Time was running out. A new ERP system was going to be implemented by an energy company. It was necessary to move thousands of documents, including assets, suppliers, invoices, and replacement parts. After reviewing the files, the transfer team found a mishmash of data, including outdated supplier information, inconsistent formats, missing values, and duplicate records.
The stakes were high: either move the incorrect data and risk years of inefficiency, or delay the project and incur millions of hours of downtime. At this point, a well-executed data migration becomes crucial.
The Elements of Data Migration That Go Beyond “Moving Data”
Organizations much too frequently view migration as a technical procedure that entails transferring data between systems.
However, in practice, it involves more than just data transfer; it also involves making sure that:
Clear and consistent data across systems is what is meant by accuracy.
Continuity: Ongoing operations are not interrupted.
Compliance: Adhering to the law and industry standards.
Value Creation: Making it possible for new platforms (cloud, AI, ERP) to produce an instant return on investment.
A bad migration causes legacy problems in the new system and slows down initiatives, which could lead to:
exorbitant expenses and regular purchases.
audit failures brought on by inaccurate or lacking documentation.
ERP analytics and dashboards are not trusted 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 over budget and schedule, according to research. Poor migration can lead to millions of dollars in annual procurement waste, downtime, and rework expenses in sectors like manufacturing, utilities, and oil and 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. We don’t merely “move” it.
1. Evaluation of pre-migration data
We start by performing a Data Health Check to examine:
the lack of specific fields or comprehensiveness.
uniformity in formats and naming conventions.
Repetition (overlapping, duplication).
compliance with the universal 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 must be cleaned up.
Assign our taxonomy classes and attributes.
Obtain the manufacturer, vendor, part number, and model number.
Provide the unit of measurement (UOMs) and verified supplier data to make improvements.
3. Setting Up Quality Gates for Migration
Before data is sent to destination systems like SAP, Oracle, Maximo, or cloud platforms, we make sure 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-Ready Framework: Ensures that data from migrations 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:
Timely ERP/Cloud Go-Live: All tasks are finished on schedule and within budget.
Savings: Lowers inventory overhead and unnecessary spending.
Audit Confidence: Regulatory examination is available for documents that are valid and unambiguous.
Reliable data and fewer processes lead to operational efficiency.
Future-Proofing: Data organized to support Industry 4.0, artificial intelligence, and digital twins.
A Positive Effect
PiLog helped with a global oil and gas company as they made the switch to SAP S/4HANA. Over 2 million material master data points were standardized and cleansed, which resulted in a 15% reduction in procurement prices, a 20% removal of duplicate entries, and a month-long reduction in migration times.
More significantly, management could currently rely on each dashboard in their new system.
AI and Governance in Data Migration’s Future
With more businesses embracing cloud, IoT, and AI, migration is changing from a one-time event to a continuous capability. Future-ready organizations will be dependent upon:
data validation powered by AI prior to, during, and following migration.
governance structures that consistently uphold quality.
ERP, CRM, and supply chain applications all speak the same language in integrated data ecosystems.
Over the next 10 years, migration will undoubtedly involve more than just “moving data” due to PiLog’s clever strategy; it will also involve releaseing commercial 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 benefit that fosters innovation, productivity, and compliance if it is handled well.
You can migrate systems with confidence, clarity, and control when you use PiLog.
Are you prepared to finish your upcoming migration project successfully? Let’s talk about this.