Buying Intelligence: Navigating the AI Supermarket

28 Oct

person holding compass

By Amy Monaghan, Practice Innovations Manager at Perkins Coie LLP

There are numerous options for artificial intelligence (AI) products in the legal technology marketplace and more options are being added on what seems like a weekly basis (2019 has already seen a $1.2 billion explosion in legal tech investment). With the prevalence of options, what do you need to know in order to be an informed customer? The blog post will help you ask questions to identify the problem you are trying to solve and guide you through considerations when evaluating AI solutions.

Identifying the Need

Defining your business problem is the most critical task when determining whether AI is the right solution and, if so, which products meet your needs. Without a clear understanding of your firm’s or legal department’s needs, you cannot make an informed decision and could wind up wasting time and money. Potential business problems include: streamlining large volume transactions, particularly reviewing and analyzing documents; researching and drafting more efficiently; automating routine legal analysis or documents; or analyzing data, including predictive analytics. Talk to your stakeholders to identify what their specific needs are and prioritize accordingly. Once you have done so, gather formal requirements from the ultimate consumers of the solution (this can be the users and the consumers of the output), separating them into two categories: “must have” and “nice to have.” Create a matrix or checklist of these requirements for use when interviewing vendors and evaluating demos of products. Your nice-to-have’s might be on a vendor’s roadmap so including them in your matrix can help inform your product selection.  Be sure to build flexibility into your requirements for future needs—talk to your stakeholders about their business and strategic plans so you have an idea of what solutions they will need in the future.

If your need is to “try out AI,” I urge you to keep digging into that request to uncover the root issue. Similar to the recommendation to not go grocery shopping without a list, do not go AI shopping without a clear need or strategy for how you will use it. That being said, sometimes you do need to test out a technology to know what’s possible before identifying what’s necessary. In this case, your requirements will be more flexible and your exploration will likely inform your ultimate needs.

Going Shopping

With your requirements in hand, it’s time to evaluate your options. You’ve likely done some research already and have an idea of the vendors you want to speak with.  Given the rapid change in the marketplace, do a second pass to see if any newcomers have viable options. Reach out to your peers to ask about their experiences with different solutions. There is a wide range of potential solutions, from open source options to full-service, ready-to-use products.  Be sure you understand what you are evaluating and the flexibility or complexities that come with that approach. (For a wonderful analogy to brownies, see Gwyn McAlpine’s contribution to this ILTACON panel recording at about the 9:30 mark.)

When reviewing the capabilities of a product, ask vendors to tailor their demo to your specific use case. On a panel at the recent Emerging Legal Technology Forum in Toronto, Al Hounsell from Norton Rose Fulbright shared that, when evaluating no-code platforms, his firm gave each vendor the exact same use case and requirements.  As a result, they were able to hold an objective bake-off. Similarly, I participated in an initiative where we gave machine learning contract analysis vendors the same data set and asked them each to train models using the set. We then evaluated the models’ performance on test data. This approach may not be applicable for all scenarios but can be a useful way to objectively evaluate how well as solution meets your requirements.

In addition to planning use cases to direct the demo, educate yourself about the different flavors of AI and which are applicable to your scenarios.  Unsupervised AI largely deals with classification and clustering, whereas supervised AI is used for more targeted tasks like language extraction. Expert systems can use if-then-else logic along with relevancy or inference prioritization, which is ideal for expertise automation or guided interviews. A few vendors are starting to combine machine learning with other forms of AI, like expert systems, to provide multi-tasking solutions, which can be helpful for more complex use cases.

Be sure to evaluate both technical and non-technical considerations related to products and vendors.  Below are some examples of questions to ask vendors to determine if your requirements are met.

Technical Questions

  • What type of machine learning is used? Supervised? Unsupervised? Both?
  • Does the product come pre-trained with ready to use models? If so, what is the best use of the models? How often are they updated? Who are the trainers? What training data is used? Where sourced? How are the models QA’ed?
  • Do you have the ability to self-train models? If yes, do you understand the process for training models and the data and skills that are needed? Depending on the type of models you need to train, you may need very different sizes and types of data sets. Note that most products that offer pre-trained models or pre-configured templates largely rely on publicly available data, which may not be appropriate for your needs. In this case, you will want a product that allows for customization or self-training.
  • Does the vendor offer best practices or other guidance on model training?
  • Can you collaborate on model training with others outside of your organization? This is a developing request we are seeing in the industry.
  • What technical skills are needed to build applications that use logical reasoning for application building or document automation?
  • Does the vendor have an open API? This is necessary if you will need to leverage multiple solutions to solve problems.
  • Does the product directly integrate with other products? If so, how are product updates handled? Do the vendors coordinate and QA prior to updates?
  • Does the vendor offer a user acceptance testing (UAT) environment or other test environment where you can preview new features prior to release?
  • For cloud solutions, where does the data reside? Do they offer encryption keys? Who holds the keys?
  • What technology resources are needed to assist with implementation?

Company Questions

  • Always ask for the roadmap. This will give you an idea of where the company is headed and if it will be a good partnership.
  • What is their primary revenue source? Is it their product(s) or professional services? Or a split between the two? If the latter, this could indicate complexities in implementation.
  • What is the maturity of the company? Established? Startup? Working with startups might involve greater risk, but the product and company could be a great partnership. For example, I began using Kira Systems (back when they were Diligence Engine!) not too long after they came to market. It’s been a great experience working with them and their product and they have now grown to be a market leader in the machine learning for contract analysis space.
  • Do you feel good about the relationship? This will be a partnership so it will be critical to get along and trust the vendor.
  • Ask the vendors for references and talk to those references about their experience, including support.

Implementation and Support

  • Will the vendor help with implementation and rollout or provide change management guidance specific to their product? Do they have best practices and help resources? If not, preparing your own materials and programs can be very time consuming so plan ahead.
  • Does the provider offer a trial period or proof of concept pricing? This is often the best way to determine whether the product is right for your needs.
  • If subject matter experts/ultimate consumers of the product were involved in the vetting process, ask them to share their impressions and use cases for your rollout materials.
  • Consider asking your early adopters to co-present with you during rollout or provide a testimonial in another form of communication. During our Kira rollout at Perkins Coie, I asked a senior counsel to co-present with me at a firmwide M&A meeting on how he was using the product and provide guidance to his peers. His insight resonated with his colleagues and alleviated their concerns about incorporating AI technologies.
  • Will you and your users have regular opportunities to provide feedback to the vendor? What will the format be? How will the vendor use your feedback?

Conclusion

As you can see, there are many considerations when choosing and implementing AI products. Many of the current offerings come with a steep price tag.  By doing your research and knowing your use cases, you can avoid an impulse purchase at the register!

 

Introducing Robotic Process Automation (RPA) Into Your Organization

15 Oct

high angle photo of robot

By Berys Amor, Director of Technology at Corrs Chambers Westgarth

My first encounter with Robotic Process Automation (RPA) was through an introduction in early 2018 to a Melbourne start-up (Ci-Gen) who were providing intelligent automation services to businesses in the Asia-Pacific region. While the banking and insurance sector had seen rapid interest and uptake of RPA, I didn’t really understand how it could be utilised in a law firm.

At the first meeting I asked the Ci-Gen directors to talk to me about some use cases that they had been involved in. They described how a large hotel chain were using software robots to analyse expenses overnight, looking for any anomalies or unusual expenses. The aim was to capture any incorrect or unusual charges immediately, to avoid any disputes or unhappy guests.

This example made me think about how we analysed timesheet entries on a daily basis – this involved a finance team member running reports from the practice management system each morning, extracting the data to an Excel spreadsheet and then sorting and analysing the data to look for any unusual entries, as well as missing timesheets. Maybe this was something a robot could do? We identified three other processes that we could automate and worked with Ci-Gen to scope a Proof of Value (PoV) initiative. We wanted to demonstrate that software robots are able to accurately access and interact with various nominated applications, accurately capture input data, reformat/repurpose the data where required and pass data between applications as directed.

The objective of the PoV was to ascertain if RPA would be an effective approach to reducing effort in areas where there is sufficient volume and repetitive processes, with an end goal of increasing efficiency, accuracy and timeliness.

The four processes that we identified for the PoV were:

  • Client WIP Reporting – run WIP report using our BI tool and then upload the report to the client portal site for client access.
  • Timesheet Analysis and Reports – look for missing timesheets and send alert to the fee earner.
  • Non-Billable Timesheet Analysis – analyse non-billable time entries to search for narrations such as matter, client, or research to verify non-billable.
  • Partner Profitability Report – run BI profitability report for each individual partner and send via email.

The PoV was performed over a three-week period – if the project failed the investment was small, but if successful the project could scale up and be converted to a production-ready system.

The PoV was a clear success and the automation of these processes demonstrated that the software robots could interact with a range of applications, data types and data sources, and also assist with sorting and identification of mass data sets (150,000+ lines).

Fast forward 12 months and we have a fully functioning Corrs Automation Services team, made up of our Data and Automation Manager, a Process Automation Business Analyst and our two robots, Robbie and Dexter! It was really important to launch the automation services with a dedicated business analyst and this was factored into the business case for RPA. If the task of looking for processes to automate was part of our already busy team of business analysts, then we would not have achieved immediate results, quick wins and the project could have floundered.

Since the implementation of RPA the Corrs Automation Services team have analysed and automated numerous business processes. We created an RPA Evaluation form to determine whether a process is a good fit for RPA. It has questions such as: is the process documented, what systems are involved, what inputs are required and what frequency, and what are the perceived benefits of automating that particular process. It is also important to measure improvements by documenting the before and after results.

The team have worked closely with the finance team to automate many reports and processes, for example we created a workflow template for a robot to run utilisation reports for each partner from our business intelligence application. Each report is bespoke to the partner and is distributed to them automatically with 100% accuracy. This robot template is also a being used to compile and distribute many different reports to various groups

While RPA is typically used for back office processes and functions, we were keen to let our robots work within the practice groups themselves. Our first opportunity came early in the project when we were migrating our conveyancing service from an on-prem SQL database to a cloud-based e-conveyancing platform. We estimated that it would take a paralegal six to eight weeks to re-enter the existing property developments into the new platform – a tedious task with lots of room for error.

The first step was to populate the cloud platform with 8,000 solicitor records. The team then programmed a robot to read an Excel file, validate each data field and then log into and input this data into the new cloud application.

The second step was to migrate over 400 property lot records for the first development, which  involved the robot logging into the old database, extracting all the records and inserting them into a spreadsheet, validating the format and performing a split and merge, before logging into the new platform and entering each record. The migration was completed by the robot in 12 hours with 100% accuracy. This workflow is now being used to migrate other projects.

The RPA project has allowed Corrs to transform roles rather than replace them, giving employees time to invest their talents in more engaging and interesting work. Robots are extremely accurate and consistent – they are much less prone to making mistakes or typos than a human worker and operations can be performed 24/7 as robots can work tirelessly and autonomously without requiring manual trigger. As a result, process cycle times are more efficient and can be completed at a faster speed compared with manual process approaches.

SharePoint as a KM Tool

8 Oct

sharepointBy Holly Hanna, KM Firm Solutions Manager at Perkins Coie

Many law firms and law departments use SharePoint, either on premise or as part of Office 365, to host their intranet. As a hosting platform, SharePoint allows firms to publish content and link to important resources.

However, legal organizations can also use out of the box functionality to quickly build prototype knowledge management solutions, gather feedback from stakeholders, and then publish to targeted practices.

Lists and Libraries

SharePoint lists and document libraries are core SharePoint features. Files are stored in document libraries, and then linked in a list that is displayed on a page and made available to end users. This simple framework provides an ideal platform for prototyping legal knowledge management solutions.

Libraries can be used as a common repository for key practice documents and workflows can be added, so that when documents are submitted, they go through a review process before being given the ‘seal of approval’ and made available to practitioners.

In addition, many practices track resources and best practices in either Excel or Word. Such resources can be easily moved to a SharePoint list, giving attorneys additional functionality and flexibility.

With either a list or a library, you can create a scoped search that returns results against the specified target, making it easy for your end users to find the one piece of information they’re looking for in that specific data repository.

All About the Metadata

With both lists and libraries, the true strength of SharePoint as a knowledge management tool lies in the ability to apply metadata columns and enforce data types and field entries – functionality that doesn’t exist with a Word document or Excel spreadsheet.

For example, if you’d like to create a searchable list of state blue sky laws and associated requirements, you can create data columns based on whether there are exceptions available, whether plan and regulation D filings are required, fee information, etc. You can set some columns to be required, and you can also give users a dropdown of options to select from, ensuring that data remains normalized; users can also attach associated documents for reference purposes. Views of your list can then be created (e.g., show only laws with an employee benefit plan exemption) and those views can be added to a SharePoint page that is available to practitioners.

SharePoint on Steroids: Office 365

To be successful, any knowledge management repository needs to be easy to contribute to, easy to update, and easy to search. On premise SharePoint solutions are both easy to update and easy to search, but adding new content can be challenging for end users. Workflows are difficult to create, and intake forms need to be created and managed using InfoPath 2010 (a deprecated Microsoft product) or a separately licensed product such as K2 or Nintex.

However, with Office 365, we can take advantage of Flow and PowerApps to easily create intake and workflow solutions. Workflow solutions can display different fields to different users depending on their level of permissions, so an approver can see a set of data prompts that a submitter cannot. The form itself is modern and intuitive. And since it’s a cloud solution, it can also be made available from a mobile device if desired.

Microsoft also has a robust artificial intelligence (AI) platform that holds promise for legal organizations looking for new and innovative ways to interact with key data resources.

Conclusion

While many legal organizations use SharePoint as an intranet platform, it is also a valuable knowledge management tool that allows you to quickly spin up prototypes and proofs of concept, validate with your stakeholders, and publish to your practice groups. Practices that are currently using Word or Excel to manage key resources will be better served by moving those solutions into SharePoint. And Office 365 provides new avenues for knowledge management solutions with a focus on the end user experience and ease of use.

Leveraging Artificial Intelligence to Populate Knowledge Management Repositories

16 Sep

abstract blackboard bulb chalk

By Gwyn McAlpine, Knowledge Management Director at Perkins Coie LLP

Among the Knowledge Management (KM) community, one question we commonly hear is this: “How can I use artificial intelligence (AI) to populate KM repositories?”  I have good news and less good news.  There are pockets of success out there, but you need to be realistic about what AI excels at today.

The Problem

KM can involve significant manual effort that entails subject matter expert involvement.  Developing forms banks, practice-specific content, and matter and experience databases requires someone familiar with the area of law to parse through documents and matter information to identify standard practices and relevant data points.  Because our subject matter experts are often timekeepers or otherwise have limited bandwidth, initiatives that require their input can often stall.

Not surprisingly, as technology advances, inquiring minds want to know if AI can replace some of this manual effort.  The nirvana that many want to attain is for technology to successfully analyze piles of documents and data to build gold standard documents and provide insights into our matters and people.  Complete nirvana is still a dream—or at least a lot more work than we imagine it to be.  Nonetheless, creative KM professionals are coming up with ways to use today’s technology to augment the work of the KM team for the benefit of the practices.  Note that this post is not discussing attorneys using AI to supplement their client work, for example, to aid in research and document review (technologies that KM may manage), but rather KM professionals or attorneys using AI to supplement their work in developing KM content.

Today’s Successes

At ILTACON 2019 in August, a fantastic panel presented on “AI-Powered Knowledge Management,” which directly addressed this question.  Click here to listen to the recording.  If you are interested in this topic, it is well worth an hour of your time.  You can also read a recap of this session from the Legal Executive Institute here.

The four panelists presented on efforts at their firms to use AI to further KM projects.  A common thread among their projects is that they are all using AI technologies to extract data and clauses from final documents with software often used for contract analytics, such as ContraxSuite, Kira or iManage RAVN Extract, which then populates a database for easy reference and/or further analysis.  Stated differently, the panelists are applying the technology to unstructured documents and pulling structured data points, such as dates, amounts, and specific clauses, from them into a database.  Use cases were largely around collecting data from transaction documents for two main purposes: (i) to get a big picture of trends and (ii) to be able to find a matter in which a specific set of circumstances occurred.

Interestingly, most of these projects are still in pilot or limited production, validating that these types of use cases are still relatively new.  A KM peer I interviewed for this blog post noted that the relevant technologies have been used by law firms for only a few years, and the early days were likely spent on rolling them out for their core purpose, typically contract review for due diligence.  Firms may only recently be exploring other applications for these technologies.

The panelists were united in their lessons learned.  These projects require investment—from up-front project design and model training, to subject matter expert validation, augmentation, and analysis of results.  Like with many other applications of AI, technology is streamlining the work, but not replacing it.  Someone must dedicate time to and prioritize the effort.  But once you get started and become more familiar with the capabilities of AI, you will think of more use cases that leverage the ability to extract data points.  Extracting data alone is useful, but coupled with metadata tagging and data visualization tools, such as Power BI, it can drive powerful insights—and attorneys get very excited about these insights.

Tomorrow’s Hope

My nirvana state of using AI to build gold standard documents is not quite there yet—at least, not at a level of accessibility to apply broadly.  If you have a very specific use case and the volume to justify the work, you can combine professional services, technology, and a lot of elbow grease to achieve this goal.  But for most use cases, the level of investment required today may be too great for the payoff.

However, if we focus on using AI to supplement and streamline steps in the process, rather than rely on it to achieve the end goal, it is clear that AI can contribute toward document repositories as well as databases of information.  One way to employ AI to create KM document collections is to use contract analytics software to isolate provisions in work product that require redacting, so you can add sanitized precedents to your forms bank.  Another is to extract similar clauses across sets of documents to speed up the work in analyzing standard, alternate, and nonstandard language.  The challenge here is crafting a human-technology partnership that leverages the abilities of each in an efficient manner.

Technology is changing rapidly and may lead to different possibilities within the next few years.  In the meantime, though, AI can be used to further KM projects provided that you set realistic expectations and design your project to take advantage of its current capabilities.

What are the Best Ways to Drive Adoption and Reduce the Risk of Resistance to Change?

25 Jul

orange and and brown chess pieces

By Sharon Ford, Technology Education Specialist at Perkins Coie

There are many interesting changes in the Knowledge Management (KM) area including AI and machine learning, chatbots, automation and more.  Many of these initiatives involve technology changes, but they also result in process changes including how people work, and they may evoke emotions including concerns about job security.  Regardless of the type of change, one thing you need to keep in mind is organizations don’t change; people do. If individuals need to change, then there needs to be a focus on people when initiatives are implemented and that is where change management comes in.

Whether a change being implemented is defined as a KM change or any other change, I encourage you to evaluate every project you are implementing with a change management lens.  How can you do that? While this is not an official change management model, I’m going to leverage something you probably learned back in grade school – the Five Ws. The Five Ws (sometimes referred to as Five Ws and How) are questions to be answered for basic information gathering or problem solving.  They are often mentioned in journalism and research, and they comprise a formula for getting the complete story on a topic.

The 5W example can be applied to provide a change management lens for your projects including:

1) What’s the Why?

2) Who’s your Sponsor?

3) Who is impacted?  And, what is the impact?

4) How will you engage stakeholders? And, where can they find more information?

5) When and how will you measure adoption?

Below is a brief overview of each.

What’s the Why?

The Why or the Vision should identify how this change makes your organization competitive and should explain the WIIFM (what’s in it for me) for different stakeholder groups.  It should include why the change is happening and the risk of not changing. Whenever possible, tell the why in a story to allow people to connect to the vision not only with their heads but also with their hearts.

Who’s Your Sponsor?

Prosci has conducted multiple studies on successful change efforts and found the most important factor for success is sponsorship.  A Sponsor should remain active and visible throughout the life of the project, not just identify the need for change then announce it and walk away.  Often, the Sponsor comes from the organization that is causing a change, but a project will be more successful if leaders from the impacted areas are engaged and show visible support for the effort.  Part of the change management activities should include providing a roadmap for the Sponsor(s), so they know the activities and the commitment required.

Who is Impacted?  And, What is the Impact?

People typically identify stakeholders by role, but you should also consider other aspects, for example, their typical workflow, their current frustrations, and their usage of a mobile device.  These and other factors influence the level of impact. Personas, which are often used for marketing purposes, can also be created as part of stakeholder identification for a project to capture the different needs and expectations of various stakeholder groups.

How Will You Engage Your Stakeholders?

A quick and easy answer is to engage them early and often.  You may have heard of the “Rule of 7,” a marketing principle that states prospects need to come across an offer at least seven times before they really notice it and start to act.  That is a good rule for stakeholder engagement as well. Also, ensure the communications for a project incorporate the listening side (e.g., meetings, surveys, an email address or a project page where people can provide input, ask questions and get more information).  Remember the perception of a change can differ by stakeholder group, even by individual, so to help reduce resistance, you need to listen to concerns and feedback. You should also consider creating a Change Agent Network for your project. Change Agents are early adopters who receive training and advance details on the initiative, so they can proactively engage others, assist with adoption and help to reduce resistance.

A term that is gaining some traction is change engagement instead of change management.  Wouldn’t you rather be engaged than managed?

When and How Will You Measure Adoption?

Remember the quote from Peter Drucker, “If you can’t measure it, you can’t improve it.”  Understanding adoption behavior is helpful in identifying whether a change is providing value.  Identifying adoption metrics has its own subset of the Five W’s. You need to think through what to measure, when to measure, how to measure and who should measure.  When you are identifying and tracking metrics, think of adoption as a phase reported over time rather than a single event.

Keep in mind that people know how to do their jobs the current way.  Even if the current way is cumbersome and inefficient, it’s comfortable.  Thinking through the Five W’s can help you focus your change management lens and guide people through their concerns and resistance.

It is also important to note that people often fear change because they fear failure or criticism.  Building a culture where people are willing to risk failure in order to change and grow is also a major factor in successfully implementing change – perhaps a topic for future blog.

2019 ILTACON – Session Highlights for Knowledge Management Professionals

18 Jul

ILTACON2019

By Deborah S. Panella, Director of Research & Knowledge Services at Cravath, Swaine & Moore LLP

If you haven’t already figured out why ILTACON 2019 is so important to Knowledge Management professionals, check out the below! There are a number of reasons you should register and join all your ILTA colleagues in Orlando.

ILTACON is the organization’s premier event for peer-driven educational programming, with advanced content offered in a variety of formats to suit every learning style. The exhibit hall is packed with business partners ready to show you their products and services in a friendly and low pressure environment. And numerous networking opportunities are provided so that you can meet and talk to speakers, other attendees and exhibitors throughout the week, including several times carved out specifically to gather with KM colleagues.

New this year, Filament is helping ILTA design three collaboration sessions, each with an expert facilitator, to deliver an interactive and action-oriented experience.  Sunday’s theme is “engage and plan,” Tuesday’s is “understand and ideate,” and Thursday’s will be “decide and activate.”  This winning combination ensures that you will bring actionable knowledge back to your employer in the form of case studies, best practices, insights and strategies, along with connections to people who share your goals and challenges.

Below is a small sampling of the many KM-specific educational sessions to consider, but there is clearly no shortage of relevant and timely related programming. For KM professionals, one key benefit of ILTACON is that you are certain to meet professionals with complementary skills and experiences that go beyond pure KM. Their perspectives will help you broaden your knowledge of the legal industry and the tools, technologies and practices used by related disciplines such as legal project management, marketing & business development, financial planning and analysis, learning and development, and litigation & practice support.  For that reason, we urge you to consider all sessions, not just the ones listed below.

KM Strategy, Leadership, and Professional Development – Including Ways to Foster and Embrace Innovation

KM Tech Tools: Document Assembly & Document Automation; Enterprise Search, Experience Management, Extranets, Intranets & Portals

Thank you to all the volunteers from the KM & Marketing CCT and ILTACON Team Coordinators who helped create this resource. We hope their hard work can be of value to many.

The Geography of Legal Innovation – Firms, People, Tech

14 Jun

Image by nugroho dwi hartawan from PixabayBy Gordon Vala-WebbBuilding Smarter Organizations

I was recently talking with Professor Dan Linna at Northwestern about his very provocative Legal Services Innovation Index. It is a “pilot project to create an index of legal-service delivery innovation” using “indicators of innovation on [260] law firm websites” (pulled using Google Advanced Search against those firms’ websites organised into categories and jurisdictions). It consists of both a catalogue of innovative offerings and an “Index” of innovation.

It made me wonder if this Index for firms matched two other possible indicators of innovation in the legal services / law practices industries across eight key jurisdictions (United States, United Kingdom, China, Germany, Netherlands, Australia, Brazil, and Canada):

Warnings

First, some apples-to-oranges caveats:

Apples and oranges on opposite ends of weigh scale Image by Tumisu from Pixabay
  • The time series don’t line up (the Innovation Index was done last year; Chin’s numbers are from February 2018; and my LinkedIn search was done just now)
  • The Innovation Index includes things like AFAs as an “innovation” (which may not map well to whether firms have an “Innovation” person or not)
  • LinkedIn’s “Law Practice” and “Legal Services” industries include people who are not with law firms; and, obviously, some people are almost certainly doing some innovation (maybe even a lot) without having it in their LinkedIn job title
  • Firms might have innovation people located in other jurisdictions (e.g. India) which wouldn’t be counted; and LinkedIn is not as widely used in certain jurisdictions (it is available, for example, in China – 50 million users – but is not as ubiquitous as in the US – 160 million).

However, I think the results are interesting – and possibly indicative of some intriguing patterns.

Firms are All Talk and No Action?

There is likely no surprise here for anyone seriously paying attention but there seems to be a mismatch between the Innovation Index – firms TALKING about innovative things on their website – and organisations having people to DO innovation. The correlation between the two (for the selected jurisdictions) is only 0.38.

A kinder explanation might be that, since the Innovation Index includes alternative fee arrangements (AFAs), the correlation would improve if we included job titles with “Pricing” or “AFA” or “Feedback” in them (click here for that LinkedIn list). I suspect the answer is a combination of both of these (look for my upcoming post on that).

High Correlation Between Titles and Tech Firms

Dart in center of target Image by Deedster from Pixabay

There is an extraordinary level of correlation – 0.93 (or near perfect!) – between the number of people with “innovation” in their titles in a jurisdiction and the number of legal tech firms in that country.

Of course correlation is never causation; I suspect that the causal arrow for both is coming from two sources:

  1. The growing willingness of clients to use their increasing legal-services purchasing power (pushing firms to make changes)
  2. The larger size and and greater operational sophistication of legal departments (whereby they become customers for the direct purchase of technology).

CLOC’s extraordinary growth – and the plethora of firms and tech companies attending their latest conference – is a telling example of both these phenomena.

Is China a Legal Innovation Leader?

The Innovation Index gives Chinese firms a score of 666.3 – which is almost as high as the US firms (at 671.7). But, looking at the other data sets, there are only two people in China with “innovation” in their titles and only one legal tech firm.

One explanation of that high Index score came to me from Norm Letalik, an immensely experienced law firm leader, who reminded me of how competitive the Chinese legal market is. This pressure comes not just from lawyers but other forms of legal services providers:

“the exclusivity enjoyed by legal professionals [in China], and the precise scope of activities to which it applies, are becoming unclear; and the existing regulations may face the risk of being circumvented”

Source: Jing Li, “The Legal Profession of China in a Globalized World,” International Journal of the Legal Profession

As to the very few people who have “innovation” titles, LinkedIn has struggled to get traction there (as has every Western company). Perhaps it is also that firms in China are “post-innovative” – with everyone doing it but no one having the title? Or perhaps the function is called something else?

And, seemingly, Stanford Law’s CodeX Techindex is significantly underestimating tech firms outside of North America such as those in China (one?!) and in the UK (see following section).

The United – Legal Tech – Kingdom!?

UK firms get an Innovation Index more than three times the US’ (and China’s) with a score of 2,068! And they have the highest ratio of “innovation” titles to any jurisdiction’s population (i.e. 2.35 to US’ 1.1). That would make the country the United – Legal Tech – Kingdom!

The UK legal market was early into privatization deals, and with London’s financial markets, has seen a lot of multi-jurisdictional work with high fee structures. That gave – at least the big firms there – the size and margins to help with the early adoption of innovative approaches. Potentially that early innovation lift was enhanced by the UK legal services market becoming open to alternative business structures (which provided at least a psychologically impetus for innovation if not also actual market pressure).

It also seems anomalous that the UK is reported to have less than one-tenth the number of legal tech firms as compared to the US (35 to 460 respectively); again, it seems (like China) that their legal tech firms are being under counted in the Techindex.

US Legal Tech is HUGE

Whatever the real count of legal tech firms, there is no doubt that the number of legal tech firms in the US is huge – 460. Canada is next largest at 52 (with UK in third place trailing – as noted above – at 35 tech firms). Whether it is the sheer size of the US tech capital markets, their effectiveness, or something in the water – whatever it is, it is working to generate lots and lots of legal tech.

Canada and Australia – Punching Above Their Weight?

Kangaroo Image by Free-Photos from Pixabay

Canada and Australia are pretty small jurisdictions relative to the US; but in both cases they seem to be punching above their weight:

  • Both have more people with innovation titles than you would expect relative to the US population (Australia has three times the number; and Canada almost twice the number)
  • Canada more than matches the US in the number of expected (i.e. adjusted for relative population size) legal tech firms; Australia trails with just half the number expected – perhaps more under-counting of tech firms outside of North America?

Of course Australia has pioneered alternative business structures for legal service delivery (click here for more) so perhaps their innovation (relative) people lead is not surprising. What might explain Canada’s legal tech strength? Could the world’s first legal tech incubator – Ryerson’s Legal Innovation Zone – be part of the explanation?

Change Over Time?

The most interesting question might one that cannot be answered right now: Is the rate of innovation accelerating? (And, if so, are the rates different for different countries?) We simply don’t have the time-series data that we would need to do that analysis.

Final Questions

  • What is happening in China in legal tech? Are there implications here for the rest of the world?
  • Should Americans pay more attention to legal tech developments in the UK (and also Australia and Canada)?
  • Could running the LinkedIn job title searches every six months provide a simple but effective innovation “velocity” metric?
  • What would it take to encourage Prof. Linna to revisit his Innovation Index? And let us all help CodeX LegalTech to build a more complete list (anyone can submit a legal technology company for inclusion).

Note: To see the raw calculations in Excel just send me your email address.