Drive Contract Visibility by Prioritizing Data Quality

10 critical evaluation considerations to get the most out of your contracts post-signature

There’s a new round of enthusiasm for (and investment in) contract lifecycle management (CLM) systems. It’s not the first I’ve seen; I’m sure it won’t be the last. At its core, this uptick in enthusiasm and investment is a good thing–it means organizations are realizing the nearly unlimited potential and value hidden away in their contracts and are eager for a tool to give them deeper visibility. 

But it’s the same old story.

An organization invests in a CLM system. At investment, departments organization-wide are sold bold claims about searchability, reporting, analytics, and overall visibility into contracts.  

But eventually, they all realize the same thing: those bold claims don’t hold true throughout the entire contract lifecycle. 

CLMs are excellent tools before the deal is signed. They are transactional systems designed to move a deal from request to signature. If you’re in the legal department, you probably benefit from your CLM. It reduces deal cycle time and improves legal efficiency by creating standard contract templates, tracking redlines, and automating approvals. 

But when it comes to post-signature contract management, other departments get frustrated that they still don’t have the complete visibility into contracts they were expecting … or worse …  were promised. 

This happens for four reasons:

1. Buyers typically focus on optimizing the pre-signature contracting process and don’t give post-signature much thought beyond ‘searchable repository.’
2. Legal, IT & Procurement buyers don’t fully engage other leaders across the business, like sales ops or finance, so they miss key requirements.  
3. There isn’t a solid plan for the legacy contract migration, or understanding that it will take 2-3 years post-go-live for sufficient go-forward data to be captured in document creation. 
4. Project teams dramatically underestimate the complexity of contracts and commercial relationships and the data challenges that complexity creates.

The first three issues are easily solvable in the buying process. But the last one is more fundamental. Unfortunately, it’s also one of the most difficult to evaluate.

To get the full value out of post-signature contract management, data quality is the most important feature of your CLM

Contract visibility is rendered virtually useless without reliable contract data extraction features like search, reporting, and analytics. They either produce misleading results or require significant manual effort from your teams to derive meaningful insight. Even advances in Contract AI have yet to address these issues without significant set-up effort and manual clean up. 

CLM software is an important piece of your technology stack, but it won’t address contract visibility.

Even the International Association for Contract & Commercial Management (IACCM) acknowledges the disconnect.

“Driving successful results depends on an organization’s ability to integrate the CLM tool within its technical infrastructure, provide the right focus for implementation with proper user training to obtain accurate data and continued executive sponsorship and support.”

If you are a sales, customer success, or finance user and your primary objective is visibility into your contracts and commercial data so you can efficiently retain and grow your current customers, you’ve probably noticed it’s tough, if not impossible, to get the answers you need out of your CLM system or contract repository. 

You’re starting to see more and more missed opportunities and wasted efforts. It’s not for lack of trying. For the most part, it’s not even a lack of software features. The data those features rely on is either incomplete, outdated, inaccurate or simply missing.  

When you’re looking at CLMs, the first question you need to ask is who is on the hook for entering data and managing quality: both for the historical contracts and the ongoing deal. 

The second you need to ask is whether that person is prepared to live with limitations in features and coordinate manual work by multiple teams. 

The third is … how can we avoid as much of this manual work as possible? The answer – by evaluating the data quality of the system in question.

For post-signature contract visibility, you can evaluate CLM data quality by focusing on these 10 critical functionalities 

1. Reliable Search, Reporting, or Analytics on OCR quality: You can’t reliably search or extract data from documents with bad OCR. While most new PDFs have modern OCR capabilities, many historical contracts have been faxed several times. They can’t be reliably searched and data cannot be extracted, so they require manual review.  
2. Contract status determination for a user: Contracts are complicated. Terms get amended. There are product-specific terms. Users still have to find and read through contracts to figure out which terms are currently in effect and which apply in specific situations … and not in others. 
3. Reporting on amended terms (or customers or products): Out of the box, CLM search and reporting is based on individual documents. Without a major upfront and ongoing investment in data quality on your part, amendments, pricing schedules, etc. will create many duplicate records if the underlying data is not amended. On the flip side, if you get a result of a non-standard limitation of liability clause in the MSA, you will have to find and read through all amendments to see if it’s still in effect. 
4. Standardization of third-party paper and template variations: CLM systems typically flag exceptions or capture entire clauses regarding non-standard paper. This requires users to read, interpret and enter data manually (and consistently) for reporting and analytics to be reliable. 
5. Assignment of product-specific terms: Orders and pricing exhibits are not always in scope for CLM implementations. But front line teams need to know how the contracts connect to the purchase history. It’s a major undertaking to map orders to contracts and product-specific terms complicate it even more. This means there is no way to view how terms such as price uplifts vary across purchased products.
6. Ability to produce a reliable customer summary: Revenue teams think about customer relationships, not documents. There is no way to view a customer-level summary of in-effect contract terms, pricing and dates within a CLM alone without reading through all of the individual documents for a customer. 
7. Product hierarchy mapping: It’s impossible to determine whitespace and compare data across systems within a CLM, because product names written in the contract are inconsistent and don’t align to current offerings.
8. Account hierarchy mapping: Contracts and purchased assets are spread across multiple and/or duplicate accounts, because contract entities and affiliates are inconsistent and have changed over time. Plus, sometimes your customers acquire each other.  Without good hierarchy management something as simple as finding all of the contracts for a customer becomes impossible. 
9. Complete contract data visibility: Important information, such as renewal notification date, is not written in the pre-signed contract. That means it must be manually interpreted and derived from contract language after the fact. Just calculating the renewal date is much harder than people think if a significant percentage of deals renew on a date other than the effective date. 
10. Easy integration with other crucial LOB systems: Non-contract data such as product activation date and purchase history is required to interpret contracts correctly. But it’s stored in other systems, not the CLM. These integrations are more complicated than most teams think and probably worth a blog post on their own. 

So how does Pramata help?

Our Repository as a Service (RaaS) solution is built specifically to deliver complete contract visibility and data access teams like legal, sales, and finance need post-signature.

As a part of our offering, we do the heavy lifting for our customers so they never have to enter a single piece of data, train AI technology or worry about quality again. Our Effortless Contract AI cleanses, organizes, extracts, and analyzes all your contracts. And it’s backed by an AI Assist team, a team of experts to close any gaps that technology alone can’t solve. 

The result: 99%+ accurate, reliable contract data to power your post-signature contract management search, reporting, and analytics.