CLM in a Pandemic World: Speed, Simplicity, and Safeguards through Contracts AI (Part 2 of 3)

Organizations often lack transparency and understanding of costs, risks, administrative processes, and obligations inherent within their agreements. Their biggest challenge is to make this relevant information available to stakeholders. Here is where Contracts AI can be instrumental.

From Mainspring’s first-hand experience with close to 100 companies, we have seen the digital transformation power of Contracts AI. In a recent article, we introduce the Business Transformation model and the CLM Future State. It introduces concepts to document and automate processes with CLM best practices without a major financial commitment. This article focuses on how Contracts AI can help the cornerstone functions, such as Procurement, Sales, and Legal, yet be just as beneficial for HR, R&D, Finance, and IT.

How Contracts AI Help Us Work Faster and Smarter

The terrific computing power of AI, machine learning, and visualization has been proven to be successful in analyzing contract data to find outcomes in important decisions. For instance, Contracts AI and machine learning can automate and improve forecasting by analyzing historic and real-time transaction information, including negotiated price discounts, agreement redlines, and obligations in contracts. Technology can also absorb and correlate external factors and suggest a simulation based on anticipated effects. Imagine contract data taking into account patterns from a range of data sources, including economic projections or competitor activities, and the effect of this most recent pandemic.

Supply Chain Disruption, Risk, and Uncertainty

As a result of this pandemic, companies are suddenly finding themselves vulnerable for not receiving products, parts, and services on a timely basis, if at all. This sudden disruption has forced organizations to strive for resilience across supply chains driving interest towards bringing suppliers closer to end markets. Supply chains built on available cash, just-in-time inventory, and distributed sourcing might require companies to make immediate adjustments, such as:

• Establishing a multitude of secondary contractual relationships with backup suppliers as safety plans for potential future disruptions
• Reprioritizing their selection criteria of existing and new suppliers to factor uninterrupted supplies to be just as valuable as cost and speed to market
• Extending payment terms to conserve cash

By sifting through and reviewing thousands of contracts, Contracts AI can help identify current payment terms and the number of buy-side contracts having highest propensity of risk, i.e., containing clauses and language that are most vulnerable to potential supply chain disruptions. This enables organizations to take a proactive response to these risks based on a full understanding of the ramifications for amending or terminating these agreements as well as preparing for the next round of contract renewals and negotiations. The specific clauses presenting the greatest risk impact are further highlighted in the section below.

Sales Cycle Delays Yet Active Collaboration

On the sell-side of the organization, companies are seeing a decline in new deal volume, which will impact most sales forecasts adversely. Responses to sales outreach and prospecting have decreased, suggesting that sales strategies need to be adjusted to reflect the current buying reality. Sales organizations need to get more creative, and they can turn to their contract data for these inputs. Considering aligning services and products to contractual obligations and outcomes to prove the ROI that prospects will need to show when trying to loosen budgetary constraints. Here is where Contracts AI can be powerful. Data from contracts, connected with strong value props, can turn soft ROI targets into hard ROI outcomes. 

Reinforcing Speed, Simplicity and Safeguards with Contracts

Contracts have always been the fundamental mechanism in which customer and supplier relationships and obligations are established. The elements contained within are the basis for understanding coverage, risk exposure, and resulting liability. Organizations can minimize risk and increase understanding by bolstering clauses across all agreements with greater clarity, precision and safeguards. Contracts AI alleviates manually poring through and reading thousands of existing contracts for actual occurrence, context, and exposure. The following clauses having the most legal risk implications can be easily highlighted for improvement and additional safeguards:

• Termination
• Force Majeure
• Indemnification
• Limitation of Liability
• Insurance
• Confidentiality
• Intellectual Property and Ownership
• Automatic contract renewal provisions

This acquired transparency allows attorneys to then strengthen the provisions of contracts and/or craft pre-approved alternate clauses that can be easily substituted for streamlining negotiations and protecting mutual interests.

Leveraging Contracts AI as the Muscle and Engine for Operations

The intelligence from data and repetitive tasks loses effectiveness unless companies can properly operationalize and adjust their processes accordingly. Consider executing the following key activities on a continuous basis:

1. Portfolio/Project and Supplier Prioritization – Crisis checklist to evaluate portfolio projects, customers, and suppliers systematically against key metrics, including answering: “Are we still able to deliver, either internally or with potentially affected vendors?” “In what way does the project address new business priorities for customers?” “Does the project assume functioning supply chains?“
2. Review and update existing “grants of authority” with new checks and balances
3. Update clauses in existing standard templates with language that is more precise and less ambiguous, including consideration for payment terms and performance incentives that are aligned with new priorities such as “continuous, uninterrupted supply”
4. Use Contracts AI to aggregate, collect, measure, assess, and learn from data, as input to Contracts Analytics

This is the second article in a series of three. The first article can be found here where we introduced the Business Transformation model and the CLM Future State.  It outlined concepts to document and automate processes with CLM best practices without a major financial commitment.  Our next article will focus on interpreting, predicting, and prescribing a course of action for greater resiliency using contracts and Contract Analytics.