Despite the inroads enterprises have made with digitization, most companies still have a wealth of information that has yet to be digitized. In addition, numerous types of electronic information like video call transcripts, audio recordings, and instant messages exist but are not centralized in a searchable data repository. 

Both examples underscore the challenges of dark data, which Gartner defines as “the information assets organizations collect, process, and store during regular business activities, but generally fail to use for other purposes.” 

The widespread shift to remote working has boosted dark data growth, as the majority of employees have been working in highly distributed and remote environments. Relying on company-owned laptops for virtually all business activities ranging from document-sharing to video calls to email creates a significant amount of dark data. It also introduces an additional data management challenge in that employees are more likely to copy centralized content to their laptops but fail to upload the documents after altering them. 

A recent TechRepublic article examined the risks of not managing dark data. We’ve outlined some of the most significant among them below, including: 

Legal Concerns

Failing to manage dark data can lead to legal, security, and compliance headaches—for example, imagine if your company were to be embroiled in a lawsuit and need access to dark data as part of the discovery process. 

Poor Decision-Making

If properly managed, some components of dark data could reveal insights that could give organizations a competitive advantage. However, not having access to dark data can cause employees to make the wrong decisions for the business. 

Significant Waste 

Lost employee productivity is one example of the waste associated with dark data, as it will take them longer to search and obtain the information they need to do their jobs. In addition, storage costs increase as organizations store data without utilizing it. 

Enterprise Data Silos 

Since dark data is essentially invisible to the business, it also adds to the challenges associated with enterprise data silos, impeding business intelligence efforts.

So, what should organizations do to get a handle on these risks? A good best practice is to create data safekeeping policies and frequently train and retrain employees on them. In addition, conducting audits can ensure that both data and data changes are synchronized between individual workstations and central data repositories.

Addressing dark data can seem like a daunting challenge, but the more that companies can tackle this data in real-time as it’s created, the greater their likelihood of ultimate success. Head over to TechRepublic for more on how to do this effectively.