Ever since Relativity announced their new GenAI aiR suite of tools based on OpenAI's GPT-4 model,...
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A DSAR — or Data Subject Access Request — is a request made to an organisation or company (the data controller) by an individual (the data subject) for all data the controller holds on the subject.
Anyone can submit a DSAR, and with a legal one-month deadline, they can often bring unwanted pressures to businesses.
The process of completing a DSAR is similar to a typical eDiscovery project. This means, for a company like Altlaw, there's no difficulty in modifying workflows to suit a DSAR matter.
Read on to learn how we helped an in-house legal department create a more efficient and repeatable DSAR process using various analytics.
An in-house legal department for a large-scale business approached us to streamline their DSAR process.
As a large business, it wasn't untypical that a regular stream of DSARs came through every month. Due to this, the company was spending too much time on their DSAR process and wanted to streamline it.
As well as a more streamlined process, they wanted a repeatable way of handling DSARs that could be applied to every request.
To begin with, we utilised deduplication and email threading as part of the Early Case Assessment (ECA) phase to reduce the number of documents that required analysis.
With many DSARs, the contents of several inboxes usually result in overlapping and duplicate communication. Applying these tools allowed us to drastically reduce the amount of data required for review.
After the amount of data decreased, the remaining documents were subjected to concept clustering. This analytics tool provides a high-level overview of the themes present within a dataset.
The reviewers in this case then reviewed a 30% sample of documents from each cluster, searching for relevant documents. If a relevant document was found within the 30% sample, then the remaining portion of the cluster was reviewed.
The cluster was removed from further review if no relevant documents were found.
Therefore, in principle, there was a 70% reduction in time reviewing certain clusters, meaning fewer hours combing through their data.
By configuring an approach that doesn't depend on the subject matter, the process can be easily replicated, meaning the company can apply it to any DSAR that falls into its lap.
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