As each year progresses, one thing is continually top of mind for businesses of all kinds: the budget.
In e-discovery, no one wants to miss their budget targets, whether they’re set by their team or their client—but it is a possibility we all face from case to case. Fortunately, it is usually preventable and at the very least mitigable.
With budget concerns having been particularly prominent through 2020, and that trend continuing into this year, it’s crucial to look at why and where we are generating the most costs and how we can manage them.
Review, of course, has long been a huge expense in the e-discovery processes. However, it is now facing added pressures from new challenges with evolving data types and volumes, and considerations for managing remote review teams as well. Even with these new challenges, creating efficiency for your review can still be easily achievable and directly translates to reduced total costs.
Since budgets are so important to the industry, our team at Acorn has spent a lot of time trying to think about how to best optimize its e-discovery workflows to consistently stay within parameters. To dig into this question, we’ve come up with a standard workflow for a case that is routine—pretty much what you would see across the industry—and put it to the test to understand what workflow changes can have the greatest impact on bottom lines.
With that in mind, we can have a real-world discussion around how review decisions get made and how the total cost of review (TCR) can be better managed and understood.
The working question guiding this exercise is: How do our choices prior to review affect our total cost?
To answer this question, let’s walk through an example. For our standard workflow, we’ve simply come back to the good old EDRM: collection, processing, hosting, and then review. I assigned prices to each stage that are generally close to market averages, but also nice round numbers for the sake of our math. I intend this to be an illustrative exercise, and not get into the legal arguments for increasing or reducing the scope of discovery—so keep in mind that this is entirely intended to be focused on the economics.
Establishing the Numbers
So, let’s lay out the scenario. As a baseline, let’s say we have a collection of 6 devices with costs of $500 per device and each device has 50 gigabytes of data. Assume each gigabyte contains 1,000 documents, and our reviewers work at a rate of 50 documents per hour at $50 an hour. Lastly, our processing rate will be $35 per gigabyte, and hosting will be $25 per gigabyte per month. We will also be using 4-month longevity for this case. We will be aggregating these costs throughout the months in the chart to follow.
Now that the baseline is established, let’s see how a review scenario can play out. In this article, we will focus on the collection stage. So, first question: We have the option of doing a collection broadly or doing it targeted. Which do you choose?
Collect Narrowly or Collect Broadly?
With a broad collection, we end up collecting the whole of all our data—meaning every custodian and every gigabyte that possibly could be relevant to our matter. On the surface, this has some sensibility; after all, we want to be thorough and meet our legal obligations, and we’re facing a relatively small cost of $500 per device for collection. As a result of this decision, we would collect data from all 6 devices in this case.
The alternative is a targeted collection. In this course of action, we will be more precise with our collection, avoiding custodians that are not crucial to the matter at this time. (We determine that we can go back later and collect from them if they turn out to be more critical than initially thought.) With this approach, we decide that only 4 of the 6 are crucial to our matter, so we would collect data from 4 of these devices.
Looking at the Big Picture
As you can see in the figure below, the initial costs are only marginally lower with the targeted collection—nothing too extreme. But the real impact of this collection is seen in Month 4. That’s where the numbers start to expand.
On the surface, when looking at the collection stage itself, we are faced with a difference in expenses of only $1,000. Why take the time to target your collection and risk having to recollect for a custodian later for such a small sum?
Well, as it turns out, that $1,000 savings initial isn’t the end goal—and how we collect will exponentially affect our TCR downstream. Let’s look at this through the full course of discovery.
As we see with this figure, initially our upfront costs are lower, followed by lower processing and hosting fees. But let’s look further down the line. With our targeted collection, we not only reduced our fees for Months 1 through 3, but significantly reduced our total review costs during Month 4. This led to a cost savings of approximately $25,000.
How You Can Address Collections
A targeted collection isn’t always time feasible or as convenient in the moment, but there are solutions out there that can assist with this process. One of those would be RelativityOne Collect.
RelativityOne Collect allows you to collect data straight from the source, without that data ever leaving the cloud. It currently integrates with Office 365—so, most of our emails—as well as Slack, Enterprise Vault, Microsoft Teams, Google Workspace, Bloomberg Chat, and WebEx, with additional endpoints to come. The nice thing about Collect is that you can filter your data sources at the onset, such as by custodian, date, and so on, allowing you to easily collect exactly what you need and nothing more.
Not only does Collect, and parallel tools, provide the ability to make your collections proactive, but it’s also defensibly sound with detailed reporting and a complete audit trail. This benefit that can prevent mishaps, such as those that occurred last year in Equal Employment Opportunity Commission v. M1 5100 Corp. when the defendant performed a self-collection.
Managing TCR is a Marathon, Not a Sprint
I do acknowledge this isn’t a perfect example and that we could quite possibly have to collect from another custodian as the case progresses, which would ultimately add to our costs—but in the end, even just collecting from 5 versus 6 devices is still impactful and would still reduce total review costs by at least $10,000.
Of course, this is only one consideration we should keep in mind from the onset of any matter. With this perspective, you can not only perform precise collections, but collections that are defensibly sound and create real budgetary impacts. But collections are only one step in the process, so don’t limit your focus.
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.