For many organizations, the widespread use of decentralized tools, apps, and cloud provider platforms by individual teams is both a blessing and a curse.
On the one hand, it gives employees maximum flexibility and control over the work-related technologies they use.
VP of Product Marketing, Datadobi.
On the other hand, the proliferation of departmental tools and platforms represents a significant management and visibility challenge for IT management tasked with maintaining oversight of data, storage, and compliance.
In the worst-case scenarios, the data generated by these tools can quickly grow beyond the reach of existing governance frameworks, introducing inefficiencies and compliance risks.
Adding to the challenge is the proliferation of SaaS and cloud services that promise speed, flexibility, and ease of use. As a result, business units, teams, and individual employees increasingly bypass established IT procurement cycles to adopt what they need, when they need it.
A sprawling data landscape
As organizations have embraced more cloud and SaaS solutions across departments, the resulting decentralization has created what many now call “data sprawl.” Shadow IT is also extremely common.
According to one study by Gartner, by 2027, “75% of employees will acquire, modify, or create technology outside IT’s visibility – up from 41% in 2022.”
The cumulative effect of this unfettered technology adoption is a fragmented, sprawling data landscape, much of which also exists outside organizational control.
Business-related information (from mundane to sensitive) is routinely scattered across multiple SaaS platforms, personal devices, and unmanaged cloud storage.
Add to this the enormous popularity of third-party AI apps, and IT teams have a monumental job on their hands to retain control.
Much of this material takes the form of unstructured data, such as documents, images, emails, and other files, that resist easy organization, making oversight even harder.
While FinOps practices, which are frameworks for governing and optimizing cloud spending across departments, have helped organizations rein in spending on cloud tools, they have done little to address the growing visibility problem around the data those tools generate.
This level of decentralization makes it difficult to know where critical data resides, who owns it, and how securely it’s being managed. The result is a situation where data grows faster than governance can keep up – driving inefficiency, wasting storage resources, and complicating compliance.
For organizations that don’t have a unified view of their data estate (i.e., most of them), decision-makers risk losing control of one of their most valuable business assets.
The power of visibility
So, what’s the answer? How can organizations regain meaningful control over sprawling data estates created by departmental technology choices?
For many leaders, the instinctive reaction to the various risks is just to restrict the use of department-led tools or enforce tighter approval cycles.
The problem is that, except for the most restricted technology environments, this rarely works. If an employee knows a third-party app or service will make their lives significantly easier, they will generally find a way to use it.
Instead, the most effective way forward lies in building much better visibility around what technology is being used, by whom, and crucially, how data moves between systems.
For instance, good data visibility opens the door to much better risk assessment, whereby organizations can identify duplicate, insecure, or redundant tools and allow IT to bring legitimate solutions under governance.
From a data governance perspective, a single, accurate view of data across SaaS, cloud, and on-premises systems provides the foundation for enforcing policy consistently and improving both storage efficiency and compliance.
Armed with that level of visibility, IT leaders can see where sensitive information resides and confirm that it is properly protected, while also supporting better lifecycle management by allowing data to be archived, retained or deleted according to its business value and any relevant regulatory requirements.
Ultimately, this is about ensuring that IT can see and manage the data produced by systems they didn’t necessarily select or deploy. This requires vendor-agnostic data management tools that can integrate unstructured data from multiple platforms into a single, consistent view.
When done right, organizations can balance innovation and governance, giving departments the freedom to use the tools they need while ensuring all data remains discoverable, compliant, and efficiently stored.
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