Case Study:
Rescuing a Broken
Integration During a Global CRM & ERP Migration
The Problem
A client was midway through their migration from SAP ECC to S/4HANA. They were
experiencing frequent
failures in critical order processing and reporting workflows post-migration
testing.
Business users complained that:
Orders in the CRM were not syncing with the ERP
system.
Reports contained inconsistent or outdated data.
Manual workarounds were increasing daily.
Despite the project appearing “green” on governance
dashboards, issues were mounting and trust was eroding.
Our Approach
We were brought in to assess and troubleshoot the integration and data layers. Our
method was guided
by our D.I.A.G. framework (Discover, Investigate, Align, Guide):
Discover
We quickly reviewed:
Integration architecture and data flow diagrams
Mapping logic and middleware configurations
(MuleSoft)
Business-critical processes and touchpoints
Existing performance metrics and error logs
Investigate
We conducted:
Interface trace reviews across SAP, Salesforce,
MuleSoft, and 3rd-party APIs
Data profiling to identify anomalies in material
master and order data
Custom script-based validation of ETL jobs and
orchestration flows
Findings:
Several mappings were hardcoded for legacy data
formats that had changed.
Business rules embedded in Excel had not been
codified into the workflows.
Align
We engaged business stakeholders to prioritise fixes:
Order management had the highest revenue risk.
Reporting issues were hurting decision-making, but
not operations.
We translated these into a phased remediation plan
that aligned with business priorities.
Guide
We helped:
Redesign the data mapping layer to match new master
data definitions.
Introduce pre-validation scripts to catch broken
records before loading.
Facilitate communication between tech and business
leads to prevent scope drift.
The Outcome
Order sync failures dropped by 76% within two
weeks.
Data consistency improved across the critical
reports, restoring trust in dashboards.
Manual rework effort reduced across teams.
Go-live proceeded as planned — with no major business
outages.
Key Takeaways
Early warning signs were missed due to over-reliance
on surface-level green KPIs.
Technical issues masked as business problems required
experienced interpretation.
Cross-functional understanding (data + systems +
business process) was critical to the fix.
Case Study:
From Recovery to
Prevention
Using DIAG™ at Both Ends of the Digital Transformation
Lifecycle
Client Overview
A global B2B services provider had embarked on a multi-phase digital transformation.
This included
migrating from legacy on-prem systems to a modern SaaS-based architecture,
integrating multiple acquired
platforms, and redesigning core operational workflows.
The programme was large, time-sensitive, and business-critical. But by month eight,
things were falling
apart.
The Problem
The transformation team was behind schedule, over budget, and overwhelmed.
Symptoms included:
Conflicting definitions of success across business
and IT
Repeated rework due to missed dependencies
Poor data quality blocking downstream migration
Morale slipping and vendors pointing fingers
Executive concern growing — confidence was
eroding
The project was in freefall.
Diagnosing and Rescuing a Failing Programme
We were brought in, asked to “fix the delivery issues.” But instead of jumping
straight
into firefighting, we applied our DIAG™ Framework:
Diagnose
We uncovered that the biggest blockers weren’t technical — they were misaligned
expectations, fragmented
communication channels, and unclear ownership.
Investigate
We mapped the full delivery chain — from roadmap to release — and surfaced unspoken
assumptions and
hidden gaps in planning, resourcing, and governance.
Analyse
Our heatmap of risks showed clear prioritisation mismatches, and areas of critical
underinvestment. We
clarified which parts were salvageable, and which needed rethinking.
Guide
We worked with leadership to reset the plan, clarify scope, and introduce cadence
and communication
guardrails. Delivery improved — and stakeholder trust began to return.
Later: A New Programme, A New Approach
After stabilising the initial programme, the same client approached us again — this
time
for a new cloud-native data platform rollout. But now, they wanted to avoid history
repeating itself.
This time, they engaged us at the planning stage.
Prevention: Getting It Right from Day One
Using the same DIAG™ Framework proactively, we helped them:
Align stakeholders early with a clear definition of
success
Validate architecture and integration assumptions
before any code was written
Assess data readiness and process ownership
Build a realistic, risk-aware delivery roadmap
Establish KPIs to monitor progress and signal early
issues
This second programme launched with strong alignment, clear guardrails, and minimal
disruption. Unlike
the first, it didn’t need rescuing.
Results
37% increase in delivery velocity during the
recovery
4 months shaved off Phase 2 due to early clarity
Executive satisfaction rebuilt and sustained
DIAG™ embedded as part of their enterprise delivery
approach
Key Takeaway
DIAG™ doesn’t just fix what’s broken — it prevents breakage in the first place.
Whether you’re in the heat of delivery or still shaping your vision, DIAG™ gives you
the clarity,
structure, and insight to succeed where others stumble.
