It no longer makes sense to skip Contract Analysis

Contracts are the lifeblood of any business and contain critical commercial, operational and risk data. This is why extracting data from contracts (Contract Analytics) has a very high value proposition relative to most of the things you can do with contracts. In fact, being informed by relevant data about your contracts is the key to many of the things people want to do with contracts.   

 While this seems like a fairly obvious proposition, the current reality is that most businesses operate with extremely limited contract data, even if they have already implemented a repository or Contract Lifecycle Management (CLM) product.   Most have chosen to put the analysis and data extraction problem aside and to get on with automating templates, workflows, and playbooks as best they can.  Many CLM implementations are phased to initially address only new contracts going forward and descope existing live contracts and contracts done on third party paper.  The hope is that, as new contracts are generated based on templates and negotiated based on playbooks, the CLM will incrementally be populated with data from these contracts.  

 The “automate first” approach leaves many CLM buyers with a lot of legacy contracts into which they have little to no visibility.  This ‘incompleteness’ can undermine the perceived success and ROI of many CLM implementations.  Similarly, a lack of data about legacy contracts means that automation decisions (which templates and clauses to use, which playbooks to follow, etc.) will be less data-driven and based more on the impressions of a few individuals, which further increases the risk to success. 

CLM implementations usually entail long, expensive projects, so everyone is eager to avoid failure. But there is increasing evidence that the majority of CLM projects fall short of expectations and leave people disappointed.¹  

Why have so many people skipped analysis? 

The main reason for skipping analysis and jumping into automation is that there has not really been any ‘fit for purpose’ Contract Analytics solution available.  While Contract Analytics products have been around for a while (often as part of CLMs) and have sold themselves as a panacea to this problem, buyers’ experiences with these products have been disappointing.  They often require long expensive implementations with a heavy burden on clients who must explain their business and contracts to vendors, provide many samples of provisions and, in some cases, even train models themselves (or engage 3rd party consultants).  Even after such painful implementations, the quality of data is poor with the identified/extracted contract content being limited, high level and noisy. 

 This is why Contract Analytics, as a product segment, is described by Gartner as currently in the “Trough of Disillusionment” in Gartner’s Hype Cycle.²  The lack of fitness for purpose of these products means that the review/analysis process has continued to be mostly manual with people reading through contracts. 

What if Contract Analytics actually worked?   

Let’s suppose you did have access to a ‘fit for purpose’ Contract Analytics solution, with the following characteristics: 

• • fast implementation with a low burden on clients (no explaining business/contracts, no providing large samples of provisions or no training of models) 
  • lots of granular contract content identified ‘out of the box’ 
  • potential buyers could actually try the Contract Analytics solution themselves before buying and evaluate fitness for their use case so there is no risk of not meeting expectations (i.e. buyers can load their own docs and see results in real time without the vendor curating or intervening in the process)  

A ‘fit for purpose’ Contract Analytics solution provides many opportunities: 

For companies which already have a CLM, using ‘fit for purpose’ Contract Analytics lets you do more in terms of automation: 

• • Contract Analytics can extract data from their existing live contracts and contracts done on third party paper.  This data can be pushed into their CLM or any other system where this data is useful.
  • Contract Analytics can extract data from new drafts that are coming in to be negotiated and automate workflow in relation to certain things in contracts that need to be approved/reviewed before signing.  Currently most of the workflow in CLMs for approval/review is human initiated – i.e. there is a lot of manual work in the workflow.  Instead of relying on human initiated workflow for review or approval of particular provisions these workflows can be triggered automatically when provisions are recognized by the Contract Analytics solution. 
  • Contract Analytics can extract data from newly executed contracts and push that data into a CLM or any other system where this data is useful.   

Companies which don’t have a CLM can start their automation journey by using ‘fit for purpose’ Contract Analytics to first analyze their contracts which provides opportunities to optimize and realize the highest value of any subsequent implementation of a CLM or similar solution: 

• • If a company wants to load contracts into a repository it’s best to understand what you have before you do it.  Organization of contracts has historically been based on limited/blunt meta-data manually entered by people.  With more extracted data you can organize, slice, dice and access your contracts in many different ways. 
    
  • Templates used for contract generation and playbooks for negotiation can be optimized to facilitate faster negotiations based on an understanding of what actually got agreed.  Historically templates and playbooks have been drafted based on views of negotiators which tend to impressionistic, rather than data-driven.  Data extracted by a Contract Analytics solution from existing contracts can be used to make this more data-driven. 
  • Deciding on a CLM can be very confusing.  CLMs have sold the idea that they can do everything very well but the reality is that each solution has its strengths and weaknesses.  Most CLMs say they have AI analytics as part of their CLM offering but the truth is that their AI is the weakest part of their offering.  You can decouple AI analytics as a feature from the CLM buying decision and choose the CLM that has the best workflow that suits your use cases and choose the best AI analytics solution to ‘feed’ that workflow.  

The bottom line is that ‘fit for purpose’ Contract Analytics provides great opportunities for low risk, high value ‘quick wins’.  Doesn’t everyone deserve a ‘quick win’? 

¹ Gartner Says More Than Half of Legal Transformation Projects Underperform Expectation https://www.gartner.com/en/newsroom/press-releases/2021-01-26-gartner-says-more-than-half-of-legal-transformation-projects-underperform-expectations

² https://www.catylex.com/blog/is-contract-technology-over-hyped;  https://www.gartner.com/en/newsroom/press-releases/2022-10-20-gartner-says-many-legal-departments-are-underusing-mature-technologies