An ongoing trend of the 21st century is the increased reliance on “Data Analytics” in making business decisions.
Whether it’s the world of professional sports, tech companies of Silicon Valley, or law firms of various sizes across the globe, “Data Analytics” have become more than just buzzwords and are an integral part of well informed decision making. The following best practices have the ability to bring your firm’s data management up to speed with competitors in the law industry, while turning what might be an underutilized resource into a working asset that drives revenue.
Data analysis is certainly not a new concept, but with the rise of data tracking and data mining software, we are now flooded with more data than ever. Firms are faced with the question of how to filter through this information to zero in on what is truly important. This seemingly simple distinction is the key to what will separate successful firms from the pack, drive growth, and prevent stagnation.
Firms looking to implement or revitalize their data analysis process should ask themselves three core questions:
- What data are you tracking?
- How are you analyzing that data?
- How are you applying the results?
Let’s take a deeper look at each core question.
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What Data Are You Tracking?
As the expression goes in the IT sphere: “garbage in, garbage out”. Simply put, if the data and information that you are tracking is incomplete, inaccurate, or not relevant, then the resulting decision making will be inherently flawed. Law firms should focus their data mining on their two main resources: People and Time. How and where members of the organization are spending their time is the fundamental building block for data tracking. Long-established firms would be well served to revisit this process to ensure the accuracy and relevance of time reporting. Relevant factors may include an organization member’s location, the type of work being performed, the client being worked on, the industry or practice hour, the responsible partner, and so on and so forth. These factors should be tailored to each firm specifically, but should be focused on how you would like to analyze revenue generating activities and cost centers.
How Are You Analyzing That Data?
As alluded to above, analysis should be focused on revenue generating activities and cost centers. Firms with multiple partners, practice areas, and office locations should be analyzing profitability at each of these levels. This stage highlights the importance of a well-organized IT infrastructure. A fully integrated internal network that links information from Enterprise Resource Planning (ERP), Customer Resource Management (CRM), time reporting, and financial accounting platforms is critical in factoring in all relevant data and producing easy-to-read reports and deliverables. Dashboards that provide real time data and profitability reports (e.g. by office, by client, by practice area) should only be a few clicks away.
Cloud based computing and storage has paved the way for all of a firm’s internal systems to interact. This can help prevent duplicate data input and redundant work, saving your firm valuable time that could be better spent servicing clients.
How Are You Applying The Results?
The top concerns for most law firms are income and cash flow. The application of the results of your data analytics should be focused on maximizing revenues, minimizing costs, and maintaining a steady cash flow. Fully formed reports backed by complete and accurate data will help you identify which locations, practice areas, clients, and team members are generating the most revenue and providing a steady influx of cash. Use this information to strategically reallocate resources to areas with higher profitability and greater cash flow. This will not only alleviate the strain on cash in the short term, but will also set your firm up for opportunities to grow and succeed in the long term.
It is imperative for firms to implement a process for data analytics, or otherwise risk falling behind the competition. Learn more about our Data Analytics services.
Author: John Schrumpf | [email protected]
Data Analytics
