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How to Effectively Run a Review: Reduce Overall Costs by Up to 30% with Successful Project Ramp Up & Management

Published on March 27, 2023

Acorn

Acorn is a legal data consulting firm that specializes in AI and Advanced Analytics for litigation applications, while providing rigorous customer service to the eDiscovery industry. Acorn primarily works with large regional, midsize national and boutique litigation firms. Acorn provides a high-touch, customized litigation support services with a heavy emphasis on seamless communications.

Continuing on the subject of review, the largest cost driver within the EDRM, we will consider how the factors of rework and throughput can often be hidden burdens to managing a review project.  

Last time, we focused on defining these infrequently discussed cost drivers of review. Today, we will hone in on how to reduce costs through an effective project ramp-up and successful review management. 

Establishing the Numbers 

Let’s recap the assumptions we will continue to work off of. In this scenario, we have 100,000 documents that need to be reviewed, with 15,000 documents needing to be re-reviewed (reworked) at a review throughput rate of 40 docs/hour, at a $42/hour rate. With these rework and throughput rates accounted for, this results in 115,000 effective documents reviewed. 

In today’s exercise, we will take a look at how optimizing your review team from the start and effectively managing your team throughout the project can have significant cost savings. 

Is a Large Review Team Worth It? 

In our previous Groundhog Day webinar, Senior Project Advisor Robin LeDonne discussed the importance of choosing a small efficient team of high-skilled, quality, trained reviewers, “Like a coach preparing for a game, you need to figure out who would be good on which review project and why,” Robin explained. 

By keeping track of your pool of reviewers who have a proven track record of good performance, along with being familiar with your processes, you can rest assured that your review will likely move in a positive direction. And just to be sure, let’s take a look at what the numbers say. 

In the example above, we see that having an efficient review team that has been properly trained results in the number of documents reviewed increasing by 6 additional documents/hour. Just by being strategic on who you pick on your review team, this will lower the number of documents that need to be reworked by 12%. This shows how small tweaks to your review project from the beginning can lower the overall cost of the budget by almost 20%! 

Does Reviewer Efficiency Factor into the Puzzle? 

Reducing review costs doesn’t stop at the beginning of the project. To consistently reduce review costs, you need to lower the amount of rework. So, monitoring your review team becomes increasingly important. Using reports and statistics to actively monitor your team will show you how many documents reviewers are coding per hour, as well as the overall pace of the project. 

Let’s say, for example, you have six reviewers on a project and the standard norm for reviewers is roughly 40-50 documents an hour. Like the example below, you may have one rockstar reviewer that is reviewing 90 docs/hour, have some reviewers who are reviewing in the 40-45 range, one reviewer that is a little bit below the bar, and two reviewers that are way below the average. 

Robin discussed, “So, if I was managing this team, I would coach reviewer 1, cut reviewer number 2 and 3 immediately since they are below average, and I would flag reviewer 6 to peek at later to make sure that their coding is consistent, and they aren’t just flying through without making informed decisions on each document.” 

Robin’s decision to cut reviewers 2 and 3 in this scenario shows that although the weeks to complete the review may increase by 1.3 weeks, the throughput of the reviewers is also increasing from 41 documents/hour up to 53 documents/hour. 

Even though this sample review project was extended for an additional week, it still allowed for a decrease in costs. By reducing the team, it increased documents reviewed to 53 from 40, aka 13 more documents an hour, and lowered rework by 6% which is a 30% reduction on total cost. 

How You Can Apply This 

You may fear cutting low-performing reviewers in order to meet deadlines on time, but this scenario shows that quality reviewers have a more significant effect on the budget than time to completion. Through strategic, incremental changes to your review team, you can see how using a small, efficient team reduces risks of inconsistencies that can affect the quality and costs of your review. 

Stay tuned for next month as we continue this exercise and examine how we can leverage advanced technologies to further streamline our review and further reduce our total costs. 

About Acorn

Acorn is a legal data consulting firm that specializes in AI and Advanced Analytics for litigation applications, while providing rigorous customer service to the eDiscovery industry. Acorn primarily works with large regional, midsize national and boutique litigation firms. Acorn provides a high-touch, customized litigation support services with a heavy emphasis on seamless communications. For more information, please visit www.acornls.com.