IBM Commercial and Professional Services United States

Sutherland Global Services

Security and Compliance

Sutherland needed to move beyond a manual, hard-to-scale threat-detection process so it could protect sensitive customer data and critical business functions more quickly, consistently and cost-effectively across a global services environment.

200+ alert automations
Reduced MTTD from days or weeks to just hours

Reported impact

Business outcome

Sutherland cut detection time dramatically, reduced false positives and manual effort, improved compliance reporting and made its cybersecurity operations more scalable and cost-efficient.

  • Cost Reduction
  • Productivity Improvement
  • Risk Reduction

Solution

Sutherland strengthened its existing security operations by layering IBM Security QRadar Suite into its toolset and using it as the central analytics environment for log, network and event monitoring. QRadar performs real-time analysis across security telemetry and applies AI-based anomaly detection, user-behavior analytics and predictive analytics so analysts can identify zero-day attacks and other advanced threats that manual, rule-heavy methods might miss. The company makes particular use of IBM Security QRadar SIEM to collect and correlate data from multiple sources into a unified security view, and integrates the platform with threat-intelligence feeds to support more proactive defense. Sutherland also tailors rules, alerts and reports to its own compliance and operational needs, turning QRadar into a flexible control plane for detection, investigation and response. The result is faster, more targeted security operations with less dependence on manual monitoring.

Data flow

Log data, network traffic and security events from Sutherland's environment are ingested into QRadar, correlated into a unified event view, enriched with threat-intelligence feeds and then used by analysts and alert automations to identify and respond to threats faster.

Solution architecture

2 components · 2 layers
  1. Compute
    • IBM Security QRadar Suite Analyzes security telemetry with AI to detect threats, anomalies and attack patterns across Sutherland's environment.
  2. Serving
    • IBM Security QRadar SIEM Collects and correlates data from multiple sources to create a unified view of security events and support compliance monitoring.

Architecture clues

  • QRadar analyzes logs, traffic and security events in real time.
  • Sutherland customizes rules, alerts and reports to match organization-specific requirements.
  • Threat intelligence feeds are integrated into the security workflow.

Evidence from the source

"Reduced MTTD from days or weeks to just hours"
"Sutherland has created 200+ automated alerts in QRadar"
"apply AI-based anomaly detection, user-behavior analytics (UBA) and predictive analytics"
"collect and correlate data from various sources across the IT environment into a holistic view of security events"
"conduct real-time analysis of log data, network traffic and security events"
Transparency Evidence & methodology 70/100 reference value · 87% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value70/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact0/25
    0 metrics describe measurable impact.
  • Deployment scale5/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence87%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    5 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity8/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. IBM

    Sutherland Global Services customer story

    First-party
    https://www.ibm.com/case-studies/sutherland
    Source type
    Vendor-published customer story
    Published
    Apr 25, 2024
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.