Like many other business processes, supply chain management is being positively transformed by machine learning and AI technologies. Key innovations include data extraction, supplier contract negotiations, supplier contract risk management, and supplier risk management. This convergence of AI-driven solutions with supply chain management sets new standards for efficiency, transparency, and security in supply chains. To that end, let's explore four ways to use machine learning in supply chain management.
Managing supply chain agreements with traditional methods can result in time-consuming manual reviews, missed deadlines, and overlooked compliance issues. You might struggle with locating critical supplier contract terms, leading to inconsistent pricing, missed savings opportunities, and difficulty monitoring supplier performance. Additionally, the lack of centralized visibility into key contractual obligations for supplier agreements greatly increases the risk of legal disputes, delays in delivery, and inefficient negotiations with vendors. These challenges hinder efficient decision-making, slow down operations, and can result in significant financial and reputational losses.
With machine learning and supply chain management software, you can extract key metadata fields and clauses specific to supplier contracts, such as:
With pre-defined and out-of-the-box metadata fields, an approved clause library, and clause recognition, you can quickly experience your supplier contract being broken down and easily searchable within a robust repository. You can search for fields or documents within a supplier contract record with saved searches, search history, advanced search filters, and "Did you mean...?" functionality. You can also report on fields for advanced insights into supplier contracts and contract trends.
Thanks to system and email alerts and intelligent workflow automation, you can make it so you never miss a deadline again. If a task (such as supplier selection and qualification, for instance) is not being performed in a pre-defined, timely manner, it can be escalated to another resource, increasing accountability and flexibility. You can also be proactive by easily running an ad-hoc report such as - for example - supplier contracts expiring within the next 90 days. This information and more can also be displayed on executive graphical dashboards for advanced and visually engaging analytics at a glance.
So, to positively transform supplier contract data extraction and more, consider machine learning in supply chain management software.
The manual and repetitive nature of manually reviewing and revising supplier contract documents introduces inefficiencies, with legal and procurement teams frequently bogged down by minor edits and complex legal jargon. Additionally, it's easy to overlook clauses that could have been optimized with preferred language or better positioning. Finally, without a neat and tidy way to track versions, a contract draft that is error-filled or suboptimal for one or both parties can be pushed to the proverbial finish line of contract execution.
Thankfully, you can leverage generative AI with machine learning and supply chain management software!
You can use generative AI's user-friendly and powerful technology to draft clauses and ask contract-related questions - including those about applicable laws and compliance regulations such as UCC, Incoterms, CISG, competition/antitrust laws, product liability laws, IP, GDPR, CCPA, and OFAC. What's more, you can review chat history as needed.
With supplier contract auto-redlining, you can automate the inclusion of clauses from your approved clause library - virtually ensuring that favorable clause language is included. Heightening the flexibility, you can auto-redline documents ad-hoc or configure to auto-redline documents upon upload. You can quickly see and manage automated redlines and comments with comprehensive audit trails.
Speaking of audit trails, numbered version tracking ensures that any changes made to a contract are reflected as numbered versions in ascending order. That way, collaborators know which version should be the most up-to-date. Redlines and comments can be included and updated on a user-friendly and familiar document editing interface.
If you want to simplify, improve accuracy, and streamline supply chain contract negotiations, consider generative AI with machine learning in supply chain management.
Risky language is possible in any contract - including the supplier contracts you manage. Risky language in supplier contracts can lead to significant pain points for businesses, particularly when terms are vague, ambiguous, or overly broad. For instance, unclear definitions of deliverables or quality standards may result in inconsistent product or service outcomes, causing disputes over whether contractual obligations have been met. Additionally, poorly defined payment terms or timelines can lead to cash flow issues. Ambiguous clauses related to liability, indemnification, or warranties can also expose companies to legal and financial risks, especially if a breach or failure occurs. Furthermore, insufficiently detailed termination clauses may leave businesses locked into disadvantageous agreements or struggling to exit contracts without facing penalties. These risks can erode trust, increase operational costs, and harm a company's reputation.
Fortunately, generative AI and machine learning in supply chain management software can help!
A high-risk findings area brings items such as clauses with non-standard language or uncommon clauses to your attention in a filterable list. You can dismiss clauses from the list that do not apply as "high risk" while restoring dismissed clauses to the list if needed. This central location is helpful in identifying if contract language is safe and preferred!
You can view the list of clauses imported from supplier contracts as your own company or as the counterparty in a sentiment analysis area. This will then call out clauses that are positive (in the selected company’s favor), neutral, or negative (against the selected company's favor) so that you can enjoy risk-averse and proactive governance over contract language.
If you are looking to minimize the risks within a supplier contract, consider generative AI with machine learning and supply chain management software.
In addition to supplier contract risk, there may be risks associated with the suppliers themselves.
Associating with suppliers with low Dun & Bradstreet (D&B) ratings and OFAC non-compliance can expose businesses to significant financial, legal, and reputational risks. One major downside is the potential for legal penalties, as working with suppliers flagged by the Office of Foreign Assets Control (OFAC) for sanctions violations can lead to hefty fines, frozen assets, and restrictions on future operations. Furthermore, using non-compliant suppliers may disrupt supply chains, as certain materials or services could be delayed or blocked due to regulatory enforcement.
OFAC non-compliant association also damages a company’s reputation, potentially eroding customer trust and investor confidence. Additionally, associating with companies with low D&B scores can complicate business relationships with banks and other financial institutions, as they may refuse to process payments or extend credit due to compliance concerns. The lack of reliable due diligence, which D&B scoring aims to provide, exacerbates these risks, leaving companies vulnerable to legal and operational challenges.
Thankfully, machine learning and supply chain management software that is integrated properly can help!
You can easily digest supplier information and risk at a glance using a Dun & Bradstreet Integration. Based on your inclusion of D&B account info, you can enjoy the benefits of enhanced supplier awareness and risk management. Once configured, DUNS numbers and location information can be auto-populated when you add a supplier to your supply chain management system. You can also view:
Enhance risk assessment and make informed decisions effortlessly!
In terms of OFAC, you want that OFAC score to be zero. This easy, breezy OFAC search feature will help! Like the Dun & Bradstreet integration mentioned above, you can enjoy OFAC scores at a glance. This feature integrates the Office of Foreign Asset Control's national sanctions lists to quickly check if your suppliers are associated with foreign states, terrorists, those involved with WMD, those in enemy geographic locations, and others on the SDN (specially designated nationals) list. If the supplier does render a higher-than-zero OFAC score with matches, you can view those matches to learn more.
If you are looking to associate yourself with qualified and low-risk suppliers, consider machine learning in supply chain management with advanced risk assessment tools.
Supply chain management done incorrectly can expose your organization to contract risk, supplier risk, negotiation troubles, missed tasks, and much more. Conversely, contract automation, advanced risk assessment, and detailed negotiation with machine learning and supply chain management software can increase opportunities and streamline a vast array of business processes; all you need is the right solution for the job.
To that end, book a free demo of CobbleStone Contract Insight® today!
*Legal Disclaimer: This article is not legal advice. The content of this article is for general informational and educational purposes only. The information on this website may not present the most up-to-date legal information. Readers should contact their attorney for legal advice regarding any particular legal matter.