procurement:

AI is automating or improving many time-consuming tasks or giving Procurement experts additional insights based on extremely complex and large sets of data. In simple terms, AI is simply a software solution aimed at resolving a specific task.

What is not artificial intelligence in Procurement:

chrome or plastic –plated sentient being as you see in movies. AI is not a magic solution you can tap to solve your problems. All AI solutions today in Procurement will require active expert guidance and oversight.

For what it is useful?

Artificial Intelligence algorithms can be used for the verification of users’ purchase requests and determination of the most relevant recommendations of profitable positions in real-time. With the help of AI algorithms, it is possible to analyze larger amounts of data and offer the most relevant solutions for traditional problems. What is more, AI has all power to determine more accurately and somehow hedge credit or counterparty risks.

Machine Learning is a method of letting an artificially intelligent application figure out the steps needed to accomplish a specific goal, instead of being given step-by-step instructions to perform.

For what it is useful?

Machine Learning can be used for e-planning includes the analysis of needs, sourcing planning, and source plan management.

Data Mining & Analysis — the practice of examining large pre-existing databases in order to generate new information.

For what it is useful?

Data mining allows detecting unpredictable patterns hidden in the data generated during users’ routine operations for improving the level of their effectiveness.

Smart interaction with suppliers and AI approval of this process minimizes the role of the buyer in the system reducing the risk of a human-made error to the minimum.

3 Silver Bullets of AI for Procurement and Supply Chain

And now let’s go deeper a little bit and explore more narrow and complicated things (but the most important!).

So, there are currently several major AI-based offers for strategic use in the procurement and supply chain. Let’s look at the basics of procurement automation, which are possible using AI:

  • Data Classification methods will provide a source of information for determining ideal prices and make benchmarking and comparison a reality. AI has a wealth of data on suppliers, materials, products, etc. and about processes and therefore can easily provide user companies with accurate business data and increase the transparency of costs, with a high level of automation.
  • Data Clustering methods allow you to combine and intelligently compare data for all benchmarking categories for the entire enterprise or do it separately, for prices and suppliers. By doing this, companies can obtain data on the most preferred areas for automating business processes or for making changes within individual work processes. These methods can also provide a solid foundation for more advanced analysis methodologies (for example, for linear evaluation of effectiveness).
  • Verification and reconciliation algorithms can automatically determine critical errors of data and key performance indicators (KPIs), thus providing accurate information that is essential for determining the effectiveness of procurement processes, calculating valid benchmarking results, and maintaining a history of price changes, which greatly improves efficiency analysis, measuring the effectiveness of processes and can lead to significant savings.

If you want to establish your own AI expertise make sure your team uses these methods.

The Secrets to a Successful AI Strategy

# 1 Cost analytics

Cost analytics collects, cleans, classifies and organizes all cost data, helping purchasing departments identify excessive costs. For example, AI systems can determine when different companies bought the same goods from a supplier, when the best deal was completed or when payment for goods shipped expired.

To see what you can save on, the software will classify the data. Isn’t it perfect? AI methods often fail when working with on-time deliveries or suppliers with which the company does not cooperate constantly, but from time to time. Distractions for AI systems: unfamiliar language or new geolocation. Such problems are more often faced by companies that are constantly expanding their sales geography.

In this case, the best method of return on investment is the use of intelligent systems that can analyze large volumes of transactions, including standard re-purchases.

# 2 Search for sources of supply

Using AI, purchasing managers can equip oneself with knowledge of current market conditions, upcoming mergers, and acquisitions, as well as product comparatives and real-time support. This ensures that the purchase will be made in the best conditions for the company. The use of AI technology reduces the time required to analyze all supporting data. For example, analysis of the response to submitted applications is accelerated by 80%. The AI ​​is also looking for suppliers upon request. Subject to these conditions and, therefore, upon receipt of the necessary goods, the company will enter the market much faster.

One type of process optimization — managing the purchase. It allows you to quickly purchase goods or services and preferred suppliers with minimal time spent on procurement staff. Voice commands are used to find the best price or supplier that can fulfill an urgent order. Many of these systems provide direct communication with suppliers according to strict rules governing the process following the procurement policy.

# 3 Contract analytics

Most organizations do not have a database containing all contract data, and they need a simple way to extract such information. If the company uses AI, it will view contracts faster, and also accumulate large amounts of data about it, to significantly reduce the likelihood of disputes and increase the number of successful transactions.

The advantages of contract analytics (software for concluding contracts) — it helps companies fulfill the conditions of contracts and more quickly identify cases of non-compliance.

And although the AI ​​systems used in procurement and supply chain today are not perfect, the pace of development of machine learning is constantly growing. The platforms are improving with cosmic speed. So, it is likely in the coming years, AI will become a more reliable tool for the procurement process.

Takeaway: AI and The Future of Procurement

Artificial intelligence, machine learning, data mining — these cutting-edge approaches and more will allow more efficient use of company resources in procurement and the supply chain during the following 5 years. So, which areas will be affected by AI and how? Of course, AI won’t take procurement jobs but rather dives into P2P, sourcing, contract management, risk management, and innovation.

Let’s have a closer look at AI opportunities:

  • strategic insight and foresight
  • complete digitalization of purchasing
  • automation of processes
  • purchasing processes control
  • delivery and counterparty risk management

Nowadays, procurement teams are understandably found under pressure to do more — not only in terms of greater savings but better insights, new sources of value, unexplored ways to drive even more efficiency. AI in procurement can become a perfect way of taking a measurable share of the burden.

But it is also important to remember one thing. It is impossible to simply introduce innovations in the system of the company. It is necessary, to correctly use these technologies by qualified personnel. This is the most important thing in order to get the desired result.

Inspired to learn more about AI, ML & Data Science?

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Kennedy Executive Search & Consulting is a global partner network of retained search boutiques in Europe, Africa, North America and Asia Pacific with offices in Amsterdam, Budapest, Copenhagen, Denver, Frankfurt, Johannesburg, London, Milan, Monaco, Oslo, Paris, Prague, Sydney and Vienna. The network covers 360 degrees of talent management: executive search finds and assesses the right talent in the market, consulting develops people and organizations. With the addition of Evolve South Africa, Kennedy is now active on 4 continents and in 14 countries and offers a global reach. Between the 75+ consultants and researchers, 30 languages are spoken. As a network Kennedy will run 365 strategic recruitments all over the world this year. Kennedy Executive Search & Consulting helps organizations to achieve their goals and people to enhance their careers every day.




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