Strategies and insights from our white paper, “Turning Legal Into a Value Center” 

Controlling costs is an evergreen concern for corporate legal departments. One incredibly important aspect of cost-saving projects is change management. In fact, a December 2023 survey showed that after cost containment, implementing business process improvements was the second highest priority for legal departments, with 46.7% of legal departments ranking it among the top three challenges they’re facing. 

Priori and CLOC recently partnered on a white paper, “Turning Legal Into a Value Center,” which looks at different strategies that legal departments use to achieve cost savings. Unsurprisingly, change management was a key concept that underpinned many of the strategies discussed. 

Below you’ll find some tips for handling change management—a key component of executing successful projects that optimize legal spend. To learn more, download the full white paper. 

Packaging the Value Story – Change Management & Communication 

Whether you’re launching a new internal initiative, implementing new legal technology or having conversations about spend with your outside counsel, clearly communicating your goals and expectations is necessary for success. Just about every task your legal department undertakes to drive business value and optimize legal spend contains elements of change management, and implementing change management well starts with communication.  

There wasn’t one legal operations professional who we talked to that didn’t emphasize the role of communication. Here is some advice for approaching conversations and getting buy-in from stakeholders for your next project. 

Start From the Top Down 

When you’re launching a new initiative, it is important to get the top-level stakeholders on board from the beginning. If you don’t have the support of the people at the top, it can be hard to get other stakeholders and the teams that will help you execute to come on board and follow through with the vision.  

Build Relationships 

Starting with buy-in from the top sounds great, but how do you get there? Often, successful project management (in the legal operations space and elsewhere) is a long game. You want to show the stakeholders in your company that you understand where they’re coming from and what motivates their decision-making. Communicate throughout the year so you’re not just talking when something has reached a boiling point. The more you can empathize with and show respect for the work they do, the more they will be willing to trust you when the time comes to make a change.  

Know Your Audience 

Getting to the point where stakeholders trust you means learning about their roles: What their priorities are, the type of work they do, the pain points they experience related to legal, etc. Interview your business partners and get their perspective. When combined with metrics like projected cost or time savings, anecdotes about how a given project will help team members do their job better bring the narrative you’re trying to sell together. 

Make the Business Case 

Come into discussions with an inventory of what the situation is now, where you hope to get to upon completion of the project and recommendations for how to get there. This likely includes current data and projections about the project will affect those metrics (e.g., How much time does a task take now? How and why will this initiative reduce that time spent?). Show how the solution you’re recommending brings you from the current state to that desired end state. 

Ultimately, getting buy-in for a project is about telling your value story. You want to bring your stakeholders along with you on this journey. The more you can get them involved and make them feel like they are a part of it, the more likely it is you’ll get approval and find success. Nobody should feel blindsided by the change you’re recommending, they should feel the opposite—that they had a say in how the project came together and are as much responsible for its success as you are. 

For more cost-savings best practices, strategies and insights, download the white paper, “Turning Legal Into a Value Center.” 

Strategies and insights from our white paper partnership with CLOC 

Legal technology is an increasingly important factor for corporate legal departments’ spending priorities. According to a recent report, 78% of legal departments say that “legal technology is a ‘must-have.’” 

We recently partnered with CLOC on a white paper, “Turning Legal Into a Value Center,” that shares best practices around cost-saving strategies from legal operations leaders. It was no surprise that one of the most important ways legal departments are reducing cost and optimizing their spend is through efficiencies created by technology. 

Below you’ll find an overview of five of the most common types of legal technology the legal ops teams we spoke to are using, and how they impact cost savings. To learn more, download the full white paper. 

Optimizing Spend With Legal Technology 

Rather than providing a comprehensive overview of types of legal technology (which could fill an entire white paper on its own, if not a book), in this section we’re highlighting five technologies that the legal operations professionals we spoke to found useful, particularly for optimizing legal spend and achieving cost savings.  

#1 Understanding Internal Requests – Intake Platforms 

Several of the legal operations professionals we talked to recommended intake platforms as a good starting point for legal operations initiatives. They can be thought of as a “legal front door” and help your team gather information about internal requests for legal services. You can determine which business partners are requesting work, who is requesting the most work, what that work looks like, who is doing the work and much more. This can be extremely helpful for making resourcing decisions. While off-the-shelf products exist for this function, it can also be built using project management tools that many companies already use for other business functions, or even common tools like spreadsheets.  

#2 External Spend Overview – E-billing Systems 

When it comes to legal spend, e-billing may be the most common type of legal technology. In addition to managing ongoing billing, it’s also a key source of historical data about the money you’re spending on outside counsel and other external resources: What types of matters your company is spending the most on, the vendors those matters are going to, trends in practice areas, timekeeper rates, hours spent on projects and much more. Looking at this data gives you a picture of your external legal spend and can help you identify places where you may be able to shift resources to save costs. 

#3 Tracking Tasks Efficiently – Matter Management 

Matter management tools are extremely powerful, but they also are most useful for larger companies that manage many different projects going to outside counsel or other alternative providers. Often, they are integrated with the e-billing systems discussed above. For legal departments whose outside spend is limited, it might make more sense to track matters using tools the company already has access to, like project management software or spreadsheets. However, for large legal departments, off-the-shelf matter management software can greatly enhance efficiency, storing key information about matters and giving the necessary attorneys, paralegals and other staff the ability to easily collaborate and keep track of statuses. 

#4 Doing Business Faster – Contract Lifecycle Management 

Contract lifecycle management (CLM) tools are very popular and for great reason. One of the most visible ways legal impacts other business units (and has a direct line to revenue) is by way of contracts. CLM systems track the life of a contract as it’s touched by people throughout the organization and, ideally, drastically reduce the amount of time it takes for legal to review and approve contracts. In some cases, through automation or features of particular CLMs, legal can be removed from the loop entirely, especially for low-complexity contracts. Contract management is also a space where artificial intelligence and generative AI are creating efficiencies—one company we spoke to said that leveraging AI for standard contracts like vendor agreements and Non-disclosure Agreements (NDAs) cut their review times down from as high as an hour to 5 to 10 minutes.  

#5 Self-Service Solutions – Knowledge Management 

For just about all of the legal operations professionals we talked to, knowledge management was a priority (one referred to it as the legal department “white whale” because of its huge potential and the difficulty of doing it well). Why it’s a priority is clear: When your business partners can self-serve information they would otherwise go to the legal department for, it’s a huge win. Not only does your department save that time but it also enables your business partner to get their work done faster, increasing efficiency at both ends. Organizations often use internal hub sites (e.g., wikis or FAQs) to track reference materials but more and more companies are experimenting with chatbots to surface the right information to the right people at the right time.  

For Sake of Comparison – RFPs & Decision-Making 

For many of the organizations we talked to, one of the most important aspects of evaluating legal technology is sending out requests for proposals (RFPs) to potential vendors. Usually, this comes at a stage where you’re close to making a decision and have narrowed your sights to a few options, although the process can still be helpful even if you’re just evaluating one solution and the question is whether to buy it or not. It’s likely larger companies will have an RFP process for technology procurement that you can leverage and tweak to meet your legal department’s needs. That process involves sharing your company’s current position, what you would like to achieve with the technology, the specific deliverables and timeline for the project, the budget (if possible) and other details that are relevant to the project. From there, you collect and compare the information you received and use that to inform your decision-making process.  

For more cost-savings best practices, strategies and insights, download the white paper, “Turning Legal Into a Value Center.”  

Insights from our recently-released white paper, “Turning Legal Into a Value Center” 

Providing more value for legal services is one of the top initiatives for most legal departments this year. According to a recent Thomson Reuters report, 78% of legal departments say that controlling costs is a high priority. Seeing this general sentiment in surveys and in our conversations with legal operations professionals, we partnered with CLOC to put together a resource that provides a window into the strategies legal teams are using to address this priority.  

The result is our white paper, “Turning Legal Into a Value Center,” which is based on interviews with 16 legal industry leaders and offers a jumping-off point for any legal department team looking for ideas and best practices around cost-saving strategies. In addition to giving a bird’s eye view of legal spend concerns, the paper discusses project prioritization, internal work allocation, the role technology plays, outside counsel management and more.  

Below you’ll find an excerpt, covering outside counsel management strategies. To learn more, download the full white paper here. 

Cost-Savings Strategies for Outside Counsel Management 

Many legal operations professionals and others throughout the legal industry have noted that there has been a mindset shift around the approach to outside counsel over the past decade or so. Corporate legal departments are looking more closely at their relationships with law firms and the value they provide.  

Alongside this increasing focus on value, more alternatives to traditional outside counsel have been created including legal staffing firms, Alternative Legal Service Providers (ALSPs), legal marketplaces and other “New Law” companies. This has put legal department leaders in the driver’s seat when it comes to optimizing legal spend through outside counsel decision-making. The strategies discussed below are important parts of the value conversations you should be having both internally and with your outside counsel partners. 

Right-Sourcing the Right Way 

The concept of right-sourcing is really where the rubber hits the road regarding this outside counsel mindset shift. Put simply, right-sourcing means sending legal work to the provider that offers the most value for that type of work. For most legal departments, this means first analyzing the type of work before deciding where to send it.  

Many factors can go into this decision, and it usually involves consideration of things like complexity, risk, scale and scope. Do you have a highly complex, bet-the-company litigation matter that you need handled? That should probably go to one of your trusted Big Law firms. But does it make sense to send less risky and less complex transactional work to that same firm and pay their premium rate? Probably not.  

Many of the legal operations professionals we talked to tier or score work to help determine the right provider. For example, one company used an “ABC” format where work that was scored as an “A” would go to the top level of providers (e.g., Big Law firms, senior in-house counsel), “B” work would go to a middle level (e.g., specialized small and boutique firms, solo practitioners and some ALSPs), “C” work would go to a lower level (e.g., ALSPs, LPO, paralegals and other paraprofessionals, etc.) and so on. This type of analysis can also be visualized similarly to the cost-benefit analysis discussed above. Below is a simplified example of what this process might look like. 

Cost savings is one of the biggest benefits of right-sourcing. Utilizing small, midsize and boutique law firms or ALSPs to do work that you used to send to large law firms can reduce your legal spend substantially. Multiple companies we talked to said that analyzing your legal work with right-sourcing in mind was the key to reducing external legal spend and getting more value from outside counsel. Some companies encourage the process by creating a specific target—saying that a certain percentage of work has to go to midsize firms or ALSPs, for example, and anything over that percentage requires approval.  

Another important aspect of right-sourcing is it provides legal departments with more access to diverse law firms and legal providers. It’s no secret that the largest law firms are generally lacking in diversity. One legal operations expert described this as an easy “win-win”: Small and midsize firms are more likely to be diverse and they are more cost-effective. Right-sourcing work can help you support these important company initiatives and optimize spend at the same time. 

Less Is More – Panel Consolidation  

A common but more involved method for optimizing outside counsel spend is building a preferred law firm panel program. The idea behind a panel program is that you consolidate the outside counsel you work with and choose a smaller number of firms to give panel membership to. You then send the majority of your legal work to these preferred firms and in return the firms give you better terms, whether that means alternative fee arrangements, locked rate increases or volume discounts. Additionally, it can strengthen your team’s relationship with the chosen firms and improve the quality of work because the firms become more familiar with your company and how it operates.  

One legal operations professional we talked to did a panel consolidation project and reduced the number of firms their company regularly worked with by almost 90%—from around 700 to about seven. Not only did this drive efficiency by making it easier for the legal team to manage outside counsel work (fewer firms to onboard, communicate with, review invoices for, etc., means less time spent on administrative work) but it also drove spending down through better negotiations with those firms. Another company we talked to found great success by asking panel firms to agree to locked rates for a determined time frame, which was incredibly helpful for budgeting as the company could depend on known rates for the projects those firms took on. 

Building a panel is a huge change management project that requires a lot of time and attention. And it’s not always the right solution for every company, particularly companies with smaller outside counsel needs. If it’s something your legal department is curious about exploring, here are a few tips that the legal operations professionals with panel experience shared. 

Quick Tips for Panel Success 

• Consolidate, but not too much. If you make your panel too small you could lose bargaining power and actually see your rates increase.  

• Review your panel on a regular schedule. Usually yearly, most companies running successful panel programs review the cost, performance, timeliness, and other aspects of their panel firms on a regular basis to decide to continue with current panel members and/or bring new firms on.  

• Utilize it consistently. The more you allow “step-outs” to your panel firm, the less useful the data you collect will be. For companies that use it consistently, panel data gives a great window into legal spend and aid budgeting and forecasting processes. 

• Consider a hybrid panel. For companies with large regional needs or lots of niche work, a panel might not make sense at first glance. But you still may be able to create a panel of firms for high-profile, “bet-the-company” cases and make a significant impact on those costly matters.  

For more cost-savings best practices, strategies and insights, download the white paper, “Turning Legal Into a Value Center.”  

With the proliferation of AI-based tools for legal at a seemingly all-time high, a pressing concern for most legal teams is — how can I validate the effectiveness of Legal AI tools while safeguarding the confidentiality and security of my company and its data? Or, put more simply, how do I pick the right solution(s) for my team and organization?

Having worked in legal tech for 13 years, I’ve had numerous conversations with lawyers and legal operations professionals about the various challenges they hope technology can solve, many of which haven’t changed for the last 10 to 15 years (such as locating contracts). But despite its great potential, using AI-based legal solutions requires adjusting our expectations or at least better understanding new trade-offs.

At Ravel, the company I co-founded out of Stanford Law School in 2012 before joining Knowable, we always thought the best AI was AI you didn’t know was there. We set out with the goal of helping lawyers solve the kind of problems that only software, cloud computing, and, yes, AI could help solve. We always believed the attorneys didn’t need to know how the software was made, just that they could rely on it, but therein lies the crux of the issue. How can you discern which tools are right for your organization and best suited for a specific task? And how do you manage potential new risks, whether it be intellectual property, copyright, or quality?

Historically, the answer to those two questions was pretty simple. We would test the product and evaluate the result. If the answers were good enough, we’d move forward with a plan to iterate and improve over time. But that was before 2023 (well, really 2022) and the mass market advent of Large Language Models (LLMs) like GPT, Bard, and Anthropic.

Today, we must ask different questions to get to the right answer. During the inaugural Harvard Law AI Summit, a leading specialist in artificial intelligence (under the condition of anonymity as per the Summit’s rules of attendance) pointed out that while we don’t understand how LLMs work, humans have often used technology we don’t understand, such as cooking. We cooked food and made all kinds of dishes for over 10,000 years before understanding the underlying science. Trial and error were all we had. But as legal experts, is trial and error acceptable? Can we really afford that level of risk?

7 Critical Questions

In reality, we don’t have a choice. AI is not coming; it’s already here. Here are seven questions to ask your potential Legal AI provider to help you determine if a particular AI solution is suitable for your organizational needs and, more importantly, to identify which provider you are willing to entrust with a certain level of risk.

1. Is your IP protected?

This question seems fundamental, but the consequences are real. Remember the news story about Samsung engineers who fed proprietary source code into ChatGPT that OpenAI then used as training data to answer other users’ questions? Each time you ask a model to do something for you, it’s curating information and delivering an output from numerous sources. Despite having millions or trillions or more data points, open and public models are learning from every input and, in some cases, can serve up proprietary information given the right prompts.

There are ongoing debates about the legal risk associated with AI and its potential infringement, but the bottom line is your IP needs to be protected. Ask your provider if you have the right to use the AI’s output or if it belongs to someone else from whom you must seek permission. Also, ask whether the provider owns the model and has copyright in the answers. Most companies today state that you have the right to use the answers, but you should confirm before selecting a provider. Lastly, ask if you are indemnified in the event of copyright infringement. In a world of trial and error, you have a right to know.

2. What models are being used? And are they open or restricted?

This is a variation of question one, but it’s an essential component of your evaluation. The point highlights three types of LLM models that you should understand. Models like GPT are open,  public, and continuously learning from everything it ingests, updating its knowledge and making it available to anyone using the tool. Forked models are customized based on an open-source model from a fixed point in time, only answering questions based on its existing knowledge set. Proprietary models are developed from scratch in-house and not shared externally (or can be built off a forked model). This is the ultimate build vs. buy question, with the latter requiring a heavier lift to keep the training data up to date. (see  question #5)

You should also ask if the models being used are open or restricted. Often referred to as “walling,” models can be deployed via commercial agreements with AWS or MS Azure (and hence are “walled”), but they can also be deployed without commercial protections. Pending your risk tolerance, you may be more or less comfortable with a walled or open solution. 

Importantly, providers should be comfortable sharing some details about their infrastructure. While they may not reveal the specifics (as that is undoubtedly part of the company’s IP), it is not controversial to tell you if they are multi-model or single-model, nor is sharing specific names, like OpenAI, Anthropic, Bard, or BERT. Armed with this knowledge, you can engage in proper research and better understand the pros and cons of each LLM when comparing vendors and deciding whether to build one yourself.

3. What if PII is placed into the model?

What happens if you input someone’s address or upload a document that contains personally identifiable information (PII)? Revisit questions one and two, as this could create issues with GDPR or CCPA for you and the provider, increasing your company’s risk and liability. You may need to revisit or create policies and ensure enforcement, much as you do today around the use of PII.

4. How do you prevent “model drift?”

Over time, the results of AI models “drift,” which means the results or the outputs from a model or solution change in one of two ways.

• Data Drift: When the input data changes significantly, it is considered “data drift.” For example, suppose the model is trained on older contracts, and you implement a new contracting template. Consequently, the model may be unable to predict results as well on the new documents.
• Concept Drift: There is also a possibility of “concept drift.” For example, if the meaning of a term changes (like a contracting term), the dataset becomes more expansive and, thus, less effective as we use it over time.

In both cases, the model struggles to adapt to new, unexpected changes, and hence the results change. Additionally, the company you are working with may switch to an entirely different model or a different version of a model. For better or worse, the results are likely going to be different. How will you know when that happens and are the differences acceptable?

5. Do you do the training and evaluation yourself?

Especially in a world of LLMs, training is increasingly being handed over to the model creators. In these situations, the model is no longer getting better based on specific “gold standard” data but on what it has been trained on writ large. Depending on your use case, this may be sufficient, but you may want an experienced provider to train your model to increase precision and accuracy.

With training comes evaluation — a costly and challenging endeavor. It is imperative to know how models are performing if you are going to use their outputs. Ask your provider who will be responsible for the evaluation. If the answer is you, analyze the time and resources needed to put teams in place that specialize in model evaluation and ask yourself whether you are ready to assume that cost.

6. What data do you get back?

If you use a model to extract data such as redlines, drafts, or answers to contract questions, understand what the AI tool will ultimately deliver. Is it just a blurb of text or a full string and conversation? Ask your vendor to provide real-world examples of what you will receive and in what form based on your contract data set as part of your proof of value (POV).

7. Do you guarantee accuracy?

Lastly, and likely often most importantly for attorneys and their legal teams, is how trustworthy is the output? Accuracy is a critical success metric. Many companies hedge by saying, “The model learns the more you use it,” or “As you correct the output, the model gets better.” This is highly unlikely for the reasons mentioned in questions four and five since your input data will change over time, which may improve the model and sometimes confuse it. Furthermore, there are diminishing returns to training – at a certain point, the benefits become incremental and likely not noticeable. In the end, the outcomes of AI-only tools will be unpredictable, which will erode trust. This is why it is still critical to have humans-in-the-loop (HITL) to reduce risk and ensure accuracy.

What’s Next?

Amidst all this uncertainty, what can you do? The good news is traditional approaches to minimizing risk hold up.

• Step 1: Ask all the questions above. Don’t avoid them.
• Step 2: Ensure your IP is protected contractually.
• Step 3: Ask the company to be open about the models they use and their overall approach to training and evaluation.
• Step 4: Ask about accuracy and how it will be continuously monitored and validated. (Hint: HITL should be a core part of this process.)

I am quite frankly very bullish about AI for legal. Thanks to technology, I have seen attorneys accomplish previously impossible tasks and have great outcomes. I’ve also seen lots of companies overpromise and under-deliver. My former Ravel co-founder Daniel Lewis recently made the point that lawyers don’t all need to become prompt engineers to get the benefits of AI, but we do need to ask questions and be smart about who we work with.

Have questions about how Knowable thinks about ML/AI in post-signature contract management? Visit knowable.com.

By Nik Reed, SVP, Product and Research & Development, Knowable

The advantages of digitization for law firms

The benefit of digital over analog isn’t always a given. Your legal team may find they generate their best ideas working on paper — similar to how some photographers still prefer film.

Nevertheless, the overall advantages of switching to digital systems in the legal industry are significant and undeniable. They include:

• Increased productivity — By streamlining processes using digital tools, legal professionals can complete tasks more efficiently and with fewer resources. Increased efficiency allows lawyers to focus on higher-value tasks, boosting their overall productivity. Plus, the cost savings associated with reduced overhead expenses can be passed on to clients or reinvested into the firm to fuel further growth and innovation.
• Enhanced client service — Your clients are digitizing too — often faster than the average law firm — and have come to expect the cost savings and convenience technology creates. Through digitization, you can provide clients easy access to documents, case updates and billing information. And by collecting and analyzing data about your clients, you can offer customized solutions that meet their unique needs and preferences.
• Competitive advantage — Firms that harness the power of technology can offer innovative services, respond more quickly to market changes and differentiate themselves from competitors who are slow to adopt digital solutions. By staying at the forefront of legal tech, your firm will be better positioned to attract and retain clients who value speed, convenience and innovation.
• Improved work-life balance — Legal professionals can use tools like video conferencing and cloud-based document storage to stay connected with colleagues and clients while working remotely. This offers opportunities to improve work-life balance and as a result, contribute to increased job satisfaction, stress reduction and overall improved well-being for your employees.

6 tips for hiring tech-savvy legal professionals

To find talent with expertise in areas like data analytics, cybersecurity and artificial intelligence, follow these six tips:

1. Broaden your search. When hiring, expand your talent pool to include candidates with experience in technology, data science or business. These professionals can bring fresh perspectives and valuable skills to your firm.
2. Update your job descriptions. Clearly outline the technical competencies required for each role, including any software, platforms and tools that candidates should be familiar with. Emphasizing technical skills can help set realistic expectations for potential hires and encourage applicants who are passionate about integrating technology into their legal practice.
3. Offer targeted perks and benefits. To attract and retain tech-savvy talent, provide benefits that cater to their unique needs, such as flexible working arrangements, professional development opportunities and access to cutting-edge technology.
4. Invest in upskilling and training initiatives. Some of the talent you need may already be on the payroll. Encourage current staff to develop their technical skills through training programs, workshops and certifications like Certified E-Discovery Specialist (CEDS) and LTC4 Core Competency. Partner with law schools and other educational institutions to develop specialized courses and programs for your employees tailored to the evolving needs of the legal industry. This focus on upskilling not only helps your firm stay current with technological advancements but also promotes employee satisfaction and loyalty.
5. Implement reverse mentorship programs. Pair tech-savvy junior team members with experienced legal professionals who may be less familiar with digital tools and trends. This encourages knowledge exchange, fosters a collaborative environment and helps bridge the generational gap in technology adoption.
6. Partner with a staffing firm. Collaborating with a talent solutions specialist like Robert Half gives you access to a diverse pool of professionals — contract/temporary or permanent — with the necessary blend of legal and technical experience.

Bottom line: The digitization of the legal profession is a permanent shift you and your firm must embrace to stay competitive and meet the evolving needs of your clients. By recognizing the need for change and investing in technology, talent and training, you’ll be ready for long-term success in an increasingly digitized world.

This article originally appeared on Robert Half’s blog.

Jamy Sullivan is executive director of the legal practice at Robert Half, a premier provider of talent and consulting solutions for a wide range of initiatives in the legal field, including compliance, contract management, data privacy, litigation support and more. Visit RobertHalf.com.

Modern legal entity management has finally transcended its traditional confines in the general counsel’s office, and not a moment too soon. In fact, we see this happening more frequently, with legal departments increasingly involving compliance (48%), governance (38%), finance (35%) and tax (25%) business units in entity management activities.

By no longer limiting itself to a small team of legal colleagues, the corporate record can finally be used for strategic decision-making. However, even with more business units participating in entity management, is there room to make this an even more powerful partnership? The answer lies with your colleagues in Finance & Tax.

Finance: Follow the money

Formally engaging the finance department can help more senior executives beyond the general counsel’s office understand entity management as an important business priority. Finance departments are often profit centers (as opposed to the legal department, which is often viewed as a cost center).

And for finance teams, entity data is increasingly important to their strategic planning processes. This year, the volatile markets and increased financing costs have pushed companies and funds to act more cautiously than in years past, with a higher priority on entity restructuring (and spinoffs), smaller M&A deals, and looking at past opportunities with fresh eyes. However, these short-term activities are only setting up for a bigger potential play in 2023; with high rates of undeployed capital — or dry powder — in the capital markets, 80% of Deloitte’s survey respondents believed that may be an opportunity to catch the wave and invest their cash as targets rise in value.

These opportunities, both short and long term, require a comprehensive understanding of entity data and a strong compliance track record to be competitive. Yet, 49% of companies still report using Excel to manage their entity data and a quarter reported at least one entity out of good standing in the last 24 months.

It is in the finance department’s best interest to find and invest in solutions that ensure the meticulous execution of entity management processes and empowers them to stay competitive for whatever opportunity arises.

Tax: Fighting complexity with collaboration

The Head of Tax seeks out opportunities that minimize costs and drive efficiency. Yet global complexity has hampered their agility in a trend that only seems to increase: in 2023, 45% of TMF Group’s accounting and tax experts anticipated compliance to grow over the next five years, which demonstrates the operational strain these business units are increasingly facing.

However, there’s acute awareness that with access to the right data at the right time, these heads of tax can ward off complexity. Focusing on global tax provisioning and integrating tax data company-wide are the top two priority for tax professionals in 2023, of which entity data is interlinked. By using technology to create a holistic view of the organization’s tax burden, this alignment with the legal team breeds efficiency, reduces redundancies and maximizes the potential for growth.

Entity technology: The path to partnership

In a world where collaboration reigns supreme, technology’s importance in connecting disparate business units cannot be underestimated. By creating a single source of truth for your entity data stored in a self-service database, tax, finance and legal teams can finally strategize from a collective playbook. This playbook can unlock the potential for growth, risk mitigation, and efficient decision-making. The era of entity management as a cross-functional responsibility has arrived, transforming it from an individual effort into the team sport it was always meant to be.

Diligent

Diligent Entities is the world’s leading purpose-driven entity management technology solution.  With solutions across governance, risk, compliance, audit and ESG, Diligent empowers more than 1 million users and 700,000 board members and leaders to make better decisions, faster. No matter the challenge.

Now that you know the value of partnering with tax and finance teams, take a closer look at how entity management technology can help you solidify that partnership and practice more efficient entity management.

If you ask your legal team what one of their biggest challenges is, the phrase “contract management” will undoubtedly come up. Improving the contract management process, increasing efficiency and finding the right legal tech stack is a top priority for legal operation teams year after year. Yet, many organizations still struggle with years of disorganized contracts and outdated processes. In many cases, contracts live in multiple locations and it’s anyone’s guess as to which one is the most recent version.

As a legal ops professional, “contract chaos” may not directly impact your day-to-day, but it’s a huge barrier to your legal team’s productivity. It costs the company money, whether from spending time inefficiently or paying for unnecessary outsourced legal hours. And it creates risks: the risk of no centralized visibility to contract terms and requests, the risk of missed opportunities to accelerate deals or remove unfavorable terms at renewal – just to name a few.

Even if everyone is resigned to using the current system, regardless of these costs and risks, legal operations should never be satisfied to let bad processes go unquestioned.

Generative AI can be the “assistant” your legal team needs

Another blog about generative AI? Before you tune out, we’re not here to tell you that AI is going to replace your legal team.

The truth is, generative AI has huge potential to transform the way legal teams work, but not because it’ll do real, thoughtful, legal work for them. Instead, generative AI will be the assistant your lawyers always wished they had. A tool that can effortlessly read and summarize large document sets in seconds, or instantly pinpoint parts of a contract that aren’t in line with your company’s playbook. Amplifying each legal team’s capabilities by removing admin work is where generative AI really shines.

While we can’t cover everything in one short article, we’ll touch on three of the ways incorporating generative AI into your contract management process can solve many of the traditional CLM shortfalls.

The Challenges of Traditional CLM

Even with a CLM in place, managing contracts can still be a complex and time-consuming endeavor. Traditional CLMs, even when they incorporate some degree of AI, often suffer from these common limitations:

• Without a central (and clean) repository, the system is trying to pull contract data from fragmented sources, or missing some sources entirely.
• The system isn’t able to effectively analyze contract data in real-time, as each new contract is added.
• The system’s functionality is based on rules, which even with the help of AI, fails to capture the full meaning that lives within contracts.
• Rigid templates and workflows can’t possibly work for the large variety of contracts most organizations deal with.
• The system doesn’t have the ability to understand relationships and hierarchies between different contracts within the same document family, nor does it know how to organize these document families on its own.
• The system focuses on individual documents and not the entire library of contracts or the relationship between different documents.

As you might guess, traditional CLMs with these limitations might be a step in the right direction but they’re hardly a full solution to your legal team’s needs. Moreover, any tasks performed by, or information gleaned from, this type of system still needs a thorough review by a highly trained (and highly paid) legal professional. In some cases, investing in a traditional CLM can create more work than it relieves, which doesn’t delight your legal team or anyone else around the company who feels the ripple effect of difficult contract management.

Generative AI is changing the game

Enter generative AI. And forget, for a moment, the publicly available large language models (LLMs) like Google’s Bard or Microsoft’s Bing, which are impressive but not platforms you should trust with the entirety of your company’s contract data.

Instead, we’re talking about generative AI that exists within your CLM platform and only draws from the contracts and documents you provide it. In this way, the AI lives inside a closed environment, known in technical terms as a sandbox.

How is generative AI different?   

Generative AI has the potential to provide unprecedented levels of accuracy and speed for anyone looking to unlock the data within hundreds or thousands of documents. With the right data set and prompts, generative AI can perform a wide variety of detailed contract analyzes that traditional approaches cannot.

Unlike traditional methods, generative AI takes a more flexible approach that centers around learning and simulating human-like language capabilities. This means the models don’t need strict templates and standardized workflows, but rather acquire language skills in an unstructured manner, similar to humans. This revolutionary ability allows legal teams to automate more aspects of their document review process than ever before, all without having to manually create or update templates.

Generative AI can also provide invaluable insights into the risk factors that might otherwise be hidden deep within contracts. It does this by quickly summarizing documents, identifying discrepancies, and analyzing risks from a variety of angles.

By leveraging this technology for your legal team’s needs you can reduce costs while improving accuracy and efficiency across multiple areas of your business. And here’s how!

3 ways generative AI empowers legal teams

All of this sounds great, but you want to know how generative AI will make a concrete difference in your legal team, sales team, procurement team, or others’ processes. Here are just three of the ways generative AI + CLM, when done correctly, can reduce the burden on your legal team and empower them to serve the entire business better.

1. Quickly summarize contracts 

Generative AI can be used to quickly review large numbers of documents and pull out key terms, themes, changes over time, etc. This dramatically reduces the time a highly-trained human needs to spend doing the same. With the right prompt, “Summarize the changes across the master and all amendments,” for example, and the right data set, generative AI can provide an accurate answer that would have taken a person hours of reading to obtain.

2. Instantly analyze risk 

When provided with your compliance and playbook requirements (in plain English, no less!) generative AI can identify terms and conditions in your contracts that present risk or are entirely noncompliant. Having these risks pinpointed removes the most time-consuming step and allows your legal team to address the risks in order of priority.

3. Assist in contract authoring 

Sure, there are plenty of cases when you need an attorney to draft a custom portion of a contract. But there are many more instances when standard language will do the job, as long as it’s compliant with your best practices, industry standards, and your contract playbook. Generative AI can be used to speed up contract drafting by suggesting language based on past agreements and current business objectives. It can also detect discrepancies between existing contracts and your standards, and alert attorneys of potential risks that arise based on contract language.

Limitations of generative AI for legal teams

No discussion of generative AI for legal teams would be complete without touching on the limitations of this groundbreaking technology.

While it can provide a powerful tool for quickly reviewing and summarizing documents, identifying discrepancies, and analyzing risks, it’s also subject to the same biases as humans, particularly when trained on biased or incorrect information. Additionally, generative AI can suffer from “hallucinations” where it produces seemingly factual information that simply isn’t.

Most of the major pitfalls of using generative AI in the legal context can be mitigated by high quality, clean data on the input side and skilled prompt engineering, along with an expert human’s review, on the output side.

A new world of AI-powered contract management

These three capabilities are just scratching the surface of how generative AI can aid legal teams (and, as a result, the rest of the company) work faster, smarter, safer, and for less cost. For a deeper dive into the game-changing ways AI can power a new way of managing contracts, check out The Ultimate GenAI Playbook for Contract Management by Pramata.

Legal transformation is no longer a goal or a looming trend – it is a commercial imperative. Legal departments must embrace change, formulate a plan, and action it, fast, in order to control their future.

In May 2023, the global legal community gathered in Las Vegas for CLOC’s annual meeting. Unlike its physical location, CLOC is a fertile place where ideas are developed, strategies shared, and potential solutions are unpacked. Industry leaders collaborate. Curiosity is rife, plans are ignited.

But when the lights go down and we return to the office, what can be done to effect real legal transformation? Some ideas generated at CLOC have been consolidated here, along with insights and market trends. Here are four key pillars for you to embrace and help create change.

Generative AI

Generative AI (GenAI) is expected to bring real transformation to the legal industry. You must face it head on, experiment with it, use it and adapt to its current form, while at the same time preparing for the iterations and exponential improvements that will likely follow.

As most assess the impact of GenAI, there is some hesitancy in the market for buying legal technology – a ‘wait and see’ approach.  A better strategy may be to focus on fixing internal processes and getting documents and organizational knowledge in order now, enhancing current processes and know-how while GenAI continues to improve and any pitfalls are addressed. New skills are vital; prompt engineering must be mastered. For GCs, questions surrounding privacy, security, ethics, and IP concerns should be top of mind.

Techstack: The market

The market is still growing, although is bordering on being overrun with CLM solutions. Any current digital solution will need to adapt to GenAI over time to survive. Assessing legal tech has become more challenging of late, and vendors can be vague on GenAI capability for only so long.

Legal departments should focus on leveraging their existing techstacks. Through a process of strategy and road-mapping, they should determine if existing and planned legal tech will become stranded by the recent developments in GenAI.

Techstack: People and process

Legal departments need clear guidance to decide between expert systems and GenAI. Outside counsel management tools still need better data and insights on spend (an easy win), while the savings from reducing this spend can be used to fund other investments. On pricing, as outside counsel begin to use GenAI in client delivery, the billable hours will become redundant and pricing models may shift to fixed fee or effective fee arrangements. System integration and UX should be front of mind for legal departments, together with a new form of change management that reflects the seismic impacts of GenAI.

Enterprise technology

Enterprise technology is rapidly merging with legal tech, transforming the financial, security, and integration discussions within organizations.

For legal departments which are open to repurposing enterprise tech, the immediate focus is how to better utilize what you already have. Begin with a strategy and a desired end state. Consider whether you have internal development teams to assist with pilot programs. If not, find out where you can bring in outside support.  Be realistic about the pros and cons of onboarding as opposed to upfront investment in design and build.

Where to begin?

Most legal departments are in the early stages of transformation and the use of legal tech. This results in transformation immaturity and a lack of insights and data, which are crucial for optimal decision-making. There are key questions to address: where should a legal department begin on the journey? How can a legal team imagine what good looks like, and how can it get there? The immediate focus for your legal department should be in seeking to understand where you are now, to facilitate mapping for the future.

Data

Data and metrics underpin legal transformation and are some of the keys to unlocking transformation. Data allows teams to make data-driven decisions and to create maturity frameworks which help teams assess where they are on the transformation journey. Data is critical to demonstrate the value of legal, workload, spend, and ROI on initiatives, and for building the business case for investment.

However, most legal departments struggle with incomplete or unreliable data, and there is discernible hesitancy in this area with teams overburdened by overreporting obligations or the collection of data that isn’t eventually used.

Simple data strategies can be created through identifying outcomes and strategic goals, and then mapping to the data required. There are possible quick wins, through leveraging existing tools and datasets and pre-configuring new tools to help capture the data wanted. Legal departments should become focused on developing a plan to gather data now, and to consider what data and metrics to capture later.

KPMG Law can help you with your transformation. KPMG Law professionals can walk with you through the key challenges, wherever you are currently placed on the maturity pathway. There is so much more to transformation than ideas and conversations. They can help you get there, together.

Legal services may not be offered to SEC registrant audit clients or where otherwise prohibited by law

Why centering your contracting transformation on technology can lead to its failure (and how to stop this)

Nearly 70% of Chief Legal Officers (CLOs) planning to invest in technology over the next 24 months will invest in new or updated contract management tech, according to the 2023 ACC Chief Legal Officers Survey.

Still, Gartner predicts that by 2025, corporate legal departments will capture only 30% of the potential benefit of their contract life cycle management (CLM) investments.

Better contract management is clearly a priority for in-house legal teams – and one that they’re willing to invest in, but those investments rarely live up to their full potential. Why?

For most organizations, the fundamental issue comes down to an overly simplistic view of the contracting ecosystem.

Common view of the contracting ecosystem

In many organizations, “contracting transformation” and “CLM tech” aren’t just mutually inclusive, they’re virtually synonymous.

It’s easy to see why: CLM software promises tremendous improvements – if successfully implemented. So, for many teams, the contract ecosystem equals CLM tech. With stories of failed CLM tech implementations so common, many have adjusted their view of contracting to include a thin layer of process (but only those decisions immediately surrounding tech, like workflows, templates and playbooks).

Legal departments endeavoring to transform contracting are generally guided by this viewpoint, tempted by the promises of AI silver bullets, and it severely limits the (necessary) scope of their project.

A broader view of the contracting ecosystem

Because the common understanding of contracting is too narrow, “contracting transformation” often falls short of anything remotely transformative.

A broader view of the contracting ecosystem must consider the approach to work, contract artifacts, contract data, people, and culture in addition to tech and a more comprehensive understanding of process.

These inputs help inform a target operating model – a vision of contracting built on a clear understanding of demand and supply capacity, guided by the objectives of stakeholders across the organization.

Why consider all contracting inputs during contracting transformation projects?

In instances where bad contracting processes lead to consequences, the tech is rarely the central issue. Failed CLM tech implementations are generally derailed by deep-rooted, systemic issues, such as departmental silos or bad contract data (no surprise given that the average organization holds commercial data in 24 different systems).

The cost of poor contract management

Poor contract management costs companies 9% of their bottom line, so it’s little wonder that so many teams are eager to improve. Tech solutions have sold many in-house legal teams on the promise of “plug and play” improvements, but reports on CLM suggest that transformation generally takes at least 12 months – and often much longer. alarmingly high rates of CLM tech implementation failure (and the fact that 30% of legal departments who currently have contract management software in place acknowledge that it is underutilized) tell us that CLM software isn’t a silver bullet.

Technology is a powerful enabler, but only if it’s implemented thoughtfully as part of a larger strategy – it can’t solve operational issues. When organizations approach contract transformation from too narrow a viewpoint, they don’t realize that they should be considering broader issues at all. The larger, critical context goes unseen.

Better contract management helps mitigate risk, save money, and generate revenue faster. But achieving a contracting target operating model takes planning and legwork, which can only begin once a broader perspective is established.

Designing a contracting target operating model

Designing a target operating model starts with an assessment of the current state of contracting to understand capabilities and uncover opportunities for improvement.

Before this assessment can begin in earnest, it’s important to do some early legwork. Take the time to complete initial tasks like developing a project plan, identifying key stakeholders, and collecting project data. This is particularly important in industries where a large percentage of the workforce is involved in contracting – such as telecoms, where the average organization involves 26% of its workforce in contracting. Not only is it more difficult to identify key stakeholders in these instances, but it’s also easier to forget someone.

Assess the contracting current state

With a plan in place, teams can analyze data and stakeholder needs (through interviews or questionnaires), define and prioritize pain points, and conduct root cause analyses. Because so many organizations know something is causing issues within their contracting ecosystem, but few have clarity on exactly what that is, a root cause analysis is a critical step in connecting the dots.

At the end of the assessment, organizations are left with greater visibility into the current state of their contracting, including a view of process, operations, pain points and underlying causes.

Understanding the current state is vital. As the saying goes, you don’t know what you don’t know. Less than 11% of organizations view their existing contracting process as very effective, so it’s clear why many teams want (or need) to improve contract management. But without an understanding of the starting point, they can’t see where breakdowns are occurring or how much improvement is truly possible.

With the current state established, design of the target operating model through future state visioning can begin. This involves efforts such as conducting a future state workshop and identifying barriers to achieving the desired future state, then assessing and simplifying the path to the desired future state (including with respect to CLM tool functionality).

Establish a contracting capacity model

A key part of target operating model design is understanding and quantifying both demand and supply – the “why, how and what if?” behind both sides of the equation. This process entails some further examination of the current state. Ask questions like these around both the supply and demand sides to create a capacity model:

Demand side questions to identify contracting capacity:

• Is all current contracting necessary?
• What are the demand flows?
• What segments and types of contracts?
• What quantitative measure of complexity drives resource matching? How is this being done today?

Supply side questions to identify contracting capacity:

• Where, how and by whom is contracting done?
• What are the productivity metrics? Is this optimized?
• How will technology affect productivity?
• How do low-touch and no-touch contracting assumptions affect the capacity model?

A clear capacity model better illustrates future state potential, and the gap between that vision and the current state.

Envision the target state and map a path

A target operating model is driven by a number of inputs across the contracting ecosystem, each of which bring benefits that grow more pronounced when they build off each other.

This marks an opportunity to prioritize changes and identify quick wins. For example, if an organization realizes that all current contracting is not necessary, or that expensive resources are currently handling low-complexity contracts, they may find opportunities to affect change and realize savings quickly.

From here, organizations have enough information about their starting point, target operating model and potential roadblocks create a map that links the current state of contracting to the future state vision.

Depending on the current state and target operating model, this roadmap may include improvements, negotiation artifacts, process flows, technology enablement and change management.

Achieving the target operating model

Once developed, implementing the contracting target operating model requires three key workstreams: artifact development, contract management system (CMS) enablement and data migration.

Updating contract artifacts

During artifact development, teams can leverage the information gained throughout the assessment and planning process to update their master service agreement (MSA) or other primary agreement templates. With these foundational artifacts in place, teams can update ancillary documents and finally, develop a playbook.

As part of this workstream, teams can harmonize or consolidate remaining documents to work alongside the new MSA. They will also develop an index of provisions for their clause library, which supports the creation of playbooks inclusive of rationale for standard risk positions, acceptable fallbacks and use-cases, escalation protocol and more.

Selecting the right CLM technology

Part of CMS enablement may involve selecting CLM technology. It’s important to leverage a complete understanding of user and system requirements to select a solution with features that align to stakeholder goals.

But of course, even an ideally suited CLM tech solution is only one piece of the puzzle. A data hygiene plan, which focuses on ensuring the data going into the new system is correct (and correctly formatted), and a system to ensure more seamless, widespread adoption help ensure that the tech does its job as an enabler of process.

Migrating (clean) data

Given that bad contract data is one of the main roadblocks that ruins CLM tech implementations, a carefully considered contract and data migration plan is critical once technology has been selected. As part of the contract and data migration process, teams must create a data hierarchy and metadata validation report to better understand the value of their contract data (and to ensure that it is complete), followed by a migration plan (outlining details like who will do it and when it will be done).

By completing efforts like metadata cleanup and contract clause analysis to ensure that contract data is being leveraged properly and consistently, organizations achieve a clean, complete, easily searchable, de-duplicated and properly tagged document corpus in their selected CLM technology platform.

These steps support the journey from current state to target operating model. But once achieved, the TOM still has to be maintained – much like any optimized state of being, it requires upkeep.

The value of holistic contracting transformation

If the risks of too narrow an approach to contract transformation are wasted investments, organizational incongruity and ongoing revenue leakage, then the benefits of a broader view are just the opposite.

What’s more, when a contracting target state is achieved, work is aligned with the resource(s) best suited to handle it.

Contracting transformation case studies

The assertion that a holistic approach to contract transformation drives results isn’t conjecture – it’s based on years of experience.

For example, a multinational healthcare company engaged Factor to support procurement contracting transformation. At the time, the team handled 4,500 contract requests per year, but the process lacked oversight and standardization.

By designing – and continuously optimizing – a streamlined contracting process, Factor now supports 6,000 contract requests per year for this company while achieving a 25% reduction in cycle time.

In another instance, a Top 3 Management Consulting firm engaged Factor to assess current contracting processes, desired future state and complete a root cause analysis for the implementation of contract lifecycle management technology. As part of this process, Factor completed a large-scale document review across a variety of document types, including MSAs, SOWs, NDAs and more. We uncovered and provided qualitative data on issues that must be resolved before CLM tech can be implemented, avoiding a failed implementation.

In still another example, an educational publishing company was looking for cost savings, associated process improvements and operationalization. Factor introduced self-service contracting for lower complexity contracts – with the right tooling and training, they are now executed by business managers, contract owners or purchasers. This speeds up time to contract for business stakeholders and increases capacity for higher complexity, strategic contracts.

Additionally, we have helped the legal team refine templates, create playbooks and train their team members to enhance their contracting capabilities. As a result, the organization has seen 35% shorter cycle times across all procurement categories.

There’s no denying that technology is a critical part of modern contracting, but organizations that zero in on CLM and gloss over the bigger picture sow early seeds of failure. If a contract transformation project is a key objective for you, start by shifting your perspective – take a broader approach and realize faster results.

For more on how to drive the greatest impact from your contract transformation project, get in touch.