McDonald Carano powers expedited review with predictive coding

Their Story

McDonald Carano is Nevada’s premier law firm, with over 50 attorneys working across Reno and Las Vegas. The firm focuses on staying ahead of the technology curve and being at the forefront of innovation in their commitment to clients.

The Challenge

The McDonald Carano team was recently reliant on outdated, clunky ediscovery technology. Simple tasks, like running searches or productions, proved cumbersome and time-consuming. In addition to being slow and difficult to use, their legacy solution lacked both basic ediscovery capabilities and advanced ones, such as analytics and machine learning.

Attorneys at the firm obviously preferred to focus on their most impactful work but, with the previous solution, found themselves instead getting lost while navigating non-intuitive interfaces or impatiently waiting for documents to load. Instead of using the software, employees would often convert hundreds to thousands of files manually and then produce these all by hand.

In Everlaw, we’re choosing a company that’s already ahead of the curve and has demonstrated that they intend to stay there. They have cutting-edge features that their competitors lack and they show a much greater commitment to continued innovation.

– Robert Sawyer, Director of Information Technology

Cognizant of these challenges, leaders at the firm knew they needed state-of-the-art, innovative ediscovery software that could scale to meet the firm’s needs. They needed a solution that could process and produce documents very quickly.

The Everlaw Solution

When evaluating solutions, the McDonald Carano team explored the document review, advanced analytics, and predictive coding capabilities of the Everlaw platform. Attorneys and paralegals quickly recognized the blazing speed and intuitive interface.

They learned that they could easily upload native or processed data to the platform, quickly investigate their document corpus, apply search filters to cull down data, and review documents in context. The team was also impressed with the way Everlaw handles email threading. After a thorough evaluation, McDonald Carano selected Everlaw for the software’s ease of use and industry-recognized features, and the company’s clear commitment to innovation.

Results

In an initial review on the platform, McDonald Carano leveraged a combination of Everlaw instant search, date filters, and visual email threading to narrow down the initial review corpus by 76%. They then used Predictive Coding to prioritize their review further, surfacing more likely relevant documents (based off of their previous coding decisions), reducing the original data volume by 96%. After isolating all relevant documents, the Everlaw production wizard allowed the team to easily produce the relevant documents and share the results.

The review team leveraged machine learning and other features for cost reductions, significant time savings, and efficiency gains. The cost savings delivered to the client were two-fold: first, the McDonald Carano team reduced the total amount of data hosted by the firm using Everlaw early case assessment tools, such as Search Term Reports and Data Visualizer. That helped identify and delete irrelevant data, reducing both the total amount hosted and the associated fees.

Everlaw handles email conversations better than any other platform, displaying email threads in a visually intuitive way that puts everything in context and is easy for attorneys to understand.

Everlaw ultimately sped up and streamlined the review process. Reviewers no longer wait for searches to populate or for documents to load in the viewer. Previously manual tasks, such as coding or redacting documents, are now done automatically in Everlaw via Batch Coding and Pattern Redaction, allowing users to tag dozens of documents and redact all instances of a keyword, phrase, or pattern at once, instead of document by document.

 


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