Category: Enterprise Legal Management

The COVID era has been exceedingly difficult and distressing for people worldwide. We needed to quickly adapt to a new way of living and working that has mostly deprived us of the comfort and familiarity we took for granted. Almost overnight, we had a “new normal” thrust upon us, and we had no choice but to embrace it to save lives.

Our way of life has never been such a rapid global shift. One of the most striking changes has been in how we work. Long commutes and distracting office work are now distant memories. We are now a remote-first workforce. Research has shown that we quite like our new working arrangement, with more than half of workers saying they want to continue working from home after the pandemic has eventually eased.

COVID-19 has not only led to people working from home, but it has also led to them working at different times and in different locations. With schools and support provisions shut, many people needed help to juggle work and home-schooling, caring for family members, volunteering, or other commitments. This led to an unavoidable rearranging of the working day, starting earlier or working in the evenings and weekends to keep up. But with this flexibility came an advantage to work to patterns that maximize individuals’ productivity, rather than being forced to work traditional business hours. When not in lockdown, workers are also choosing to work elsewhere. Between lockdowns, we have had colleagues working remotely from Cornwall, Poland, and Dubai. This all means much of the workforce is working on a different time, different place basis.

This new work-from-home revolution will have enormous impacts on many industries, but what does it mean for legal, and more specifically, how will technology play a role? We are not clairvoyant, but here are five legal tech trends we think we will see over the coming months and years because of the pandemic.

1) ASYNCHRONOUS WORKING

Lawyers must embrace asynchronous collaboration and communication tools to facilitate productive working across teams. While many lawyers have quickly adopted synchronous tools to support remote working in lockdown (e.g., video calls and instant messaging), many have not yet adopted asynchronous platforms for genuine project management. We will see more lawyers experimenting with team collaboration tools like Confluence or Notion and project management tools like Jira, Trello, Asana, and Monday. We may even see lawyers adopting Agile ceremonies like sprint planning and daily stand-ups.

This trend will also accelerate the creation of next-generation matter management tools, evolving from systems of record to full systems of engagement and collaboration. It will not just be productivity tools; there will also be a rise in the use of asynchronous learning platforms to ensure remote workers have access to learning and development at a time that best suits their working pattern.

2) KNOWLEDGE MANAGEMENT, SHARING AND ACCESS

Quick and timely access to legal know-how is critical to a remote team’s mutual knowledge and everyone’s performance. Remote workers can no longer walk across the office to ask a colleague for help and guidance. Calls and instant messaging do not necessarily help since people are already fighting digital distractions and may not be online when guidance is required. Asynchronous collaboration tools help by enabling know-how to be captured and shared – but we will see greater adoption of knowledge management solutions that allow team members to easily access knowledge whenever and wherever they are.

This is where we see AI tools developed to simplify knowledge discovery, connect, and structure know-how from different sources, keep knowledge up-to-date, and deliver it in context within workflows. Search functionality (not always seen as that exciting) will also become one of the most important tools in a remote worker’s arsenal. For this reason, we will also see the growth of solutions that help to centralize data to streamline and optimize the search experience. However, while the search returns results, it only sometimes delivers specific answers. We are also likely to see the maturing and broader adoption of chatbots and decision automation tools that help provide direct answers alongside the underlying sources.

3) LEGAL GIG ECONOMY

Flexible resourcing isn’t necessarily new in legal – LOD (Lawyers on Demand), Axiom, Peerpoint, and Vario have been doing it for some time. However, large numbers of employees “going remote” during the pandemic have given organizations a better idea of what a remote workforce can achieve.

Surveys have consistently shown employee productivity is high during the pandemic. Organizations are therefore accelerating their move towards a leaner operating model, bringing in temporary, freelance resources for specific legal tasks or projects as and when needed. This delivers a much more cost-efficient approach and enables businesses to tap into a dispersed talent pool. While demand will grow, so will supply as lawyers and paralegals look to capitalize on the flexibility of remote working to build portfolio careers or find a better work-life balance.

We will see significant growth in online flexible resourcing platforms that help connect organizations to an army of remote lawyers and paralegals looking to take advantage of the new normal. These platforms will either be “catch-all” – covering all legal resources – or niche, focusing on connecting businesses with legal experts in particular fields.

4) EMPLOYEE MONITORING TO SUPPORT LEGAL OPERATIONS

One benefit of office work is that managers can see what their teams are doing, how they are working, and whether team members are struggling. This is more difficult when managing remote teams. Therefore, organizations need to find ways to measure employees’ productivity and working patterns and highlight any potential issues.

However, it is about ensuring performance meets standards and providing employee well-being. “Technostress” has been highlighted as a significant problem for many people working remotely, and managers must look for the warning signs. They will also need to ensure they are still identifying training and support needs and calling out inappropriate behavior (bullying, discrimination, sexual harassment, etc.), which can increase in remote environments.

While many lawyers are familiar with recording and accounting for their time, not having to do this is one of the main reasons they enjoy working in-house over private practice! Nevertheless, we expect to see more law firms and corporate legal teams invest in digital, online employee-monitoring systems to help maintain productivity, ensure well-being, and increase transparency, essential metrics for effective legal operations. We may also see existing legal tech platforms add employee-monitoring tools as an option so that employers can track team behavior, e.g., tracking active/inactive status, monitoring page activity within the tool, etc. One way to avoid replicating law firm time recording or overly authoritarian monitoring is to track behavior for limited periods at intervals rather than an “always-on” approach.

We may also see a different kind of monitoring, one focused less on the output and more on outcomes. As teams shift to project management software, they will likely begin to track performance against OKRs and KPIs. This is a good way of ensuring performance without being too overbearing. Ultimately, we’ll see organizations and teams adopt a mixture of tools to help them maintain performance and deliver desired outcomes when working remotely.

5) FROM LEGAL PLATFORM TO ENTERPRISE INTEROPERABILITY

The most striking workplace effect of the pandemic is the accelerated and standardized adoption of digital productivity and collaboration tools. While many in-house legal teams and their firms were using video conferencing and instant messaging tools like Zoom, Google Meet, and Slack, many were still in the stone age regarding remote collaboration and communication tools. But that all changed when COVID-19 struck. Microsoft Teams saw its active users skyrocket 160% from 44 million in March 2020 to 115 million in November of the same year. Slack and Zoom have seen similar explosions in adoption. These tools have become the common language of remote working.

Legal technology vendors of all sizes will need to re-evaluate their strategy and move away from trying to drive users to their unique platforms and ecosystems. Instead, they will need to find ways to offer value in the systems where users prefer to work. This means a greater focus on plug-ins, integrations, and open APIs. It may even mean deconstructing existing products to embed functionality and extend tools such as Microsoft Teams.

HAS LEGAL TRANSFORMATION FINALLY ARRIVED?

The obvious theme that ties all the above is that technology will be essential to facilitate workers and their organizations transitioning to the new remote, distributed model (both inside and outside the legal domain). Technology is pushing at an open door for once – employees and employers cannot adopt digital productivity, collaboration, and communication tools quickly enough.

We are still in the infancy of the remote working tech revolution, so only time will tell whether the above predictions happen. Whatever happens, COVID-19 has changed the game for remote working. Remote-first will be the trend of the 2020s, and legal technology vendors should be making this a core component of their product and customer success strategies if they do not want to be left behind.

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John McCarthy, the computer scientist and “father of AI,” defined artificial intelligence as the science and engineering of making intelligent machines, especially intelligent computer programs.

When AI gets mentioned in the context of enterprise legal applications, it is usually referring to “machine learning.” In machine learning, systems learn from outcomes and decisions and improve with experience without being directly programmed to take certain actions or reach specific conclusions. These machines analyze data and discover patterns without significant human intervention, typically requiring only a training dataset.

Machine learning is often confused with rules-based automation, workflows based on pre-programmed “if this then that” algorithms. Legal buyers need to recognize the difference when looking to deploy AI within their departments. If the machine isn’t analyzing and learning from the data but is using pre-programmed, non-evolving rules to automate processes and outcomes, then it’s not AI.

Legal teams usually bring in machine learning to improve efficiency and productivity, as machines can perform tasks faster than humans, freeing legal counsel to do higher-value work. These applications include:

• Legal Research: reviewing, tagging, and ranking documents relevant to a matter or eDiscovery, highlighting questionable ones that need human review.
• ReviewAI: Identifying and flagging clauses for review, searching for missing clauses, and redlining in bulk and at speed.
• Invoice Review: Coding, approving, rejecting, or flagging line items and invoices (where rules-based automation isn’t an option.)
• Data Extraction: This can apply to invoices, contracts, documents, or any requirement where a mass of non-structured data must get organized and classified.
• Litigation analytics: Analyzing trial data to predict outcomes of litigation.

GETTING THE MOST FROM MACHINE LEARNING

The above use cases and benefits can transform the legal profession. However, legal departments currently implementing an AI-powered legal solution may be disappointed by the true scope of these tools, especially if they are at the start of their digitalization journey. Buyers do not see the promised benefits and are beginning to question the hype.

The very nature of machine learning is that it needs data to deduce the patterns that help it to evolve and learn. This data doesn’t just need to be abundant in volume; it needs to be complete, accurate, fair, and free of bias. Improved accuracy vs. a human is a benefit often touted, but this is only the case if the data from which the machine is learning is accurate in the first place. Poor or insufficient data will mean the machine does not have enough data to learn from and will not fully deliver the anticipated outcomes and benefits.

Perhaps even more concerning, however, is that the machine will draw partial or incorrect conclusions from a deficient dataset and take the wrong action or reach the erroneous conclusion – thereby creating hidden risk. Ironically, AI can negatively impact productivity if a human must go back over the work, identify issues, and correct them. More severe, though, is if these incorrect conclusions result in damaging actions for the business, even litigation. The reliability of your machine learning needs to be a factor when accounting for legal risk, and legal teams need to understand their role in feeding machine learning tools with quality data and training to avoid these issues; as the saying goes, “you get out what you put in.”

If this sounds paranoid, some examples from other industries will help show why it is critical to be careful when deploying AI. In 2018, Amazon created a tool to review engineering CVs and flag the top ones for an interview. The intention was to automate a time-consuming process. To train the machine, they used the dataset of current Amazon engineering employees plus applications from the last ten years, which happened to be predominantly men. The machine “learned” that ‘more male’ candidates were the best for the role. Amazon soon ditched the tool. Poor data was also at the heart of IBM Watson’s failure to accurately diagnose and treat cancer patients. The data used to train the machine was hypothetical rather than real patient data and frequently gave poor advice. These examples demonstrate not only the importance of complete data for machine learning but the fact that it is hard to predict unexpected consequences before they happen.

The above examples demonstrate the importance of quality and unbiased data, even when the aims are straightforward. AI is not for complex legal work; it speeds up routine tasks, supports better decision-making, and sometimes takes actions based on those decisions. In fact, some of the best examples of AI deployment are where machine learning tools have been combined with rules-based systems to first identify and categorize data and then take defined steps based on that categorization.

MACHINE LEARNING AND E-BILLING

Spend management is a legal-specific application using rules-based automation and machine learning together. For example, Onit’s European legal spend management solution BusyLamp uses the following AI functionality for clients and/or law firms that prefer not to use LEDES files:

• Data extraction: Pulling relevant information from PDF invoices, relieving smaller law firms from the burden of generating complex invoice files.
• Invoice Reviews: Some law firms struggle to code invoices in a way that clients can understand. BusyLamp AI takes unstructured invoice data and auto-classifies every task to enable automated invoice review.
• Legal Analytics: Unstructured invoice and matter data can be analyzed to enhance strategic decision-making.
• Block Billing: English time narratives can be analyzed so that block billing, a practice that usually contravenes billing guidelines, can be identified.

IS AI RIGHT FOR YOUR LEGAL DEPARTMENT?

Using point solutions such as the e-billing example above allows legal departments to take advantage of machine learning benefits for gains in specific areas of legal operations. But machine learning is by no means critical to make efficiency and productivity gains; most BusyLamp clients start small and aim big by tackling the issues of collating knowledge, structuring, and cleansing their data sets, and then building automated workflows.

When you gather requirements for your next legal technology project, start by mapping out your current processes, roadblocks, and desired outcomes before looking at any specific technology tool. As you evaluate software vendors, you will discover various solutions and workflows to your problem, which may or may not involve AI.

Remember, you should never use AI for AI’s sake – it is rarely the silver bullet. Almost every legal technology tool uses rules-based (non-AI) automation to relieve the legal team of admin and mundane, repetitive tasks; this will be a fantastic starting point for most teams setting out on their digital journey.

There is no doubt that machine learning is playing a huge role in improving the productivity of the legal profession and will allow in-house teams to take a more pivotal, strategic role in their businesses. But as a profession familiar with risk mitigation, a degree of caution must be applied when looking to reach the machine learning “promised land.” Accurate, high quantities of data alongside a careful selection of technology tools will significantly reduce your exposure to these risks and help you make a success of your team’s digital transformation.

Because AI is so dependent on the data it receives, the real transformational tipping point will not be in using these solutions within the legal function alone but in the enterprise-wide application of machine learning tools. Imagine the insights and outcomes achieved by analyzing documents and data across an entire organization, not just the legal function. This is only achievable with integrated legal and enterprise tech tools and robust, extensive, consistent data.

The “power of AI” and its ability to change the legal profession are beyond question. However, it is essential to proceed with caution and lay the groundwork to ensure that your legal department sees the benefit of machine learning rather than learning that it has been sucked in by the AI hype machine.

While e-billing has brought new transparency, control, and clarity to the billing process for in-house teams, one criticism of “conventional” e-billing is that the client is still not able to see the time and expenses being charged by their external law firms until the final invoice is sent (whether that is a draft or an engrossed version).

The goal is to be able to see the work carried out and the associated costs during the life of the matter itself and be able to query or even reject items early in the billing cycle. This is necessary for accurate cost control, forecasting, and avoiding invoice surprises. This WIP (Work in Progress) information has long been the subject of discussion between in-house legal teams and law firms. Until recently, law firms have only been able to provide rough estimates of accruals – usually at the end of each month – without any detail.

The key areas that an in-house legal team should be able to monitor to stay in control of its legal spend are:

• Cost overruns against budget/forecast.
• Counsel’s pre-billing time entries
• Large amounts of a single activity (e.g. research, drafting etc.).
• Wide date ranges between the work carried out and the time/fees submitted to the client.

WIP REPORTING IS BENEFICIAL FOR LAW FIRMS AND CORPORATE LEGAL TEAMS

Modern legal spend management solutions such as Onit’s BusyLamp includes WIP reporting as a key feature. It adds an extra dimension to the relationship between corporate legal teams and their external law firms. Some of the advantages of WIP reporting for both parties include the following:

• The law firm adds value for the client through enhanced billing data – over and above the provision of quality legal advice.
• The law firm has confidence that the work performed (so far) has been accepted by the client, and there will be no pushback when presenting the final invoice.
• The client has more certainty that the work is done correctly and in line with the billing guidelines. Detailed actual spend versus budget can be monitored early in the transaction and through all its phases

CHALLENGES OF WIP REPORTING FOR LAW FIRMS

Despite these benefits, implementing WIP reporting has its challenges. While some law firms have embraced the requests from their clients to provide timely and accurate WIP information, several law firms still need to fully meet the WIP reporting requirement.

A common concern is that firms view the “raw” WIP information as law firm data that the client should not see. Many large international firms have specialist revenue controllers working within the legal teams and closely with the deal partners. These firms also have well-established billing processes, a crucial part involving revenue staff and partners reviewing the WIP for each matter before finalizing the bill. They will decide which items of time to charge. More importantly, they will also check that time narratives are worded appropriately and are suitable for the client’s view.

In most firms, lawyers get advice regarding appropriate content for matter narratives. Still, several hundred associates can work on matters, and it is impossible to “police” what they enter before the bill data is “cleaned up.” The firms are reluctant to go through this cleaning-up process on the WIP data (even though it may be for a small number of bills) as partners see it as doubling up on work. Furthermore, no partner wants to be the first to allow a client to review WIP information in case it contains inappropriate content.

Another reason sometimes quoted by law firms for not wanting to provide WIP revolves around the timing and process issues associated with WIP information. What are the consequences if the client rejects some or all of this information? Some firms argue that if WIP information must be re-submitted, it may fall outside the acceptable time limits between the work done and when it gets billed. These firms often seek to establish reasonable windows and processes for WIP review and resubmission if any line entries are not approved.

A final objection is that producing WIP files in the LEDES e-bill format requires development work to be scheduled by the Finance/IT Systems team. Some firms have implemented manual workarounds for supporting WIP submissions, but this is not sustainable in the long term and for a growing number of invoices.

OVERCOMING WIP REPORTING CHALLENGES

E-billing vendors, in-house legal teams and law firms have together come up with a number of compromises to address these challenges, which include:

• Line-Item Narratives: If this is a concern, parties may agree to drop narratives from the WIP upload or substitute them with holding text saying that the narratives will be on the final bill. If approved, the clients would at least see costs and the associated activity or expenses based on the LEDES code (e.g., communicating, drafting and so on).
• Billing Cycles and Accruals: The client can achieve similar output if the billing cycle is reduced to a calendar month, allowing them to view that month’s work. Another option would be to improve the information supplied as accruals. This would not give all the time details to the in-house team but would meet some of the requirements.
• LEDES Output Requirement: To address the concerns of law firms about possible additional IT development work, Onit has developed two alternative methods used with BusyLamp:
  • Firms can output their WIP information as an Excel spreadsheet, which can then be uploaded into the e-billing application as required by the client. As all law firms have access to Excel as standard and have staff who can use it, the issue of needing expensive billing system changes gets minimized.
  • AI functionality in BusyLamp can extract non-LEDES-format, unstructured WIP data into meaningful and useful reports for the in-house legal team.

For a successful WIP reporting implementation, legal teams should engage with the law firm partners early in the process and discuss the requirement for WIP reporting. This should include why the in-house team requires WIP and what they aim to achieve from tracking it. It will help overcome some of the arguments against providing WIP and help all parties explore suitable alternatives that still give the in-house legal department what they need to succeed.

Request a demo of BusyLamp eBilling.Space today.