The Data Migration Trap in ERP TransformationHeading

By Ken Renganathan, Senior Strategic Solutions Executive

ERP system consolidations are on the rise! Over the years, large organizations have accumulated multiple ERP systems for a variety of reasons including best of breed approach and inorganic growth of business. However, a complex ERP ecosystem leads to issues related to maintainability, inconsistency, and the ability to accommodate new business functionality. It can also slow down an organization’s embrace of modern digital technologies.

Many organizations today are looking to enable a single source of the truth, deliver better user experience, reduce total cost of ownership, and facilitate more transparency and audit trails through consolidation of their ERP landscape. This may be to a select few systems or, in many cases, just one. The industry is undergoing a vast number of S4 and Fusion programs with huge investments.

While the business benefits of ERP consolidation far outweigh the time and investment required for such programs, they require meticulous planning and methodical execution – including tangible milestones delivered en route to the end-state consolidation.

One of the most common traps in ERP programs, particularly involving multiple-legacy system data, is underestimating the importance of data migration. Data migration can be complex and time consuming to the extent that it can delay and derail the entire program. Makes sense though… after all, the accuracy and completeness of data migration from disparate systems directly impacts core business processes in finance, sales and customer management, supply chain, and other business-critical elements.

Bringing in or establishing expertise in specific ERP solutions (like SAP or Oracle, to name the two most popular) is important, but organizations must also look to incorporate proven approaches that bring predictability and automation to data migration from various systems.

A comprehensive approach addresses the following key elements to improve efficiency, establish predictability, and increase cost effectiveness:

  • Data validations and data load
  • Automated reconciliations
  • Automated functional testing
  • Reduced cutover time

So how do you escape the data migration trap? My next article will highlight an automation-driven approach with “no programming” that guarantees faster and complete data migration at just 50% the cost of traditional methods.

Stay tuned…

Recent Posts

Executive Perspective: Why Securing Your Data is the Key to Winning with AI

As CXOs, we’re all focused on leveraging AI to drive efficiency, innovation, and competitive advantage. The conversation often starts with infrastructure (GPUs, LLMs, and copilots), but let’s be clear: AI doesn’t run on GPUs. It runs on data. And if our data isn’t secure, nothing else matters. Unsecured and unclassified data undermines trust, exposes us to risk, and jeopardizes the very AI strategies we’re betting our futures on. It’s not about chasing the next shiny tool; it’s about building a foundation that allows AI to scale safely, responsibly, and securely.

Quantifying the Value of Data in Financial Services

In the financial services sector, data is a critical asset that drives profitability, risk management, regulatory compliance, and competitive edge. However, measuring its value remains challenging for many CFOs across sectors of the financial services industry regardless of organizational size or country of operations. CFOs rely on accurate data for forecasting, budgeting, and strategic planning. Quality data leads to better decision-making, optimized capital allocation, and swift responses to market changes. It is also vital for risk management, regulatory compliance (e.g., BCBS 239, Basel III, AML/KYC), and avoiding fines and reputational damage. “Fit for Business Use” data also supports customer retention, personalized services, and improved revenue stability. Data-savvy CFOs leverage insights for long-term growth.

AI Starts with Data: Go From Hype to Results

AI continues to dominate the conversation in business. From executive meetings to strategic roadmaps, AI is no longer just a trend but a real driver of transformation. The challenge is that while nearly every organization is talking about AI, very few are prepared to use it in a way that delivers measurable outcomes and lasting impact. The difference between hype and outcomes almost always comes down to two things: the quality of your data and your organization’s readiness to execute.

Exciting Updates from Informatica World: Paradigm Embraces the Future of Agentic AI

The digital landscape is evolving rapidly, and staying ahead means embracing the latest innovations in data management and artificial intelligence. At this year’s Informatica World, Paradigm is thrilled to share the groundbreaking advancements unveiled by Informatica, centered around their latest agentic AI solutions on the Intelligent Data Management Cloud (IDMC) platform.

Modernizing PowerCenter: The IDMC Way – Better, Faster, Cheaper

For many organizations, Informatica PowerCenter has been the workhorse of their data integration for years, even decades, reliably driving ETL processes and populating data warehouses that feed BI reports. However, this longevity often leads to a complex environment that can hinder agility and innovation.

Boost Growth with Data-Driven Hiring for Boutique Consultancies

Consistency is key to a boutique consultancy. Delivering quality services day in and day out, even as client demand fluctuates, relies heavily on having the right talent at the right time. Perhaps one of the largest operational challenges for small and mid-sized consulting firms, though, is matching recruitment cycles with cyclical demand. Without scalable, data-driven talent practices, consultancies can suffer from misaligned capacity, lost revenue streams, and stalled growth.

Strategies for a Successful Journey in Building the Dream Team

In the whirlwind world of project management, the success of a project often hinges on the strength and consistency of the team behind it. Imagine embarking on a journey where building a high-performing project team is not just about assembling a group of skilled individuals; it’s about fostering collaboration, trust, and a shared sense of purpose. Based on my personal experiences, let me take you through this journey with some strategies I use to help you build and lead a high-performing project team.

The Ultimate Guide to AI-Enhanced APIM Analytics for Enterprise Success

Enterprises increasingly rely on Application Programming Interface (API) Management (APIM) to streamline their operations, enhance customer experiences, and drive innovation. Azure API Management is a comprehensive solution enabling organizations to manage, secure, and optimize their APIs efficiently. However, beyond API management, APIM analytics – particularly when integrated with AI and data analytics – empowers senior executives with critical insights for real-time decision-making.

Why PMOs that Leverage Power BI are More Successful

Project Management Offices (PMOs) are increasingly turning to Microsoft Power BI as a game-changing tool to enhance their project management processes. By leveraging data visualization and analytics, PMOs can make informed decisions, streamline reporting, and improve overall project outcomes.