  {"id":27547,"date":"2018-11-09T17:27:24","date_gmt":"2018-11-09T22:27:24","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-rctom\/submission\/lexisnexis-and-legaltech-automating-a-high-skill-service-industry\/"},"modified":"2018-11-13T18:02:36","modified_gmt":"2018-11-13T23:02:36","slug":"lexisnexis-and-legaltech-automation-of-legal-services","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/lexisnexis-and-legaltech-automation-of-legal-services\/","title":{"rendered":"LexisNexis and LegalTech: Automation of Legal Services"},"content":{"rendered":"<p>&nbsp;<\/p>\n<p><b><i><a href=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Logo-1.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-27541\" src=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Logo-1.png\" alt=\"\" width=\"365\" height=\"77\" srcset=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Logo-1.png 792w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Logo-1-300x63.png 300w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Logo-1-768x162.png 768w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Logo-1-600x127.png 600w\" sizes=\"auto, (max-width: 365px) 100vw, 365px\" \/><\/a><\/i><\/b><\/p>\n<p><b><i><\/i><\/b><b><i><a href=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Law-Pic.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-27533\" src=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Law-Pic-1024x569.png\" alt=\"\" width=\"762\" height=\"424\" srcset=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Law-Pic-1024x569.png 1024w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Law-Pic-300x167.png 300w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Law-Pic-768x426.png 768w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Law-Pic-600x333.png 600w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Law-Pic.png 1574w\" sizes=\"auto, (max-width: 762px) 100vw, 762px\" \/><\/a><\/i><\/b><\/p>\n<p><strong><em>\u00a0<\/em><\/strong><strong><em>\u00a0<\/em><\/strong><\/p>\n<p><em>\u00a0\u201cThe digitization of legal data constitutes [a] megatrend transforming workflows and business models. The volume of data used in legal advice has increased exponentially\u2026\u00a0 In the future, the ability to screen, analyze, and interpret unprecedented volumes of data will become just as critical to law firms\u2019 success as the \u201cart\u201d of delivering legal advice is now\u2026 The use of technology solutions to handle standard, low-skill legal tasks could reduce the ratio of junior lawyers to partners by up to three quarters of the ratio seen in the current pyramid model\u201d<\/em><\/p>\n<p>&#8211;\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 <em>How Legal Technology Will Change the Business of Law, BCG &amp; Bucerius Law School<sup>(1)<\/sup><\/em><\/p>\n<h2><\/h2>\n<h2><strong>Introduction to LexisNexis<\/strong><\/h2>\n<p>LexisNexis is one of two leading providers of computer-assisted legal research\u2014the company\u2019s mission is to \u201chelp lawyers increase productivity, improve decision-making and outcomes, and generate value for their organization\u201d<sup>(2)<\/sup>. Founded in 1970, the company pioneered the electronic accessibility of legal and journalistic documents<sup>(3)<\/sup>. Today, LexisNexis offers a suite of products, including a widely used \u201csearch engine\u201d for case law, advanced templates for legal documents, practice management software, and other tools for the professional legal market. The company\u2019s product portfolio incorporates over 30 terabytes of content, representing the world\u2019s largest electronic database for legal and public-records related information<sup>(4)<\/sup>.<\/p>\n<p>As illustrated in this essay\u2019s opening quote, industry participants have begun to realize the potential value that data, analytics, and artificial intelligence can bring to the legal industry; while we\u2019re likely years away from the transformative impact predicted by BCG, increasing venture investment <span style=\"float: none;background-color: transparent;color: #333333;cursor: text;font-family: Georgia,'Times New Roman','Bitstream Charter',Times,serif;font-size: 16px;font-style: normal;font-variant: normal;font-weight: 400;letter-spacing: normal;text-align: left;text-decoration: none;text-indent: 0px\">(&gt;$350M invested from April-Sept 2018, compared to ~$100M in full year 2010 <\/span><sup>(5)(6)(7)<\/sup><span style=\"float: none;background-color: transparent;color: #333333;cursor: text;font-family: Georgia,'Times New Roman','Bitstream Charter',Times,serif;font-size: 16px;font-style: normal;font-variant: normal;font-weight: 400;letter-spacing: normal;text-align: left;text-decoration: none;text-indent: 0px\">)<\/span> and corporate interest in LegalTech are bringing products to market that offer law firms significant advantages in terms of efficiency and capability. Given the realities of this environment, LexisNexis has a choice: innovate or be left behind by more progressive challengers.<\/p>\n<p><a href=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Product.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-large wp-image-34290\" src=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Product-1024x640.png\" alt=\"\" width=\"640\" height=\"400\" srcset=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Product.png 1024w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Product-300x188.png 300w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Product-768x480.png 768w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Product-600x375.png 600w\" sizes=\"auto, (max-width: 640px) 100vw, 640px\" \/><\/a><\/p>\n<p style=\"text-align: center\"><em>Product Snapshot: Lexis Advance (case law search engine \/ LexisNexis&#8217; most widely used product)<\/em><\/p>\n<p>&nbsp;<\/p>\n<h2><strong>Developing Legal Technologies<\/strong><\/h2>\n<p>LexisNexis has continued its legacy of innovation through significant organic and inorganic investment in machine learning, natural language processing, and other artificial intelligence technologies.<\/p>\n<p><u>Example 1 \u2013 Organic Investment \/ Internal Product Development<\/u>: In 2017, LexisNexis introduced the Lexis Answers feature to the company\u2019s case law search engine (the company&#8217;s most widely used product<span style=\"margin: 0px;line-height: 107%;font-family: 'Calibri',sans-serif;font-size: 11pt\"><span style=\"color: #000000\">\u2014<\/span><\/span>marketed as \u2018Lexis Advance\u2019). While legal research tools have historically been limited to basic search results and standard Boolean logic<sup>(8)<\/sup>, Lexis Answers uses machine learning and natural language processing to add three major improvements to the Lexis Advance product: A) search queries can be framed as standard English-language questions (e.g., \u201cwhat is the definition of joint tortfeasor?\u201d), B) search results more accurately predict the most relevant, comprehensive, and clear results for each individual user (based on the user&#8217;s query, firm, search history, and other data), and C) search queries are dynamically anticipated \/ suggested to the user<sup>(9)<\/sup>.<\/p>\n<p><u>Example 2 \u2013 Inorganic Investment \/ Acquisition of New Technologies:<\/u> LexisNexis has made a number of acquisitions aimed at enhancing the company\u2019s technological capabilities, including Lex Machina (in 2015)<sup>(10)<\/sup> and Ravel Law (in 2017)<sup>(11)<\/sup>. LexisNexis has used the technology acquired through these deals to expand its case law database, improve the functionality \/ efficiency of its core products (e.g., improving search results), and provide end-users with computer-generated predicted outcomes for various legal strategies (taking into account a wide range of factors including historical case results, presiding judges, competitive intelligence on opposing parties, witness credibility, etc.)<sup>(10)(11)<\/sup>. These functionalities provide customers with immediate, differentiated insight, and although current predictive capabilities are somewhat limited, the value proposition to customers will likely increase as these technologies improve and penetration\/adoption rates increase.<\/p>\n<p><strong>\u00a0<\/strong><\/p>\n<h2><strong>The Future of Efficiency and Automation in Law<\/strong><\/h2>\n<p>LexisNexis should continue investing heavily in new technologies, both through internal product development and selective acquisition. In the short-to-medium term, LexisNexis should focus its product development efforts on areas that A) represent a large percentage of lawyers\u2019 invoiced hours, and B) allow for relatively straightforward automation. The graphic below outlines a high-level framework\u2014product development opportunities addressing tasks in the top right quadrant, such as Legal Writing, represent the most attractive short-to-medium term opportunities. However, technologies that address the bottom right quadrant may still represent important short-term opportunities, and the top-left quadrant represents the highest value projects in the long-term.<\/p>\n<p><a href=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Framework.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-large wp-image-27532\" src=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Framework-1024x930.png\" alt=\"\" width=\"640\" height=\"581\" srcset=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Framework-1024x930.png 1024w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Framework-300x272.png 300w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Framework-768x697.png 768w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Framework-600x545.png 600w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Framework.png 1510w\" sizes=\"auto, (max-width: 640px) 100vw, 640px\" \/><\/a><\/p>\n<p>Rapidly increasing venture \/ corporate funding and quickly improving technologies have peaked the interest of industry stakeholders, however many questions remain. To what degree, and how soon, will artificial intelligence automate the more complex workstreams performed by Big Law (e.g., Negotiation, Legal Analysis and Strategy)\u2014will these technologies extend beyond standardized \/ basic workstreams? How slowly \/ rapidly will consumers adopt these technologies?<\/p>\n<p>(753 words)<\/p>\n<p>&nbsp;<\/p>\n<h2><strong>Appendix<\/strong><\/h2>\n<p><a href=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Appendix-1.png\"><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-27542 alignnone\" src=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Appendix-1-1024x882.png\" alt=\"\" width=\"433\" height=\"373\" srcset=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Appendix-1-1024x882.png 1024w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Appendix-1-300x258.png 300w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Appendix-1-768x662.png 768w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Appendix-1-600x517.png 600w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/LN-Appendix-1.png 1400w\" sizes=\"auto, (max-width: 433px) 100vw, 433px\" \/><\/a><\/p>\n<p>&nbsp;<\/p>\n<h2><strong>References<\/strong><\/h2>\n<ol>\n<li>Bucerius-education.de. (2016). <em>How Legal Technology Will Change the Business of Law<\/em>. [online] Available at: http:\/\/www.bucerius-education.de\/fileadmin\/content\/pdf\/studies_publications\/Legal_Tech_Report_2016.pdf [Accessed 9 Nov. 2018].<\/li>\n<li>Lexisnexis.com. (2018). <em>About Us &#8211; LexisNexis<\/em>. [online] Available at: https:\/\/www.lexisnexis.com\/en-us\/about-us\/about-us.page [Accessed 9 Nov. 2018].<\/li>\n<li>Miller, S. (2012). <em>For Future Reference, a Pioneer in Online Reading<\/em>. [online] WSJ. Available at: https:\/\/www.wsj.com\/articles\/SB10001424052970203721704577157211501855648 [Accessed 9 Nov. 2018].<\/li>\n<li>UPI. (2012). <em>Lexis-Nexis founder Don Wilson dies<\/em>. [online] Available at: https:\/\/www.upi.com\/Lexis-Nexis-founder-Don-Wilson-dies\/36121164992489\/ [Accessed 9 Nov. 2018].<\/li>\n<li>Ambrogi, R. (2018).\u00a0$200M In Two Months Says Investors No Longer Snubbing Legal Tech. [online] Above the Law. Available at: https:\/\/abovethelaw.com\/2018\/07\/200m-in-two-months-says-investors-no-longer-snubbing-legal-tech\/ [Accessed 9 Nov. 2018].<\/li>\n<li>Packels, S. (2018).\u00a0<em>Venture Capitalists Pour Another $115M into Legal Tech Platforms | The American Lawyer<\/em>. [online] The American Lawyer. Available at: https:\/\/www.law.com\/americanlawyer\/2018\/09\/11\/venture-capitalists-pour-another-115m-into-legal-tech-platforms\/ [Accessed 9 Nov. 2018].<\/li>\n<li>O\u2019Keefe, K., Reuters, T. and Reuters, T. (2017).\u00a0<em>Investment In Legal Tech Is Slowing While Legal Tech Is Booming<\/em>. [online] Above the Law. Available at: https:\/\/abovethelaw.com\/2017\/11\/investment-in-legal-tech-is-slowing-while-legal-tech-is-booming\/?rf=1 [Accessed 9 Nov. 2018].<\/li>\n<li>Clelaw.lib.oh.us. (2011).\u00a0<em>BOOLEAN SEARCHING<\/em>. [online] Available at: http:\/\/www.clelaw.lib.oh.us\/Public\/Misc\/Boolean%20性视界ing.html [Accessed 9 Nov. 2018].<\/li>\n<li>Lexisnexis.com. (2017).\u00a0<em>You Ask. Lexis\u00ae Answers\u2014new machine-learning feature on Lexis Advance<\/em>. [online] Available at: https:\/\/www.lexisnexis.com\/infopro\/keeping-current\/b\/weblog\/archive\/2017\/06\/29\/you-ask-lexis-174-answers-new-machine-learning-feature-on-lexis-advance.aspx [Accessed 9 Nov. 2018].<\/li>\n<li>LawSites. (2018).\u00a0<em>Exclusive First Look: Ravel Law&#8217;s Integration with Lexis Advance | LawSites<\/em>. [online] Available at: https:\/\/www.lawsitesblog.com\/2018\/02\/exclusive-first-look-ravel-laws-integration-lexis-advance.html [Accessed 9 Nov. 2018].<\/li>\n<li>Lex Machina. (2015).\u00a0<em>LexisNexis Acquires Premier Legal Analytics Provider Lex Machina<\/em>. [online] Available at: https:\/\/lexmachina.com\/media\/press\/lexisnexis-acquires-lex-machina\/ [Accessed 9 Nov. 2018].<\/li>\n<li>Remus, D. and Levy, F. (2015). Can Robots Be Lawyers? Computers, Lawyers, and the Practice of Law.\u00a0<em>SSRN Electronic Journal<\/em>.<\/li>\n<\/ol>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Most discussions of job automation tend to focus on relatively unskilled labor &#8211; self-driving cars, factory automation, etc. However, companies applying technology toward the automation of white collar jobs are gaining traction &#8211; this piece examines progress in the Legal Services market.<\/p>\n","protected":false},"author":11509,"featured_media":27554,"comment_status":"open","ping_status":"closed","template":"","categories":[],"class_list":["post-27547","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry","hck-taxonomy-organization-lexisnexis","hck-taxonomy-industry-legal-services","hck-taxonomy-country-united-states"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-rctom\/assignment\/rc-tom-challenge-2018\/","yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - 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