Ask the Magic 8-Ball; “Is Predictive Defensible Disposal Possible?”


The Good Ole Days of Paper Shredding

In my early career, shred days – the scheduled annual activity where the company ordered all employees to wander through all their paper records to determine what should be disposed of, were common place. At the government contractor I worked for, we actually wheeled our boxes out to the parking lot to a very large truck that had huge industrial shredders in the back. Once the boxes of documents were shredded, we were told to walk them over to a second truck, a burn truck, where we, as the records custodian, would actually verify that all of our records were destroyed. These shred days were a way to actually collect, verify and yes physically shred all the paper records that had gone beyond their retention period over the preceding year.

The Magic 8-Ball says Shred Days aren’t Defensible

Nowadays, this type of activity carries some negative connotations with it and is much more risky. Take for example the recent case of Rambus vs SK Hynix. In this case U.S District Judge Ronald Whyte in San Jose reversed his own prior ruling from a 2009 case where he had originally issued a judgment against SK Hynix, awarding Rambus Inc. $397 million in a patent infringement case. In his reversal this year, Judge Whyte ruled that Rambus Inc. had spoliated documents in bad faith when it hosted company-wide “shred days” in 1998, 1999, and 2000. Judge Whyte found that Rambus could have reasonably foreseen litigation against Hynix as early as 1998, and that therefore Rambus engaged in willful spoliation during the three “shred days” (a finding of spoliation can be based on inadvertent destruction of evidence as well). Because of this recent spoliation ruling, the Judge reduced the prior Rambus award from $397 million to $215 million, a cost to Rambus of $182 million.

Another well know example of sudden retention/disposition policy activity that caused unintended consequences is the Arthur Andersen/Enron example. During the Enron case, Enron’s accounting firm sent out the following email to some of its employees:

 

 

This email was a key reason why Arthur Andersen ceased to exist shortly after the case concluded. Arthur Andersen was charged with and found guilty of obstruction of justice for shredding the thousands of documents and deleting emails and company files that tied the firm to its audit of Enron. Less than 1 year after that email was sent, Arthur Andersen surrendered its CPA license on August 31, 2002, and 85,000 employees lost their jobs.

Learning from the Past – Defensible Disposal

These cases highlight the need for a true information governance process including a truly defensible disposal capability. In these instances, an information governance process would have been capturing, indexing, applying retention policies, protecting content on litigation hold and disposing of content beyond the retention schedule and not on legal hold… automatically, based on documented and approved legally defensible policies. A documented and approved process which is consistently followed and has proper safeguards goes a long way with the courts to show good faith intent to manage content and protect that content subject to anticipated litigation.

To successfully automate the disposal of unneeded information in a consistently defensible manner, auto-categorization applications must have the ability to conceptually understand the meaning in unstructured content so that only content meeting your retention policies, regardless of language, is classified as subject to retention.

Taking Defensible Disposal to the Next Level – Predictive Disposition

A defensible disposal solution which incorporates the ability to conceptually understand content meaning, and which incorporates an iterative training process including “train by example,” in a human supervised workflow provides accurate predictive retention and disposition automation.

Moving away from manual, employee-based information governance to automated information retention and disposition with truly accurate (95 to 99%) and consistent meaning-based predictive information governance will provide the defensibility that organizations require today to keep their information repositories up to date.

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Predicting the Future of Information Governance


Information Anarchy

Information growth is out of control. The compound average growth rate for digital information is estimated to be 61.7%. According to a 2011 IDC study, 90% of all data created in the next decade will be of the unstructured variety. These facts are making it almost impossible for organizations to actually capture, manage, store, share and dispose of this data in any meaningful way that will benefit the organization.

Successful organizations run on and are dependent on information. But information is valuable to an organization only if you know where it is, what’s in it, and what is shareable or in other words… managed. In the past, organizations have relied on end-users to decide what should be kept, where and for how long. In fact 75% of data today is generated and controlled by individuals. In most cases this practice is ineffective and causes what many refer to as “covert orunderground archiving”, the act of individuals keeping everything in their own unmanaged local archives. These underground archives effectively lock most of the organization’s information away, hidden from everyone else in the organization.

This growing mass of information has brought us to an inflection point; get control of your information to enable innovation, profit and growth, or continue down your current path of information anarchy and choke on your competitor’s dust.

 

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Choosing the Right Path

How does an organization ensure this infection point is navigated correctly? Information Governance. You must get control of all your information by employing the proven processes and technologies to allow you to create, store, find, share and dispose of information in an automated and intelligent manner.

An effective information governance process optimizes overall information value by ensuring the right information is retained and quickly available for business, regulatory, and legal requirements.  This process reduces regulatory and legal risk,  insures needed data can be found quickly and is secured for litigation,  reduces overall eDiscovery costs, and provides structure to unstructured information so that employees can be more productive.

Predicting the Future of Information Governance

Predictive Governance is the bridge across the inflection point. It combines machine-learning technology with human expertise and direction to automate your information governance tasks. Using this proven human-machine iterative training capability,Predictive Governance is able to accurately automate the concept-based categorization, data enrichment and management of all your enterprise data to reduce costs, reduce risks, enable information sharing and mitigate the strain of information overload.

Automating information governance so that all enterprise data is captured, granularity evaluated for legal requirements, regulatory compliance, or business value and stored or disposed of in a defensible manner is the only way for organizations to move to the next level of information governance.