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How automation enables review teams to work smarter, not harder

| Written by Altlaw

For those that are caught out unawares, eDiscovery costs can quickly spiral out of control.

Particularly as litigations are growing more challenging.

Data sets continue to expand in volume, with more complex and varied formats, making manual tasks far more time-consuming and labour-intensive with each passing case.

This leaves internal resources thin. And as shrinking budgets mean many firms and in-house legal departments don’t have the option of increasing headcount, the only way to address these difficulties is to make their existing resources go further.

In short, legal professionals must do more with less.

By eliminating the burden of basic and highly repetitive tasks, and allowing the principles of intelligent human decisions to be significantly scaled up, automation is helping review teams to keep costs under control, reduce errors and risk, and enhance productivity.

Read on and discover just some of the ways automation is helping legal professionals to achieve more efficient, cost-effective and productive eDiscovery practices.

 

 

TOFU-part2-feliminate_img1. Eliminating irrelevant information

Early case assessment (ECA) is a vital process in developing an informed understanding of a litigation.

The data gathered during this process can help legal teams determine the amount of risk involved, and also guide their strategy and decision-making later down the line.

By automating certain tasks and processes in bulk, Analytics tools can allow discovery teams to cull and categorise large volumes of data in ways that are both efficient and effective.

 

There are tons of different tools out there, all with individual capabilities and purposes, but broadly speaking, Analytics serve to:-

  • automate previously labour-intensive processes
  • identify different sources of information that are conceptually or contextually similar, and group them accordingly
  • weed out duplicates and other low-value documents
  • structure and prioritise the review process.

 

When used with the right intent, Analytics tools can slash data volumes, and structure or group documents in a way that makes their contents clear at first glance, which minimises the time spent scanning irrelevant documents.

Email Threading is just one example of an effective Analytics tool, and it has been shown to reduce data volumes by between 25 and 50 percent, according to Relativity.

This means that in as little as a few clicks, Analytics tools can help reviewers work more efficiently from the get-go – eliminating irrelevant information, and offering an insight into the key themes and topics present within their case files.

The results of this can then guide expectations, budgets and review workflows, ensuring that available resources are used as effectively as possible.

 

TOFU-part2-meta_img2. Capturing metadata

In eDiscovery, the need-to-know information within a document batch doesn’t just lie in the contents of the documents themselves, but in the context and history of those documents.

When a file was created, who it was initially authored by and sent to, how many times it’s been updated or accessed and who by – this information is more commonly known as metadata, and it is often vital to the collection process.

Metadata can offer immense value to legal professionals by helping them to clarify a document’s relationship to the case at hand.

But, it can also present a number of challenges.

Firstly, some documents can have literally hundreds of different metadata fields, among them being ‘hidden’ or ‘embedded’ forms of data that are not immediately visible or accessible to certain users.

 

Secondly, metadata is very fragile.

Simple actions such as opening a folder, forwarding an email or previewing a document can tamper with a file’s metadata, and leave it irreversibly altered.

This of course can present grave consequences for the review team responsible for the documents.

Thankfully, eDiscovery software can automate the processes of capturing, preserving and managing metadata, allowing you to quickly extract rich historic and contextual data from your document batch, without spoiling their contents and thus avoiding any grave ramifications.

 

 

TOFU-part2-redact_img3. Redacting sensitive information

Once data has been collected, reviewers must ensure that any information that could be used to personally identify someone – or that is otherwise of a sensitive nature –  is redacted prior to production.

Traditionally, this process of redaction has been done manually.

(And for those less comfortable with modern technology, it is still done this way.)

But performed manually, document redaction is a highly inefficient and costly process.


Not to mention staff often find the repetitiveness of it tedious, which negatively impacts their morale and increases the probability of errors. This in turn increases the likelihood of receiving regulatory fines and penalties.

Thankfully though, there are now numerous eDiscovery solutions on the market that come with automated redaction tools, capable of identifying sensitive words, phrases, and patterns – such as a credit card number or home address – and immediately redacting them.

These tools can then replicate this action instantly, across large quantities of data.

 

Auto redaction tools like these also save time on the manual process of drawing redaction boxes over the sensitive information in question, which simply adds hours to an already time-consuming process.

Overall, automation in this area takes a repetitive, labour-intensive and error-prone task, and streamlines it to give you a fast-acting, precise and consistent system.

One that you can trust to keep your documents in ship shape.

Plus, automated redaction tools are also a fantastic way to quality control your productions before sending them to opposing counsel.