5 ways you can use eDiscovery techniques outside litigation

5 ways you can use eDiscovery techniques outside litigation

  • Blog Post
  • Posted on 17 June 2015

Electronic Discovery (eDiscovery) as a process is not limited to discovery in legal disputes. The use of the term eDiscovery has now become synonymous with the process of handling large volumes of electronic data and goes far beyond the traditional definition.

Electronic Discovery (eDiscovery) as a process is not limited to discovery in legal disputes. The use of the term eDiscovery has now become synonymous with the process of handling large volumes of electronic data and goes far beyond the traditional definition. 

There are many services and software tools available being sold under the eDiscovery banner but not necessarily just applicable to eDiscovery. Compliance, statutorily regulation, internal investigations and information governance are all areas where the eDiscovery process is used to effectively identify relevant information.

Here are 5 ways you can apply the eDiscovery process, outside of eDiscovery:

1.  Untangle your web of data

All of your data is collated and copied into a central data store.  It is then categorised by type and all duplicates are eliminated.

Data is created in many different forms, using a wide variety of software applications – PDF, Microsoft Word, Excel, email, etc. Often this data is duplicated, backed up and shared with others resulting in multiple copies. There are very few limits to the organisation of data and therefore the structure it is stored in is inconsistent. When the business need arises for your data to be categorised, it is very difficult to do so without applying structure to it. This is the basic premise in the first stage of eDiscovery processing. 

2. Remove the junk and find the gold in your data

Wouldn’t it be great to find the gems amongst your mass of documents? 

Computer Assisted Review is the most recent development in the eDiscovery process and is geared towards large amounts of data – 100,000 documents or more. Using Computer Assisted Review you can teach the software what a relevant document is for your purposes. This is done by reviewing a very small proportion of your data and then applying that same logic to the entire data set. Each document is then assigned a relevancy ranking and can then be reviewed in order of priority based on that relevancy.

3. Group similar documents together

With near-duplicate detection you can group together documents with similar text content so they can be classified together. 

This not only helps with consistency but can also save you time as it is often possible to review just one document and apply the determination to the rest of the similar documents.

4. Remove those unwanted emails

Did you know there are about 182.9 billion emails sent and received per day worldwide? (source: digit.com) 

To reduce the load of emails to be searched through, Email Threading is used to identify emails which exist within chains of other emails so they can be discarded or grouped with the rest of the email chain. Due to the nature of email communication this can reduce the number of documents which need to be reviewed by a considerable amount which will save you time and money.

5. Don’t miss a thing in your data

You can go one step beyond standard keyword searching with Keyword Expansion. 

Most people are familiar with keyword searching and with search engines at our fingertips this is now second nature. Keyword Expansion uses search technology to suggest additional keywords related to those you have already chosen. The suggested keywords will often come up with terms which directly relate to your data set but which you may not have thought of otherwise. 

If you can’t find what you are looking for or want to turn your organisation’s masses of data into a valuable asset, get in touch with one of our consultants.

 

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