JordanFurlong + data   130

Corporate Law On Verge of Making Things Simpler with Complex Analytics | Legaltech News
Compelling and statistically accurate, at least according to HBR’s survey. The large portion of respondents, 41 percent, categorized data science and analytics as a “medium priority,” while 38 percent identified as being in the early planning stages. As for the two extremes, 16 percent of respondents called data science and analytics as a “high priority,” while only 6 percent said it was “not a priority.”

Baker posited several theories as to why analytics may be bounding up the ladder, ranging from the sophistication of the tools now available to the general wealth of data resting at a company’s fingertips. Still, while more companies may be engaging with analytics, they’re not all doing it at the same level or even with the same goal in mind. Baker alluded to a general progression in ambition that emerges as law departments start to become more comfortable with data and analytics.
clients  data  analytics 
june 2019 by JordanFurlong
Despite Appetite for Insights, Firms Still Struggle With Matter Profiling | Legaltech News
till, the “Using AI to Digitize Lawsuits to Perform Actionable Data Analytics” session at day two of the conference posited that despite the fact that there’s a large appetite for such insights at law firms, there are a few obstacles standing in the way. Chief among them? Matter profiling is very difficult work.
Patrick DiDomenico, chief information officer at Ogletree Deakins, for example, noted that  the process of structuring unstructured data being expensive and altogether mind-numbing work. Incentive is also an issue. Lawyers beginning work on a new matter may not have much data to work with and once they do, it’s time to move onto another case.

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“It’s something that everyone wants but no one is willing to contribute to,” DiDomenico said.

Panelists compared the infrastructure necessary to effectively mine data for insights to a three-legged stool. A firm needs the right people, process and technology in place, a triumvirate that is oftentimes nonnegotiable. Without having a standardized process designed for data collection, for example, there’s a chance that firms could inadvertently collect the wrong data pertaining to a matter.

“I’ve experienced deficiencies in all of these areas, and it can definitely be problematic,” DiDomenico said.
data  analytics 
may 2019 by JordanFurlong
Business of Law Podcast-Tagulous Demo for CLOC Las Vegas Institute 2019 – Business of Law Podcast
Microsoft Legal Business, Operations, and Strategy demonstrated a proof of concept project called Tagulous at CLOC’s 2019 Las Vegas Institute. This project is designed to instrument communications like email with text tags to create a flexible and extensible approach that enables data collection and workflow automations. It allows organization to develop domain specific training sets that link unstructured data (standard communication text) and structured data (tags) to enable machine learning scenarios.
ops  robo  it  data 
may 2019 by JordanFurlong
How Slaughter and May Is Making Use of Legal AI Across The Firm – Artificial Lawyer
Woods and Stewart also talked about how the firm is making the use of tools such as Luminance a key part of the training they now expect their trainees to be involved in.

For example, all of S+M’s trainees (i.e. junior lawyers before formal qualification as solicitors) now use Luminance and train with it.

Alex Woods, Head of KM
‘We have embedded AI into our legal training. Trainees have to teach Luminance clauses as part of their training. This is not seen as separate from the practice of law,’ they explained.

This clearly shows just how seriously S+M is taking this. However, this is not completely without challenges, Woods and Stewart also highlighted the need for proper governance around classification of data and legal terms that may have been taught into the AI system.
data  robo  innovation  analytics  training 
march 2019 by JordanFurlong
Data Doesn't Make Decisions | 3 Geeks and a Law Blog
Intelligence is for Issues, Insights are for People this is a new discovery for me. I noticed that many CI practitioners and departments have adopted the insights nomenclature. I couldn’t quite understand why, the connotations of insights over intelligence is less harsh for sure, but there has to be another reason. KITs, Key Intelligence Topics, the corner stone to any good CI project/function starts with defining a business problem or a topic and then getting executive sponsor. Akin to “what keeps you up at night Ms. Firm Management”. But Insights, are about more than data, insights are about seeing beyond the obvious or as the dictionary defines it “seeing into a situation”.  To see into something, means applying a layer of emotional intelligence or EQ. It means understanding motivations, trusting instincts and accounting for a human context.  That is very different than intelligence and not just in connotation and it something worth exploring more in this hyper data driven legal future.
km  data  analytics 
march 2019 by JordanFurlong
Legal Tech in Law Firms – A Conversation with Legal Technologist Dera Nevin – Ten-Three
“The generalized criticisms of law being slow to adopt technologies may minimize some of the realities of operating technology in the legal context. Tech in law, especially technology that relies on dataset training, takes longer to mature then consumer-facing technology.  For example, some of the datasets we use as inputs to train machine learning may come from case law, on topics which are highly fragmented, unique, and specific. These datasets are the opposite of the large, aggregated sets like driving routes collected by Uber that are highly repetitive and common. Often, we don’t have the scale of data to train machines quickly and so legal technology can take longer to mature.”
robo  data  it 
february 2019 by JordanFurlong
Are Lawyers Ready to Be Managed by Metrics? | Legaltech News
But it likely wouldn’t stop there, the executive says. It is likely that, if such information existed, the company that owned it would serve as a marketplace for lawyers. It would match its knowledge of lawyers’ work and price history with clients’ desires.

“Take the Uber analysis and imagine ‘Lawber,’” the executive says. “That’s the way our clients will, in a few years from now, buy our legal services. They will say, ‘Here is my problem, and here are my levers: price, quality, safety.’ There is a mixture there that they can select, and then out comes a law firm or a legal team that is assigned the work.”

The executive suggests that consulting firms like the Big Four or billing technology providers are best positioned to serve this role in the market. The key is having a platform that has analyzed a vast enough swath of legal purchases and prices to set the market.
data  clients  firms  pricing  value  metrics 
february 2019 by JordanFurlong
The State of Alternative Legal Service Providers - Prism Legal
The report Alternative Legal Service Providers 2019 was released last week. Perhaps influenced by the subtitle, “Fast Growth, Expanding Use and Increasing Opportunity”, the many articles covering it suggested the findings portends trouble for law firms.

I read the report differently. Below, I focus on a few findings and statements that stuck out for me. This is not a summary so I recommend reading the entire report to learn more about alternative legal service providers.

The report is by “Thomson Reuters Legal Executive Institute, in partnership with Georgetown University Law’s Center on Ethics and the Legal Profession, University of Oxford Saïd Business School, and U.K.-based legal research firm Acritas.” I first saw it publicized at the TR Legal Executive Institute blog on 28 January 2019 at Alternative Legal Service Providers Report 2019: ALSP Market Experiencing Rapid Growth & Expanded Use.

High growth – 12.9% CAGR reported. And a Ron caveat. “In just two years, revenues for alternative legal services providers have grown from $8.4 billion in 2015 to about $10.7 billion in 2017. This represents a compound annual growth rate of 12.9% over that period.” That is 27% over two years, a number I will reference below.
newlaw  data 
february 2019 by JordanFurlong
GCs Are Offering Work on a Silver Platter—and Law Firms Aren't Taking It | Corporate Counsel
There are two main buckets of data. There is data on spending and data on matters. Clients want both. On the spending side, Altman Weil’s Rees Morrison talked about a finding in his company’s CLO survey in which nearly 73 percent of chief legal officers said none of their top 10 law firms provides useful data on spending. None!
On the matter side, DHL Supply Chain Americas GC Mark Smolik gave an example of what he wishes law firms would do—and it’s something none of his firms ever has. He suggested a firm might want to look at, say, all of the employment cases emanating out of his California warehouses. Maybe they find that 50 percent of the cases are coming from one warehouse, and one person is the culprit. The GC can then take that information to its business units and work out a solution. It makes the GC look good and it makes the law firm look good to provide that kind of actionable intelligence. Other GCs echoed similar requests during Legalweek’s Business of Law Forum.

There was a suggestion by one panelist that perhaps law firms aren’t incentivized to present those types of data-driven solutions because it could put them out of work, or at least out of some work. The panelist suggested law departments may need to find a way to pay for such advice.

It seems to me that there is a clear opportunity for law firms here to use the data they have to engender trust and kudos—and just maybe some more work—from their clients.
data  clients  analytics  firmds 
february 2019 by JordanFurlong
Driving Analytics Into Practice: Advice from the Data Driven Lawyers | Dewey B Strategic
Overcoming Resistance. Readers who have met resistance from lawyers when they tried to introduce analytics products in their firms will find some insights to justify exploration of analytics products in their firms. Of course every new technology introduces new risks as well as rewards. Back in the 1980’s some lawyers refused to try the early versions of Lexis and Westlaw. Some lawyers relied on online research results without understanding the limits of the content or the ineffectiveness of their search strategy.  We face  similar  risks with  analytics. both Reckless and uninformed over reliance on  analytics could have adverse consequences and slow adoption.
data  analytics  change  clients 
january 2019 by JordanFurlong
Ogletree Deakins Partners With AI Company to Build Better Data | The American Lawyer
Ogletree, Deakins, Nash, Smoak & Stewart last April became the first law firm to publicly announce a licensing deal with legal AI firm LegalMation, which generates automated responses to complaints in just a couple minutes.
Now, the Atlanta-founded AmLaw 100 firm will be the lone Big Law labor and employment firm to use the tool, announcing Wednesday it signed an exclusive partnership arrangement to use the LegalMation platform and to build new products from it.

Until now, Ogletree had used the product on employment cases in California, but it will expand that use to Texas, New Jersey and Florida as well as other jurisdictions as they become available on the LegalMation platform, the firm announced. In addition to drawing up answers to complaints, the product also drafts responses to discovery requests.
Through the partnership, Ogletree lawyers will train LegalMation’s artificial intelligence system and also help in the development of new auto-generated reports through the system. Those reports could include case analytics, case summaries and other high-volume prelitigation tasks, the firm said.

Patrick DiDomenico, the firm’s chief knowledge officer, said the license with LegalMation is intended to help the firm’s lawyers spend less time on routine legal tasks such as drawing up answers to complaints. Down the line, he said the tool’s ability to capture data on complaints will help its lawyers make more insightful decisions while litigating cases.

Patrick DiDomenico, chief knowledge officer of Ogletree Deakins.
“Having access to LegalMation [exclusively] is an obvious benefit,” DiDomenico said. “More importantly, I think it demonstrates the commitment we have to each other. We are both very serious about this partnership. And that is an indicator of how hard we are both going to work to make this mutually beneficial and beneficial to our clients.”
robo  data  firms  innovation 
january 2019 by JordanFurlong
An Rx for Data Dizziness: Getting Started with Data Requires Smarter Strategy (075) | Legal Evolution
How should legal teams get started with data?  Here’s a prescription, along with a #RealTalk diagnostic.
In Post 066, I shared that law firm and law department leaders often ask me how to get started with data analytics. I also shared that I usually respond by asking about their most important strategic objectives.

For today’s post, I will play doctor and take a cut at a framework to serve as a prescriptive roadmap. The above graphic is the result. It visualizes a practical framework to think structurally about high-value applications of data.

To Design a Value Proposition for Data Analytics, Start with Clear Thinking Around Needs
As with any new idea, tool, service or product, the key to designing a successful value proposition is to think deeply about the needs of the intended end-user.

Decision support, when applied to sufficiently high-stakes contexts in both the business of law (e.g. new business models for legal service delivery) and practice of law (e.g. litigation finance), likely offers the highest probability of generating material economic returns or a strategic leap forward for the sponsoring organization. Of course, identifying the decision opportunity and shaping the analytics approach requires a high threshold of domain knowledge as well as technical expertise across both data engineering and data science competencies — hence the need for a multi-disciplinary team.
data  analytics 
january 2019 by JordanFurlong
Law firms have debts to pay before investing in innovation
Let’s stretch the analogy further and look the forms of debt that many law firms have accrued:

Technical debt: over the past 2–3 decades law firm have acquired and installed layers upon layers of operational systems. And then added more layers to make them work together, as they are all from different providers on different platforms. And then added more layers to extract value from them, such as BI and analytics tool. And for some firms, this is on top of custom-coded software undoubtedly containing some technical debt of it’s own. This is a very complex and expensive challenge, which creates drag and friction in operations. 💰

Data debt: within these systems lies a vast amount of business and practice information. In many law firms I’ve advised, we’ve encountered tens of millions of documents in DMS or RMS systems and hundreds of millions of time entries in billing systems going back many years. Unfortunately, over the years this data was not always curated, categorized or otherwise captured in ways that support new needs around business and practice analytics. It is a very expensive proposition to go retroactively update all of this data, and we can’t wind back the clock. 💰

Procedural debt: for decades, lawyers have “sold law” by the hour while non-lawyers did their best to support them. For reasons that have been well covered in the legal market, this is no longer tenable. But changing the way lawyers have always worked and how legal services are delivered to clients is a monumental challenge. Almost every professional, cultural and economic incentive in a law firm fights against this change, which makes it a very expensive and risky undertaking.💰

Structural debt: the law firm itself, usually a partnership operating on a cash-based model in which equity partners withdraw all profits each year, is also being challenged. How can a firm properly invest in its future, or pay down the debts I describe, in this model? Furthermore firms cannot accept outside investment thanks to ABA and state bar regulation, so their only recourse is to incur bank debt to cover the other debts, or to ask the partners to pay in themselves. This is a big ask. 💰
management  innovation  data  process 
november 2018 by JordanFurlong
Bloomberg Law to Offer Lawyer-Client Representation Analysis – Artificial Lawyer
The company representation tool does not seek to make predictions on a lawyer’s likely success, but instead seeks to give inhouse legal teams, or rival law firms, a blueprint of that lawyer’s working life: who they’ve helped, what trends can be seen in the cases they take, and where do they have the most experience in terms of jurisdictions.

It will show an attorney’s experience representing companies in federal courts with additional data taken from Bloomberg Law’s comprehensive case law database and news sources.

Armed with this information companies can then make better informed judgments about who they want representing them – without having to rely mainly on lawyer bio pages or word of mouth. In short, they can take a more data-led approach.  

The company said this will complement Litigation Analytics’ existing judicial, company, and law firm capabilities, which Bloomberg Law says also ‘enables attorneys at law firms to quickly gain intelligence on their competition and chart winning legal strategies’. It added that this new extension will be packaged up at no additional cost with the existing plans of subscribers.

The key areas the new extension will help with are summarised as:

What companies has an attorney represented?
What is an attorney’s areas of expertise and practice areas?
What is the trend of an attorney’s litigation?
In which jurisdictions does an attorney have experience litigating?
Is this going to totally revolutionise litigation planning? Not yet, but it’s a useful development that shows that Bloomberg Law is serious about building out its legal data analysis capabilities and leveraging legal information where it can. And, as the group says, this journey has really only just got started, with the main Analytics platform launching a couple of years ago.
marketing  online  clients  data 
october 2018 by JordanFurlong
What Would that Law Firm Merger Look Like? New Tool Allows 'What-If' Modeling | LawSites
Speculation about potential law firm mergers and acquisitions makes for good sport, not to mention serious business. Today, ALM Intelligence released a tool that gives speculators some hard-and-fast data and the ability to model what a potential merger would look like.

Available to subscribers to ALM Intelligence’s Legal Compass platform for data research and analysis, the M&A modeling tool allows users to analyze potential mergers and acquisitions within the legal market and create a profile of what the merged firm would look like.

“Law firms are always playing the ‘what-if’ game, and this tool enables firms and consultants to assess various potential combinations,” Patrick Fuller, vice president, legal, said in an announcement of the tool. “Additionally, it becomes a core competitive intelligence tool for rivals as part of the assessment of pending law firm mergers.”

The tool allows users to:
data  metrics  analytics  consulting  mergers 
september 2018 by JordanFurlong
A Race to the Bottom for the AmLaw 200 and Below? Doesn't Have to Be. | Rainmaking Oasis, LLC
Four significant industry surveys were released in the month of May:  Citi 2018 Q1 Law Firm Survey, the 2018 Altman Weil Law Firms in Transition Survey and the 2018 AmLaw 100 and AmLaw 200 reports. There was some discrepancy in how recent findings were conveyed or interpreted, but they shared several common themes related to demand, revenue and profitability:

Overall, demand growth surged in Q4 2017 and continued in Q1 2018, but collections slowed down, and expenses grew, for many firms negating revenue growth (Citi report)
The elite firms, the largest firms and the most profitable firms continued to pull away from the majority – this was true in both the AmLaw 100 and the AmLaw 200 groups and certainly between the groups:
The AmLaw top 50 reported the best results in Q1: AmLaw 100 saw a 6.3% growth in PPP
15 of the top 20 most profitable firms were based in NY; profit margins for the top 20 ranged from 47-65%
There was 5.5% revenue growth for AmLaw 100 firms in 2017 compared to a .2% decline for the AmLaw 200, although the top firms in the AmLaw 200 group saw an increase in 2.7% which is better but still only half of what the AmLaw 100 average increase was
8 of the second hundred firms had revenue growth of 10% and another 22 had revenue growth of 5%, but 32 firms saw revenue shrink (AmLaw 200 report)
Volatility in the market is still present: 47% of firms saw a decline in revenue in Q1 (Citi report) and 27% saw demand decline in 2017 and Q1; most firms have seen up and down trends in demand and revenue growth from quarter to quarter and year-to-year
The trend immediately following the 2009 fall-out of work flowing to the second 100 firms as a better cost alternative has ceased for the most part
data  firms  clients 
june 2018 by JordanFurlong
New Ogletree Deakins Director of Data Analytics Talks Challenges of Labor Data | Legaltech News
What are some of the biggest challenges to working with labor data?

The biggest data challenges are access and reliability. The client simply wants to run the business, and most human resources and IT professionals are already working 40-plus hour jobs. Because everyone is so time-starved, it is sometimes difficult to access data. Clarity in communication and flexibility are essential on our part in order to facilitate an efficient transfer of relevant information.

Reliability of the data can also add to the challenge of providing a cost-effective, reliable end-product. A large portion of our job is to go through the data, identify issues, and rectify them in a manner that results in a consistent, reliable analysis database, what we often refer to as “cleaning” the data.

What are some projects you’re hoping to tackle in working with Ogletree?

That is an excellent question! The projects can be separated into two specific areas: client-facing projects and internal, operations-based projects. The client-facing focus will be any litigation-related opportunities currently being outsourced to consulting firms that do not require a testifying role. This will grow to include capabilities around non-litigation statistical/economic consulting. Ogletree already possesses strong internal groups, particularly those focusing on pay equity and OFCCP/EEO audits. I will work with these groups to enhance their existing capabilities.

For the internal, operations-based projects, my goal is to assist management in identifying opportunities to create greater efficiencies wherever possible. One example would be identifying areas in which data analytics can lead to more productive results.
data  analytics  clients 
may 2018 by JordanFurlong
My long history with law firm scorecards (047) | An essay on leadership
Leadership and management are not part of the legal education canon.  Yet, that is bound to change as more lawyers stumble forward into these disciplines to cope with the relentless growth in complexity we face on a daily basis. In the meantime, however, we are at risk for misinterpreting the tides of change.

For example, many lawyers and law firms (and initially this professor) are quick to conclude that the goal of scorecards is to save money.  Yet, in most cases, the motivation is scarcity of internal bandwidth. An important task done well and efficiently frees up time and mental energy to tackle other strategic priorities. Saving money, or getting more value per dollar spent, is a by-product of a more disciplined approach to one’s job as lawyer-manager.

The first step in this more disciplined approach is formulating the evaluation criteria.  Initially at Safelite and DHL, Mark Smolik focused on seven criteria:  (1) understands our objectives / expectations, (2) expertise, (3) responsiveness / communications, (4) efficiency / process management, (5) cost / budgeting skill, (6) results delivered / execution, and (7) compatibility with company values.  Each criteria, in turn, is defined by a set of specific behaviors.

What managing law firms looks like
For ideas like scorecards, lawyers need examples rather than abstract descriptions. In 2016, I ran some focus groups for what would later become Qualmet. Below are some of the graphics from those sessions (credit: Evan Parker from LawyerMetrix).
data  metrics  clients  firms  ratings 
may 2018 by JordanFurlong
Why prediction in legal tech needs to die quickly – Samuel Witherspoon – Medium
For starters a machine stating a probability is less appealing than a human providing comfort and counsel. We underestimated this element of human behaviour. People in the midst of a legal dispute do not think rationally or reasonably.

Second — knowing what the likely outcome of something is misses a critical component — how to get to the outcome. The prediction itself ignores that the path to the result is long, winding and perilous. It ignores that if the other party is not behaving rationally no amount of forecasting will help you. If the legal system was rational people wouldn’t take two hours off work to fight a $30 parking ticket. Human’s are inherently irrational. The legal system is run by humans.

I assume under the phone is the prenuptial agreement since the person is behaving rationally when they get married too. Or maybe its just their vows. Or maybe its an empty folder since this is a stock photo. Also there is a small plant on the table.
Third — disputes are messy. Litigation is messy. In our case we were trying to provide a tool for people to negotiate with their spouse with in an effort to keep their divorce in the ‘uncontested’ stream (meaning they recognized that the outcome was a foregone conclusion so why argue about it). We solicited feedback from our customers relentlessly.
litigation  predictions  robo  data 
may 2018 by JordanFurlong
So there’s been some buzz about legal data lately … – Slaw
There is not enough data in court decisions to provide good analytics for individual judges in particular areas of law. To adequately assess a prospective professional ball player requires thousands of swings in an activity with relatively simple inputs and results. Most judges will not write more than several hundred decisions in a long and active career with complex inputs and outputs, only some of which are available for analysis, as many court activities don’t leave a readily available written record. It’s not impossible to quantify human interactions like this, but it leaves out important nuance.

Aside from publicity materials and hype induced press coverage, I have not heard positive stories about the application of artificial intelligence in law. In fact what I hear from people trying to apply AI to legal materials is that they experience general frustration. Start-ups are pivoting away from legal analysis to subject areas that have more accessible datasets and less complicated source material, and those that haven’t frequently struggle to answer simple questions. There are many applications for automated analysis of legal documents, but as far as I can tell so far they tend toward extracting particular information such as judges’ names, and, as the field has moved on, this is no longer considered “AI”. Even something as simple as saying what a case is about turns out to take nuance that computer programs struggle with (in fairness on occasion I have struggled with that too).

The application of AI to legal data also suffers from the paired issues of restricted access to raw data and access to the required computing power being generally available. In the first week of studies doing an MBA they teach that for a business to be successful long term there needs to be some kind of competitive advantage, and using third party resources to parse a dataset is readily replicable.
robo  predictions  data 
may 2018 by JordanFurlong
For Better Outside Counsel Relationships, Tell Firms How They're Being Measured | Corporate Counsel
Yeung and Cunningham discussed metrics that might be important to in-house counsel that might not be tracked by most firms, including diversity data or how efficiently different firms’ lawyers are completing work. By increasing communication between the two sides about metrics and expectations, both can better track the metrics that matter to the other, leading to better staffed matters and greater overall satisfaction.

“Sit down with [firm CIOs] and say, ‘Give me an idea of what it is that you’re doing.’ And have them show you these types of [dashboards] that we’re talking about today, and give them pressure to work with you in that sense,” Cunningham said. “Some firms will really enjoy that, and some firms are the ones swimming naked when the tide goes out.”
clients  data  metrics 
may 2018 by JordanFurlong
The Empire Strikes Back 💥 and 2017 Is (Mostly) a 🎉 Win 🎉 for Am Law 100
In short, this view of the 2017 revenue growth takes some of the bloom off the top-line figures. At the same time, I think it’s generally consistent with ALM’s take — as Roy Strom summarized in his big picture narrative, there is some 😟 anxiety 😨 in the air.

For law firm leaders and equity partners picking up the annual rankings to check your PPEP ranking, don’t be lulled into a sense of complacency by the summary stats. As noted above, 5.5% revenue growth and 6.3% PPEP growth — on average — are undoubtedly great numbers. But if your own firm’s numbers were lackluster, know that it’s because one half of the Am Law 100 has grabbed the lion’s share.
data  metrics  firms  profitability 
may 2018 by JordanFurlong
Standardized Legal Security Assessment Should Be Reality, Says CLOC | Legaltech News
With this in mind, CLOC is looking to streamline the process through an ongoing initiative that will ultimately look to provide corporate legal departments with a common set of criteria and methods through which to scrutinize cybersecurity. Tully laid out seven criteria that, from his work both at Gilead and previously at Qualcomm, are necessary in any sort of standardized assessment:

Assessments of all vendors, not just a small subset;
An ongoing thorough assessment process, rather than one time at onboarding;
Auditing vendor responses, not just rely on vendor self-reporting;
A cost-effective solution, without affecting quality of assessment;
The ability to leverage security assessment information at the time of choosing a vendor, i.e., within a matter management or e-billing tool;
Remediation advice and assistance, to help our vendors improve their security posture; and
The ability to benchmark our vendors.
Sound like a lot? Perhaps. Tully noted that when coming up with an initial assessment at Qualcomm that instituted all of these factors, it took him over nine months. But without asking these questions up front, he said, corporate legal departments can’t truly travel the road to security.
cybersecurity  data  standards  ops  clients 
april 2018 by JordanFurlong
Amazon LLP – Ed Walters – Medium
Amazon LLP would post its prices for commodity work, and its billable rates for non-commodity work. At the beginning of an engagement, it would tell clients a distribution of prices for similar engagements, with means and median prices identified. During the RFP process, the firm would identify factors that add to cost or complicate the matter.

I used to work in a superb large law firm, and I recognize that transparent pricing of legal services sounds naïve. But now I work in a company that consumes legal services, and I can affirm that mystery pricing is a major source of risk for clients of law firms. Clients would rather pay more than be subject to unknown, open-ended pricing.

Imagine for a second that you were purchasing a book on Amazon. You could buy from Amazon at a fixed price, or a re-seller, for a limitless mystery price you would only know after the purchase was complete. Buyers would never, ever purchase at the mystery price.

Or imagine that you went to a nice restaurant with lobster on the menu at a market price not listed on the menu. When you asked the server about the market price, he told you that the price would depend on the time it took the fisherman to pull it from the water, the price of fuel for transport, and the time it took the chef to prepare it — and that you would find the price at the end of the meal when you got the check. Zero diners would order the lobster, no matter how good it was.

Do we really expect sophisticated purchasers of legal services to continue to order the lobster at a limitless, unknown market price?

Data Driven.
It’s hard to assess the price of legal services, but law firms have the most information about past engagements, and they are in the best position to price the risk of being wrong.
amazon  data  competitors  innovation  pricing 
april 2018 by JordanFurlong
Data (Gold) Mining: The Rise of the Law Firm Data Analytics Teams | Legaltech News
At Littler, Eigen found himself primarily tasked with questions from firm leaders about pricing and predictions—how things can and should be budgeted, and how to predict potential outcomes. He also worked a lot on data projects requested by clients. “We’re scraping data sources or amalgamating data sources external to the firm. Sometimes we use internal firm data as well, but we’re looking for data and trying to find ways of answering questions on behalf of clients” with data, he notes.

Many of these client-facing projects centered on litigation risk assessment. “If you can get ahead of that risk and fix problems before they materialize into very, very costly and time-consuming litigation, that’s great. Clients in that circumstance are willing to pay a lot for high-quality analytic work to get ahead of that risk,” Eigen says.

Notably, some practice areas may be better equipped to adopt broader data resources and projects than others. “Labor and employment is a more fertile ground for this to happen than, say, mergers and acquisitions, because L&E is commodity work, and there’s a lot of competition,” Eigen notes.

But instead of using data to change inefficient firm practices or advise clients differently, as businesses and technologists often tout of their analytics investments, Eigen is seeing firms primarily leverage data for narrow competitive uses that can help them develop slight advantages over other Big Law firms. Data practices that today seem cutting edge could easily be undercut without more structural changes to attorneys’ relationships to data. For example, Eigen has seen some clients starting data-based legal risk modeling that his team does itself. “It’s likely to change over time,” he says.

Likewise, Borden says that firms don’t often value their data teams appropriately until they see that their efforts produce direct profit. “The big challenge is turning the position into a money-making one. In a law firm, the world is divided into those that make money and those that eat money,” he says.
data  analytics  firms 
april 2018 by JordanFurlong
Am Law 200 firm signs on with Fireman & Company to build AI-enabled “What’s Market” database – Fireman & Co.
“Many firms are struggling to identify practical ways to use AI in their firm. The firm provided us with a clear vision and definition for their What’s Market AI application – a tool that other firms have had to manually build and curate in the past. One of the most common challenges law firms have is tapping into their own data to make better decisions, both for their internal purposes and to help deliver better client service.  This is the first of what we expect to be a series of AI use cases that help law firms leverage their own data to drive AI, particularly as firms are increasingly interested in robust matter profiling and experience management systems.  We see AI feeding these systems, in both breadth and depth of content, in ways that have never been achieved at most firms.
robo  data 
april 2018 by JordanFurlong
Making the Case for Analytics: How to Persuade Your Team to Jump on Board | Legaltech News
The use of sophisticated data analytics is transforming the way litigation is managed in the U.S., and it appears that in-house counsel are welcoming these technology-powered insights. More than seven in ten corporate counsel now say they encourage their outside counsel and vendors to use data visualization and analytics, according to a 2017 Bloomberg/Catalyst survey report. Still, inside and outside counsel, as well as e-discovery technologists, face challenges when it comes to persuading their litigation colleagues to embrace the use of analytics in e-discovery.

While you may understand that the value of analytics is self-evident in almost any matter, it can be difficult to make the case to your colleagues, especially with limited time and opportunity for lengthy discussions and demonstrations. With that in mind, here are some practical ideas for persuading your litigation team members to leverage the power of data analytics in e-discovery:
analytics  data 
march 2018 by JordanFurlong
From 700 Law Firms to 7: Avis' Changed Approach to Legal Work Has 'Saved Millions' | Corporate Counsel
“We have promised them they are it, there will never be more than them. The way it’s structured, since every firm has its own sandbox, they can all work with each other,” Tucker said. “If it [the case] is not in your box, you won’t get it, so they cooperate to supplement strengths or weaknesses, so no there’s no more bidding or contests.” 

Tucker says taking away the sense of competition has allowed firms to work more closely with each other and with Avis. But Tucker says the end of bids doesn’t mean the company expects lower quality work from firms, and that Avis has called out subpar outside work when it happens.

In exchange for Avis’ promised loyalty, the firms agreed to let the company pay discounted rack rates. Avis had a calculated global target rate that was then adjusted to account for geographical norms.

At times, the seven firms may send certain specialized work to their international affiliate law firms, but Avis does not have to manage the relationship with those affiliates.

The seven firms are required to follow Avis’ outlined blended rates based on staffing configuration. Under Avis’ model, Hatti says, there is an emphasis on firms using associates and LPOs when appropriate instead of partners, with exact staffing percentages outlined in the firms’ agreements. He says the firms will have to outline goals to increase diversity and inclusion each year, a growing demand for law firms in general.

“We will see savings, and the other advantage is it takes away the burden of us monitoring a law firm, and shifts the burden to the law firm to correctly staff our matters,” Hatti noted. 
clients  firms  convergence  data 
march 2018 by JordanFurlong
AI Beats Lawyers in NDA Review Accuracy - LawGeex Study - Prism Legal
hat Machines Beat Lawyers Is Not Surprising. Many lawyers may be surprised that the AI won; I am not. I started comparing human versus machine performance in discovery document review in the early 1990s. Even then, with an earlier generation of natural language processing operating against text generated by OCR,  it was clear then that the machines often performed better. A decade later, the predictive coding discussion in eDiscovery document review began in earnest – and continues. Many studies have found predictive coding is more accurate than lawyers.
Courts Not a Barrier to Adoption Here. Predictive coding uptake has been slowed down by the need for judicial review and acceptance, a process that takes years. In contrast, for NDA reviews, in-house counsel get to decide on their own what approach to use. They don’t have to persuade a court. (I am sure some will say, “well what if something was missed and it leads to litigation”. My answer: so what? Whatever litigation has arisen over NDAs to date is the result of human action – or perhaps failure in action.)
A Move to Evidence-Based Decisions re How Lawyers Practices. The way lawyers practice is based on history and precedent. Rarely do we have evidence to support one practice approach versus another. Though some may find flaws in the study, I applaud it for providing what appears to be well-grounded evidence. The predictive coding acceptance battles teach us that controversy over study design may arise. Good. That’s how science and empirical testing is supposed to work. If you do not think one study is properly conducted, do your own. Or point out the flaws and hope someone else fixes them.
robo  contracts  data  innovation 
march 2018 by JordanFurlong
The Law Firm Disrupted: How Predictable Can Litigation Get and How Fast? | The American Lawyer
BLM, an insurance-focused firm in the U.K., announced this week a partnership with the London School of Economics that will advance its goals of becoming a leader in advanced data analytics. Three professors, including experts on decision-mapping, machine learning and an actuary, will work with the firm’s proprietary data to better understand the costs and outcomes of its cases.

Reporting on this development, The Artificial Lawyer said a “litigation prediction battle” is heating up among firms in the U.K. insurance space, with BLM’s rivals such as Clyde & Co and Kennedys making similar investments.

“The idea is to move from statistics to prediction,” said Andrew Dunkley, BLM’s head of analytics.

But how good can the predictions get? Dunkley said the goal is not to get to “95 percent accuracy” when predicting a case; rather, it is to predict better than the best human lawyer or to provide new information that helps that lawyer make a better prediction.
predictive  litigation  data 
february 2018 by JordanFurlong
Leading law firm joins forces with LSE professors to find ways to predict litigation - Legal Futures
National insurance law firm BLM has teamed up with three professors from the London School of Economics (LSE) in a two-year research project to create models that predict the cost, length and outcome of litigation.

Andrew Dunkley, head of analytics at BLM, said artificial intelligence (AI) would be an “important part” of the partnership, but the crucial thing was the way it blended technology with actuarial knowledge and ‘decision science’.

“What decision science looks at is taking decisions in an uncertain environment, like litigation, where you don’t have complete information,” Mr Dunkley said. “You may not have enough information to come to a confident prediction.

“At the start of the dispute, you have a bit of information about the case, but there is lots of information you don’t yet know. You still have to make a decision about whether or not to invest in the litigation.”

On the LSE side, the partnership will be led by Professor Henry Wynn, head of the decision support and risk group. He will be joined by Professor Pauline Barrieu, head of LSE’s statistics department and principal examiner for the Institute of Actuaries, and Professor Milan Vojnovic, chair in data science and expert on machine learning.
litigation  data  analytics  predictive 
february 2018 by JordanFurlong
Resetting the Process: An inside look at the state of legal operations | In-House Ops
necdotally, I would estimate that most corporations in this industry, 60 percent or so, are at the foundational level in terms of building out their operations function. About 35 percent are at an advanced level. They’ve done some really good things, but they’ve got much room to improve. Only about 5 percent are at what we would consider a mature level, and even those have some significant areas left for improvement.

Brenton: Prior to operations, we had been solutioning in silos, and we have evidence that that doesn’t work. It might look good on paper, but when you go to implement, it just doesn’t work.

On Embracing Technology

Franke: When we look at the CLOC operations maturity model, a lot of companies have implemented or started to implement the basics. But if you look at a competency like dashboards and data analytics, a competency found in somewhat more mature ops functions, we see that this is an area that’s still beyond the grasp of many companies. So, while a percentage of companies may be moving down the path to operational maturity a bit quicker and may be a bit further along, in some cases having adopted a lot of tools and AI, many other companies are still near ground zero. Even a technology like contracts management has only been implemented by maybe 50 percent of corporations, and most don’t have robust implementations with comprehensive processes to support their tool.

Brenton: I think the tech companies have been much more collaborative and willing to share because we’re not regulated and have a culture that is different in terms of sharing information about processes.

On Billing Methods – and Market Forces

Franke: It’s not so much about getting away from the billable hour as it is about what things should cost. When you hire a contractor to do work on your house, they fix their bid based on the different resources that they have to bring to the table – plumbers, electricians – and what that’s going to cost them. There’s an underlying hourly rate there, but they know how many hours it’s going to take to install a new faucet or sink. They don’t try to figure it out for every job.

Law firms, however, start from scratch every time they do an M&A deal or a tech transaction or an employment contract. Good contractors know how to do a remodel and when to use tools rather than manual labor, and they know how to staff a job.

That’s not been the case with law firms. We’re getting away from that – firms are gathering data, figuring out optimal staffing models, determining when to outsource, etc. That allows them to offer AFAs that are win-win.
firms  ops  clients  metrics  data  pricing  process 
february 2018 by JordanFurlong
Legal Services and the Consumer Price Index (042)
I have harped on the topic of “lagging legal productivity.”  The above analysis shows that if legal services cannot be delivered more efficiently, ordinary citizens will forgo legal services.  This is not a prediction; it is a statement of what is happening today.  State courts are glutted with self-represented litigants. At the same time, lawyers struggle to find clients who can support their practice.

The problem is not the necessarily the escalating cost of a lawyer’s time ($260/hr in the most recent CLIO survey, see Post 037), but our failure to update our institutions so that ordinary citizens can resolve their legal problems in a convenient and cost-effective way.  In other words, it’s time to redesign some of our most hallowed institutions.  This is the challenge of the next generation of lawyers, judges, and legal educators.
access  courts  innovation  data 
february 2018 by JordanFurlong
What I'm Learning About AI and the Law From #Legalweek18 | Legaltech News
Adding a caveat to that was Brian Kuhn, the global leader and co-founder of IBM Watson Legal. Kuhn envisions—and it sounds like IBM is implementing—the creation of “cartridges” of specialized legal information that can be deployed for various legal tasks. That’s a mouthful, I know.

But imagine this: A firm that specializes in antitrust law “trains” an AI algorithm to interpret documents relevant to that practice area. Then, the firm sells that piece of trained software, allowing a firm weak in antitrust to gain capacity (and removing the need, perhaps, to bring on a bunch of antitrust partners).

Another point hammered home here: AI is only as good as the data it’s trained on. Krow referred to this as the “garbage in, garbage out” problem. Arruda adds that it’s not just having sufficient “Big Data,” it’s whether that data is usable in its current form. “Clean data” is the new buzzword.
cartridge  robo  it  data 
february 2018 by JordanFurlong
New Pricing Strategies Drive Revenue Gains at Hogan Lovells | The American Lawyer
To gain leverage with clients, Williams’ team develops data particular to each client that shows them the value they are getting from Hogan Lovells. The specifics may range from standard market rate breakdowns to efficiency savings projections; forecasting qualitative outcomes against projected risks; and client-specific historic legal hourly legal spend modeled against alternative fee proposals.

Dennis Tracey, head of litigation for the Americas at Hogan Lovells, says his department has established an ironclad rule: Any lawyer who wants to negotiate an alternative fee arrangement with a client “has to run it by Terry and his team,” Tracey said.

Tracey calculates that, as a direct result of the pricing team’s influence, his department’s domestic litigation revenues per lawyer rose 5.2 percent in 2017. The firm has entered into alternative fee arrangements with several major clients that have agreed to give Hogan Lovells all their domestic litigation matters in exchange for negotiated flat fees, generating $34 million in revenues, Tracey said.

But Green said it’s not just about smart pricing helping the firm secure a large volume of work. He said the pricing group has also given Hogan Lovells’ lawyers more confidence to negotiate higher fees, even with their most-cherished clients. Pre-Williams, he said, “we were afraid,” but being able to harness data-driven strategies has changed that.
pricing  data 
february 2018 by JordanFurlong
2018 Citi Hildebrandt Client Advisory - Citi Private Bank
We are pleased to share the 2018 Citi Hildebrandt Client Advisory, our annual publication which outlines the current landscape of the law firm industry, how law firms are responding to these conditions and their best opportunities for growth in 2018.


The law firm industry remains in a channel of modest demand growth with high levels of dispersion and volatility1,2:

Revenue growth during the past several years has come primarily via standard rate increases as realization has been under pressure, and the modest demand growth has added limited lift
Headcount growth has come in the form of increased lawyer leverage, as equity partner headcount has remained essentially flat
Margin growth, where firms have been able to achieve it, has come in large part from overhead expense controls as the industry has become leaner
future  firms  data 
january 2018 by JordanFurlong
Knomos Knowledge Management Inc. wins Blakes innovation contest - The Lawyer's Daily
That was the genesis of the Blakes Global Legal Innovation Challenge. Run in partnership with Law Made, a Toronto-based company that invests in and promotes legal technology startups, the contest attracted competitors from around the world, but it was Knomos Knowledge Management Inc. in Vancouver that claimed victory.

Its solution, a functional prototype of a data visualization tool known (for now) as the Knomos VisuaLaws app, is based on an application the company has made available to the public. That tool allows anybody to search federal or B.C.-based case law and returns the results as a “heat map” — a visual representation of the most relevant and frequently cited cases. And it’s exactly this type of visual response that Blakes thinks will be useful.

Carla Swansburg, Blake, Cassels & Graydon LLP

“We wanted [a tech solution] that would respond to a client problem and an inefficiency we saw in our practice,” said Carla Swansburg, director of practice innovation, pricing and knowledge.

“We wanted to design our own custom solution with a developer that would be something that clients would really benefit from. When we are dealing with innovation and service delivery and new technology, we almost always look to the client-facing solution: what is it going to do for clients in terms of practice efficiency and making their lives easier.”
innovation  firms  data 
january 2018 by JordanFurlong
Law firms try self-analysis, ‘Moneyball’ style
t has also allowed the firm’s attorneys to spot trends such as increased use of representation and warranty insurance, says Mr Knapke. Clients, he adds, “want to make sure they’re competitive but they’re not going too far — they need reassurance that what they are doing is the right thing”. The firm’s evolving proprietary database helps ensure clients and advisers more fully understand “what’s going on in the market”, he argues.

Littler Mendelson, by comparison, is focusing on using data analytics tools to help its clients to detect employment risks.

The employment law specialist briefed its global director of data analytics, Zev Eigen, to help clients review operational concerns. These ranged from ensuring disadvantaged minorities were properly welcomed into the workplace, calculating and examining the justifications for pay discrepancies between men and women, and identifying other dangers of employment lawsuits.
robo  data 
december 2017 by JordanFurlong
Law Firm MDPs Part 4: Service Delivery Solutions | Rainmaking Oasis, LLC
Designed as a combination of legal data analytics and legal operations consulting services, this service solution is intended to help in-house legal departments achieve their management objectives and innovative legal services solutions. According to their web site, “Our team includes more than 30 practitioners with deep expertise in computer science, actuarial science, probability and statistics, business and project management. We bring smarter science and new ideas to the business of law.”  The firm supplements these technology tools and resources with economic and business advice. This solution is co-led by Chris Emerson, Bryan Cave’s Chief Practice Economics Officer, and Katie Boyd, a partner at the firm and its Chief Innovation Officer.

Baker Donelson has developed a suite of products, approaches and service offerings around Legal Project Management (LPM) all in an effort to help clients  improve service delivery (budget predictability, workflow efficiency and team collaboration), enhance business operations (lower spend, minimize risk, prove value) and achieve operational excellence of strategy, people and process.  Core LPM solutions offered include:

BakerManage™ is a patent-pending tool that is combined with Lean Six Sigma processes to improve efficiencies and budget predictability and transparency.
BakerManage™ LPM Program Development and Training: on lean process improvement, reliable budgeting, innovative pricing, team management and enterprise lawyer management technology.
BakerManage™ Workflow Management: a tool that automates BakerManage™ and other processes to optimize resources.
LPM Secondment/Sourcing to augment or second professionals to clients who have limited access to LPM expertise.
BakerLean™: Process for developing budgets, project plans and pricing models.
The Legal Project Management solutions team is comprised of lawyers, certified legal project managers, Lean-certified professionals, technology and automation specialists, and others. In 2016, Baker Donalson announced an affiliation with Legal Shift, a consulting and business advisory. Through the combined team, the firm offers a more robust blend of advisory services with their project management tools:

Legal process improvement
Contract workflow strategy
Litigation readiness assessments
IP paperless process design
Business operations (re)design
In-house/outside counsel alignment
Matter budget compliance program development
Pricing model development
Technology assessment planning, selection and implementation
Knowledge management, contract discovery and compliance, practice support solution design
eDiscovery process improvement, vendor selection and performance measurement; repository management
service  innovation  client  strategy  robo  data 
november 2017 by JordanFurlong
Lex Machina Launches Bankruptcy Appeals Analytics Module | Dewey B Strategic
oday Lex Machina is releasing a new module which covers district court bankruptcy appeals. Until now all prior Lex Machina modules have focused on federal trials. The Bankruptcy product covers 18,000 bankruptcy appeals filed since 2009. This is Lex Machina’s first foray into appellate analytics.

The Lex Machina CTO, Karl Harris is quoted in the press release: “Although there are relatively few bankruptcy appeals cases at the district court level compared to commercial or employment litigation cases, the stakes are incredibly high for all those involved, so it is imperative that attorneys know the lay of the land before entering the courtroom. With Lex Machina, attorneys will now be able to get critical insights into the behaviors of district court judges, allowing them to provide the most informed counsel and formulate the best case strategy.”

Bankruptcy practice is highly specialized and Lex Machina developed the new module based on feedback received from top bankruptcy litigators. The new product incorporates 10 practice-specific tags and 15 unique “dispute appeals” categories, which will enable attorneys derive insights a competitive advantage throughout the appeals process. Since bankruptcy appeals are much less common than traditional appeals it is more challenging for attorneys to gain insights into judges and outcomes.

As part of the product development process, Lex Machina interviewed top bankruptcy appeals lawyers to better understand their needs and incorporated their feedback directly into the new offering. As a result Lex Machina developed 10 new filers and 15 appellate categories.
data  analytics  bankruptcy  predictive 
september 2017 by JordanFurlong
When Will Disruption Hit the Legal Industry | The American Lawyer
The data show that a similar number of firms (29 and 30) discontinued operations in each cycle due to bankruptcy, dissolution, merger into stronger entities, or falling below the Am Law 200 revenue cut off [Table 1(a)]. However, there is a sharp contrast in the number of firms that experienced RPL declines. Seventy-four firms experienced such declines in the second cycle compared with only 6 in the first cycle, [Table 1(b)]. This shows that the price erosion that we see for Big Law in aggregate since 2007 (Figure 1) varies markedly across firms and that, as evidenced by the slightly higher number of firms in the PPP 1-50 and PPP 51-100 cohorts that have experienced RPL declines, it affects higher-profit firms slightly more than lower-profit firms. Said differently: the erosion of price realization that economics tells us to expect is in fact occurring, is concentrated in a subset of firms, and is hitting firms of all profit levels.
So why aren't partners feeling the pressure more? A piece of the answer is that law firms have been able to mitigate the impact of price erosion on profitability. As Tables 1(b) and 1(c) show: in the first cycle, roughly the same number of firms experienced price erosion (RPL) and profitability (PPP) declines; in the second cycle fewer firms have suffered a decline in profitability than have suffered price erosion. There seem to have been two major levers in mitigating the effect of price erosion on profitability: cost reduction and nonequity partner changes.
On cost, as Table 2 shows, while firms of all profitability levels increased cost-per-lawyer over the first cycle, they slowed this growth dramatically through the second cycle. Indeed the 100 most profitable firms (the PPP 1-50 and PPP 51-100 cohorts) actually reduced average cost-per-lawyer. This probably reflects that it is easier for the more profitable firms to lower costs because they are typically starting from a higher cost position than their lower-profitability counterparts and thus have more to trim.
data  firms  profitability  future 
september 2017 by JordanFurlong
Prism Legal Early Observations from the GC Thought Leader Experiment (Live) - Prism Legal
A surprise here: the panel firms do worse than non-panel firms. Caveates here are that there is a lot of variability. Key takeaway is that panels don’t always work. They work only if properly managed. The experiment is now looking at what drives panel success, where they do succeed.

Deckleman Comments: DXC established a panel this year post its mergers. We look at panel firms as strategic partners. We are identifying upfront where the opportunities are and who inside and at the firm must interact – establish the right connections. Panel is not just about lowering fees – we want that but passion about client responsiveness and being able to support us in a deep way. We have gone beyond our incumbent firms that fit what we now want. Many of our firms are in the AL panel – not necessarily in traditional size brackets or geographic locations. We are getting high quality at effective rates. With AL, we are regularly evaluating firms – this is key to keep relationship dynamic. We are taking steps to keep competition injected in the process (so that we don’t end up with typical incumbency problems).

PayPal does not currently have a panel. GC’s initial thinking was that the company would need a panel. But this finding this suggests that forming a panel is first step in a process, not the last. So to move forward with a panel is a process that requires cultivating relationships and foster business intimacy. The panel needs to be about value-add, not just cost savings.

Flex – panels need to be managed. We look to AL for guidance on how to manage panels. We’ve had good experiences with panels with some exceptions. This helps us up our game.

Firoz – one issue we see frequently is that panels are overweighted to one type of firm. Panels can work but take active management. “A lot of potential but avoid the pitfalls
data  clients  firms 
september 2017 by JordanFurlong
How AI Will Change Reputation As A Proxy For Quality
AI is making waves around the world. Some of those waves are crashing down on professions, such as law. Old world practices are giving way to new world technology. Some of the customs are changing as well. As AI gives us ways to turn guesses into objective reality, how we find professional services may change.
quality  data 
september 2017 by JordanFurlong
Value Drivers: Sylvia Chen, Google's Patent Counsel and Head of Patent Operations - Qualmet Legal
Our key metrics are based on the “management triangle” – quantity, cost and quality. Because the Google Patents Team mostly uses flat-fee billing, cost is not necessarily a cost per unit, but includes accuracy and timeliness of billing – which are additional objective metrics related to cost. Quality is measured using more subjective metrics, which we seek to define more tightly every year.

What tools do you use to collect and analyze the information?

We use our docketing tool, our billing tool and our in-house survey tool (Google Forms). There are no custom tools. Everything is off-the-shelf, but we do have data scientists (analysts) embedded in our team who have helped refine some of the metrics. For example: when should completion of a task be considered timely versus tardy? Our outside counsel were considering that an activity completed on the date when they made a submission. Based on thoughts about Google’s goals, we decided instead to measure  completion as the date when we received an accurate submission.

How much time and resources does your team spend on the evaluation process?

A lot. We have an entire program that addresses how to improve communications, relations, expectations and feedback with our firms, and our annual score card is an important piece of that program. It takes 2.5 person-months a year to support the process. Other than people’s time, there are no additional costs.
data  analytics  quality  clients  firms  process 
september 2017 by JordanFurlong
Prism Legal Intriguing New Legal Services Innovation Index - Prism Legal
The Catalog and Index represent, in start-up terms, a minimally viable product (MVP). MVP means it solves some problems but needs work and plans exist for improvements. The current Phase I goal is “to add to and improve legal-industry discussions about legal innovation and technology”. I applaud and share this goal.

I had a similar goal in mind when I published my R&D in Big Law list in June 2015 (which gets a shout-out on the Innovation Catalog page as a consulted source.) The Catalog lists innovation categories. The Catalog entries are based on human research and literature review, looks at many recent innovations such as alternative fee arrangements (AFA), artificial intelligence (AI), data analytics, and incubators. It also includes some older approaches such as document assembly and “information management”.

The Catalog also tabulates which law firms offer which each Catalog entry and includes other important information. Scanning the Catalog by firm, I’m pretty sure I can identify some missing law firm entries. So I suggest that every firm review this list and, if they have a product or service that meets the criteria, click the link at the bottom of the the Innovation Catalog page to submit it. (Note that I have included the Catalog as an embedded Tableau object below. And below that one static screenshot in case Tableau does not render for some readers.)
innovation  data  firms 
september 2017 by JordanFurlong
A Conversation With Six General Counsel | Corporate Counsel
What is a hypothesis we’re testing that you find interesting?
Brian Levey, Upwork: The honeymoon period hypothesis is interesting to me.  Clients become the ‘bright shiny object’ upon engaging a firm, but what happens to performance over time?  I’d be interested to know what works in staying a priority at the firm.
Lee Reichert, Molson Coors: I’m interested to see how the performance of firms in the biggest cities compares to that of firms elsewhere – on things like quality, responsiveness, outcomes, and expertise.  Are there differences?  Given the breadth of our business, this finding can influence how we make counsel selection decisions.
Josh Sherbin, TriMas: The discussion on alternative fee arrangements seems to be all about cost and negotiating down to the dollar.  It would be nice to see from the data whether and how non-hourly fee arrangements fit with satisfying, strategic client-firm relationships.
Damien Atkins, Panasonic: I’d like to stress-test flat fees and success fees.  Since they affect partner compensation, often creating financial uncertainty, they’re likely to change behavior and may impact work product and client service.  I’m curious to see what the data will show.
Bill Deckelman, DXC Technology: As we just worked with you in selecting our panel of strategic partner firms, I would like to see what the data says about law firm panels.
Brian Chevlin, Pernod Ricard: I’d like to test that out as well.  My belief is that having a preferred set of firms – once we’ve identified the highest-performers – is the ideal state, as the firms get to know our business.  Related, what can we do to make panels especially valuable for us and the firms?
clients  data  analytics  firms  pricing  convergence 
august 2017 by JordanFurlong
The GC Thought Leaders Experiment | Corporate Counsel
Overall, this is a grassroots movement of GCs interested in re-shaping the legal market to make it work better for all – law firms and clients alike. “There are different management approaches – but how do we know if they’re real or a fad? We’re keen to test things like law firm convergence, flat fees, value billing, competitive tenders, firm size and reach, and legal project management,” said Jonathan Pearl, Sony Electronics’ General Counsel. “We want to know what works and why.”
Damien Atkins, General Counsel of Panasonic North America, puts it this way: “There is a lot of guesswork by clients and firms as to what drives better outcomes, and we’re all shooting from the hip. Across the companies involved in this experiment, we’ll have a vast amount of data that can answer these questions. If we get this right, we’ll help reinvent an industry in need of reform.”
While AdvanceLaw staff will collect and analyze real-time performance data across this 18-month experiment (testing which in-house and law firm behaviors produce the best results), the general counsel will, themselves, share and discuss the insights through a forthcoming series of articles.
One of the first questions to be answered is whether law firm performance indeed drops off after an early honeymoon period. Related inquiries will examine which client practices can prevent this, and what firms can do to keep clients engaged and happy over the long run. Josh Sherbin, General Counsel of TriMas Corporation remarks, “I’ve noticed a honeymoon period, and that’s why I think it’s important to evaluate firms at least annually. But this is anecdotal – I’d like to see how significant the issue is, and most importantly, the best ways to fix it.”
The early analysis, based on several hundred law firm-client relationships, suggests a U-shaped curve of performance – a client’s firms start out strong, deliver worse performance after the honeymoon period, and then recover over the course of subsequent years. A more complete analysis of this finding, with a discussion of implications, will be written about by one of the participating GCs next month.
clients  data  firms  service 
august 2017 by JordanFurlong
3 Geeks and a Law Blog: Convergence Initiatives and Panel Programs — What If The Data Says We're Wrong?
Regardless, I’ve long believed most convergence initiatives waste considerable time for limited benefit despite the fact that I regularly consult on convergence initiatives.

[For those who are unfamiliar with the term, “convergence” is the prelude to a preferred provider, or panel, program. It is the consolidation process by which a law department selects their preferred providers. These initiatives can often reduce the number of firms used by 60% or more. While a few win big, hundreds of firms can lose a client in the process.]

I am saying this now because AdvanceLaw and 25 of their GC’s have forced my hand (see here, here, here, and here for more details on this fantastic undertaking; see here for my initial encounter with AdvanceLaw).

AdvanceLaw is publicly conducting a study of what works and what doesn’t with respect to outside counsel management. This includes convergence initiatives, which are part of my consulting business. I therefore feel compelled to lay down a marker.

AdvanceLaw is performing a mitzvah. I could not be more in on their bringing data-driven decision making to the retention and management of outside counsel. Yet I am moderately confident that their findings will not bolster my sales pitch (another instance where I would be ecstatic to be proven wrong).

I predict that they will find little-to-no correlation between convergence initiatives and satisfaction with outside counsel. That is, when AdvanceLaw comes out with a data-supported list of the approaches that drive the most perceived value for in-house counsel, convergence initiatives will not rank near the top.

And that is because convergence initiatives, in isolation, do not accomplish much. They are a stage-setting exercise. They are a precursor. To me, a finding that convergence does not deliver high independent value is like finding that the mere purchase of home exercise equipment or gym membership does not result in physical fitness.
convergence  clients  data  pricing  firms 
august 2017 by JordanFurlong
How Firms Should Be Measuring the Profitability of Matters | The American Lawyer
How MPH Works
Consider two idealized matters. Matter A is a year-long counseling arrangement. It's relatively low leverage—1.5 associate hours per partner hour, but the client pays full billing rates. Matter B is a litigation matter that settles before going to trial. It's relatively high leverage—4.1 associate hours per partner hour, but the client is getting a 15 percent discount so realization is only 85 percent. Table 1 below shows the calculations of the matters' MPH. Gross revenues are determined simply as hours multiplied by billing rate, (the examples use the same average partner and associate hourly billing rates of $1,000 and $650, respectively). For ease of comparison, gross revenues are $1M for both matters. The matters' realization is applied to gross revenues to determine net revenues from which associate cost—approximated as one quarter of the associate billing rate (discussed more later)—is subtracted to determine margin. Margin is then divided by partner hours to provide MPH.

Hugh Simons
The final line of the calculation presents the matter's MPH as a percent of firm target, typically the MPH level implicit in the firm's financial plan, (every annual plan has such a metric in it ). There are a number of reasons to look at MPH in this way. One is that, because the MPH metric is new, partners don't have a feel for what constitutes a "good" level of MPH in the way that they do for, say, an individual's billed hours; comparison to a target level makes it easy to assess. Another is that comparing a matter's MPH with a target brings into the assessment of profitability how well the matter is contributing to covering the firm's fixed costs and to meeting the firm's profit expectation. Finally, as billing rates increase year by year, the level that constitutes a good MPH also rises; looking at MPH as a percent of firm target allows the assessment of what constitutes a strong MPH to rise naturally over time.
The calculations show that the high-leverage, low-realization Matter B has the higher MPH—111 vs. 80 percent of firm target. That is to say, each partner hour on Matter B is contributing significantly more to coverage of the firm's fixed costs and generation of its partner profit pool.
profitability  metrics  data  firms  partners 
august 2017 by JordanFurlong
What GC Thought Leaders Experiment Is About (Hint: Not Cost) | The American Lawyer
The roots of the Thought Leaders Experiment lie in what the industry has not yet done with data: use it to test which client and law firm behaviors measurably improve satisfaction and lead to the best relationships. We are doing this by looking at data relating to thousands of matters to see how client and firm practices (such as the existence of a law firm panel) impact client assessments of quality, responsiveness, expertise, trust, and innovation. (You can see more detail on the project here.)
By contrast, most data in the legal industry is used for benchmarking, which can tell us the cost of the average deposition, but won't tell us what causes a representation to go well overall. That's why this project is not a benchmarking exercise. We aren't comparing rates, nor ranking firms and lawyers—we're looking at which practices work best. In fact, one goal of this effort is to get the legal profession off the topic of cost, and focused more on quality, value, long-term relationships, and successful legal representations. We have no plans to use billing records in this project.
Instead, we are building on an aspect of our work that has always been the most useful. For eight years, we've been collecting in-house clients' informed, professional assessments of law firm performance. Beyond using this to help with counsel selection, we're regularly asked to present this "voice of the client" data and feedback at law firm retreats and in-house meetings—it can offer a very practical view of what works and what doesn't.
cleinmts  data  analytics 
july 2017 by JordanFurlong
GC Data Sharing Plan Is 'Wake-Up Call' for Law Firms | The American Lawyer
“There are going to be winners and losers here,” said William Henderson, an Indiana University Maurer School of Law professor who studies the business of law. “If you understand how this works and build your business around the right answers to these empirical questions, you will get more work. If you choose to ignore this, you will be cut out of work.”
The project is being run by a consultancy called AdvanceLaw, which includes general counsel and invited law firms.
The data the GCs are sharing includes firm names, billing rates, billing arrangements, matter types, practice areas, relationship length with outside firms, if a firm is a preferred provider and frequent performance reviews from in-house counsel. Every month, a different general counsel will write a report answering a new question based on the data.
Outside Counsel React
Law firm leaders reacted to the project with a mix of excitement and angst.
The excitement was borne out of a desire to please clients and an acknowledgement that law firms could use more input from clients on how to do that.
“I’d love to see the results of what they learn and be able to communicate that to people here to help us be better at what we’re doing,” said Timothy Mohan, chief executive partner at Chapman and Cutler, a finance-focused Am Law 150 firm with $196.5 million in revenue last year.
data  clients  analytics  pricing  firms 
july 2017 by JordanFurlong
An Open Letter From 25 General Counsel | The American Lawyer
While large clients spend millions of dollars and thousands of hours a year working with their law firms, firm leaders are making structural, growth, technology, and market-entry decisions that turn on assumptions about what clients want. We believe that, working together, we can provide a helpful road map, suggesting which practices and innovations lead to positive results and strong relationships. Through better information, we hope to move the profession forward.
We are working together with AdvanceLaw to tackle this challenge. This is a real-time experiment testing which in-house practices (e.g., convergence, value billing, competitive bids) and law firm attributes (e.g., firm size and structure, legal project management) tend to produce the strongest relationships, satisfaction, and results. The methodology is fairly straightforward: we are collecting and sharing outcomes and performance evaluations on a wide range of legal matters with AdvanceLaw staff, who are determining which behaviors consistently generate better results. Through a large data set, across our companies, we are moving beyond the anecdotal to measure what really works.
The data set has already grown to represent thousands of matters; as the project continues, it will encompass millions of data points allowing for a detailed analysis of many critical questions. As the results come in, a number of general counsel from our group will author articles offering thoughts on these findings, including practical implications for both clients and law firms.
We know we can’t answer every key question, but we hope this effort will lead to a better conversation among leaders of the legal profession about service quality and innovation.
clients  data  analytics  firms  future 
july 2017 by JordanFurlong
Slave to the algorithm | Feature | Law Society Gazette
Milos Kresojevic, information architect at Freshfields Bruckhaus Deringer, reminded ICAIL that legal AI must address the needs of the practice and its clients and that there was a danger of firms focusing on the much-hyped technology rather than its practical results. He outlined how Freshfields links together a portfolio of commercial AI products – including Kira Systems and Neota – to create bespoke solutions that can then be productised to differentiate the firm’s services. As he explained later, however, differentiation involves significant effort. Freshfields’ real estate transaction team in Germany has trained Kira to recognise over 1,000 German language documents, thereby retraining the technology to create a unique Freshfields version of Kira whose output interfaces with German AI-powered data extraction engine Leverton. Freshfields is currently training Kira to work in more languages. ‘Applying AI solutions in multiple jurisdictions increases the firm’s reach and its ability to handle more complex work,’ explains Kresojevic. However, he is frustrated by the lack of an end-to-end legal AI offering. While there are multiple products for document comparison and data extraction, the end result is an Excel spreadsheet or a PDF document! Firms such as Freshfields are using legal engineers: to bring together a smart portfolio of AI products into an end-to-end solution that delivers the firm’s business strategy and extends its competitive advantage. Kresojevic believes that the firms that are building complete solutions will continue to disrupt the market.

Disruption with a social purpose

A similar strategy, with a very different objective, is disrupting the opposite end of the legal services spectrum. Alan Larkin, director at Family Law Partners in Brighton, has used intelligent technology to respond to government cuts in family legal services and the subsequent increase in the number of litigants in person.

According to the SRA, a third of people consider legal services to be inaccessible. Consequently, vulnerable people are being dragged through the family courts, at considerable cost to the courts service and further damage to the families involved. ‘They are missing the early intervention which lawyers used to bring, when public funding was available,’ Larkin says. ‘I understand the rationale behind proposals for an online court, but by the time cases reach court, the damage is already done. If local authorities developed an online portal where people could access advice, some of them could be directed to mediation and potentially avoid court altogether.’

However, there is a distinct lack of online resources for people seeking advice on family break-ups, the division of assets, child maintenance and so on.
robo  data  analytics  access  family  innovation  it 
july 2017 by JordanFurlong
Why We're Open-Sourcing Our Contract Analytics Platform - ContraxSuite - LexPredict
Today, we are proud to announce that we plan to open source the development of our core platform for contract analytics and document analytics – ContraxSuite. This code base and our public development roadmap will be hosted on Github under a permissive open-source licensing model that will allow most organizations to quickly and freely implement and customize their own contract and document analytics. Like Redhat does for Linux, we will provide support, customization, and data services to “cover the last mile” for those organizations who need it.

We believe that a very important future for law lies in its central role in facilitating and regulating the modern information economy. But unless we start treating law itself like the production of information, we’ll never get there. Before we can solve big problems with smart contracts, we need to start by structuring existing legacy contracts. We hope our actions today will help lawyers, companies, and other LegalTech providers accelerate the pace of improvement and innovation through more open collaboration.
opensource  robo  data  analysis 
july 2017 by JordanFurlong
Law Librarian Try Chief Knowledge Officer | The American Lawyer
"Our work has gone beyond research and into AI, data analytical tools, and business development," says Steve Lastres, director of knowledge management services at Debevoise & Plimpton. "We are providing a level of service and customization that we have never offered before." For example, the knowledge management (KM) team at Debevoise publishes 19 curated newsletters each week focused on different practice areas.
"There's value in serving up relevant content to 50 people within a practice area," Lastres says. "They don't have to go looking for it, and it develops trust between the attorneys and the KM team."
"Business and competitive intelligence is very important, given the competitive [business] environment," says Marlene Gebauer, director of knowledge solutions at Greenberg Traurig. "These tools generate a huge amount of data—and it is getting more granular, so the research now is a lot more complex and takes a lot more time," she adds. (She declined to discuss how the firm uses these tools, citing firm policy.)
library  compintell  intel  knowledge  km  data  analytics 
june 2017 by JordanFurlong
National | Interview with Blue J Legal CEO Benjamin Alarie on intuition versus the data
BA: It’s always wise to be critical and examine critically these new technologies as they’re being developed, and it may be picking up on current flaws in the system. But we set the bar really high for artificially intelligent systems in ways that set up an unfair contest between algorithms in human decision-making. Every year in North America tens of thousands of people are killed in automobile accidents but the threshold for autonomous vehicles has to be 100 per cent safe. That’s probably the wrong standard to hold self-driving vehicles to. In the same way, in the U.S., if you are convicted of a crime on the eve of a judicial election — and there’s been a lot of empirical evidence around this — there’s a tendency, among judges, to err on the side of being harsher in sentencing.
robo  data  analytics 
june 2017 by JordanFurlong
Ravel Launches Law Firm Analytics - Robert Ambrogi's LawSites
The legal research service Ravel Law today announced the launch of a new feature, Firm Analytics, that provides insights on law firms’ litigation histories that can be used for competitive intelligence and research into firms’ litigation activity.

I am traveling today and have not seen this new feature. Ravel CEO Daniel Lewis says it can be used to:

Understand a firm’s litigation history by case type, venue, motion win rate, and judge.
Rank and compare firms by their case volume and motion win rate across more than 30 practice areas and specific venues.
Create custom comparisons and reports using an array of variables.
By way of example, Firm Analytics can be used both by firms and by in-house counsel to gain insights into firms’ experience and performance. It could also be used by an associate working on an employment law case to quickly find the previous employment law cases the association’s firm handled, understand the motions involved and past win rates, and discover the arguments that worked best.
research  data  analytics 
may 2017 by JordanFurlong
This GC Thinks He Can Quantify the Long-Subjective Art of Service Provider Value | Legaltech News
James Beckett, CEO of Qualmet, told Legaltech News that the platform compares value-based on inputs from law department team members. Individual members of the legal team first conduct evaluations of a legal matter, including associated lawyers and firms, using quick forms intended to take about one minute to complete. From there, the platform assesses performance quantitatively, with results coming in six categories:
Understanding  of the client’s business;
Appropriateness of effort;
Resource management; and
Overall satisfaction.
The results can then help with quantitative comparisons between firms, with legal spend added into the equation for context. Beckett said law departments can also customize the formula with their own metrics as they see fit, though some elements of the formula will remain consistent among all deployments.
value  client  kpi  metrics  data 
may 2017 by JordanFurlong
Unlocking the power of relational data to improve collaboration - The Lawyer's Daily
Similarly there is a lot of attention being paid to the ways in which collaboration at law firms produces greater profit. For instance, Heidi Gardner, a professor at Harvard Law School and former consultant, has written extensively about how law firms should be gathering and analyzing relational data in order to drive profitability. She evaluated billing records from several large firms over time to show the consistent connection between collaboration and success.
collaboration  data  analytics 
may 2017 by JordanFurlong
Bigger Data, ‘Tech Terror’ and Diversity Disparities Mark CodeX’s Fifth FutureLaw | Legaltech News
Nevin said to ensure that practitioners are truly using data effectively requires “understanding what needs enforcing and to what ends. Are the ends based on logic, or on emotion?” That interpretation, at least for now, is still something that only humans can do. Panelist Josh Becker, CEO of Lex Machina, reiterated this point in discussing his company’s approach to data, saying that the company prefers actual data to “anec-data,” i.e., data that is anecdotal.
The panel that followed looked at the ways in which human-programmed rules presented a slightly different approach to managing large data sets. Panelists described using “checklists” and “worksheets” that verify compliance with pre-established conditions. Harry Surden, the panel’s contrarian and associate professor of law at University of Colorado Law School, encouraged panelists and audience members to think carefully about how codifying rules in technology can unintentionally codify broader value systems.
Michael Mills, co-founder of Neota Logic, said that despite their vantage points, rules-based and data-driven approaches share an interest in using technology to sharped legal deduction and reasoning. “In the end, all of this is about inference,” he said.
“Most successful systems are indeed a hybrid. The difference is how you create those rules,” he later added, noting that analytics teams use data sets to drive rules while other programmers look to build algorithms in by hand.
data  diversity  robo 
april 2017 by JordanFurlong
Missing in Action: Impute Intelligently Before Deciding Based on Data | Legaltech News
One choice would be to drop the matters that have a missing data point. But leaving out matters can result in a debilitating loss of other information on those matters, such as number of timekeepers, duration, etc. To counter this problem, analysts employ a range of methods to plug in plausible numbers for missing numbers and thereby save the remaining data. These methods are called "imputation," and imputation is an important step when you prepare data for analysis. This article explains various methods of imputation, starting with the simplest and ending with sophisticated methods.
The first inquiry, however, is to determine why data is missing. If numbers are missing because of an identifiable reason, such as the Los Angeles corporate practice group failed to provide any data on fees, you take a different tack than imputation to obtain the absent data. More commonly, however, data is missing with no discernible pattern for why. If the "missingness" is due, for example, to the L.A. office simply being lazy about recording or reporting their data, but their numbers would have been statistically similar to all of the other offices if they had been available, then that would be one situation. However, if L.A. didn't report numbers because they were really awful, and they conveniently "forgot" to send them in so as not to be embarrassed, then that would be "missing not at random." In any event, software can help visualize the gaps and make clear if there is a pattern or simply the slip-through-the cracks of life.
data  analytics 
april 2017 by JordanFurlong
This Law Firm Is Betting on Data | Big Law Business
ackson Lewis P.C. is launching a data analytics group to bolster its labor and employment practice and to tackle new and non-law projects for its employer clients.

“We have a team of lawyers, statisticians and data scientists that will support the various practice groups in the firm with their analytics needs as well as undertake proactive analytics projects on behalf of our clients,” Eric J. Felsberg told Bloomberg BNA.

Felsberg, a principal in the firm’s Long Island, N.Y., office, will lead the JL Data Analytics Group. “It’s a resource group within the firm,” he said.

The analytics group may offer “damage assessments” for legal cases, Felsberg said. For example, if workers claim they were underpaid, the group could analyze their “electronic footprint” to determine their likely work hours by checking the times they swiped their identification badges into and out of the building and when they logged on to and off of their computers, he said.

Client projects not connected to specific legal cases could include a business that is “trying to figure out head count needs,” for which the group could analyze the staff’s attrition history, Felsberg said. Analytics also could help an organization “offer targeted training” to its personnel. The group could identify the units where poor service generated complaints so the client could avoid providing corrective training for its entire workforce.
data  analytics 
january 2017 by JordanFurlong
5 Cases Where Data Analytics Reduce Costs and Risks for Regional and Boutique Firms | Legaltech News
With stunning advancements in techniques and document review software over the past five years, industry surveys now estimate that 65 percent of "big law" firms now utilize data analytics to improve case outcomes. But even as costs have steadily declined—as confidentiality and admissibility concerns have been readily addressed and as dramatic case successes have mounted—only about 10 percent of regional and boutique firms currently have ready access to expertise in the field.
For many law partners assessing an entry point, one key has been in the client development arena—or how to produce a swift and reliable initial result at a known cost. Outside experts in data analytics look to get more out of the available case data, reduce human error and risk, and save 30 to 70 percent (or more) in costs and time. Several examples below illustrate the case for competitive advanced analytics.
data  analytics 
january 2017 by JordanFurlong
National | Analyze this: How data is reshaping the in-house role
Analyze this: How data is reshaping the in-house role



In 2014, Charles McCarragher and his legal team at TD Bank Group faced a problem familiar to in-house counsel: too much work and not enough people to do it. 

More staff, in his view, was not the answer. “Adding lanes to the highway is not the way you solve rush-hour traffic,” says Mr. McCarragher, Assistant Vice-President Legal (Technology), especially without a quantitative explanation for “we’re busy.” Instead, he turned to data analytics—the business of mining internal and external company information to drive decisions—a strategy gaining ground with in-house counsel as they look to manage growing demand for legal services and add value to an organization’s bottom line. 

“There is a high level of acknowledgement that data analytics is central to the discharge of a general counsel’s mandate,” says Deloitte Partner David Stewart, co-author of the consulting company’s annual General Counsel Report. “The question is, ‘Are they happy with where they are today and do they feel they are optimizing the data and tools to their full advantage?’ A lot of people would say there is a lot of room for improvement.”

At TD, the need to rethink contract review procedures came to a head in 2014. 

With the quantity of work “increasing year over year,” McCarragher’s five-person team spent about 75% of their time on high-risk legal matters—the equivalent of 10-20% of work volume on an annual basis. Only 20% of the time was left for low-to-medium risk issues that accounted for 80-90% of the volume and still required scrutiny. 
data  analytics  roboclients 
december 2016 by JordanFurlong
Analytics in the Workplace: A Q&A with Jackson Lewis on Employment Law Data Science | Corporate Counsel
Q: Analytics is all the hype in legal tech. How is Jackson Lewis jumping onboard?
A: We provide predictive analytics services that leverage data reflecting past events to inform future decision-making. For example, we can help optimize recruiting functions by examining those qualifications of past successful hires to help inform talent acquisition teams’ recruiting efforts. Additionally, we provide predictive pay analyses that leverage past pay data to inform appropriate pay setting for employees and future hires. We have also begun helping clients recognize the power they hold in data that they have not previously used. For example, we assist clients with assessing employee engagement by examining building card swipes, GPS records, and the like. This can be particularly helpful during litigation involving hours worked, for example.
data  analytics 
december 2016 by JordanFurlong
University of Toronto Law Journal: Vol 66, No 4
data  robolawyer  future 
november 2016 by JordanFurlong
Littler Mendelson Gambles on Data Mining as Competition Changes |
Littler Mendelson Gambles on Data Mining as Competition Changes
An MIT Ph.D. is diving deep into data analytics for the labor and employment firm. But Littler is not alone.
data  robolawyer 
november 2016 by JordanFurlong
Optimal Pricing Of Legal Services And Big Data | Above the Law is interesting from a general perspective in that it essentially shows the power of data in the legal space. The firm is profitable and growing rapidly, with annual revenues of around $4 million at this point. The whitespace that is not yet being exploited by or anyone else, though, centers around two factors: price optimization and services targeting.

Lawyers traditionally set an hourly rate and in most cases use that rate for all clients. Occasionally, however, if a client has a particularly high willingness to pay, the attorney might charge a higher rate. Uniform pricing across clients is not efficient, though. Lawyers should be charging different clients different hourly rates based on the value of the services to each specific client. Doing that kind of price optimization is hard with a traditional legal business, but with specific data like that derivable from, more effective pricing is certainly feasible. A good example of effective price optimization is Google. The website charges different costs for the same advertisement based on characteristics of that advertisement – primarily keywords used.
data  procing 
november 2016 by JordanFurlong
Paul Hastings Latest Big Firm to Dabble in Data Analytics |
The tools Barnett’s team uses go beyond keyword search to study what he calls topics and patterns in the documents. Barnett said work his group is doing can save clients two thirds the cost of data review and can help lawyers understand a case faster.

For example, when a pharmaceutical company faced an enforcement subpoena, Paul Hastings needed to review 5 million documents in a short period of time. A group of contract attorneys was able to identify documents that were significant to the case at a 1.6 percent success rate, while Barnett’s process identified significant documents at a 20 percent success rate.

The contract attorneys cost $115,000, compared to Barnett’s method, which cost the client $40,000.

“There’s no question that technology assisted review is going to be a lot more efficient and effective,” said Gordon Cormack, a computer science professor at the University of Waterloo in Ontario, Canada. Cormack works with Maura Grossman, a former of counsel at Wachtell, Lipton, Rosen & Katz who developed a document identification process at the firm before leaving the firm in June.
e-discovery  data  analytics 
october 2016 by JordanFurlong
Nextlaw Labs expands portfolio with legal services quality assessment provider QualMet | Nextlaw Labs
Nextlaw Labs, the collaborative innovation platform launched by global law firm Dentons, today announced its investment in QualMet, an early-stage startup that brings quality assessment metrics to in-house counsel and law firms. The investment marks the seventh company to enter Nextlaw Labs’ portfolio.

QualMet provides a streamlined cloud platform and standardized process for in-house counsel and law firms to benchmark the quality of legal services across industry sectors, firms and legal practice areas. The company focuses on key performance metrics that are critical to delivering value.

“QualMet sets the bar by which we evaluate legal services and improves collaboration between in-house and external legal counsel,” said Dan Jansen, chief executive of Nextlaw Labs. “We see this as an exciting opportunity to bring major law firms like Dentons and their clients into an important dialogue about improving and defining the quality of legal services.”

The underlying concept for QualMet was created by Mark Smolik, general counsel with DHL Supply Chain, who has been using a prototype of the evaluation platform for the past eight years. “Legal departments tend to focus on managing and reducing costs, and much less attention is placed on the quality of legal services. It became clear to me early on that the legal industry was in need of a paradigm shift.” said Mark. “Quality, and collaborative conversations about it, are two of the key missing ingredients in optimal value creation for both in-house and outside counsel.”

QualMet allows in-house counsel to easily assess the quality and business value of their legal service providers, share results to align expectations and goals, use industry benchmarks to identify opportunities for improvement, and find the best-in-class law firms based on evaluations by their peers. On the other side of the equation, QualMet allows law firms to learn how clients perceive their contributions, benchmark their performance vis-à-vis other law firms and develop a strategy to improve and maximize business opportunities.
quality  metrics  innovation  data  analytics 
october 2016 by JordanFurlong
The Complications and Complexity of Evaluating Risk Analytics | Legaltech News
We may also assume that various sources of relevant information are equally analyzable. Business systems comprise a variety of data formats that are often difficult to interrogate. In many contexts, discovery proportionality principles can provide a basis for limiting the scope of data collection and analysis of sources such as backup storage media. In others, however, it is inapplicable. For example, in presenting certain claims for reimbursement, expenditures must be supported by source documents like invoices and canceled checks. If these records exist only in paper form in a warehouse, supporting the claim after the fact can be very expensive and labor-intensive, but unavoidable. The principal concern isn't whether information is obtainable, but at what cost.
If we assume our analysis tools can read and evaluate data in any format, we can be obviously wrong sometimes and not-so-obviously wrong other times. It is obvious that certain kinds of data, like encrypted drives or boxes full of paper in an off-site warehouse, cannot be queried or even directly read by a machine. It is less obvious that scanned paper documents in PDF format do not have machine-readable text until optical character recognition (OCR) is applied, or that chat logs, SMS, email, and web form text fields all have different metadata, units of measurement, formats, and even language structure.
Often we assume data can be easily queried to answer business or legal questions. This assumption has both syntactic and semantic underpinnings. The syntactic assumption is that our question can be interpreted by the system. Computers are unforgiving, so a system that expects you to enter "09" rather than "September" in a month field will deem your input syntactically invalid and fail. The semantic assumption is that what we ask is exactly and completely what we want. Unfortunately, every literal request we make is replete with unspoken context that may be important.
data  analytics  predictive 
october 2016 by JordanFurlong
New Legal Trends Report provides data insights for small- to medium-sized law firms – Slaw
For the first time ever, small to medium-sized law firms have access to information that can help them make decisions like some of the world’s best businesses. Traditionally, solo-, small-, and medium-size law firm data has relied heavily on self-reported or anecdotal data, which is often heavily skewed due to both small sample sizes and the inherent unreliability of self-reported data. When contrasted with actual usage data, an entirely different picture of the legal landscape emerges, including surprising insights such as:
On average, attorneys are only expending 28 percent — roughly two hours — of each eight hour workday on billable activities.
Law firm utilization rates increase as additional attorneys are added, but plateau at five to nine attorneys.
When adjusted for cost of living, Nevada, Connecticut and Illinois emerge as the most profitable states for attorneys based on real hourly rates; conversely, Nebraska, Tennessee and Wisconsin are the lowest hourly rate states in real terms.
metrics  data  solos 
october 2016 by JordanFurlong
Does Legal Analytics Really Need “Big Data” to Make Predictions? – Slaw
But predictive analytics and machine learning projects vary wildly in scale and scope. It goes without saying that there are many predictive analytics problems in law that would require far more than 1.5 million decisions in order to make strong predictions. But there are also situations where we know in advance that certain elements are highly predictive of certain outcomes, and in a case like that, even a small data set can provide good predictive guidance. There’s a huge difference between a hypothetical product that could accurately predict the outcome of any case just by analysing the text of past written decisions (this is likely impossible at the current moment) and a predictive analytics product that provides an answer to a well-defined question with only two possible outcomes. For instance, Blue J Legal is a legal tech tool that uses machine learning, but it doesn’t claim to answer any possible question anyone might ever have about tax law. Instead, it’s currently tackling specific classification problems, like whether someone is a contractor or an employee.
All this being said, most analytics, both in general and specifically in the legal space, are actually descriptive and not predictive. Descriptive analytics can usefully describe and categorize a dataset without making a probabilistic claim. Though not “predictive” in the technical sense, this method can still be used to see patterns in historical data in order to make smart, educated inferences about outcomes.
data  analytics 
october 2016 by JordanFurlong
Emerging Legal Technology Forum: The Role of Mindset
Katz’s wide-ranging keynote touched on themes such as economics of law; the industrialization of what had been an artisanal trade; and the role of data and analytics in re-making the economic structure of the industry. In his introduction, however, he touched on another underlying theme that drove nearly every conversation during the course of the Forum. What legal technology and innovation is all about, he said, is building a better legal supply chain with better measurement of value in the elements of the chain.
supplychain  it  firms  data  analytics  metrics 
september 2016 by JordanFurlong
The Legal Whiteboard
From 2007 to 2012, the share of total law office receipts shifted by about 5% away from individuals toward businesses. Revenues for Offices of Lawyers grew during this period from $225 billion to $246 billion.  However, when we run the numbers, the total receipts for lawyers serving people declined from $65 billion to $59 billion.  That is a relatively large absolute decline in just five years.  It suggests an actual contraction in the amount of legal work for people. Yet during this same period, the nation grew from 288 million to 302 million people

These fairly stark results continue the trendlines of the Chicago Lawyers I and II studies.  Chicago Lawyer I showed that roughly half of lawyers in Chicago in 1975 were working for people and half were working for corporations. This was the basis for the Heinz-Laumann two-hemisphere theory.  When the study was replicated in 1995 (Chicago Lawyers II), the data showed twice as many organizational lawyers versus people lawyers, so hemi (as in half) no longer applied.  Further, among lawyers in solo and small firms -- the primary practice setting for people lawyers -- income had dropped significantly in inflation-adjusted dollars. In contrast, lawyers in large firms and in corporate legal departments experienced significant gains.
data  access 
september 2016 by JordanFurlong
Gaining a Strategic Advantage Through Analytics for Contracts | Legaltech News
Enterprise business is moving towards a world where acquiring, processing and sending information is revolutionized, making the old habits of storing contracts in a file cabinet and never looking at them again obsolete. We now live in an era of instant and impactful analytics, yet some businesses still operate the old-fashioned way, with sluggish manual contracting processes and static reports that don't tell the whole story or provide actionable intelligence.
In an effort to overcome the challenge of "information overload," the market has shifted its focus from "more data" to "the right data." The need for actionable data has driven analytics initiatives that distinguish the interesting from the valuable. There is no longer a desire to answer every question—just the questions that matter.
Finally, as the market demand for high-powered and intelligent analytic systems has increased, the ability to provide greater levels of visibility, personalization, usability, interaction and convenience became possible through cloud platforms. These best-in-class platforms have brought all data, all processes, and all users to one universally accessible place, and enabled analytics solutions to provide the instant, accurate, and actionable data consumers demand.
contracts  analytics  data 
september 2016 by JordanFurlong
Buying Into Business Intelligence: Inside Analytics for Firms and Legal Departments | Legaltech News
Owen Byrd, general counsel and chief evangelist at Lex Machina, a legal analytics company purchased by LexisNexis last year, has seen the evolution as law firms and their corporate clients increasingly ground their conversations in statistics. "Historically, the dance between law firms and potential clients has been a pretty subjective one. It has not been grounded in a lot of data and analytics. But that's changing."
Collecting and possessing the data is one thing. Applying the data to drive true efficiencies is another, and it's a step many law firms and corporate legal departments struggle to take.
Not Your Normal Corporate Practice
The definition of what business intelligence (BI) actually is depends on who you're talking to. Some call it the transformation of raw data into meaningful information for business purposes, which sounds a lot like data science. Others say it goes beyond data science, integrating new technologies into the analysis process.
In his own definition, Byrd breaks down BI for corporate legal departments into two key categories: the business of law and the practice of law. The former is the process by which these departments can gain a better return on investment, often through targeted hiring of outside counsel or strategic placement of people and time within the department itself. The latter is how the data can influence how a lawyer practices, such as data that explains a judge's dismissal tendencies or the likelihood of defendant success in different jurisdictions.
To explain BI in context, he provided a practical example. Suppose you're a growing West Coast technology company, and you're sued for patent infringement for the first time in Chicago. There is always the option of using a firm you're already comfortable with that has a Chicago office. The numbers, though, say it takes a long time to get to trial in Chicago, and a higher price-per-hour large firm may not be preferable. "Are they still going to use their go-to firm?" Byrd asks. "Probably. But they are going to look at the data, and if there's a hot-shot boutique in that district… maybe they can look at the list and call them up. That's business intelligence."
intel  business  metrics  data  analytics 
september 2016 by JordanFurlong
Confirming the Growing Use of Analytics Tools in Corporate Legal
More specifically, the report indicated that the top three uses for data analytics in e-discovery are culling (72.4 percent), early case assessment (72.4 percent), and relevancy review (71.1 percent). The report additionally reflected increasing reliance on analytics for review prioritization (64.5 percent) and fact finding (55.3 percent). Such a trend is noteworthy since it suggests that legal professionals are using analytics tools in a more intelligent and strategic fashion, such as identifying key documents in a particular matter rather than culling irrelevant materials.
data  analytics  clients 
august 2016 by JordanFurlong
Perspective: In Legal Sphere, Data Isn’t Big, It’s Narrow and Knowable | Big Law Business
Stage Three means mining the data that’s sleeping peacefully in our contracts to mitigate our biggest risks sooner and more intelligently.

It means negotiating smarter contracts going forward, because we know what our aggregate risks and surpluses are across the existing contractual population. It means knowing how contract provisions we’ve negotiated in the past have correlated to actual outcomes, like long-term margin defaults or renewals. It means stripping months out of the contracting cycle, resulting in greater revenue realization and faster revenue recognition.

It means smarter mergers, where we’ve identified upsell and cross-sell opportunities before the deal is consummated, or the price set. It means applying accurate risk scores to high volume contracts (the commercial equivalent of the consumer FICA score) to adjust acceptable risk levels according to the margin potential of each deal.

That’s the promise of Stage Three. It’s a Legal game changer.
contracts  data  analytics 
june 2016 by JordanFurlong
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