My 2020 vision for in-house legal teams? Time to start embracing data-driven decision making
The availability of AI technology and the pressure on corporate legal departments to become more efficient is encouraging the adoption of data-driven decision making. By that I mean, using data from prior
transactions or matters to inform strategic and tactical decisions about future matters.
The rise in AI, legal bots, and contract automation is helping ensure this is going to be one of the key legal trends of 2020. And it can’t come too soon.
Looking back to my time as head of contracts at Asda, decisions on how we would approach contracting were often made based on our lawyers’ experience and instinct.
We had an award-winning team, so we usually got it right, but there were inconsistencies and we were hit hard when one of the team left the business, taking all their contextual knowledge with them.
What’s more, most contract negotiations necessitated escalation to a senior member of the legal team, which created a bottleneck in the overall process.
To address these issues we invested time and effort building a playbook to standardise and codify our approach to common contractual issues. The playbook was extremely effective (and still in use as far as I know), but putting it together required serious thought and the exercise was far from scientific – we relied upon our collective corporate memory to get it right.
Fast forward three years and more and more corporate legal teams are now using data to spot patterns in negotiation outcomes and inform playbook development.
Harvesting data from digital contracting systems
At SYKE we focus on selecting, configuring and delivering digital contracting systems for corporate legal teams. These systems are capable of capturing vast quantities of data. If the systems are set up correctly this data can be an invaluable resource to a corporate legal team’s senior leadership.
Below I have listed some examples of the kind of data that can be captured by a digital contracting system:
- Time from contract instruction to conclusion, potentially segmented into phases, e.g. gathering instructions, drafting, negotiation, approval, signature, storage
- Negotiation patterns – what is being negotiated and how the negotiation is resolved
- Resource allocation amongst internal and external lawyers
- Patterns in demand for contracts, potentially segmented into business units and sales/purchasing cycles
- Key contract data to enable effective management of contracts, e.g. expiry dates, key milestones
- Commercial and legal risk indicators, e.g. non-standard payment terms, indemnities, irregular liability
By analysing these data points, future strategic and tactical decisions are far easier to make and the outcomes are better.
Challenging misconceptions about the legal team and improving the approval cycle
Recently a customer was able to use data from a digital contracting system to challenge the misconception that the legal team were causing delay in the contracting process and identify the real bottlenecks.
In this example, the approval of non-standard payment terms accounted for 60% of the approval cycle for all contracts. Armed with this data the customer worked with their finance team to adjust internal processes so that certain deviations are automatically approved whereas others are strictly prohibited and not available to users as an option. This has drastically shortened the approval lifecycle.
Analysing data from existing contracts
Corporate legal teams are also increasingly using AI tech to analyse data from existing contracts. This is more challenging (and thus costly) than collecting real-time data, but the output can be worth the investment. Typically I see this kind of activity as part of a corporate legal team’s efforts to migrate to a digital contracting system, so the focus is key contract data, but there are also some interesting alternative uses for compliance and playbook development.
Our work for the AA is a good example of this in practice. The AA had two separate issues to address. Firstly, they needed to capture 30 data points from 2600 contract documents to enable those contract documents to be uploaded to their new digital contracting system. Secondly, they needed to vary the contracts for GDPR compliance. Working with legal service provider P3 and AI tool eBrevia, we extracted the data and uploaded it to their new digital contracting system. We then uploaded a copy of the data to contract automation tool Contract Express to produce letters of variation. The entire effort took just over a month and was relatively inexpensive vs. traditional methods.
Deviation analysis using data from negotiated contracts to reduce the negotiation cycle
Working for another customer, we determined that negotiation of one contract template (terms and conditions for the purchase of services) accounted for 90% of the utilisation of their contracts team resource. By drilling into the data, we determined the reason it was draining so much resource was that liability was uncapped and indirect loss not excluded. Adding a market fair cap and exclusions immediately halved the utilisation spent on this template freeing up time to deal with high risk/complex issues.
As more and more businesses harvest data through legal technology, the trend for reusing this data to improve legal operations will grow. Mature customers who have been using legal technology for several years are recognising the wider business benefits it brings them.
Analysis of contracts is made easier once they are digitised and held in a central depository. Very quickly it becomes apparent systemising contracts with vendors can yield better returns (unnecessary variances are avoided), and costly disputes minimised when the root cause of previous instances is identified (this can be as simple as contracts that are not countersigned by both parties).
As lawyers ourselves at SYKE, we recognise the industry we love is going through an unprecedented period of disruption.
Corporate legal teams need to embrace the data they already have access to and start to codify their operations through the adoption of playbooks and contract automation.
Rather than fear the change ahead, we believe there are great opportunities to do things even better, save clients money, and improve outcomes for both them and their customers.