The time was running out. A new ERP system was going to be implemented by an energy company. It was necessary to migrate thousands of documents, including assets, suppliers, invoices, and replacement parts. Upon reviewing the files, the migration team found a disarray of data, including obsolete supplier details, inconsistent formats, missing values, and duplicate records.
The stakes were high: either move the inaccurate data and risk years of inefficiency, or delay the project and incur millions of downtime. At this point, a well-executed data migration becomes crucial.
The Reasons Data Migration Is Not Just About “Moving Data”
Organizations much too frequently view migration as a technical procedure that entails transferring data across systems. However, in practice, it involves more than just transferring data; it also involves making sure that:
Clear and consistent data across systems is known as accuracy.
Continuity: Ongoing operations are not interrupted.
Compliance: Adhering to legal requirements and industry standards.
Value Creation: Making it possible for new platforms (cloud, AI, ERP) to produce ROI right now.
A bad migration causes legacy problems in the new system and slows down initiatives, which could lead to:
exorbitant prices and recurring purchases.
audit failures brought on by inaccurate or lacking documentation.
ERP dashboards and analytics are mistrusted by users.
Decision-making is delayed because “the system doesn’t reflect reality.”
The Global Context: The Importance of Migration Today
83% of data transfers either fail or go beyond budget and schedule, according to research. Poor migration can cost millions of dollars annually in lost procurement, downtime, and rework expenses in sectors including manufacturing, utilities, and oil & gas.
Clean migration has become a major priority in boardrooms because to the growing use of cloud computing, SAP S/4HANA transformations, and AI-driven analytics. Businesses understand that data migration is the initial phase of digital transformation and that failure is not an option.
The Intelligent Data Migration Method of PiLog
Before your data even reaches the new system, PiLog turns it into a reliable business asset. It’s not only that we “move” it.
1. Evaluation of pre-migration data
We start by performing a Data Health Check to examine:
completeness, or the lack of specific fields.
uniformity in formats and naming conventions.
Repetitiveness(overlapping, duplication).
adherence to the global taxonomy established by PiLog.
2. Automatic Enrichment & Cleaning
Utilizing PiLog’s master data repositories and ASA (Auto Structured Algorithms), we
Free-text and unstructured descriptions should be cleaned up.
Assign our taxonomy classes and attributes.
Obtain the manufacturer, vendor, model number, and part number.
Provide the unit of measurement (UOMs) and verified supplier details to make improvements.
3. Setting Up Quality Gates for Migration
Before data is moved to destination systems like SAP, Oracle, Maximo, or cloud platforms, we ensure that it satisfies quality criteria.
4. Governance After Migration
Migration is the beginning, not the end. To ensure that the new system remains dependable, consistent, and clean long after it goes live, we apply data governance principles.
What Makes PiLog Unique for Data Migration?
SAP-Endorsed Apps are trustworthy programs that have earned SAP certification.
Over 25 years of standardized master data are available in Global Taxonomies & Repositories.
AI-Powered Automation: Reduces errors and speeds up cleaning.
shown proficiency in a variety of fields, including as manufacturing, utilities, oil & gas, and aerospace.
Future-Reliable Framework: Ensures that migration data is compatible with predictive analytics, AI, and the Internet of Things.
Results That Are Important to Businesses
From the standpoint of the buyer, PiLog’s move is revolutionary rather than merely technical. Experience of the client:
ERP/Cloud Go-Live on Time: Projects remain on schedule and within budget.
Savings: Lowers inventory overhead and pointless purchases.
Audit Confidence: Regulatory review is applied to documents that are clear and compliant.
Trustworthy data and fewer processes lead to operational efficiency.
Future-Proofing: Data organized to support Industry 4.0, digital twins, and artificial intelligence.
A Beneficial Effect
PiLog worked with a global oil and gas company as they migrated to SAP S/4HANA. They cut procurement costs by 15%, removed 20% of duplicate entries, and shortened migration timelines by months by cleaning and standardizing over 2 million material master data points.
More significantly, executives could immediately rely on each dashboard in their new system.
Data Migration’s Future: AI + Governance
As more businesses embrace cloud, IoT, and AI, migration is becoming a continuous capability rather than a one-time event. Future-ready organizations will be dependent on:
data validation driven by AI prior to, during, and following migration.
governance systems that consistently uphold quality.
ERP, CRM, and supply chain applications all use the same language in integrated data ecosystems.
Over the next ten years, migration will undoubtedly involve more than just “moving data” due to PiLog’s clever strategy; it will involve unleashing business value.
Concluding Remark: Transfer Value, Not Problems
Poor data migration is a silent killer of digital transformation in today’s cutthroat environment. Migration can be a competitive advantage that fosters productivity, creativity, and compliance if it is handled well.
You can transfer systems with confidence, clarity, and control when you use PiLog.
Would you prepared to make your next migration project a success? Let’s talk.
Avoid Data Migration Risks: How PiLog Makes the Switch to Cloud, ERP, and SAP Systems