The Rise of the Machines: Surviving (and Thriving) in a Legal Tech World
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The document discusses how legal organizations can leverage data and artificial intelligence to improve contracting functions. It describes how moving from traditional reporting to cognitive insights powered by machine learning and natural language processing can provide benefits like optimization of approval workflows, alternative clause recommendations, and prediction of contract compliance and cycle times. The document also outlines how AI could take organizations to the next level through capabilities like an intelligent virtual agent and machine learning to automate parts of the quote-to-cash process.
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The Rise of the Machines: Surviving (and Thriving) in a Legal Tech World
- 1. #AccelerateQTC Neil Hughes, Elliott Yama, Lauryn Haake, David Bayer May 4, 2017 Rise of the Machines Surviving (and Thriving) in a Legal Tech World
- 2. David Bayer VP, Text Analytics Lauryn Haake Managing Director Elliott Yama Assistant VP Neil Hughes Writer
- 4. Data, Data, Everywhere… Commodity Data are now a separate Asset Class Accessible 10% increase in data = $65M net income Analyzed <0.5% of all data is analyzed & used 44ZB $65M .5%
- 5. “Weaponize” Your Data 1. Data is valuable… when properly harnessed 2. Do you really know your data? 3. Blind spots = more risk, lost revenue, wasted time
- 6. 6 One small step for man…
- 7. Reports: Measuring the Contracting Team
- 8. Reports: Measuring the Contracting Function
- 9. 1. Data science enables better decisions 2. Data analysis can drive behavior 3. Complex transactions and infinite data points requires more than human review Moving from Reporting to Cognitive Insights
- 10. Moving from Reporting to Cognitive Insights Cognition Integration Authoring and Negotiation Reporting and Analysis Repository Machine-driven insight to raise performance against key metrics Connection to Quote-to-Cash, ERP and other systems Efficient drafting, approval and execution abilities Understanding risks, obligations, key dates and other contents All contracts accessible to those who need them INCREASINGROI
- 11. Cognitive Insights Drive Contracting Function • Approval Optimization • Alternate Clause Recommendations • 3rd Party Paper Clause Reconciliation
- 12. Cognitive Insights Drive Contracting Function • Contract Compliance Prediction • Contract Cycle Time Prediction • Clause Library Setup Guidance
- 13. • Computers can beat humans at chess and Jeopardy, but not karate • Productivity, speed and scalability • Even though a computer can learn, it must first be taught Humans & Machines: Sleep, Scalability and Sarcasm 13
- 15. • Skynet, Ultron and self-awareness • Intelligent Import and 3rd Party Paper Processing • Machine Learning/Natural Language Processing Artificial Intelligence
- 16. Artificial Intelligence Takes Us to the Next Level Using NLP, Max understands your conversational intent and provides you with intelligent, frictionless guidance, rule execution and approval workflows. Powerful Virtual Agent With Machine learning, Max can provide intelligent recommendations, make predictions and complete components of the QTC process so you don’t have to. Intelligent Transformational Max adds a conversational layer over every process in QTC amplifying existing ROI.
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Editor's Notes
- Music was primarily enjoyed via analog storage for most of the 20th century. 8-tracks and cassettes made music more mobile. In the 1980s, digital media gobbled up the music market. Quality increased and it again became easier to jump straight to a song without the endless hours of rewinding/fast-forwarding. First TEST PRESSING – Strauss “Alpine Symphony” (1979) First PRODUCED – ABBA “The Visitors” (Aug 17, 1982) First SOLD – Billy Joel “52nd Street” (Oct 1, 1982) – in Japan First MANUF. IN U.S. – Bruce Springsteen “Born in the U.S.A. (Sept 1984) CDs gave way to MP3 and converged with the Internet for cloud-stored and delivered music anytime, anywhere on varity of devices Now we have apps like Pandora, Spotify, etc that not only deliver music, but leverage data from users’ collections, preferences and listening habits to deliver custom playlists based on recommendations. So other than the fact that you can now answer a few more questions at Trivia Night at your local bar, why does this matter?
- Because the evolution of music (among other things – movies (Netflix), shopping (Amazon), fitness (Fitbit), etc is being fueled by data. Measurement is a modern obsession, but it's too expensive to collect numbers if you can't use them to take action. Data has become one of the most important commodities in our world. According to the World Economic Forum, data are now a separate asset class. The data volumes are exploding, more data has been created in the past two years than in the entire previous history of the human race. Data is growing faster than ever before and by the year 2020, about 1.7 MB of new information will be created every second for every human being on the planet. By then, our accumulated digital universe of data will grow from 4.4 zettabytes today to around 44 zettabytes, or 44 trillion gigabytes. ______________________________________________ For a typical Fortune 1000 company, just a 10% increase in data accessibility will result in more than $65 million additional net income. Retailers who leverage the full power of big data could increase their operating margins by as much as 60%. At the moment less than 0.5% of all data is ever analyzed and used, just imagine the potential here. _______________________________________________ From Amazon to Uber to Facebook and Netflix, data have driven a rise in collective intelligence through connectivity. It is only natural that applying the same data-driven principles to your legal department can yield incredible results and competitive differentiation. In fact, in my world of contract management, converting your contracts from simple documents stored out of sight into data-driven, crowd-sourced prediction and advisory engines can innovate and optimize the way you do business in real-time.
- And today, it’s more than just having a system with a reporting function to show us what has already happened… we see that real-time data-driven feedback all around us at home and work and on vacation… We now have refrigerators in our homes that tell us when we’re running low on milk, watches that tell us how well we slept and cars that drive themselves… all because of data. What if your contracts could speak to your legal department like our home appliances are now doing? What if obligations that you’ve spent months or years negotiating weren’t just buried on the back pages of some quickly-forgotten document, but rather became fuel for proactively managing your business? What if the risks you accepted because you thought they were highly unlikely to occur were part of a profiling mechanism that gave your company advanced warnings of potential issues instead of learning about them after the lawsuit was filed? The amount of data contained in, and more importantly, across your contracts can give you the big picture and help you navigate the regulatory and compliance landscape without adding headcount or slowing down the process. (CLICK) In fact, when the data is properly harnessed, you can actually do more with less… and faster. __________________________________________________________________________________________ (CLICK) Do you really know your contract data and what it’s trying to tell you? How many you have? Active vs expired? Autorenewing? What terms and clauses are in them? Which business processes rely on the contract metadata to be efficient… or work at all? Can you spot potential conflicts or issues ACROSS contracts… or just within them? __________________________________________________________________________________________ (CLICK) The lack of visibility into contract obligations and liabilities creates exposures to risk that cause attorneys to feel the need to review every contract in detail, regardless of risk profile or value. This is a drain on the already-overburdened staff and leads to increased risk overall. These issues can snowball when the sales team’s process is slowed by this inefficient review and the finance team is unable to properly recognize revenue and approve non-standard deal terms. Altogether, these issues across the company create legal risk, lost revenue, and wasted time.
- So what does weaponized data in contract management look like today? REPORTS
- See contract quantities by line of business Drilling down into contract types Further drilling down into quantity of contracts processed by contract management/negotiator Further looking at those contracts by contract value Individually, each report may tell you something specific…. (CLICK)
- But when aggregated, you may start to see not just the quantity of contracts being cranked out, but the quality and value of those contracts to your business This is visibility that may not be available if your contracts are stored in file cabinets or various folders across a network system.
- Introducing data science, use case modeling, natural language processing and machine learning allows: You to “see around corners” in negotiating your contracts – leveraging data from past deals, related deals or even other systems like matter management which may house data about disputed contracts. The system to automatically create risk profiles during contract authoring or provide real-time, dynamic guidance to your contract manager instead of them relying on the old 3-ring binder of rigid rules for when a certain clauses is included or what levels of damages are acceptable for the specific deal or what venues are acceptable for the choice of law provision. Or in the bigger picture, provides visibility and insight into threats that exist ACROSS contracts (not just within an individual one) – for example – does this pricing violate an existing Most Favored Nation or Preferred Provider Provision in another customer contract that you wouldn’t have known to look for (or known it even existed). In HLS, things like Stark Law and Anti-Kickback require hospitals to actively monitor their physician agreements to insure compliance with payment rules, or perhaps uncover contracts with physician’s family members, etc.
- Kicking it up a notch, moving from reporting to cognitive analytics moves us up the contracting maturity model and converts our view of data from being solely reactive to becoming proactive.
- THE NETFLIX EFFECT: Approval optimization – Recommends optimal approval processing steps for sales and purchasing contracts based on the approval process applied historically to similar contracts. The solution considers approver availability to optimize approval cycle time. Approval optimization helps your operations team streamline approvals for maximum efficiency and effectiveness. Alternate clauses recommendations – Recommends alternate clauses where needed in sales and purchasing contracts to manage risk. Alternate clauses are recommended based on comparison with similar clauses and historical, similar contracts. The solution keeps track of all clauses in a given contract in order to guide your sales reps to generate self-service contracts. 3rd party paper: clause reconciliation – Risk rating and recommendations to reconcile third-party terms based on analysis of language, terms, and historic contracting practices. This solution helps your legal operations team efficiently evaluate and reconcile terms and conditions of 3rd party paper in the contracting process.
- Contract compliance prediction (Risk scoring) – Track customer compliance of contract terms that may impact revenue and gain machine learning insights into non-compliance risks with early warning predictions based on analysis of historic contract and customer performance. The solution helps sales reps, global account managers, and contract teams drive contract compliance and reduce revenue leakage with data-driven insight. Contract cycle time prediction – Predicts the cycle time to execute a contract based on analysis of the contract template, terms and conditions, and approval history. The solution helps your sales reps and sale operations teams with recommendations for clauses and terms to reduce delay and speed cycle time. Your legal and finance teams benefit from guidance for on-time arrival of contracts and early warning delay risk identification. Clause library: setup guidance – Applies machine learning to historical contracts to help your legal team to build a clause library with risk scores based on historical downstream outcomes. Your legal team gains insight to create a library of clauses to empower sales reps to generate their own sales side contracts and improve sales efficiency.
- Computers can beat humans at chess and Jeopardy, but not martial arts There are still some human activities that computers can’t learn Productivity, speed and scalability Machines do not tire, even when faced with endless, mundane tasks Humans lack computing power to process large amounts of data quickly or scale to reach larger audiences Machines don’t read between the lines, pick up contextual clues and insights from abstract concepts (basically, they don’t get sarcasm) Even though a computer can learn, it must first be taught Tuning algorithms, human-assisted contract review Understanding poorly drafted contracts Researching missing or incomplete information Resolving conflicts in data
- Moving beyond predictive insights, we’re entering a paradigm shift in simply interacting with our technology – both at home, and now at the office. Data is powering our shopping, our TV watching and now even our corporate contracting function… The evolution of intelligent agents makes replicating the human experience possible and makes the contracting process as easy as having a conversation. Of course, some companies are leveraging data in even broader terms than just their contract portfolio…