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Download Our Newest Deep Dive Case Study on Pandora Media

How Pandora Tuned In to Information Governance
To Take Control of Its Most Sensitive and Valuable Information Assets

An IGI Case Study

Usually when we think "Information Governance," we think traditional, large, litigated and regulated organizations. But as more and more organizations come to understand the value of IG, this image is rapidly changing. Recently, Pandora Media — a juggernaut in the streaming music business — partnered with IGI Supporter Active Navigation and its experts in governance and file analysis on a major IG project. We were fortunate enough to be able to do a deep dive on this project and bring the details to you.

Download the latest entry in our IG At Work series to learn:

  • How Pandora got rid of 60 percent of its unstructured data.
  • What it took for the company to identify and protect its most valuable and sensitive data. 
  • How Pandora developed policies for governing unstructured information.
  • How Pandora built executive support for IG. 
  • How Pandora used file analysis software to reach its IG goals.
  • How Pandora was able to sell the merits of IG to its employees.

The company that emerged on the other side of this critical IG project was more efficient, more versatile and more competitive. And their IG program only continues to grow in its sophistication and impact.

Click here to access the case study in the IGI Community.

 

Guest Post: Privacy Lost – Can Information Privacy Survive the Era of Analytics?

Authored by Kon Leong, CEO and Founder of ZL Technologies

In a recent article published in Harvard Business Review, I discussed the growing capabilities of analytics technologies, and the need to be conscious of the privacy implications that accompany them. Though I believe the piece to be of general interest, it also offered focused advice for a management audience. Now, I would like to take a step back and expand the data privacy conversation, as well as provide some insight for the executive level.

Decoding Data Privacy

When I published the initial article, several of my colleagues responded that they believe data created at work necessarily cannot constitute personal information, and therefore belongs solely to the employer. Though I may have at one point agreed with this statement, my thinking has shifted in recent years. The influx of new data sources has given rise to more personal data being created—at work, at home, everywhere—while it simultaneously becomes harder to separate personal data from corporate data. In light of these changes, it could be time we rethink what privacy in the workplace really means.

In a corporate context, some might define privacy as meaning no organizational knowledge of sensitive, personal information. Due to regulatory and legal requirements to collect and preserve data, and the increasing rate at which such data is created, this is quickly becoming unrealistic. Do organizations then do their best to ignore this data, until it’s needed by Legal or Compliance? In today’s age, turning a blind eye to sensitive information and pretending it doesn’t exist is akin to the philosophy of “see no evil, hear no evil, speak no evil”: The problem is that just because sensitive information goes untouched, doesn’t necessarily remove any or all privacy and security concerns.

Because it’s near impossible for us to keep personal data out of the organizational reach, more reasonably, modern privacy might simply come to mean that personal data cannot be improperly utilized, processed, or accessed. Although counterintuitive, in order for this type of system to work, an organization must have complete command over its data. In other words, rather than knowing as little as possible, this new information governance approach seeks to know more in order to exert control over data.

The following insight highlights this paradox: The CIA’s system of managing classified information could arguably be very intrusive because of the oftentimes private nature of the content it manages, and the expansiveness of its reach. However, thanks to classification schemes and access privileges, data can only be accessed for its intended purposes, thus ensuring privacy is maintained.

Privacy by Design

Although it can be extremely effective, the governance approach to privacy is easier said than done. Privacy can’t just be an afterthought. It must be instituted by design, at the architectural level of an organization’s information strategy.

Before going down this path, organizations should consider convening an information governance committee to determine what kind of compliance and ethical values they want the latest information technologies to usher in. The committee can help define corporate policies on gathering, handling, managing and analyzing what is perhaps the most significant asset of the modern enterprise: information.

Concurrently, begin internal assessments of employee values on privacy, ethics, and fair use of data. You may need to account for significant cultural and regulatory variations across different regions and countries. Such findings can then inform and guide the information governance committee in creating policies down the line.

The Road Ahead

When I published the original article in Harvard Business Review, I hoped to jumpstart the information privacy conversation. When compared to Europe, it’s hard to ignore the fact that the U.S. perspective towards privacy is less developed. However, with data growth only increasing, and new ways to track, monitor, and analyze individuals springing up all the time, it’s a conversation that’s getting harder to avoid, within living rooms and boardrooms alike.

These reasons alone might not be enough to get the U.S to rethink privacy. But if money talks, fines of up to 4% of global sales should be at least enough to get the ball rolling once the GDPR hits next May. Let’s just hope that for companies who wait until then to start planning, it’s not too little, too late.

 

Hidden Bias in the Black Box: Info Gov as a Key Check to Algorithmic Bias

by Jason R. Baron, Drinker Biddle & Reath, as seen on Legaltech News

With each passing day, we are 
 increasingly living in an algorithmic universe, due to the easy accumulation of big data. In our personal lives, we experience being in a 24/7 world of "filter bubbles," where Facebook has the ability to customize how liberal or conservative one's newsfeed is based on prior postings; Google personalizes ads popping up on Gmail based on the content of our conversations; and merchants like Amazon and Pandora feed us personalized recommendations based on our prior purchases and everything we click on.

While (at least in theory) we remain free in our personal lives to make choices in continuing to use these applications or not, increasingly often what we see is the result of hidden bias in the software. Similarly, in the workplace, the use of black box algorithms holds the potential of introducing certain types of bias without an employee's or prospective employee's knowledge. The question we wish to address here: From an information governance perspective, how can management provide some kind of check on the sometimes naïve, sometimes sophisticated use of algorithms in the corporate environment?

Algorithms in the Wild

An early, well-known example of the surprising power of algorithms was Target's use of software that, based on purchasing data (e.g., who was buying unscented lotions, cotton balls, etc.), was spookily able to predict whether a customer was likely pregnant. Target sent coupons for baby products to a Minnesota teenager's home before the teenager's father knew about the pregnancy, leading to a bad public relations episode. A different example is Massachusetts' use of a mobile app called Street Bump, where smartphones riding over potholes and the like would automatically report their location for local government to fix. The problem: the resulting map of potholes corresponded closely with the demographically more well-off areas of the city, as those were the areas where individuals knew to download the mobile app and could afford smartphones in the first place.

In workplace hiring decisions, facially neutral algorithms sometimes reveal a hidden bias based on how features are selected and weighted, or where certain variables used in the algorithm essentially function as "proxies" for real world racial or ethnic differences. For example, a software feature using the variable "commuting distance from work" as a factor in deciding which candidates to hire may, depending on local geography, discriminate based on race. As Gideon Mann and Cathy O'Neill stated in Harvard Business Review (12/9/16), "When humans build algorithmic screening software, they may unintentionally determine which applicants will be selected or rejected based on outdated information—going back to a time when there were fewer women in the workforce, for example—leading to a legally and morally unacceptable result."

Once on the job, employees may experience a very different kind of filter bias through software targeting the risk of internal threats to the company. The more advanced programs coming onto the market use sentiment analysis (e.g., algorithms looking at language used in emails) to predict whether certain individuals are more likely to display anger or other inappropriate behavior in the workplace. This capacity can be combined with matching up external sources of data on individuals obtained online, including credit report updates, crime reports, and certain types of medical information, to essentially triage the employee population into "high-risk" and lower risk categories, so as to target the keystrokes made by a few. If this all sounds like we have truly now entered a pre-crime, Minority Report world, it does.

IG and Its Role with Algorithms

What can or should be done? Mann & O'Neill suggest to avoid making decisions solely by use of an algorithm, but include what they call "algorithm-informed" individuals. They further suggest, "[w]e need to audit and modify algorithms so that they do not perpetuate inequities in businesses and society," with audits to be carried out either by inside experts or by hiring outside professionals. These are both sound suggestions.

Advocates of information governance (IG) argue that corporations with an IG program in place have a built-in mechanism to escalate data-related issues to a standing committee, consisting of either C-suite representatives or their delegates. In a growing number of corporate models, an individual with some kind of IG designation in their title will have been given authority to call together ad hoc groups to resolve specific data policy issues.

One could well imagine a chief information governance officer convening an ad hoc task force of the IG council, including a C-suite representative of the corporate human relations (HR) department, along with the person who approved or manages the data analytics software used by HR and a senior counsel, to perform the kind of "audit" of hiring practices envisioned above. Similarly, an ad hoc task force including the chief information security officer, senior HR office personnel, and other IT representatives and senior counsel could be asked to review how well internal monitoring of employees is working, and how much transparency or notice should be given to staff on such monitoring.

Along these lines, organizations might consider tasking a group of individuals—under the auspices either of the IG structure or as a freestanding committee—to perform a similar function to a present-day institutional review board, but limited to predictive software's effect on human subjects. Such an "algorithm review board" (ARB) would be tasked to provide approval and/or oversight of any use of analytics in the workplace aimed at targeting present employees or prospective hires, so as to serve as a check against possible hidden bias or a lack of notice where appropriate.

Some corporations (Microsoft and Facebook) have taken initial steps to implement, at least on a selected basis, an ethics review board being used in an equivalent way to an ARB. However, the practice remains rare across all industry verticals, notwithstanding the growing power of analytics in all aspects of daily life.

In his book, "The Black Box Society: The Secret Algorithms That Control Money and Information," law professor Frank Pasquale states that "authority is increasingly expressed algorithmically," and that "[d]ecisions that used to be based on human reflection are now made automatically." But, as computer scientist Suresh Venkatasubramanian has put it, "The irony is that the more we design artificial intelligence technology that successfully mimics humans, the more that A.I. is learning in a way that we do, with all of our biases and limitations."

This new reality calls for consideration of some kind of human intervention to serve as a quality control check on the black box (even if it means humans employing a second algorithm to check for bias in the first!) In the coming world we live and work in, adoption of some kind of IG framework that includes reviewing the possibility of algorithmic bias in the workplace will be appreciated by an increasingly sophisticated populace.




Jason R. Baron is Of Counsel at Drinker Biddle & Reath LLP in Washington, D.C.

 

Information Governance Benchmark 2017: The Business Value of Long-Term Digital Information

In 2016 we were pleased to work closely with IGI Supporter Preservica to benchmark the state of the industry on the critical issue of governing and preserving long-term digital information. Our Benchmark Report exposed the troubling dynamic that while virtually every organization (98%) needs digital information for longer than ten years, very few (16%) have a viable approach.

This year, we dig even deeper, trying to get to the bottom of this dysfunctional dynamic and learn what IG professionals are doing about it.

The upshot?

Our 2017 research could not be clearer: long-term digital information is more important than ever. It's driving business value and protecting organizations from risk. It is also proliferating, and can be found in more business functions and systems that before. Finally, the consequences of failing to properly govern and preserve long-term digital information only grow graver, with the impact felt all the way up to the CEO and board of directors.

Here are some additional highlights:

It’s the C-suite that suffers most. IG professionals told us that their CEOs, General Counsels, heads of Records Management, CIOs, and Boards of Directors are those most affected by failure in this area. Dropping the ball on governing and preserving long-term digital information not only creates multiple sources of legal, security, and compliance risks, but it also starves the organization of the information raw materials it needs to understand what happened so it can intelligently predict what will happen. As big data technologies and techniques continue to radically improve our ability to harness our data, this failure will only grow as a grave threat to competitiveness and innovation.

Business value rises to compliment risk. Value and risk are two sides of the same coin –a dynamic that has played out since the very beginning of commerce itself. But while legal and regulatory requirements have long driven preservation and governance of long-term digital information, the quest for business value is rising as a major driver too. In fact, the vast majority of organizations (83%) realize (or plan to realize) direct business value from their long-term digital information, targeting areas like market analysis, product development, and customer service.

Proliferation across systems and functions. While it is no surprise that collaboration environments (e.g., file sync and share, enterprise content management) are identified by IG professionals as the most likely location for long-term digital information, we were surprised by other systems in the top five, including accounting and transactional systems. Long-term digital information is proliferating.

Awareness of technological solutions lags. Why do organizations struggle to realize business value from their long-term digital information? IG professionals told us that two of the biggest reasons are organizational immaturity and a lack of proper tools and technology. At the same time, they told us that capabilities like “ensuring readability and usability of information” and “proving authenticity and trustworthiness” are critical to their ability to govern and preserve long-term digital information. These are capabilities that can in fact only be delivered through technology, and in fact technology that has been designed specifically to address the range of challenges inherent to long-term digital information. These technologies are available today, and it is disappointing to see that awareness of them and access to them continues to plague organizations.

We have captured additional insights in a series of infographics that we encourage you to download and put to good use as you build support for solving this problem in your organization. It was a pleasure to work with Preservica on this research, and we hope you get value from its insights. We look forward to bringing you the next benchmark in 2018.

Click here to view & download the Preservica 2017 Benchmark Infographics in the IGI Community.

 

Guest Post: Preventing the Surprise Attack of the Email Monster

An Integro White Paper

Introduction
When one thinks of a monster, you likely drudge up some sort of creature that wreaks havoc at will, always lurking behind the scenes waiting for the most inopportune time to appear, then emerging and causing untold damage to everything in its path as it rages out of control. The worst kind of monster being the one that continues to grow unchecked.

Ironically, this same description fits company email when it is unceremoniously archived en masse. It sits quietly squirreled away in massive files, expanding at incredible rates, stockpiling seemingly harmless dialog. As the email archive balloons, it consumes ever more resources and then without warning surfaces surprising conversations that create a potentially harmful scenario for the company as it faces litigation. Fortunately, there is a way to effectively get control and manage this monster to reduce risk, avoid runaway archiving costs and improve litigation preparedness.

Five to six years ago, email management was thought of as an interesting idea but it seemed easier to stick with the prevailing philosophy of storing everything forever. Storage was believed to be cheap, search was easy and most tools to manage email were considered cumbersome.

What executives didn’t foresee when making this decision was that the exponential growth in content, combined with the increase in litigation activity and heightened threat of breach, would end up making the ‘store everything’ decision an unsustainable approach of monstrous proportions.

Doing The Math
According to the Radicati Group’s Email Statistics Report, 2015-2019, in 2015, the number of business emails sent and received per user per day totals 122 emails per day. This figure continues to show growth and is expected to average 126 messages sent and received per business user by the end of 2019.

When you consider an employee handles approximately 122 emails a day, the volume of email for a 5000-person organization over a work week of five business days would be more than 3 million emails. Over a year that would be more than 220 million emails.

The volume of business information being retained has come into focus as organizations see their Information Technology budgets rapidly being consumed by the ever-growing cost to store the burgeoning volumes of information.

Not only is archiving all your email expensive in terms of gobbling up today’s available dollars, it is also eating away at the organization’s ability to evolve since strategic initiative funding must be sacrificed to the burden of storage costs.

Frightening Thoughts for Corporate Counsel
When the Federal Rules of Civil Procedure were modified in 2006 to address the issue of electronically stored information (ESI), it changed the handling of electronic evidence which in turn changed the way cases are argued and evidence is collected and preserved. It became clear to the business world that eDiscovery was challenging, costly and extremely difficult to manage. Although the need exists to be ‘eDiscovery ready’---having proper governance and defensible preservation and disposition of ESI (including email)--- achieving success in this area still seems elusive for most organizations.

Besides the risk of over retaining information by archiving everything, it is simply too expensive during the eDiscovery process to sort through all the electronic water cooler chat that happens on a daily basis to find evidence germane to pending litigation. Any company that has ever had to write a check to cover eDiscovery costs knows they need to find a better solution than wholesale archiving of email content.

They also know that without changing their email management strategy, each eDiscovery will become ever more costly with more email to search through and more email that matches preservation criteria.

Enforcing email management polices has also been further complicated by the growth in the disconnected user base resulting from expanded access capabilities. Employees may be accessing the mail system from a smartphone, tablet or other existing or future devices or access points, yet organizations still need to enable email management policies regardless of how their employees are interacting with the system.

Attempts at Dealing with the Email Monster
To date, business policy regarding the retention management of email was established not based upon what was proper and best for the business, but instead upon the limited tools available to enforce policy. This unfortunate reality has fostered ineffective email management policies of the past decade including:

  • Keeping it all – the most common archiving mistake from the last decade which has caused the over-retention challenges we see in this decade.
  • Placing mailbox size quota on the whole mailbox--- ignoring the value of individual emails. When the users hit the limit and find themselves in ‘email jail,’ users sort by size and delete the largest emails. Thus keeping the clutter of smaller emails and likely losing important emails.
  • Personal over-archiving – many firms addressed the system storage problem by allowing users to save email in files on their local hard drive. This only enabled user over-retention and exposes firms to massive eDiscovery headaches and costs.
  • Deleting all email at “x” number of days – this obviously fails considering that records do exist in email and the company is wholesale disposing of them. It is also highly disruptive to end users and they’ll pursue workarounds causing even greater issues for information governance.

The above approaches fail considering that it is not the age, size, sender or recipient that determines the value of individual messages. The value of email messages, just like with paper, is determined by what the message says. Most messages are transient, and of fleeting value. A few emails document the business of the organization, and others are helpful to the users in performing their job duties. Thus, classification of email based upon content value is imperative. Two divergent camps have emerged:

  • Auto classification – while attractive for obvious reasons, this has proven unsuccessful due to the costs and level of effort required to train the auto classification software, and considering the highly unstructured, colloquial and brief nature of email.
  • Manual classification – While users know their email the best, many attempts have suffered due to the approaches and tools provided to enable the user to do this easily and quickly.

The best approach has proven to be an elegant blend of auto and manual classification. Automation and ease-of-use are critical, and the time expiration and size quota features must be leveraged intelligently. This, combined with executive support and good communications, enables firms to achieve the goal of proper email retention and governance, including defensible disposition of the majority of email as transient content.

Landing on the Critical Fix List
The original driver of email management was systems efficiency and regulations in the securities industry, which led to archiving. Archiving all email has simply proven untenable. The new drivers can be summarized as:

  • Reduce risk posed by email that was unnecessarily retained
  • Reduce eDiscovery costs of searching and reviewing oceans of clutter
  • Reduce runaway storage costs

Any one or a combination of these factors has caused email management to rise to the top of many organizations’ critical fix list.

Managing the Email Monster with Value-Based Information Governance
Most organizations are moving envelopes through their email system but they don’t know what is in them. With Integro Email Manager™, organizations gain visibility into what is inside the envelope so that informed decisions can be made, based on actual content versus basic email identifiers, and avoid an embarrassing and perhaps costly surprise email surfacing in the future.

Integro Email Manager offers value-based information governance that applies Auto Classification with Human Oversight™, customized to meet your specific business needs. It enables your organization to:

  • Properly retain and govern what’s important
  • Dispose of what you don’t need as early as possible
  • Avoid disrupting the productivity of the end user

When email is received, Integro Email Manager automatically evaluates the content of all messages and calculates its value. Typically this evaluation will only identify a few messages that qualify as relevant business communications – a business record. These few messages, that exceed the set probability thresholds, will then be declared and classified automatically as records. If Integro Email Manager’s confidence rating on a message is close to record caliber, a suggestion will be offered to the user with its confidence rating and suggested records category.

Importantly, the employee remains in control and can change the classification based on their personal knowledge of the email. This type of consideration is only necessary on a few of the messages received each day and only takes a moment. Users can also quickly tag messages as records when email is sent, or use their own folders to auto-tag messages as records. The same tagging method also enables users to keep messages longer in a centrally-managed, personal storage. The majority of messages will be auto disposed per a transient, short retention policy.

The Integro solution includes SmartAssist®, which uses contextual classification to provide suggestions. SmartAssist is initially trained with example emails but then continues to learn on the fly at the user level as it receives feedback based on user work patterns. SmartAssist is unique to Integro Email Manager and enables companies to gain the support of its workforce to achieve the goals of true value based retention.

Integro Email Manager eases cultural adoption because you can start with generous retention periods and refine policy overtime in a stepped fashion. Employees are able to remain in control of their individual work habits as they create and name their own folders they plan to use. With a click of a button these custom folders map to the corporate file plan. In addition to self-managed folders, users can tag the few important messages where they are, anywhere in the mailbox, to be retained longer for personal use or as company records. Most importantly, emails can be tagged as the message is sent and all internal recipients easily see the records designation.

Integro Email Manager (IEM) is the only proactive email content management solution for Notes, Exchange, and Office365, enabling organizations to keep what’s important and eliminate what’s not. IEM can govern email in place or can be integrated with leading ECM systems.

While this solution can assist companies across industries, it is an ideal fit for any company that has any one or combination of the following attributes:

  • Large base of email users; typically starting at around 2,000 employees
  • Regulated industries
  • Litigation risk or activity

 

 

Guest Post: Big Data From Employees Lead to Big Risk For Employers

This article was originally published on The Relativity Blog. It was written by Sam Bock, editor of The Relativity Blog and a member of the marketing communications team at kCura.

Between Wikileaks, tech experts, and the Federal Trade Commission, we have no shortage of sources reminding us on an almost daily basis that the Information Age brings both invaluable new resources and technology, and a significant threat to personal privacy. Data is everywhere, and it’s accessible by more entities than ever—including employers.

To get to the heart of how employees understand data privacy and how their online behavior at work can impact it, kCura recently commissioned a survey conducted by Harris Poll among 1,013 US adults age 18 and older who were employed full-time or part-time, working in a traditional office setting for at least 50 percent of the time, and are not freelancers (referred to as “employees” throughout).

We learned that although nearly all employees (98 percent) say their privacy is important to them, the majority (60 percent) have used their personal device in some way while connected to their company’s WiFi, which potentially sacrifices that privacy while at work. Here’s a look at the results and how employers can protect themselves against excess data proliferation.

Check out the full report for more insight into the data, a method statement for the survey, and more insights.