All Case Studies
Energy & UtilitiesSAPSupply Chain &AI-Driven Operational Efficiency

AI-Powered SAP Platform Optimization

Global Energy Corporation

40%
Reduction in Order Processing Time
60%
Improvement in Asset Uptime
$4.2M
Annual Cost Savings
70%
Faster Procurement Cycle

Business Context

The organization and its strategic environment

A $7.8B energy company operating across 14 countries needed to modernize its SAP landscape to support predictive operations. The company was spending $23M annually on unplanned maintenance and losing $4.6M per quarter to procurement inefficiencies.

Technology Landscape

Systems and infrastructure before DGT

SAP ECC 6.0 with heavy customization, SAP PM for maintenance, SAP MM for procurement, legacy SCADA systems, and disconnected field service tools across 340 remote sites.

The Challenge

What the client was facing

Manual procurement processes with 72-hour PO processing times, reactive asset maintenance causing $23M in annual unplanned downtime, and field technicians using paper-based workflows with no real-time SAP connectivity.

The DGT Solution

How DGT addressed the challenge

DGT implemented an AI-powered optimization layer across the client's SAP S/4HANA environment, including intelligent procurement automation, predictive asset maintenance using IoT sensor data, and real-time operational dashboards. MobileOps connected 340 field sites to SAP in real time.

DGT Accelerators Used

MobileOpsInsights360

Delivery Approach

How DGT executed the engagement

Parallel workstream approach: procurement automation, predictive maintenance, and mobile deployment ran simultaneously with shared integration layer. Bi-weekly releases with production validation at each cycle.

Governance Model

How the engagement was managed

Executive sponsor (COO), program management office with 3 workstream leads, weekly cross-workstream sync, monthly board update, and dedicated safety compliance review for maintenance workflows.

Timeline & Phases

The execution roadmap

1

Assessment & Architecture

3 weeks

SAP landscape audit, IoT sensor inventory, AI readiness scoring

2

S/4HANA Migration

10 weeks

Core migration with DataBridge, procurement automation build

3

Predictive Maintenance

6 weeks

IoT integration, ML model training, alert configuration

4

MobileOps Deployment

4 weeks

Field app deployment across 340 sites, offline sync

5

Optimization & Hypercare

4 weeks

Model tuning, dashboard refinement, knowledge transfer

Risks Addressed

Key risks DGT mitigated during the engagement

Data migration from heavily customized ECC 6.0
IoT sensor data quality and latency across remote sites
Field technician adoption in remote locations with limited connectivity
Safety compliance for AI-driven maintenance scheduling

Why DGT Won

What set DGT apart in this engagement

23 years of SAP expertise with energy sector specialization
MobileOps accelerator purpose-built for remote field operations
Proven AI/ML integration methodology for industrial IoT
DataBridge ensured zero-downtime migration with 99.8% accuracy

Outcome Metrics

Measurable before-and-after results

MetricBeforeAfter DGT
PO Processing Time72 hours43 hours
Unplanned Downtime$23M/yr$9.2M/yr
Field Data Entry Time45 min/visit8 min/visit
Procurement Cycle18 days5.4 days

The Impact

Headline results delivered

40%
Reduction in Order Processing Time
60%
Improvement in Asset Uptime
$4.2M
Annual Cost Savings
70%
Faster Procurement Cycle
"DGT transformed our SAP operations from reactive to predictive. The results exceeded our expectations within the first quarter."

James Richardson

VP of Operations, Global Energy Corporation

Could This Work in Your Environment?

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