Contract Analytics Quality: Is it The Solution to our Data Problem?

Contract Analytics Quality: Is it the Solution to our Data Problem?
by Viraj Chaudhary

Inspired by a recent Forbes Magazine article: More Data Doesn’t Guarantee That Analytics Will Deliver Digital Transformation – the question turned to whether contract analytics quality is the solution to the in-house legal space. In the article, Kaan Turnali highlights that we have a growing data challenge. He points to the often-quoted concept that, “90% of the data we have today was generated in the last few years.” Then, it goes to highlight the accelerating velocity of data growth that we face. We see parallels in the world of in-house legal teams and contracting. A clear example is the tens of thousands of active contracts that a company manages at any given moment.

In Contract Management Needs: 3 Stages of Maturity, Sarvarth Misra points out that contract management in today’s digital businesses has 3 phases of maturity. Regarding contracts, digital technology adoption is in one of the three phases:

  • Neophyte
  • Early Adopter
  • Mature User

The latter two phases delve into driving digital transformation with greater use of cloud computing tech and AI (artificial intelligence). Ultimately, AI helps contract management systems (CMS) deliver much better contract analytics quality. Naturally, this helps make sense of this growing stockpile of big data. 90% of the data we have today was generated in the last few years.


In our world of contracts, bringing all agreements and records into a single repository is the first step. Arguably, most organizations still need to get to this stage. But, that’s just the setup. The first step in the business transformation toward digital innovations – is to bring all the contracts together into one virtual place.

Remember the data repository is only the first step in the business process for improving your decisions. It comes down to the data analytics and contracts analytics quality to provide insights.


The business model changes to onboard all contracts into one place is important. It means using digitizing tools or services to do away with the manual, paper-based agreements. But stockpiling more digital data isn’t the key to an effective digital transformation strategy. At this point, we must step away from the legacy technology of merely housing more information.

Ultimately, the question about contract analytics quality arises. Good contract lifecycle management systems use AI to pull out pertinent extracts from your contracts. Key aspects include highlighted deviations, critical times (termination, auto-renewals), significant agreement risks, and so on. Therefore, pulling out these analytics from your database of accords, lets your team start asking the right questions, such as:

  • When do key contracts end or renew?
  • Can you glean more value from the contracts than before (volume discounts, timing bonuses)?


One of the challenges with many CMS technologies is their reliance on machine learning rather than AI. The subtle distinction between these two is that one system you must train (machine learning), whereas the other has already been trained and is ready to go (AI).  Part of contract analytics quality is the speed with which it can be collected and analyzed.

Having trust in the contract analytics quality of your system comes more readily when its AI has been trained by seasoned professionals, and in our case at ContractPodAi – professional legal engineers. This is rather than having to take on the challenge and 6-month trial-and-error cycle to bring your own system up-to-speed. The additional challenge is whether your own team has trained the AI effectively and correctly.

Naturally, the best option is to work with the CMS vendor and to ask if their solution is ready to go, out-of-the-box.

As Forbes pointed out, “if we can’t trust our data, we won’t use it – no matter how much we have.”


Supply chains around the world race to get products and services to customers as fast as possible. They understand that customer-centricity is all about providing speedy and accurate delivery. Also, it is about delivering a positive customer experience. 90% of the data we have today was generated in the last few years

Part of contract analytics quality is the speed with which it can be collected and analyzed. Think about the due diligence you put into your contract discovery/analytics phase in the same way. Clearly, it is important to be thorough and accurate. Contract analytics quality is all about this. But, you also have to be fast. Truly, that’s the beauty of an artificial intelligence enhanced analytical tool. Using natural language processing and interpreting terms and clauses in context is important. The fact that the machine can do this at superhuman speeds, is equally important.

In another blog post explaining contract analytics, the C-level request scenario comes up. First, an executive asks for a cross-sectional analysis of all your contracts. With thousands of contracts, the agreements management team works day and night to collect this information. Then, after two or three weeks of intense work, the executive suite has moved on to other business concerns.

Now, part of contract analytics quality – is the speed with which it can be collected and analyzed. This is where a powerful AI-equipped CMS will make your team shine. Best of all, the agreements team can focus their time and effort on interpreting the results – rather than on the mind-numbing collection phase.


Now, having all your agreements and data in one place (system of record, common repository) is an important first step. Effective data analysis and timely interpretation are another. But, it is equally important to emphasize the need to communicate the results. With analysis in hand, informing and educating your stakeholders about the agreement’s analytics and reporting capabilities is key!

If stakeholders don’t know that contracts data, and more importantly the analysis exists – then they will not consume it. They will not know to seek it out from your team.


So, is contract analytics quality on its own solution to our contracts data problem? No.

However, having this as a powerful piece of an end-to-end contract lifecycle management (CLM) tool – will go a long way to improving the situation in your company.

Getting a handle on your growing mountain of agreements data is about having the tools that give you a:

  • Single contracts repository
  • Trusted AI analytics
  • Speed
  • Insight communications

Now, let’s revisit our opening question if contract analytics quality is the solution to our contracts data problem. Without a doubt, the answer is YES – when paired with a solid out-of-the-box, AI-equipped CLM.

Find out more about ContractPodAi – the most advanced end-to-end, out-of-the-box CLM on the market today. So, if you are looking for a full contract management software solution in the LegalTech space, look no further. We make ‘More for Less’ mean ‘More Impact For Less Stress.’

Viraj Chaudhary

 Viraj Chaudhary
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