Attorneys Are Getting Better at Tech But There Are Still Some Challenges
October 24, 2019
The best attorneys put bad actors in prison, but in order to do that they need to gather evidence to support their cases in court. With the plethora of data types and sources, attorneys must organize it for quick recall, but data also comes with its own mistakes. JD Supra reveals the, “Top Five Data Collection Mistakes” and ways to avoid them in the litigation process.
There are two main data types: traditional and nontraditional. Users create traditional data, organize and place it in workflows. Nontraditional workflows comes from sources there have few or no collection or processing procedures. These usually come from social media, chat applications, cloud platforms, and text messages. Attorneys need to determine what data types they are handling in litigation, but be aware of potential mistakes.
The easiest mistake to make is not realize that different data types require different collection methods. Extracting information from a computer requires knowledge about its operating system and manufacturer. Cell phone data has its own complications, such as if the data is backed up on a cloud or if the vendor must be contacted to retrieve metadata. Discovering who owns data is another issue. Data is stored on personal devices, the cloud, third party systems, and more. Ownership becomes questionable as well as if data must be shared if not physically owned. Governance policies, customer workflows, and data maps are necessary in order to address data ownership.
Proportionality cannot be ignored. A court could rule that retrieving data outweighs its usefulness. Any data, however, could change a case:
“As always, the success of this argument will depend on the specific facts of a case. For example, one federal court held that a request for text messages was disproportional to the burden of collecting and producing them even though they had been produced in a pre-litigation investigation because the text messages only added minimal evidentiary value to the case. Litigators must be able to clearly articulate a proportionality argument in order to successfully avoid the production of minimally relevant/useful data.”
Misunderstanding proportionality is understandable, but not recognizing data structure and storage is a beginner’s mistake. In order for eDiscovery algorithms to work, they need to be programmed to scan data from different database structures and storage devices. Programming the algorithm wrong is the same as expecting a US electric appliance to work in another country. Data structure and storage is not universal. Attorneys need to remember to cover all data points, search everything. Another amateur mistake is forgetting to collect data that does not provide context for raw data, it is like trying to decipher a secret code without the cipher key.
These are simple mistakes to make, but with new technology and data types new mistakes will develop. Keeping abreast of new trends, technology, communication methods, and data laws will prevent them from appearing.
Whitney Grace, October 24, 2019
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