Law Firm Dashboard
The managing partners at law firms have good understandings of their practice from being in the office every day and knowing the status of cases. However, it is hard to grasp exactly what is going on operationally and this blindness can lead to losing opportunity to maximize profit. There is more you can learn from the data that comes out of day-to-day operation of law practice.
Implementing operational metrics like this will help law practices increase their bottom line — “what gets measured, gets results”
Many law firms struggle to have a single platform to measure their operations due to the fact that, there are many different systems and tools. Aver Analytics can help you and deliver a dashboard like below; start measuring your performance today.
Clio (https://www.clio.com) users, please click here take a look at a Dashboard based on a sample Clio data.
Law Firm Practice Dashboard
Visually shows the most critical KPIs (Key Performance Indicators)
New clients stats, Average Billing per Client, Staff Utilization, etc. provides the “health” check for the managing partners
Insights
Most managing partners take a close look at the Billing, Staff Utilization, and Aging Receivables. But, they mostly do this review in a vacuum. A dashboard like below should be readily available for everyone in the law practice to see how each of them are performing and contributing.
What is interesting is that, most managing partners pay good attention to the Days receivable outstanding, but they never monitor the number of days it takes from the last billable hour logged to actual invoicing date. 30 days delay in getting the invoice out to clients is as bad as 30 days aging as receivables.
Microsoft Power BI is the tool Aver Analytics uses. It is an “add-on” cloud based tool. This means, you do not replace your existing systems (Case Management System, timekeeping, etc). Power BI simply connects to multiple data sources you already have. There is no replacement and there is no special upgrading required now or in future.
Source: Based on sample, randomly generated data set for demonstration