How We Delivered Core DLP, Classification, and DRM Controls in Five Months for a National Public-Sector Data Authority

The situation

The client is a national authority responsible for collecting, managing, and safeguarding large-scale statistical and public-sector datasets spanning multiple internal systems and business units, including highly sensitive and regulated information critical to national reporting, planning, and decision-making. As data volumes grew and digital operations expanded, so did the pressure to protect that data with consistent, enforceable controls.

The environment had grown faster than its controls. Modernization efforts were running in parallel, and no unified mechanism governed how sensitive data was classified, accessed, and shared across the estate.

The mandate was concrete: establish enforceable data protection controls, spanning classification, leakage prevention, and rights management, aligned with the national data governance and data handling requirements that bind public-sector bodies, and do it on a hard deadline set by internal governance mandates.

For an organization whose datasets underpin national planning and reporting, uncontrolled disclosure is not an IT incident; it is a public-trust problem, and it lands on leadership.

The challenge

Six conditions made this program materially harder than a standard tooling deployment:

1. Sensitive data sat distributed across legacy and modern environments with limited centralized visibility.
2. Classification was inconsistent or incomplete, and ownership of many datasets was unclear.
3. No unified controls existed for leakage prevention or rights management: once a sensitive document was shared, internally or externally, the organization could no longer track or control it.
4. Legacy systems imposed real integration constraints on modern security platforms.
5. Multiple stakeholder groups brought differing operational priorities and dependencies.
6. Internal governance mandates fixed the timeline, while full operational continuity was required throughout deployment.

Left unaddressed, that meant growing risk of uncontrolled data exposure, limited audit readiness, and a shrinking ability to enforce data governance policy at scale.

The approach

ExeQut designed a phased transformation around the legacy estate as it actually was, not as modernization roadmaps promised it would become. The engagement ran as six defined phases: assessment, gap analysis, planning and design, implementation, integration and optimization, and validation and enablement.

Assess, then design as one architecture

The engagement opened with an assessment of data flows, storage locations, classification maturity, and exposure risks, followed by a gap analysis across visibility, classification, policy enforcement, and leakage prevention. From there the team designed a single unified architecture rather than four disconnected tools. Data security posture management (DSPM) provides continuous discovery and risk visibility. Forcepoint DLP enforces exfiltration controls across communication channels. File data classification standardizes labeling, and SealPath DRM applies persistent protection that follows documents beyond organizational boundaries. All four capabilities were deployed within the program; the five-month milestone in the headline covers the three enforcement layers, with DSPM providing the discovery backbone throughout.

Enforcement was integrated with the existing security and identity infrastructure so controls applied consistently across endpoints and network layers. Existing infrastructure was reused wherever possible to cut integration overhead.

High-risk domains first

Rather than a full-scale simultaneous rollout, deployment was phased with the highest-risk data domains first. That decision reduced exposure on the most sensitive datasets early in the program, well before the full rollout completed, while keeping the live environment stable.

The resident engineer model

A dedicated ExeQut resident engineer was embedded inside the client environment to keep execution continuous. When integration issues surfaced between legacy systems and the new platforms, they were resolved rapidly on the ground, cutting the inter-team dependency delays that stall these programs.

ExeQut consultants led governance, architecture alignment, and implementation oversight. Cross-functional workshops brought security, IT, and business stakeholders to the same decisions. Weekly progress reviews validated every milestone with client stakeholders, and risk and dependency tracking was maintained continuously across the implementation streams.

The resident engineer model removed the delay that kills these programs: the gap between a design decision and its execution on the ground.

Align policies early, validate continuously

Classification and DLP policies were aligned early to avoid rework and policy fragmentation. Discovery and classification runs then swept the organization's distributed repositories, spanning legacy and modern estates and multiple business units, and surfaced hidden and misclassified sensitive data.

DLP policies were tested across communication channels and data flows and refined against operational feedback. DRM controls were validated against external document protection scenarios, the step where, in our experience, rights-management projects most often stall. A centralized governance model with defined escalation pathways handled policy definition and exceptions, so edge cases were governed instead of becoming outages. User awareness sessions prepared staff for the new classification and handling standards, and continuous monitoring and optimization hardened rules against real traffic rather than assumptions.

The outcome

The organization now has a unified, enforceable data protection foundation across environments that were previously fragmented:

• Core DLP, classification, and DRM enforcement live within five months.
• Centralized visibility into sensitive data across legacy and modern estates: leadership can now see where sensitive data lives and how it is classified.
• Exfiltration controls enforced across communication channels, and protection that now travels with sensitive documents, inside the organization or beyond it, closing the tracking-and-control gap the program started with.
• Consistent classification and handling standards in force across the estate.
• Audit readiness the organization can evidence: continuous discovery of sensitive data assets, standardized classification, and a governed exception process.

Throughout deployment, live operations continued without disruption, across both legacy and modern environments, including the statistical and reporting work the organization exists to deliver.

The engagement did not end in dependency. Knowledge transfer, user enablement, and operational readiness work moved day-to-day operation to the client's own teams and raised the organization's operational maturity in managing data security at scale. Ongoing policy and exception decisions sit with the governance model the program put in place.

The ROI case is time and exposure. The more-than-half timeline reduction is measured against the alternative the program design rejected at the outset: a conventional full-scale simultaneous rollout of the same four-control scope.

Every month cut from the timeline was a month less of leakage exposure on nationally significant datasets, and a month less of consulting, staffing, and licensing spend accruing before enforcement was real.

Designed for the future

The architecture is built to extend as the program matures: enterprise data governance expansion, integration with SOC and security monitoring, cloud data protection as workloads migrate, and AI-driven classification as the capability matures.

What we took from it

1. Anchor data protection in operational reality. Policies that ignore how people actually work get bypassed; policies refined against operational feedback get adopted.
2. Embed the engineering. A resident engineer inside the environment collapses the feedback loop that otherwise makes complex integrations slow.
3. Align classification early. Classification is the shared language of DLP, DRM, and governance; settling it first prevents downstream rework in all three.
4. Treat legacy constraints as design inputs. Architecting for coexistence beat waiting for modernization to finish.
5. Phase by risk, not by system. Incremental, risk-ordered deployment buys risk reduction early and holds stakeholder confidence through the rollout.