Communication is key to business. For evidence of this, just consider the fact that we send 125 billion business emails every day. It’s also the reason why enterprise social networks and work collaboration tools have become so popular. These tools streamline communication, which has a direct impact on productivity. A study of Workplace by Facebook conducted by Forrester Consulting has shown that the platform can increase task efficiency, decision-making, innovation, and onboarding enough to offer an ROI of 400%.

While email and enterprise social networks are both communication tools, they also share another important characteristic: both an email string and a corporate chat conversation are unstructured data. This is important if you consider the modern data landscape in large enterprises. But before we get into that, let’s briefly discuss the difference between structured and unstructured data.  

Structured vs. Unstructured Data

Structured data can best be described as anything that exists within a relational database. In other words, if data resides within a relational database management system (RDBMS)—the basis for SQL (Structured Query Language)—it’s by nature highly structured. A bank account or employee directory are good examples of this. There’s high consistency in terms of fields and values across database entries, so the relational nature of the data is easy to understand and the database is quick to search. 

Unstructured data is anything that does not reside in an RDBMS. And as this definition of unstructured data suggests, a lot of the data in modern enterprises would qualify as such, including PDFs, text documents, spreadsheets, presentations, images, videos, and audio files. 

Importantly, all the communication tools that modern enterprises use—email, mobile text messages, social media, and enterprise collaboration platforms—obviously also exist within the realm of unstructured data (although they do have some structure thanks to metadata). And given how much communication takes place, these sources are responsible for massive amounts of data that organizations aren’t always sure how to deal with.         

The Challenges of Unstructured Data 

According to Forbes, around 80% of enterprise data is unstructured—and more than 70% of companies are unsure how to manage and protect this data. Moreover, data volumes are increasing at an incredible rate. The IDC states that the global datasphere will increase from 33 zettabytes in 2018 to as much 175 zettabytes by 2025—and 30% of this data will need real-time processing. 

For enterprises, this has profound implications. Consider, for instance, the typical litigation process within an enterprise. According to an article by eDiscovery software vendor Logikcull, the American Bar Association estimates that as much as 80% ($42 billion dollars per year) of total litigation spend goes towards document review. 

As data volumes increase, legal teams have more and more documents to collect, process, and review. And given how relevant communication trails typically are to legal proceedings, teams also need to collect and process thousands of emails, text messages, social media posts, and direct messages. Collecting and transforming all of these into records that’ll be defensible in a court of law takes time and money.

Another challenge in the age of so much unstructured data centers around recordkeeping regulations and data security. Regulations such as the GDPR and CCPA, as well as increased consumer pressure, are forcing enterprises to handle information in a responsible manner and respect the privacy of all involved. This means keeping accurate records of all data related to social media channels, website content, and mobile text messages to show regulatory compliance—something that can be difficult to do in a real-time environment where things are constantly evolving.       

Unstructured Data and Enterprise Social Networks

Like email and social media, enterprise social networks—such as Workplace by Facebook, Slack, and Microsoft Teams—are responsible for large volumes of data within enterprises, and this data can be incredibly valuable yet complex to manage.

As is also the case with email, enterprise social networks aren’t merely conversational tools, they also facilitate information sharing and collaboration. While this is useful and can greatly improve productivity, it also means that companies need to carefully consider the legal and data governance implications of any enterprise collaboration tools they implement. As with email, enterprise social networks can be used for inappropriate conversations and unsanctioned data sharing. 

Returning to the challenge of eDiscovery and litigation mentioned earlier, it’s important to consider how enterprise collaboration tools are forcing legal teams to change how they operate.

“Legal teams are used to documents. Not chat rooms. But chat rooms are taking over,” writes Logikcull in a guide on discovery and investigations in Slack. “In one survey, nearly 20% of companies who adopted Slack saw their email use decline by 40 to 60%. Today, if you’re only dealing with emails, you’re missing half the story… With Slack, users can direct message, create chat rooms, share files, edit—or, depending on the context, spoliate—Slack messages from the past, and more,” 

And Slack is certainly not alone in this—all modern collaboration tools are responsible for transforming the eDiscovery process.

Then there’s the challenge of recordkeeping. Within a financial services firm, for instance, the emails of regulated employees (such as registered investment advisors) need to be archived in order to comply with SEC and FINRA regulations. The same is true of internal collaboration tools—internal social media conversations are official records, too—so these need to be archived in order to be ready for an SEC audit. 

Monitoring, Data Loss Prevention, and Legal Hold 

As enterprise social networks continue to supplant email and become the hubs that facilitate internal communication and collaboration, organizations need to implement these tools in a way that ensures they retain a tight hold on data. To do this successfully, companies need to be able to:

• Monitor activity in enterprise collaboration tools to identify inappropriate conversations;
• Put a data loss prevention (DLP) strategy in place that prevents the sharing of sensitive data;
• Place flagged data on legal hold to prevent disposal as part of regular retention scheduling. 

Given the benefits of enterprise collaboration tools, it’s understandable that organizations want to roll them out quickly, but proper implementation is crucial. These enterprise social networks represent a significant new unstructured data source that has to be governed responsibly in order to protect data, comply with regulations, and facilitate eDiscovery.      

Pagefreezer assists companies with the monitoring, collection, and archiving of enterprise social networking data to mitigate risk, prevent data loss, and enforce communication policies. Learn how we can help your organization by speaking to one of our experts.