legal

Predicting the Future of Information Governance

Bill Tolson 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.

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Finding the Cure for the Healthcare Unstructured Data Problem

Bill Tolson Information Governance , , , , , , ,

Healthcare information/ and records continue to grow with the introduction of new devices and expanding regulatory requirements such as The Affordable Care Act, The Health Insurance Portability and Accountability Act (HIPAA), and the Health Information Technology for Economic and Clinical Health Act (HITECH). In the past, healthcare records were made up of mostly paper forms or structured billing data; relatively easy to categorize, store, and manage.  That trend has been changing as new technologies enable faster and more convenient ways to share and consume medical data.

According to an April 9, 2013 article on ZDNet.com, by 2015, 80% of new healthcare information will be composed of unstructured information; information that’s much harder to classify and manage because it doesn’t conform to the “rows & columns” format used in the past. Examples of unstructured information include clinical notes, emails & attachments, scanned lab reports, office work documents, radiology images, SMS, and instant messages.

Who or what is going to actually manage this growing mountain of unstructured information?

To insure regulatory compliance and the confidentiality and security of this unstructured information, the healthcare industry will have to 1) hire a lot more professionals to manually categorize and mange it or 2) acquire technology to do it automatically.

Looking at the first solution; the cost to have people manually categorize and manage unstructured information would be prohibitively expensive not to mention slow. It also exposes private patient data to even more individuals.  That leaves the second solution; information governance technology. Because of the nature of unstructured information, a technology solution would have to:

  1. Recognize and work with hundreds of data formats
  2. Communicate with the most popular healthcare applications and data repositories
  3. Draw conceptual understanding from “free-form” content so that categorization can be accomplished at an extremely high accuracy rate
  4. Enable proper access security levels based on content
  5. Accurately retain information based on regulatory requirements
  6. Securely and permanently dispose of information when required

An exciting emerging information governance technology that can actually address the above requirements uses the same next generation technology the legal industry has adopted…proactive information governance technology based on conceptual understanding of content,  machine learning and iterative “train by example” capabilities

 

The lifecycle of information

Bill Tolson Information Governance , , , , , , ,

Organizations habitually over-retain information, especially unstructured electronic information, for all kinds of reasons. Many organizations simply have not addressed what to do with it so many of them fall back on relying on individual employees to decide what should be kept and for how long and what should be disposed of. On the opposite end of the spectrum a minority of organizations have tried centralized enterprise content management systems and have found them to be difficult to use so employees find ways around them and end up keeping huge amounts of data locally on their workstations, on removable media, in cloud accounts or on rogue SharePoint sites and are used as “data dumps” with or no records management or IT supervision. Much of this information is transitory, expired, or of questionable business value. Because of this lack of management, information continues to accumulate. This information build-up raises the cost of storage as well as the risk associated with eDiscovery.

In reality, as information ages, it probability of re-use and therefore its value, shrinks quickly. Fred Moore, Founder of Horison Information Strategies, wrote about this concept years ago.

The figure 1 below shows that as data ages, the probability of reuse goes down…very quickly as the amount of saved data rises. Once data has aged 10 to 15 days, its probability of ever being looked at again approaches 1% and as it continues to age approaches but never quite reaches zero (figure 1 – red shading).

Contrast that with the possibility that a large part of any organizational data store has little of no business, legal or regulatory value. In fact the Compliance, Governance and Oversight Counsel (CGOC) conducted a survey in 2012 that showed that on the average, 1% of organizational data is subject to litigation hold, 5% is subject to regulatory retention and 25% had some business value (figure 1 – green shading). This means that approximately 69% of an organizations data store has no business value and could be disposed of without legal, regulatory or business consequences.

The average employee creates, sends, receives and stores conservatively 20 MB of data per day. This means that at the end of 15 business days, they have accumulated 220 MB of new data, at the end of 90 days, 1.26 GB of data and at the end of three years, 15.12 GB of data. So how much of this accumulated data needs to be retained? Again referring to figure 1 below, the blue shaded area represents the information that probably has no legal, regulatory or business value according to the 2012 CGOC survey. At the end of three years, the amount of retained data from a single employee that could be disposed of without adverse effects to the organization is 10.43 GB. Now multiply that by the total number of employees and you are looking at some very large data stores.

Figure 1: The Lifecycle of data

The above lifecycle of data shows us that employees really don’t need all of the data they squirrel away (because its probability of re-use drops to 1% at around 15 days) and based on the CGOC survey, approximately 69% of organizational data is not required for legal, regulatory retention or has business value. The difficult piece of this whole process is how can an organization efficiently determine what data is not needed and dispose of it automatically…

As unstructured data volumes continue to grow, automatic categorization of data is quickly becoming the only way to get ahead of the data flood. Without accurate automated categorization, the ability to find the data you need, quickly, will never be realized. Even better, if data categorization can be based on the meaning of the content, not just a simple rule or keyword match, highly accurate categorization and therefore information governance is achievable.

Healthcare Information Governance Requires a New Urgency

Bill Tolson Information Governance , , , , , , , ,

From safeguarding the privacy of patient medical records to ensuring every staff member can rapidly locate emergency procedures, healthcare organizations have an ethical, legal, and commercial responsibility to protect and manage the information in their care. Inadequate information management processes can result in:

  • A breach of protected health information (PHI) costing millions of dollars and ruined reputations.
  • A situation where accreditation is jeopardized due to a team-member’s inability to demonstrate the location of a critical policy.
  • A premature release of information about a planned merger causing the deal to fail or incurring additional liability.

The benefits of effectively protecting and managing healthcare information are widely recognized but many organizations have struggled to implement effective information governance solutions. Complex technical, organizational, regulatory and cultural challenges have increased implementation risks and costs and have led to relatively high failure rates.  Ultimately, many of these challenges are related to information governance.

In January 2013, The U.S. Department of Health and Human Services published a set of modifications to the HIPAA privacy, security, enforcement and breach notification rules.  These included:

  • Making business associates directly liable for data breaches
  • Clarifying and increasing the breach notification process and penalties
  • Strengthening limitations on data usage for marketing
  • Expanding patient rights to the disclosure of data when they pay cash for care

Effective Healthcare Information Governance steps

Inadvertent or just plain sloppy non-compliance with regulatory requirements can cost your healthcare organization millions of dollars in regulatory fines and legal penalties. For those new to the healthcare information governance topic, below are some suggested steps that will help you move toward reduced risk by implementing more effective information governance processes:

  1. Map out all data and data sources within the enterprise
  2. Develop and/or refresh organization-wide information governance policies and processes
  3. Have your legal counsel review and approve all new and changed policies
  4. Educate all employees and partners, at least annually, on their specific responsibilities
  5. Limit data held exclusively by individual employees
  6. Audit all policies to ensure employee compliance
  7. Enforce penalties for non-compliance

Healthcare information is by nature heterogeneous. While administrative information systems are highly structured, some 80% of healthcare information is unstructured or free form.  Securing and managing large amounts of unstructured patient as well as business data is extremely difficult and costly without an information governance capability that allows you to recognize content immediately, classify content accurately, retain content appropriately and dispose of content defensibly.

Can you wipe your twitter ramblings, and should you?

Bill Tolson Information Governance, Social Media , , , , , , ,

In December of 2011, the Library of Congress and Twitter signed an agreement that will eventually make available every public Tweet ever sent as an archive to the Library of Congress.

While writing a blog post last week, I began  to wonder how long all my twitter postings would be available and who could look at them. For the fun of it, I went back through approximately 6 months of my old twitter postings, re-tweets and replies (yes you can do it, it’s relatively easy and you can look at anyone’s).

 I’ve been pretty good about keeping my twitter posts “business-like” and have steered away from personal stuff like “I just checked in to the Ramada Inn on route 11…can’t wait for the evening to begin!”, or “does anyone know how to setup an off-shore bank account?” or “those jerks over at Company ABC are a bunch of losers”.  But many tweeters aren’t so disciplined and have posted stuff that could come back to haunt them later. I could imagine a perspective employer reviewing a candidate’s twitter history or even worse an attorney conducting research for a case using the public twitter archives to create a timeline.

With that in mind, could you delete your twitter postings and should you? Twitter does allow you to delete specific tweets one at a time but as far as I can determine, Twitter does not give you the ability to delete your entire twitter history short of deactivating your account. From the Twitter website:

How To Delete a Tweet

If you’ve posted something that you’d rather take back, you can remove it easily. When you hover over your Tweet while viewing your home or profile page, you’ll see a few options appear below the message.

To delete one of your Twitter updates:

  1. 1.       Log in to Twitter.com
  2. 2.       Visit your Profile page
  3. 3.       Locate the Tweet you want to delete
  4. 4.       Hover your mouse over the message (as shown below), and click the “Delete” option that appears

Voila! Gone forever… almost. Deleted updates sometimes hang out in Twitter search. They will clear with time.

We do not provide a way to bulk delete Tweets. If you’re looking to get a “fresh start” on your Twitter account without losing your username, the best way to do this is to create a temporary account with a temporary username, and then switch the username between your current account and the temporary account. Please see our article on How to Change Your Username for more info. 

On December 30, 2011, CNET published a story titled “How to delete all your tweets” which highlighted a product called TwitWipe. TwitWipe is a free tool that allows you to delete ALL your past tweets in one fell swoop. This may be handy because you can clean out your twitter account and start fresh without changing your username and dumping all your hard won followers.

This is an interesting capability but I think the more important question is why would you use this drastic of a step? The four most obvious reasons one would want to delete all their twitter postings and start fresh would be:

1.       You went through an unfortunate period in your life that you would rather forget

2.       You were regularly conducting criminal activities through your Twitter account

3.       You are considering a run for the presidency

4.       For whatever reason, you don’t want your twitter postings archived and available at the Library of Congress

The ability to delete ESI can be dangerous if done at the wrong time, especially if civil litigation is anticipated. Deleting a single tweet or every tweet you have ever posted can be construed as destruction of evidence if those tweets could have been relevant in litigation. ESI, no matter its format or where it’s stored, is potentially evidence  and should be at least considered when protecting ESI for litigation hold. Attorneys on both sides need to include social media content like twitter postings in their eDiscovery plans and be sure to warn all custodians about deleting/editing  social media content once litigation is anticipated.