What Is Post-Executed Enterprise Contract Intelligence?
The three ideas behind it — post-execution, enterprise scale, and contract intelligence — and why your already-signed agreements are full of untapped risk and value.
I spent 10 years working on post-executed enterprise contracts intelligence. This is a loaded concept, so let’s break its 3 main parts down one at a time:
Post-executed – these are contracts that have already been signed or executed, otherwise known as post-signature contracts, as compared to pre-execution or pre-signature contracts that have been drafted, negotiated or redlined but not signed by all parties.
Enterprise – at least one party to the contract is a very large business, such as a F500 company.
Contract Intelligence – enabling people to make legal and business decisions by turning contracts into structured data that can be searched, filtered, reported on, and analyzed at scale.
Let’s dig into this in greater depth – including how these concepts influence one another.
Deeper Dive
Post-executed
First, we should dig into the implications of what it actually means for a contract to be post-executed.
Contracts are written agreements containing the terms of an exchange, including legal obligations on both sides.
Post-executed means the contract is already signed. This means we’re past the drafting stage, negotiation, and redlining — the language has been finalized and agreed to. In other words, pending an amendment to the original contract or another legal mechanism, the language is locked, and the rights and obligations in effect.
Enterprise
Being a large enterprise has many significant implications for contracts as well.
Range and volume of contract types
One implication is that the volume of contracts is much, much higher for large enterprises than it is for smaller businesses.
This happens for a few reasons.
First, enterprises are large, diversified companies, often with multiple business units, many customers and vendors, many products and services, and a more complicated supply chain. For example, everything ranging from the need to manufacture things to the need to distribute products and services at scale means that there are many more significant business exchanges and many corresponding opportunities for contracts across a range of contract types.
These may include manufacturing agreements, reseller or distribution agreements, licensing agreements, partnership agreements, leases, and other types of customer and vendor contracts.
Contract Families
Another implication is that because enterprises have been around for a long time, they have business relationships and contracts from many different periods.
This includes older contracts with longer lifecycles, often including multiple rounds of contracting between entities. These relationships may include more than just an initial master agreement. They may also include NDAs, amendments, statements of work, order forms, addenda, and other related documents.
As a result, large enterprises can have very large families of related contracts.
Complexity of individual contracts
Relatedly, the complexity of the contracts themselves tends to be very high for enterprises. Large enterprises have all sorts of complicated requirements built into their contracting practices.
This is partly due to being subject to different regulations as a result of their broad reach of business activity, often spanning geographies and business lines. Also, because they have been in business for a long time, different laws, rules and conventions may have applied over different periods of time.
It’s also because they are at greater risk of litigation, leading to more robust risk allocation measures. This is driven in part by increased opportunities for something to go wrong, given their higher levels of business activity and transaction volume. It is also driven by the fact that large enterprises often have more money and assets to pursue, making them more attractive litigation targets relative to smaller entities.
As a result, they often have to be more aggressive about risk allocation. This can lead to lengthier, more detailed provisions that limit liability exposure in different circumstances.
Net of these considerations, the population of contracts at a given enterprise is highly mixed. It is not homogeneous or standardized.
Even the same type of contract may have many different variables and complexity drivers baked in.
That gets compounded further by other complexity drivers, such as:
File quality. Many of these documents include emails, scans, pages with coffee stains, handwriting in the margins, or image-only PDFs. Each of these can reduce the quality and reliability of OCR (optical character recognition). Bad OCR means the text may not be properly recognized by AI models. So before any AI touches the contract, the file often has to go through a chain of preprocessing steps just to become usable. Example here: link
Multi-document files. One file will often contain multiple discrete parts. For example, you may have the core contract, cover pages, exhibits, addenda, additional terms and conditions, and other related documents all in one file. Determining which document or clause takes precedence can be a very challenging exercise as a result. Example here: link
No system of record. Enterprises are diversified, with many business units, siloed repositories and multiple custodians. As a result, there is often no central place where all contracts live. Companies frequently can’t even find their contracts, let alone analyze them. And when they do find them, they are often dealing with legacy systems that contain partially executed agreements, duplicates or overlapping documents.
Compounding Complexity
Each of these factors would create complexity on its own. Enterprises often deal with all of them at once, across hundreds of thousands of documents.
So there is a range of complexity drivers, and many of them are closely linked to large enterprises. That’s why the enterprise dimension is so important and why it has so many implications for contracts.
Net of these considerations, you do not have one big, centralized, clean dataset. You have many unstructured, complex, messy, difficult-to-find documents — subpopulations inside subpopulations, fragmented across many systems.
Contract Intelligence
Collectively, this is what creates the need and opportunity for contract intelligence.
Even finding contracts in an enterprise can be very challenging, let alone knowing the substance of what is in those contracts and what obligations they contain.
And this matters because hidden within these already-executed contracts are collectively huge opportunities, both in terms of risk allocation and mitigation, as well as increasing business value.
For example, it is not unheard of for a contract to lack a limitation of liability clause, which could introduce significant liability for the business, particularly if it is an older contract without other safeguards in place.
Payment terms are often suboptimal, leaving value behind or creating misalignment with the company’s standards, internal finance systems, and processes.
There may also be untapped opportunities to increase prices, or rights and restrictions to assignment, termination or exiting agreements.
The goal of contract intelligence is to take all of these contract documents and be able to search, filter, report on, and analyze them at scale.
The data points of interest vary based on the use cases and the business or legal problems people are trying to solve.
For example, in M&A diligence and integration, you might be interested in assignment, change of control, governing law, and related provisions.
For a business-as-usual type of review where a question comes up from the commercial team, you may be interested in a specific clause, such as the indemnification language agreed to in previous similar situations, or how long a contract requires the company to support a product that is being sunset.
This is a very small sample of potential use cases. The relevant questions vary depending on the business line, industry, function, department, specific situation, and place within the larger supply chain.
Contract Intelligence vs. Contract Summarization
For sake of clarity, it is important to understand that the difference between contract intelligence and a contract summary. These are complementary use cases that serve different purposes.
Contract intelligence specifically relates to turning the natural language of contracts into a structured data asset at scale, so users can gain visibility into their contract data through search, filters, reports and analytics.
In contrast, with a contract summary, you are typically doing a deeper dive into one or more contracts, often at smaller volume, to better understand the underlying nuances.
The critical difference is that the output involves qualitative descriptions of text. These are not ideal for running searches, reports and analytics at scale.
However, summaries can be very helpful when creating a diligence memo or other report to support a decision across a contract population, such as whether to move forward with an acquisition or how to prioritize regulatory remediation.
Summary
To summarize, post-executed enterprise contract intelligence involves three main components:
Post-executed – contracts that have already been signed or executed, otherwise known as post-signature contracts, as compared to pre-execution or pre-signature contracts that have been drafted, negotiated or redlined but not signed by all parties.
Enterprise – at least one party to the contract is a very large business, such as a Fortune 500 company.
Contract Intelligence – enabling people to make legal and business decisions by turning contracts into structured data that can be searched, filtered, reported on, and analyzed at scale.
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