AI in Procurement: What you Need to Know Now
These are exciting days in Procurement. Among us is a star that glitters, generates buzz, and steals headlines. Like many celebrities it is instantly recognized by just two initials—AI—but goes by other names including machine learning (ML), robotic process automation (RPA), and cognitive procurement. By any label, AI in procurement is hard to ignore.
But celebrities are often misunderstood. In the case of applying artificial intelligence (AI), much coverage predicts a quasi-utopia of perfect data, effortless analysis, and flawless forecasting. This attention feels like hype and invites skepticism. For veteran company leaders, AI in procurement may call to mind the wave of enterprise spend management. That association can muddy things further; AI is different technology with different uses.
It’s worth pushing aside doubts of the future and anchors from the past, because AI can probably help you in the present. This article offers concise answers to the big questions about AI in procurement:
- What is AI in procurement?
- What are its benefits?
- How is AI in procurement implemented and how much does it cost?
- When should a company consider adopting AI in procurement?
The last question is critical. This month, every company will either pursue a plan to advance AI in their business practices, or they will wait. In the latter group, some will be driven by strategic choice and others by passive inaction. This topic is too important to let inertia guide your course.
What is AI in Procurement?
Artificial intelligence is often defined as having machines perform tasks that normally would require human intelligence. For example, AI is being deployed by financial institutions to reduce / minimize credit card fraud, analyzing every transaction for signs of fraud.
The implementation of AI to prevent – and minimize – credit card fraud comes with several major advantages. For starters, AI can sift through transactions at an incredible speed; it is so much faster than what us humans can do manually. Instead of manual checking, companies like MasterCard can now rely on its AI to do the initial screenings.
The second advantage is accuracy. Artificial intelligence doesn’t just use a set of predefined parameters to screen transactions. It can take other factors into consideration, including a particular customer’s past transaction history to identify outlier transactions and potentially fraudulent activity.
As it applies to procurement, it may be more useful to think of AI as a supercharged multiplier to the human brain. Here machines can do what humans could not possibly do: quickly analyze massive amounts of mundane and seemingly unconnected data to reveal patterns, correlations, and anomalies.
In a sense, it’s more muscle than brain: the brute speed and reach of modern information processing are what enable AI. When that analysis horsepower is combined with human intelligence and judgment it can uncover new insights that are not just interesting, but actionable.
Specifically, AI in procurement means crunching through thousands or millions of data points from within and outside your organization. These may include:
- Transaction details
- Inventory records
- Consumption and usage data
- Contract terms and rates
- Market information
- Historical pricing
The possible inputs are virtually endless. While the blue-sky potential of AI is exciting, it’s also daunting. To capture the promise of AI it is necessary to define and narrow the scope.
“Before you answer the question of what data you need, you need to address the question of why you need it. What is the business outcome you are trying to drive?”
What Are the Benefits of AI in Procurement? Three Tiers
The myriad benefits of AI in procurement can be practically grouped into three tiers:
- Lower Cost & Greater Speed
- Greater Reach and Visibility
- New Capability
This is an arbitrary breakout based on use rather than technology, but it serves to map out a realistic progression of how AI in procurement is likely to be adopted. Not surprisingly, AI in procurement will follow an arc common to many new technologies:
The first phase of adoption will make existing procurement tasks easier and faster. The results will be lower labor expenses and quicker results to cost-justify the investment in AI and fund further growth.
In the second tier, the power and speed of AI will facilitate procurement analysis at a wider and deeper level than is currently practical. As if granted additional team members, sourcing leaders can reach wider to additional spend areas and deeper into transaction details to mine increased savings across the enterprise.
The third level of use reaches beyond the traditional procurement goals of savings, spend visibility, and supplier management. By linking purchasing and vendor information with additional data, procurement can extend its value into product development, inventory management, corporate risk assessment, or other areas.
Lower Cost and Greater Speed
Bringing Savings to Fund Growth
Most sourcing teams generate the greatest value from the usual suspects: consolidating spend, rationalizing vendors, enforcing policy and validating pricing. These perennials require good data, visibility, and exception reporting. AI can smooth the path through streamlined data collection and integration, and improved reporting that suggests specific follow-up actions. Among the standard features for AI tools are reports revealing:
- Pricing irregularities
- Usage anomalies
- Contract variance
- Suspicious spending
- Potential fraud
This type of transactional analysis is currently used by many sourcing teams, but often on an occasional or ad hoc basis because of data and interface limitations. AI in procurement will make these reports less costly to generate.
Savings available in the first tier will be expedited by the speed of AI procurement systems. Hardware and software advances have accelerated every step of analysis, including the critical first step of data input and integration. Sourcing professionals often spend many hours in the tedious and thankless tasks of data cleanup; AI routines will eliminate most of this drudgery to improve team efficiency.
Of course, the processing and analysis itself is faster and now can run 24-7, as machine learning engines continuously monitor data and proactively send notifications and alerts to procurement leaders. Indirect benefits will follow: faster response to stakeholders, better informed decisions, and more knowledgeable base for negotiations.
Greater Reach and Visibility
Greater Reach: Finding Savings in the Middle and Long Tail
Just as gas prices of less than one dollar per gallon would radically change transportation habits, the abundant computing power harnessed in AI facilitates analysis for areas of spend that previously didn’t justify the effort and priority. This second tier will offer the biggest near-term impact of AI in sourcing for many companies. Every CPO faces limited bandwidth and must rank the team’s projects. AI tools effectively allow the question: how could we address this category if we gave it an extra thousand hours of analysis? When those cycles can be executed with technology and completed almost instantly, sourcing leaders can replace either/or tradeoffs with both/and to reach more categories and vendors.
Visibility and Enterprise Alignment
AI in procurement will simplify more complex reporting that requires an enterprise view and additional inputs. Again, this is not new territory for procurement. The difference that AI will bring is in the speed and reliability of the reporting, to enable:
- Best pricing comparisons
- Identification of high-growth suppliers
- Real-time visibility into policy compliance and maverick spend
- Faster analysis of purchasing card (P-card) transactional details
- Proactive identification of imminent contract renewals or expirations
- Identification of opportunities for demand aggregation and supplier consolidation
The quality and availability of this type of reporting is greatly enhanced due to cloud-based native AI solutions and improved vendor data feeds (explained more in the implementation section of this article). The result is the democratization of data across the enterprise. If marketing, manufacturing, and other stakeholders can share real-time data with procurement, organizational friction will reduce and alignment will increase.
New Capability: Redefining What Procurement Can Bring to the Organization
By connecting to data outside the traditional scope of sourcing, AI can offer new levels of analysis that raise procurement’s strategic contribution. Consider some examples:
- Third-party supplier or industry data can be linked with accounts payable feeds to create a custom risk profile that gauges supply chain disruption and sustainability.
- Customer satisfaction data, sales reporting, and purchasing records can be connected to bring quantitative metrics and greater confidence into quality considerations.
- Historical purchases and external market information can be married to offer predictive insights that would inform negotiations and order quantities.
Can you hear the sizzle? These are the use cases that stir up the utopian scenarios. It’s not science fiction, but for most companies it’s not next quarter either. This third level of AI maturity may be bleeding edge for the next few years, available for companies that make substantial investments in technology, expertise, and experimentation.
Fortunately, you don’t have to bank on new capabilities to take the first steps in using AI. Thanks to the lower investment required you may be able to prove your ROI in the first two buckets.
How is AI in Procurement Implemented, and How Much Does It Cost?
Cost and implementation are closely connected and hold surprisingly good news, especially for leaders who have purchased any type of enterprise software in the last decade. AI in procurement enjoys both a new environment and a different paradigm, bringing lower costs all around.
Lower Direct and Indirect Costs
For starters, the concept of installed software doesn’t enter this conversation. Cloud-based solutions bring a cascade of economies as upfront purchases, version control, hardware upgrades, and licensing headaches are now artifacts for the Museum of Procurement Past.
With enterprise software, the vendor’s price tag is often just the beginning of total cost. After buying the software, companies must spend months (or years) in data cleanup, system integration, parallel systems, and process changes before value can be realized.
In comparison, AI sourcing solutions have negligible adjacent costs. The best-of-breed tools in AI are native: they were built to do nothing else. Rather than demand that you re-pipe your data and re-design your processes, these tools can generate results even if they are not the system of record. There is no rip-and-replace, and not even the biggest customer should be paying 7-figure implementation fees.
Cleaner, Unified Supplier Data and Faster Implementation
It certainly helps that supplier data is better than ever before. Vendors have been famously slow to upgrade their billing systems, but today open systems and conventional coding standards are the norm. As a result, the data integration nightmares of the past are far less common.
While your data is more likely to be complete, here’s an equally important selling point for AI: you don’t need complete data to get high-value benefits. Partial information combined with AI analytics can generate actionable insights and bring savings. Those savings can come fast: implementation for some native AI sourcing tools is as little as two weeks.
The market for AI solutions in procurement is still taking shape, and specific pricing details are generally not public. Realistically, it’s likely to take a few conversations with a provider to get a firm quote. But with cloud software, better data, and a lighter footprint, bringing AI to sourcing is likely to be both faster and more affordable than you might expect.
Even if the cost is reasonable, is it worth the investment? As always, the value captured will depend on addressing specific challenges.
When Should Our Company Adopt AI in Procurement?
Few budgets can fund speculative analysis tools no matter how great their promise. To determine whether you would enjoy a near-term ROI from AI, consider these questions:
- Have your savings mandates outstripped what you can find using the 80/20 rule?
- Do you have numerous procurement data sources that are not linked in any meaningful way?
- Is your team spending too much time wrestling with data, and not enough time capturing savings?
Finding Quick Wins
If even one of the questions above returns a “yes” it’s probably worth scheduling a demonstration. The initial insights and standard reporting of AI sourcing solutions are likely to provide clarity and reveal quick-win opportunities for your team as it has for other early adopters.
Suplari shares that one large global enterprise found over 70 different individual licenses for the same vendor, spread across different regions and business units. These transactions were often expensed / paid for via corporate p-cards or through the T&E system, making it incredibly difficult to get an enterprise-wide view of the single vendor. Combining these expenses was relatively straightforward and generated about 33% in savings through de-duplication; savings that greatly exceeded the AI solution cost.
Another client was able to uncover six-figure savings in transportation expense after just a few weeks with the AI tool. Similar first-level benefits of AI in sourcing will easily justify the cost for many companies.
“My sourcing team used to spend 80% of their time on data cleansing and data analysis. With Suplari we have seen the reverse, they are now spending 80% of their time working with business partners on hard cost savings initiatives. Suplari has already paid for itself many times over.”
— VP Procurement, Fortune 200 Retailer
Beyond the Numbers: Building Your Brand
There’s another benefit to acting soon: your procurement team can start building the skill of working with AI. As your expertise grows and the tools mature, some of the loftier promises of AI will become reality.
Wouldn’t it be a bonus if your group could lead the company in capturing the benefits of big data analysis? Could adopting AI change the brand of procurement within your C-suite?
Granted, these questions stray from the numbers and into organizational dynamics. But this is an exciting dimension to bringing AI into procurement, and it is relevant. How long have procurement leaders been seeking a more strategic role, transformation of their function, and the vaunted “seat at the table?” AI can play a central role in realizing these goals.
Realistically, the legacy of enterprise spend systems will influence how many organizations proceed toward AI in sourcing… or explain why sit on the sidelines. It’s important to acknowledge the corner office perception that those initiatives largely under-delivered, exceeding budget and schedule and never matching their promise. Compared to those memories, procurement AI projects should seem downright refreshing: capturing benefits from current technology without painful enterprise change and dizzying cost. But where sourcing leaders don’t push education and adoption, enterprises may stay stuck.
Eventually, artificial intelligence will be part of every company’s operations, in procurement and beyond. With the current marketplace offering of AI procurement solutions, your team can lead the company to the next level of automation, insights, and excellence. It’s a unique opportunity for sourcing teams not just to over-deliver results, but to extend their reach and impact.
The time is now.
Jack Quarles is a 20-year sourcing veteran and author of the bestselling books Expensive Sentences, Same Side Selling, and How Smart Companies Save Money.
If you have questions about this article or want to learn more about AI in procurement solutions, contact Suplari.
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