Many law firms are now exploring ways to become data-driven organizations. But beyond the buzzwords and the hype, what does that actually mean?
What sort of data do law firms usually handle?
Why do they want to adopt a data-driven strategy?
And, what exactly are they doing to become data-driven law firms?
The impact of becoming data-driven is incredibly high for a law firm. Data can help law firms implement better business strategies, achieve better cultural and organizational alignment, improve unit economics, and create an overall more delightful client experience.
But in order to put in place and implement better strategies in a law firm, we must move beyond hypotheticals. On a first principle level, data is what you need to be able to show people the facts and figures to support your opinion, your strategy, and of course the position of your market.
What data do law firms normally handle?
Law firms have a treasure trove of data in their day-to-day business. The data-point that first springs to mind is client data as well as their business information. But beyond that, data is omnipresent in a firm’s internal strategies, billing information, performance data, quality data, plans, intellectual properties, legal research, memos, legal updates, and human resources data.
The question, however, is: are law firms aware of these data points?
Even if they are, while law firms may possess the data, do they process the data properly to use it to benefit real business objectives?
Here are some questions worth asking related to various contexts of a law firm’s functioning:
Time-sheets: Law firms capture timesheets for each matter, but how accurate is the time captured? By that I mean, how are they capturing the timesheets? Do they have a dedicated system in place to capture them? Do they have a review and approval workflow? And is the invoicing/billing workflow linked to the time keeping system?
Performance analysis: When they have properly captured timesheets, do they use those entries as the basis to analyze the pain points of the lawyers (and potentially of the clients)? Do they analyze the utilization/billable utilization of the lawyers? And do they use these metrics to analyze how they can increase the efficiency of their lawyers, while also providing them with a work-life balance?
Process analysis: With the help of timesheets, law firms can easily identify loopholes in their current process where they are spending a lot of their resources (but not getting any benefit out of it). But do they realize that the data points needed to analyze this already exist within the law firm?
Knowledge management, intellectual property, and learning: Law firms generate a lot of intellectual property e.g. research and analysis, whitepapers, memos, articles, advisory notes, etc. But do they use them to channelize the knowledge enhancement within the organization? If they don’t, it means they are not aware of how to use it, and probably they don’t have a specific data repository for this. Even if they have one, most law firms don’t maintain it regularly.
Human Resource Data: Do they have a process or system in place to measure the quality and productivity of everyone within the organization? Do they have a system to do the skill mapping of everyone and do they also ensure that they get work per the skills? Also, do they ensure the skill enhancement for the individuals who want to add more skills or enhance the skills they have currently? This is possible only when they collect these data points and work on the needful things.
Financial analytics: Do they use the billing and invoicing data for their financial analytics? Though they capture all the time spent for a matter, how do they proceed with the billing and invoicing? Do they rationalize their actions here? Most law firms don’t analyze their Time & Expenses Incurred vs Invoiced (out of the time spent, how many hours did we bill the client?), but instead, they track by and large their realization rate (out of the invoices raised, how much did we get actually get paid?).
Why law firms should be data-driven
Law firms can use data for growth forecasting, calibrating the actual result with the forecasts to refine the process and predictions while using data analytics to make the best use of the resources. That means the best use of available skills of the people, efficient utilization of people’s bandwidth, making learning and development smoother, and making client interactions more transparent and genuine.
1. Data makes your plans more likely to succeed
Business plans and strategies should not be made out of thin air. Any sort of planning or strategy requires some data to support your decision. You can’t just come up with ideas, jump on fifth gear, and rush to implement them without analyzing the pros and cons of your decision.
And in order to do that analysis, data should first be harnessed, carefully analyzed, and then applied in your decision making.
For example, let’s say you are planning to deploy a due diligence platform within your organization from next year. How did you conclude that you need a DD platform from next year? Did you analyze the timesheets of your employees to see if they are spending a lot of time on due diligence? Did you get a chance to see the DD platforms across the globe and analyze them in line with your requirements? Did you do a return on investment (ROI) analysis with the proposal?
If you don’t have these data points with you, you will take decisions that will be almost guaranteed result in loss in terms of time & money. It might also be possible that all you required was just a virtual data room instead of an expensive DD tool. Errors in judgment such as this one can easily be avoided with the help of proper data analytics.
2. Data helps you understand the current state of your organization
Data will also make it easier for you to find out whether you are meeting your targets. It will also help you identify the factors hampering your firm’s culture, as well as identify the areas you can focus on and the areas that need improvement. Periodic analysis of the current state of the organization keeps you abreast of your plans and timelines, and helps you understand whether you are in fact moving towards your goals.
As mentioned in the earlier example, let’s say you found all possible good reasons to deploy the DD platform in your firm, how are you ensuring that you have maintained the ROI throughout the year? Also, how are you going to ensure that people in your firm are actually adopting the change and getting familiar with technology in their practice?
When you do these kinds of periodic analyses, you can understand more clearly whether the changes you are introducing are having the intended impact at all. You also make better commercial decisions. For example, say the ROI was good for two years, but the company suddenly increased the pricing which is now hurting the firm’s profitability. If we will not do this analysis, we will not be able to learn and focus on other tools available in the market that may have better value propositions.
3. Data can solve people management issues
Data can solve your people management issues, be it utilization mapping, skill mapping, learning and development, or appraisal and bonus-related issues.
Utilization mapping, for instance, plays an important role in people management. By that I mean, the firm expects its retainers or consultants to dedicate a minimum number of hours on a daily basis to the firm. The expected minimum number of hours is known as the capacity of that particular retainer or consultant. With the help of timesheets, we can easily find out where the staff is underutilized and where it is over-utilized. It will help us allocate matters to our staff in a more efficient manner.
4. Data helps you find gaps and tells us how to fill them
When we are driven by processes, data analysis helps us identify the gaps and suggest ways to address them. Once organizations start to follow standard processes, they should then identify the data points for collection, and then periodically review and analyze that data to see if they are on the right track.
For example, say we are looking for an efficiency enhancement within one of our service models and we started an analysis to better understand it. Before doing the analysis, we first need to see if we have a standard process. In case there is no standard process, we first need to define one. This is the first step towards organizing the data.
Post that, we need to get the time entries captured properly to analyze the steps in the standard process. Where is the team losing track and failing to maintain efficiency?
Based on the analysis, we can figure out whether we need to optimize the process through a technology-based solution or by internal training and development.
5. Data helps you grow
Data helps us with better market analysis, which leads to designing successful marketing strategies, understanding customer behaviour, and innovation. This puts your firm in a better competitive position in the market.
While we are busy with the business, do we keep a track of our competitors? Do we truly understand the market trend? Do we understand what our clients want? A data-driven law firm is able to consistently have successful acquisition and retention of clients by being aware of the market’s movements and trends.
Nowadays, there is immense pressure on clients’ legal teams to reduce their expenditure. Ultimately, the client team puts that pressure on the outside counsels to reduce the expenses. When the majority of clients are demanding and expecting the outside counsels to spend less, technology and practice innovation is the only solution to meet that demand trend.
When we are not keeping a track of the clients’ requirements, expectations, and market trends, it becomes nearly impossible to win our clients’ trust and confidence.
How to become a data-driven law firm
While there is no specific or defined methodology to become a data-driven law firm, here is a brief step-by-step guide you can follow:
1. Define your goals
You need to define the goals you are planning to achieve with data analytics. If it is not defined properly, you need to relook into that to fix it.
The goals can be different for different organizations. Let’s say your goal is to increase the efficiency within your organization, you can actually decide what data you are planning to collect, how you are going to do the analysis, what is expected out of that analysis, etc. Subsequently, this analysis will help you achieve your targeted goals.
When you don’t have a goal to achieve, you will lose interest to capture and analyze the data. Let’s understand this area clearly. If you don’t define your goals, you will fail to define the data points as well. Consequently, you will neither have any idea on what to do with the data available with you nor will have you be able to make decisions because of a lack of informed understanding.
2. Identify all the data you possess in your firm.
We need to understand whether we can trust the available data, whether the source is genuine, and the way it is captured is correct. We need to answer these questions before using the data for analysis.
Identification of data is pretty simple but as mentioned above, how you are going to guarantee that the data is real? For example, as mentioned earlier, if you are going to deploy a DD system and you are taking the time entry data as your base for the analysis, the time entry data should be correct. Let’s say, you have a manual unsupervised time entry process in your organization, people will have the liberty to manipulate their time entries. Suppose Person A spent 3 hours for due diligence but entered 6 hours and you don’t have an approval mechanism in place, you will be forced to believe that 6 hours is correct data. If your decisions are based on such fake data, your efficiency-building effort will be affected.
4. Collect and preserve all data in an efficient manner.
The data should be collected and kept in a searchable format with indexes, and with the proper file names for future reference. Collect all the internal and client data, and store it in a secure place like a virtual data room to avoid any alteration in the future.
Also, bring relevant processes and technologies to collect these data points. Client data and other sensitive data should be stored in a highly secured storage system like a virtual data room and other data can be stored either in an internal storage system like SharePoint or OneDrive. A periodic audit of these is one of the best ways to ensure that all data is stored in the respective systems.
5. Process and organize the data
Process and bucket all the collected data. Organizing the data will help you refer to it easily and also helps accelerate analysis of that data.
6. Analyze the data
Collaborate with people who understand data. Define the analytic methods and have signed them off by a specialist. Here, I will go back to the point number 1 & 2 where I have mentioned that the goal should be defined. Based on the goal and what documents are available, and with the help of a data analyst, you can easily decide how to proceed with the data analysis.
With this, the data analysis architecture will be ready and you will be able to use it. You can take the help of technological solutions like SQL or Python for this. Definitely, this is not the job of the lawyers. It needs to be executed by an experienced data analyst team.
7. Data presentation and prediction
On completion of the entire analysis, present the outcome & predictions to the relevant stakeholders like the partners or the senior management of the organization. Convey to them the real stats, and help them understand how they can make the best use of the available data. Give them examples of why they can predict and strategize business management. The entire process will put the management in a better position to take strategic decisions.
In the above example, if you are planning to deploy a DD system in your organization, with completion of the entire cycle you will be in a position to understand whether you actually need a system in a place. And if you need a system, will you be able to generate more revenue? If you will be able to generate revenue, which system will be best suitable as per the requirements and budget?
When predicting, it is also essential to map the predictions with the real events in the future to refine your process. Suppose, you predicted $20 MN profit and in actual you didn’t generate 50% of it, you should go back to the entire process once again to see where you went wrong during the previous analysis. This will help you to optimize your process to yield more benefits in the future.
How to build (and use) a data infrastructure
1. Build a data-driven culture.
Put this into everyone’s KRA, and treat data as capital. Conduct audits to measure the adaptability of your staff regularly. Build a culture where people understand the importance of data, how to create and preserve data, and are curious about how they can analyze data for decision making.
For example, considering timekeeping is an important data creation method, you can include this into people’s KRA to make sure that people are entering time as per the requirements, and have the approval mechanism in place to ensure the correctness of the data.
Make sure that if people are failing to comply with the requirements, that is getting reflected in during the appraisal process.
2. It should start with the top management
Leadership should advocate data-driven business decisions. For example, the appraisal of employees should not be based on anonymous feedback by their managers. Their feedback should be backed by relevant data to correlate by the management while deciding the bonus and increment. These kinds of moves will influence the people to create and use more data points in the future and also, it will bring conviction among the people to adopt the change.
3. Start with easier goals & an easier data set.
This will help everyone at your organization to understand the process and its importance of it. For example, time-keeping practice is something all can understand and relate to. This can be an easy way to start a data-driven journey in your organization.
4. Set strategies and calibrate to refine the process and methodologies.
As mentioned earlier, you should have a goal in place. Act as per your goals and periodically analyze the outcome to see the loopholes of your process. Refine it wherever required to optimize the process.
5. Don’t forget to act on the analysis
Ensure to act upon the predictions. We need to ensure that we are acting on the predictions, to arrive at which we spent so much time and effort. If we do the entire data analysis correctly but don’t act on the predictions, we will not be bringing any change.
For example, say you predicted that if you onboarded “Tool X” for DD, your profitability will increase. But somehow, you ended up onboarding “Tool Y” which was never shortlisted during the analysis. This is a deviation from the objective of that entire analysis. The results can be terrible since the alignment was against the scientific methodologies of data analysis for efficiency building.
Encourage everyone at your firm to use data, especially for taking any sort of strategic decisions. This will end the bad practice of taking decisions on the basis of presumptions & biases.
6. Train your staff
To follow the data infrastructure, people need to be trained properly. Expectations need to be clearly set by the management as to how they are going to deal with their data.
For example, if you are using a virtual data room for preserving client data, everyone in your organization interacting with the data should be trained well on the platform. They should have a fair understanding of the technology platforms to comply with the mandates.
Consider identifying enthusiasts and evangelists within your team to drive the efforts and increase the pace of adoption.
7. Communicate the benefits to people
Let them get excited about the outcome, and frequently incentivize their efforts. Communication plays a crucial role in change management. In order to adopt a new thing, people need to understand its benefits first, and after that they need to be incentivized for their efforts whether through awards, bonuses, or other forms of recognition.
8. Invest in some technology
Deploy simpler technology solutions that can easily be understood by all. There are a lot of user-friendly tools available globally.
We need to deploy tools as per our goal and requirement. For example, if client data storage is our priority at the moment, we need to invest in a subscription to some good virtual data rooms to store the client data.
9. Embrace the fact that this is a continuous process
You will end up discovering new things every day. You will apply them, see good results, and then explore more. It will be a great exercise once it becomes a part of your culture. Sometimes, we don’t do things intentionally, but still end up discovering new things. These new discoveries will help us get into new avenues with new goals to maximize value creation for the benefit of our organization.
A data-driven law firm is a superior law firm
As a law firm, when you are driven by data analytic approaches, you will maintain all client and billing-related documents in proper places with the highest level of security. You will gain access to the historical data present in your organization, leading to quicker and more accurate validation of your decisions at any given point in time. This will lead to better transparency both within and outside the organization.
For example, when you have the time entries in place and you are transparent to the client showing the time entries, you will win the trust of your clients, will retain them for longer, and win more business from them.
With the increase of your access to data, you will end up taking more meaningful decisions. With more meaningful decisions, the organization will gain the confidence and trust of both employees and the client who are the two main pillars of the organization. It will help you to measure KPIs & improve the productivity of your organization and also helps to maintain consistency.
More importantly, it will act as a gateway to new avenues & areas which you have ignored to date.
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