Over the last twenty years, e-discovery has become a significant part of litigation. Even in relatively uncomplicated cases, e-discovery can play a significant role in success or defeat. Most lawyers think that e-discovery is only significant when dealing with large scale litigation involving huge corporations. But even individuals can create a huge amount of data that could be relevant to a case. Think of the emails sent and received, either personal and work-related, all the Facebook posts and messages, all of the tweets and other social media posts that might be relevant. When faced with these circumstances, even small cases involving individuals can create a significant amount of data that could seem overwhelming.
It does not have to be that way.
Smart discovery practices involve a broad understanding of what needs to be found in order to prove or disprove a particular claim.
To do this, lawyers have to know what is necessary and what needs to be found. This pre-discovery outline will help determine if there is any missing data or information. It will also help in determining what witnesses to depose in order to understand what systems to search to obtain data.
Hire Out or Go In-House
There are two things that law firms should consider when faced with an e-discovery situation:
1. Should an outside company be hired to deal with it?
2. Should the task be performed in-house?
Many companies focus exclusively on handling e-discovery tasks for law firms. These companies develop a plan, determine where to look for the data and who to ask, implement the plan by sifting through data to determine if anything is missing, and put the information together in a form that is useable in the courtroom.
In some instances, depending upon the size of the case and the size of the potential data sets, as well as the amount of costs, the client is willing to spend on acquiring the data, law firms may decide to perform the tasks in-house. Often, creating an e-discovery division in your firm might decrease case costs as well as increase efficiency. But this decision depends on the number of employees available, the firm’s technological expertise and even the basic issue of does the firm have enough physical space for what will be required. If the decision is to go in-house, however, there are several issues that should be considered.
The first thing for law firms to consider is whether the firm can economically justify bringing e-discovery in-house. Obviously, it should not be done if all the firm has one case. However if the firm has been outsourcing e-discovery tasks at significant cost, then it might behoove the partners to create an e-discovery division within the firm. Before a decision is made, a detailed budget should be created outlining the cost of creating such a division.
Hire a Pro
One of the first things to do is to hire an expert who has experience in setting up and running an e-discovery operation. This should be done merely as a precaution during the decision making and budgeting stage. This will ensure that no issues are missed and an accurate budget can be created. Once the project begins, this professional can be charged with implementing the firm’s vision and plan.
The Nuts and Bolts
Now we come to the part of the discussion where most attorneys eyes glaze over — technology. Several technology related issues need to be addressed. Will your firm buy software that can handle different aspects of the e-discovery process? Or, will your firm go all out and purchase a software suite that can handle the entire electronic discovery reference model (EDRM)?
Obviously, cost will be a factor in this decision, as well as, the amount of work. Another factor is whether the system you choose can integrate your existing clientele and already completed e-discovery work. If this is the case you might also want to consider outsourcing some of the EDRM process, but keeping in-house other aspects of the process.
A second technology issue is whether to store your data on premises in servers that the firm’s personnel control or whether to store it in the Cloud. There are positive and negative aspects to each. This decision might be answered by which software suite is used. Some systems are designed to use the Cloud, and the data is stored in vast server farms such as Amazon’s Web Services division.
Participating in new ventures can be risky. Creating your own e-discovery shop in-house is no different. By taking on this new aspect of its clients’ services, law firms are responsible for new areas of liability. Therefore, law firms must do a thorough review of its errors and omissions coverage to determine whether more coverage is necessary for data breaches and other types of negligence related to e-discovery.
If law firms, after significant deliberation and study, are unsure as to whether to pull the trigger on creating an in-house e-discovery division, then maybe that is not the answer.
A flexible partnering agreement can be created with the outside firm where some work is done in-house and some is outsourced.
In this manner, law firms can learn the process and create more business that might justify the creation of the full-time in-house e-discovery shop.
Artificial Intelligence and Machine Learning
Whether a law firm is creating its own e-discovery division or whether it is retaining an outside firm to perform e-discovery projects, the law firm must have at least a rudimentary understanding of the cutting edge technology on finding, retrieving and managing e-discovery data. Law firms should know this in order to implement it in their own shop or to interrogate an outside shop about how advanced it is in this area of discovery.
There are two types of artificial intelligence (AI): 1) Human created rules based tasks; 2) Machine learning where algorithms allow the computer to teach itself and grow beyond set rules. Machine learning algorithms are at the cutting edge of e-discovery.
Predictive coding is an aspect of machine learning that is used in the “review phase” of EDRM. When used properly, predictive coding is very efficient at accurately locating and retaining pertinent documents in a data set. Predictive coding is where sample sets are pulled from the entire data set with those samples coded as either “responsive” (meaning the document is pertinent) or “unresponsive.”
With several sample sets coded in this fashion, the AI software can then create an algorithm for predicting the responsiveness of future documents that pass through the search software. Once the initial searches are completed, the algorithm will refine itself so that the searches will be more accurate.
Machine learning and predictive coding can get complicated and this article is not intended to explain it in detail. However, there are certain best practices that an e-discovery firm should follow.
Practice: Use the AI software in a practice setting so that all the bugs can be worked out. This is important so that once a judge and/or opposing party looks at the recovered documents, any adverse discovery decisions by the court are prevented.
Use expert reviewers: When reviewing the accuracy of your initial searches, use the best expert reviewers who know the case. Do this before the main searches are performed.
Validate results: Do not fall into the trap of assuming that the results spit out by the algorithms are correct, even with all the sampling, practice and expert reviews. The expert reviewers should continually, manually sample data from both the relevant portion of the discovery as well as the non-relevant. It is important to look for inconsistencies in the sample sets. If a significant amount of incorrectly coded documents are discovered, it may be needed to redo the whole process.
The bottom line with handling e-discovery requirements is to adapt with changing technology and law that controls what forms of technologies are allowed in court. As the technological landscape in business and personal use increases exponentially from year to year, e-discovery will become more complicated. A willingness to change when necessary will allow your law firm to exceed in successfully dealing with e-discovery.
Storing Data On The Cloud
If your firm chooses to store data in the Cloud rather than on-site, there are some important items you should consider:
- Data security and physical facility security
- Cost of servers and the employees to maintain them
- Cost of the physical space to house the equipment and personnel
- Mobility and data hosting
- Secure backup and business continuity plans.