Data Mining Your Contracts
By Andrew Banquer
June 28, 2021
Andrew Banquer is Vice President, Corporate Solutions at QuisLex, a legal services provider. He has done extensive work with general counsel, commercial practice and legal ops to turn strategic objectives into actionable projects and activities. [email protected]
Published in Today’s General Counsel, July/August 2021
If you had to name the one most valuable aspect of a contract, what would that be?
Responses to that question vary, but responders typically think about a single contract and its impact on the parties, rather than the contract’s impact on a company’s contracting as a whole. But what if the most important part of a contract is the data it generates?
If you aggregate, organize and analyze all the data included in every contract, then you will have critical insights into the overall effectiveness of your contracting process and the way you transact business. From that analysis, you can determine how to be more effective.
Contracting analytics is the secret sauce that allows you to make data-informed changes to your operating model and improve those objectives that matter most — whether that’s revenue growth, cost-savings, risk management or longer-lasting relationships with your contracting partners. It can also provide objective justification for organizational or behavioral change.
DATA THAT CAN BE DERIVED
A single contract negotiation can provide a rich source of data, including total cycle time from initiation to signature, individual cycle time elements, amount of back and forth between parties, deviations from acceptable standards, number of escalations to resolves open issues, which party’s paper was used, total cost of legal support and initiation process compliance.
The list can easily expand to include more granular data by business or function, agreement type, country, industry, urgency or strategic value. It can be further expanded after signing to see if intended results were achieved, if there were disputes, and if the parties renewed or built on the relationship. The amount of data can be mind-boggling. Fortunately, technology is designed to facilitate the contracting process and capture data along the way.
To understand what data to capture, ask yourself what you are trying to accomplish. Start with your strategic goals and what success should look like. Next, map out actions and initiatives you believe will have a positive impact. Then, look at metrics — specific measures of success within established time frames. Finally, think about what data is needed to measure your progress toward your goals.
Many companies grab data via their contract life cycle management (CLM) platform, which facilitates contract support requests, routing, approvals, signatures and recording. Some CLM tools include other functionality, such as contract building, third-party term review and collaborative drafting. These make it even easier to capture negotiation issues, cycle times, escalations and resolutions. If your CLM is not configured to capture all the data you need, you can integrate one of the many workflow tools that collect and store data during contracting. AI tools that review third-party content can also supplement your CLM or workflow tool and facilitate data capture. Other ways to gather data are through contract summaries created post-closing or by conducting postmortems, at least for complex deals.
PUTTING DATA TO USE
Organizations often gather contract data and publish reports that include facts and figures on agreement types or categories. That’s good, but it’s just data until you put it to use. If a strategic goal is to increase market share in a core product or service line, success indicators may include reduced contracting cycle time, or an increase in number of contracts closed per quarter, or number of renewals.
Assume you set a goal to shrink sales cycle times by 25 percent over a 90-day period. To facilitate that goal, you’ve added more pre-approved alternatives, required deal registration, managed routing using a workflow tool, and established follow-up procedures to spur responses from designated approvers. If your organization doesn’t already capture cycle time data, you will need to establish a baseline that allows you to compare results after you’ve rolled out your improved tools and processes.
If the average time to close a standard enterprise sales agreement is 12 weeks and, after implementing new processes, the new average is 10 weeks at the 90-day mark, you may not declare success. But not meeting a goal isn’t necessarily a bad result if you can assess why. That root cause analysis should lead to modifications to address identified gaps or weaknesses.
In this case, perhaps initial review time shrank sufficiently, but escalations to subject matter experts continued to run too long. This part of the process needs attention. You might add more pre-approved alternatives or set an escalation response time goal and track results. You may also re-communicate why this is a priority, what the data is showing and what needs to change. The point is, you have the data to understand what needs further improvement; and you can use it to identify, motivate and measure important changes.
Gathering, aggregating and analyzing contract data provides insights that lead to strategies and actions to improve a team’s chance of success. The teams that make use of the information at their fingertips have a competitive advantage. Organizations responsible for contracting can give themselves a similar competitive advantage by embracing this unheralded asset.
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