The Chaos of Collaboration Data: Understanding the New Unstructured Data Set

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In this special guest feature, Chris Plescia, Chief Technology Evangelist, Aware, highlights how conversational platforms and tools such as Slack, Microsoft Teams, Yammer, and Workplace from Meta have made the digital workplace more productive, social and collaborative but they’ve also introduced a non-standard data set into the enterprise. Chris helps customers to optimize their collaboration environments, minimize compliance and security risk and capture employee insights and value. Prior to Aware, Chris was Chief Operating Officer, Auto Club Trust, AAA Banking. He previously was with AIG as SVP – Global Head of Employee Collaboration and Digital Operations and served as Head of Digital, Collaboration and Data Analytics at Nationwide.

A McKinsey report found that effective communication increased productivity by 25-35%, and business-centric collaboration tools are fueling that growth. Utilization and adoption had been growing steadily over time, with the onset of the pandemic, 2020 became an explosive year for collaboration. 

Conversational platforms have made the digital workplace more productive, social, and collaborative but they’ve also introduced a new unmanaged set of business records. Collaboration data holds authentic and valuable insights, but also presents new risks around data management, compliance monitoring, search, and discovery.

Collaboration data does not conform to other data types in the enterprise

Collaborative tools have reinvented the way the workforce communicates, makes decisions, and executes business processes, unseating email as the primary channel for conversations and communications. 

Unlike the linear logic of email chains, these new channels fragment conversations and split them across forums. Compared to email, this type of conversational data is largely informal, nuanced and unstructured, creating a new data set with many beneficial aspects as well as unforeseen risks.

Messaging relies heavily on shorthand, slang and reactions and is often spread across public or private channels/messages. These can be quickly commented upon, edited, forwarded, and even deleted, putting full control in the author’s hands. This has created a new, modern form of business record that needs to be understood and managed by governance, risk, and compliance teams.

The new Collaboration Ecosystem

Collaboration is nuanced and varies between enterprises. While messaging platforms such as Slack, Teams, or Workplace, are the most used platforms, collaboration extends across many other solutions, including:

  • Audio-Video solutions — Zoom, WebEx, Skype, RingCentral
  • Productivity tools — O365, Google Workspace, iWork
  • File sharing applications — Box, Google Drive, OneDrive
  • CRMs — Salesforce, HubSpot, Zendesk
  • Developer tools — GitHub, Bitbucket, Atlassian

Research shows that 91% of organizations use multiple applications. Almost all of them incorporate messaging and video collaboration features. The key is bringing structure to this tangled ecosystem, implementing monitoring and management guardrails that mitigate risk. While at the same time, optimizing the balance between strict controls and usability. 

The Challenges of Non-Standard Data

Legal and regulatory scrutiny continues to expand, requiring organizations to prove stronger management and governance over this dataset. Many IT organizations are playing catch-up as the pandemic forced an accelerated deployment of new tools without having the prerequisite time to establish the checks and balances required to safeguard the data. Collaboration tools are now widely embraced across the organization, but many information security and compliance teams lack formal governance policies and tooling to manage these records. This concept isn’t new. From paper to phones to email, workplaces have learned to transition with technology and developed controls around this consistent data. But those transitions had decades to evolve and mature. Modern collaboration exploded in just a few years and this data is much different than its predecessors.

New challenges and regulatory expectations have now been set forth around managing these environments. Table stakes include the ability to actively monitor for compliance, intelligently search and discover across channels and platforms, and to have guardrails around your data for things like retention, deletion, holds and protection. 

Another key differentiator is being able to understand the sentiment and context of a message(s). Recreating the conversation five or ten messages on either side of the target communication, even after deletion, is game changing in instigations. Collaboration platforms include so many connections that it can be hard to know where to draw the line. What is clear, however, is that IT, Compliance and Legal departments must reach agreement on the policies and processes that fit their organization needs.

 Considerations of Collaboration Data Collection

Defining the controls around collaboration data is the start of good management but doesn’t solve the complexity of collection. How do you prove that collaboration messages are relevant and haven’t been manipulated? Here organizations may find themselves at odds with the apps they use to increase productivity. Most apps enable custodians to modify or remove the messages they’ve posted. Capturing and reproducing those revisions is a challenge for information security.

With traditional tools, collecting this data is no longer a one-person job, but the role of an entire team charged with finding the needles in the haystack. Management solutions must span multiple sources, enforcing regulatory, compliance and data governance direction. Additionally, many discover that collaboration apps lack visibility into the true extent of the data. A single message could include a hyperlink to a storage folder containing a thousand documents as well as screen shots with sensitive data. These so-called “modern attachments” are top of mind for data collection experts. Leading organizations are solving these deficiencies by implementing AI based governance solutions with Machine Learning and Natural Language Processing to cut through the clutter and find the “needles” much quicker and with fewer resources. 

Finding the Balance with Collaboration Data Management

Granular retention policies are the norm across most organizations, but these can be harder to apply across collaboration solutions. This can lead to messages and documents being scattered and accessible within the ecosystem long after they’ve served their usefulness. At this point, the risks of this data outweigh the benefits.

When establishing retention policies for collaboration data, organizations should evaluate the risk of retaining information against the cost of losing the knowledge it contains. Placing a value on the data will help records management teams as they set retention policies.

The risks of failing to safeguard collaboration are clear. Striking a balance between controls and insights is crucial. Too many controls ruin the experience and drive employees away from authorized tools and toward Shadow IT actions. This exacerbates risk by creating hidden environments beyond the organization’s control, often leading to fines and negative publicity. 

In a safe and innovative workplace, collaboration is where content, conversation, and people come together. Only in a compliant and secure information environment, can collaboration data yield business value.

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