Unlocking Enterprise Value Through Data Modernization
A before-and-after look at how leading organizations overcome ERP, AI, and scaling challenges
Modernizing data isn’t just a tech upgrade—it’s a business imperative. CDOs are tasked with unlocking enterprise-wide value from data, but poor data quality, fragmented systems, and misaligned strategies often slow progress. Leading organizations are moving from data immaturity to modernization—fast—by tackling three common challenges and unlocking measurable outcomes. Learn how they’re turning complexity into clarity—beginning with a strategic evaluation of their current data landscape.
Laying the Groundwork: Assessing Data Value Before Modernization
The journey to data modernization begins with a business value assessment—a structured approach to evaluating the current state of data across the enterprise. By identifying pain points such as poor accessibility, technology sprawl, and inconsistent governance, organizations can quantify the impact of modernization and define the outcomes they aim to achieve. These outcomes often include cost reduction, faster time to insights, improved compliance, and new revenue generation. With clarity on both the problems and the potential, organizations are better equipped to address the core challenges that stand in the way of data maturity.
The Future of Data Management: Enabling Scalable, Trusted, AI-Ready Data
As data ecosystems grow more complex, organizations need more than strategy—they need execution. Modern data management provides the foundation for scalable transformation, enabling trusted data flows, AI adoption, and enterprise-wide agility. By investing in core capabilities, businesses can unlock value and accelerate innovation.
ERP Transformation and Enterprise Data Strategy
Before
Organizations undergoing ERP transformations often face a landscape of disconnected legacy systems, where data is siloed and inconsistent across departments. This fragmentation limits visibility and makes it difficult to generate reliable insights. Analytics capabilities are often constrained during the transition, and IT and data teams are stretched thin, delaying their ability to invest time in data innovation. Misalignment between the data strategy and broader business goals further complicates efforts, leading to missed opportunities and inefficient operations.
Approach
KPMG LLP (KPMG) helps organizations navigate complex ERP transitions by enabling data accessibility and analytics support throughout the journey. Using AI on core data management tasks and activating automated classification, data products, and marketplaces empowers finance teams to extract value from data even before ERP systems are fully integrated. New interaction models between business and IT teams create greater synergies.
After
Once data modernization is underway, organizations begin to see the benefits of integrated, high-quality data accessibility and consumption across the enterprise. Manual data wrangling and reconciliation is reduced, processes are streamlined, and decision-making becomes faster and more informed. A scalable architecture supports future innovation, while robust governance and compliance frameworks ensure data integrity and regulatory alignment. With a harmonized data strategy and capability enablement, businesses are better equipped to seize opportunities and manage risks.
AI Use Cases and Data Modernization
Before
Many organizations eager to implement AI find themselves held back by disorganized, low-quality data that is missing key business context and ownership. Siloed systems and lack of uniform data curation make it difficult to build reliable data products, and legacy infrastructure often lacks the scalability needed to support advanced analytics. Talent shortages and unclear ROI further stall progress, while ethical and regulatory concerns around data privacy and bias add complexity to deployment.
Approach
KPMG conducts data and AI readiness assessments to identify blockers, gauge maturity, and recommend tailored solutions. With accelerators for data quality, governance, and infrastructure, KPMG helps clients build the foundation needed to power AI use cases and scale AI adoption.
After
With a modernized data estate, organizations can unlock the full potential of machine learning and AI. Clean, integrated data enables predictive analytics and real-time insights, improving decision-making across the business. Automation reduces operational costs and frees up talent for strategic work. Scalable cloud infrastructure and a portfolio of accelerators help support innovation and growth, while AI-powered personalization further enhances customer experiences. Strong governance ensures compliance and builds trust, positioning the organization for success in driving business value with data and AI.
Scaling Finance Data Products and Master Data Management
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Before
In more mature organizations, data initiatives often stall after initial pilot success. Without a clear strategy for scaling, data products remain confined to isolated business units. Scarce talent, siloed data and systems, and outdated technology stacks limit scalability and long-term success. Governance frameworks may be underdeveloped, making data product monetization difficult. Resistance to change across departments further slows progress, leaving valuable data underused.
Approach
KPMG supports mature organizations with advancing strategic data governance, multi-domain master data management, and data product factories. By leveraging KPMG AI-enabled transformation strategies, Data and Analytics Target Operating Model (TOM), and the Modern Data Platform (MDP), clients accelerate adoption and unlock new business models.
After
With a holistic approach to advancing data products, organizations can amplify value across the enterprise, unlock internal efficiency and pursue new revenue streams. Integrated data ecosystems improve operational excellence. Differentiated offerings powered by the insights data can provide enhance competitiveness. The result is a data-driven culture that fosters innovation and delivers measurable business value.
Accelerate Your Journey with KPMG
The KPMG data modernization approach combines deep domain expertise with well-established accelerators to help CDOs move from “before” to “after” faster. Whether you're navigating ERP transformation, scaling AI, or monetizing data products, KPMG can deliver the tools and strategy to unlock enterprise-wide value.
Explore how KPMG can help you modernize your data & AI estate.
The Future of Data Management: Enabling Scalable, Trusted, AI-Ready Data
As data ecosystems grow more complex, organizations need more than strategy—they need execution. Modern data management provides the foundation for scalable transformation, enabling trusted data flows, AI adoption, and enterprise-wide agility. By investing in core capabilities, businesses can unlock value and accelerate innovation.
KPMG is here to help.
Build data products that rely on agile management systems, elevated data quality, and solid operational foundations. We’ll help you establish federated data ownership practices and data models optimized for specific domains and lines of business.
Anticipate and adapt to the wide-ranging impacts AI can have on your data and organization, including budgets and data controls, secure data practices, and cloud-native architectures.
Harness the power of data ethically and responsibly with trusted data principles and governance models for managing risk.
Create a consumer lifecycle approach that incorporates self-service models, AI assistants and agents, and builds a foundation for enterprise insights.
Operate and manage your data infrastructure with integrated frameworks that support access to a broad range of data sources and make analytics faster with less friction.
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