Global Oil & Energy Company tests Automation against manual efforts
Building on Valora’s prior engagement with a large, multinational, oil and gas company on a number of Information Governance, Records Management and eDiscovery use cases, Valora was asked to provide a solution to the growing number of Data Subject Access Requests (“DSARs”) coming in as a result of the General Data Protection Regulation (“GDPR”) enacted in Europe in May 2018. With over 90,000 employees, the organization was facing a significant processing backlog. Their manual methods performed by an in-house response team were falling behind. The dedicated team of twelve staff was searching for a technical, automated solution.
Document Analytics & Rules
Recommended File Location
OCR & Text Extraction
PowerHouse Quality Control User Interface (QCUI)
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Polling a large content population, sometimes across multiple departments and languages, for very specific and tailored search terms and metadata, is an arduous task. Requests were frequent, growing, and overwhelming. Valora was tasked with running a solution alongside the current team to see if AutoClassification would out-perform, match, or lag the manual efforts.
Working in tandem with the DSAR response team, Valora configured PowerHouse to mimic the team’s current, labor-intensive process – pulling specific metadata from multiple supplied sources of content. Next we applied a set of disposition rules to determine a) which files were responsive to the DSAR, b) which files contained Personal Data, c) which files required redaction of sensitive, personal, or non-applicable content, d) which files would be produced (generally in their post-redaction format) to the Data Subject, and e) the creation of the final production set of materials for distribution.
After initial processing inside the PowerHouse platform, results were then pushed to the PowerHouse Quality Control User Interface, QCUI, for file-by-file data verification by the DSAR response team. Valora’s aggregated content dashboard technology, BlackCat, was also used to provide a higher level overview of the tagged content across populations, DSARs and time.
Valora built a fully automated system to support the DSAR team in their searches, analysis, redaction and production efforts, making them quicker, more accurate, and more streamlined, which meant less backlog and the ability to keep up with increasing demand. The result was fully tagged DSAR content sorted into their subsequent and relevant buckets for production, with tagging accuracy equivalent to, or better than the manual efforts. Overall, a substantial win!