Litigation Services Case Study
Company Size
11-200
Region
- America
Country
- United States
Product
- Domo
Tech Stack
- Data Analytics
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Productivity Improvements
Technology Category
- Analytics & Modeling - Real Time Analytics
Applicable Functions
- Business Operation
Use Cases
- Predictive Quality Analytics
Services
- Data Science Services
About The Customer
Litigation Services is a leading deposition services firm based in Las Vegas, NV. The firm serves several large insurance companies and has been recognized by Inc. Magazine as one of the 5,000 fastest-growing private companies for the past three years. Despite its success, the firm was struggling with data management, with static reporting and inaccessible data posing significant challenges. The firm sought a solution that would enable it to become truly data-driven, providing real-time insights and facilitating a more proactive, consultative approach with its clients.
The Challenge
Litigation Services, a law firm serving several large insurance companies, was facing significant challenges in managing its data. The firm's reporting was static, often resulting in outdated information. Furthermore, the data was not easily accessible to decision-makers, hindering the firm's ability to make informed, timely decisions. The firm needed a solution that would enable it to become truly data-driven, providing real-time insights and facilitating a more proactive, consultative approach with its clients.
The Solution
The firm implemented Domo, a data analytics platform, to address its data management challenges. Domo enabled Litigation Services to move from a reactive approach, driven by client demands, to a proactive, consultative approach. The platform provided real-time insights into transcript production, allowing the firm to monitor individual performance on a daily basis and provide coaching where necessary. Furthermore, Domo facilitated a common language for data within the firm, eliminating the need for extensive coaching on data patterns and enabling meaningful conversations around data.
Operational Impact
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