Hal Marcus of OpenText on managing risk and uncovering value in data


I have been interviewing Hal Marcus since his Recommind days, always getting useful insights into current topics on eDiscovery and analytics.

Recommind is now owned by OpenText and, more recently, OpenText has acquired Guidance Software. Catching up with Hal Marcus at Legaltech in New York, I asked him about the OpenText master plan for these acquisitions.

Hal Marcus said that OpenText’s ambition was to manage the full life-cycle of enterprise information management. The acquisition of Recommind and its strong analytical tools showed that OpenText was serious about discovery. Bringing in Guidance Software and EnCase takes this to a whole new level.

It is the ambition of every eDiscovery company to offer end-to-end management of information. By adding Recommind’s analytical tools and Guidance Software’s forensic tools to OpenText’s existing enterprise information management, OpenText has “the best of breed solution for each of those aspects of the EDRM”. It is not easy for enterprises to collect from any source including the endpoints and EnCase brings that capability.

OpenText has many enterprise clients and this gives open text to deep insight into how companies manage data as discovery technology find its way finds its way into due diligence, breach response, investigations and all the other areas involving data.

The imminent arrival of the General Data Protection Regulation and the increased focus on cyber security have required legal departments to get involved in IT.

GDPR is delivering the justification for investing in information management or, at least, forcing a conversation about it. Hitherto, Hal Marcus says, companies have looked at the individual components of data management – remediating this and fixing that – but the GDPR is forcing an overarching review and pointing up the need for a comprehensive strategy.

It is not all about risk – organisations are also focusing on the value of the data which they hold, creating access to valuable data by eliminating valueless data.

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