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Meeting Procurement challenges with AI

By Steve Cavolick

Earlier this year I wrote about AI and some of the underlying technologies and modeling techniques which it comprises. I didn’t go into industry-specific uses, but asked you to think about how AI is transforming your vertical.

In this month’s blog, I want to talk about AI and horizontal analytical applications: those that cut across every company in any industry. Think HR, Sales, Finance. Since every company needs to acquire goods and services at the best price and terms, you can include Procurement in that list. AI is starting to turn up more often in Procurement and is leading a digital transformation in this line of business.

Procurement is not often thought of as a strategic department, but a McKinsey report showed that in some industries, companies can have 90% or more of their annual revenues tied to contracts with suppliers and vendors. This report also showed that companies use on average less than 1% of total spending on procurement operations. When you don’t invest in or underinvest in procurement, you erode company value by not maximizing bottom line costs.

Just ask Kraft Heinz how important investing in this area is: they recently restated earnings for nearly three fiscal years because of employee lapses in the Procurement Department.

First, let’s examine the biggest challenges faced by Procurement today:

  1. Too Many Vendors: Fewer vendors means less but stronger relationships and greater buying power through lower prices
  2. Not Understanding Contracts: What happens if you agree to a contract that does not offer the best terms? What if you don’t notice evergreen terms that eliminate your flexibility?
  3. Maverick Spend: Employees making purchases themselves off contract increases the cost per transaction for a given item or service.
  4. Increasing Costs: Prices never go down, that is why it is so important to consider lifetime cost of a given purchase and not just the initial up-front cost.

A good amount of activity in Procurement is tactical, reactive, and manual, and these are the areas that can be shored up with AI. AI is already starting to help in the following areas:

  • Order Management: Procurement applications can be bolstered by data from other systems, such as inventory. Self-learning models will trigger purchase orders and requisition processes based on the enhanced data sets and will reduce the wait time on human approvals.
  • Contract Management: Natural Language Processing algorithms will parse and interpret key terms and conditions in contracts. This will lead to greater compliance, better enforcement of terms, and improved negotiation position.
  • Invoice Management: Match up and compare invoices to purchase orders. This will shrink cycle times and increase accuracy.
  • Risk Mitigation: Algorithms can leverage data from internal and external data sources to identify and mitigate supply disruptions in real-time.

The benefits of employing AI in procurement are enormous and game-changing. The Hackett Group recently said that the cost per order of world-class procurement organizations is 69% less than their peer groups. Investments in advanced analytics and AI for procurement will connect your processes to your business model and objectives.

The LRS Big Data and Analytics team has over 20 years of experience in statistics, information management, predictive analytics and AI, and data warehousing. If you are interested in understanding how we can help you find value in your data with advanced analytics, please fill out the form below to request a meeting.

About the author

Steve Cavolick is a Senior Solution Architect with LRS IT Solutions. With over 20 years of experience in enterprise business analytics and information management, Steve is 100% focused on helping customers find value in their data to drive better business outcomes. Using technologies from best-of-breed vendors, he has created solutions for the retail, telco, manufacturing, distribution, financial services, gaming, and insurance industries.