Topic starter
07/06/2026 8:55 pm
TL;DR: 83% of organisations believe poor data visibility weakens security posture and 87% say discovery and classification tools are inadequate, according to Cyera research, showing why DSPM rollouts often stall on execution, integration, and adoption rather than technology alone. The real test is whether teams can operationalise data visibility, ownership, and governance at scale.
Editorial analysis by NHI Mgmt Group, based on content published by Cyera: “Common DSPM Implementation Challenges: Overcoming Obstacles to Successful Data Security”.
By the numbers:
- 83% of organisations believe poor visibility into their data weakens security posture.
- 87% say their existing discovery and classification tools are inadequate.
Key questions
Q: What breaks when DSPM is deployed without full data visibility?
A: Without full visibility, DSPM can classify only part of the estate, which leaves shadow storage, legacy repositories, and unmanaged copies outside policy coverage.
Q: Why do poor classification results stall DSPM programmes?
A: Poor classification creates alert fatigue, erodes trust in the platform, and forces teams to spend time validating noisy findings instead of reducing real exposure.
Q: What signals show that DSPM is working well enough?
A: Look for evidence that sensitive data is discovered accurately, masking is applied where required, and remediation actions happen without long manual delays.
Practitioner guidance
- Map the actual data estate before expanding DSPM coverage Inventory approved cloud storage, shadow IT repositories, personal devices, and legacy systems so discovery starts from real data locations rather than assumed ones.
- Align classification rules to business context Test whether labels change appropriately by department, geography, and data use case, then adjust thresholds where false positives or missed sensitivity appear.
- Normalise integrations with SIEM and SOAR Check that event fields, timestamps, and alert semantics are consistent across platforms so response workflows do not duplicate or lose signals.
Bottom line: DSPM implementation problems are usually operational, not theoretical, because data cannot be governed reliably until it is found, classified, and owned.
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This topic was modified 3 days ago by NHI Mgmt Group
08/06/2026 8:39 am
DSPM rollouts fail when organisations treat visibility as a feature instead of a governance prerequisite. Data security posture management only works when discovery, classification, and ownership are all in place together. Cyera’s article shows that many programmes stall because they try to govern data they still cannot fully see. The practical conclusion is that data inventory is the control surface, not an implementation detail.
A few things that frame the scale:
- Only 5.7% of organisations have full visibility into their service accounts, according to the Ultimate Guide to NHIs.
A question worth separating out:
Q: What should teams do when DSPM conflicts with business workflows?
A: When DSPM slows access or creates friction, teams should redesign the rollout around critical datasets and documented exceptions instead of forcing broad controls everywhere at once. A phased approach preserves productivity while proving value, which reduces workarounds and resistance. The governance goal is to make protection fit how the business actually operates.
👉 Read our full editorial: DSPM implementation gaps expose why data security rollouts stall
This post was modified 3 days ago by NHI Mgmt Group