Enterprise Resource Planning (ERP) technology has hit a remarkable growth spurt in recent years. While companies have previously struggled with siloed, disconnected ERPs, demand has grown for integrated, next-generation ERP systems that work as part of a modern enterprise architecture.
Market projections paint a compelling picture, with the global ERP market expected to reach $59 billion by 2025 and continue growing at 7 percent annually through 2034. This resurgence has caught the attention of industry experts and financial leaders alike, signaling a new chapter in business process management and digital transformation. Given Spaulding Ridge’s approach to data-led innovation through the office of the CFO, we’ve had a front-row seat to the comeback. Companies interested in building on this trend should adapt—but how? To start, it’s helpful to understand why ERP technology has evolved.
The primary catalysts for this ERP comeback are widespread migration from on-premises solutions to cloud-based platforms, and the integration of advanced technologies such as Artificial Intelligence (AI) and Machine Learning (ML).
Cloud-based ERP solutions offer numerous advantages over their on-premises counterparts. First, these systems are much easier to integrate with each other, allowing leaders to get a clearer picture of global operations. These cloud systems also allow businesses to access their data and applications from anywhere, facilitating remote work and global operations. Additionally, the incorporation of AI and ML capabilities has revolutionized ERP functionality, enabling more intelligent decision-making, predictive analytics, and process automation.
One of the most significant differences in this new era of ERP adoption is the shift in perspective regarding system integration and data management. In previous “big bang” ERP implementations, the ERP system was often viewed as the central hub and single source of truth for all business data. Other systems, such as those for supply chain management or human resources, were expected to integrate with and defer to the ERP system.
In contrast, the current approach reflects the complexity of modern technology stacks and data fabrics. Most organizations have already implemented specialized tools for various business functions, such as financial planning and analysis, quote-to-cash processes, and configure-price-quote (CPQ) systems. These tools have proven their value and become integral parts of the business ecosystem. As a result, new ERP implementations are now expected to seamlessly integrate with these existing systems and provide incremental value, rather than replacing or overshadowing them.
This change in perspective reflects the maturation of enterprise technology and the recognition that different tools excel in specific areas. The modern approach acknowledges that a diverse, well-integrated technology ecosystem can often deliver more value than a monolithic ERP system trying to be all things to all departments. This shift has led to more nuanced and strategic ERP implementations that focus on enhancing overall business performance through improved integration and data flow across the entire technology stack.
With the ERP now playing a new role, companies need a new approach to integrating it with the rest of the organization. Leveraging modern data architecture is essential, and organizations without cloud-based data warehouses should consider adopting one. Implementing a data fabric architecture can also create a unified data layer across the organization, enabling seamless access to data regardless of its location or format. Once an organization has data architecture in place, it should implement real-time data synchronization (or as close to it as is possible) between the ERP and other systems. Change data capture (CDC) techniques can be employed to identify and propagate data changes efficiently, minimizing latency and ensuring data consistency across the organization.
Adopting a master data management (MDM) approach will be another key step for maintaining data quality and consistency within your ERP. This involves establishing a single source of truth for critical business data, implementing data governance policies to ensure data quality, and using MDM tools to manage and distribute master data across systems. By centralizing and standardizing master data, organizations can reduce errors, improve decision-making, and enhance overall data reliability.
These steps allow you to have more confidence in the data in your ERP ecosystem, as you can now be confident that data is aligned with information from other ERPs and your sales and finance systems. As a result, you’ll see greater operational efficiencies, increased agility, and easier compliance and risk management.
If effective data integration is the foundation for more effective ERP technology, analytics are indeed the capstone—the insights that drive data value. In today’s data-driven business environment, organizations must go beyond simply collecting and storing data; they need to extract meaningful insights that can inform decision-making and drive business growth. This process begins with assessing basic dashboards to ensure there’s a single source of truth across the organization. By consolidating data from various sources into a unified view, companies can eliminate inconsistencies and provide stakeholders with reliable information.
Once a solid foundation is established, the next step is to identify areas where end users can benefit from predictive and prescriptive analytics. These advanced analytical techniques allow organizations to move beyond historical reporting and gain forward-looking insights. Predictive analytics can forecast future trends and outcomes, while prescriptive analytics can suggest optimal courses of action based on these predictions. By embedding these analytics within user workflows, organizations can ensure that data-driven insights are readily available, informing better decisions at every level.
The benefits of implementing better analytics are numerous and far-reaching. A holistic perspective enables leaders to make more informed choices across all aspects of the business. In terms of operational efficiency, enhanced forecasting and planning capabilities allow for more accurate predictions and better resource allocation, ultimately improving overall performance. Finally, organizations that effectively leverage integrated data and analytics can gain a significant competitive advantage in their respective markets, as they are better equipped to respond to changing conditions and capitalize on emerging opportunities.
A modern ERP also enables several interesting test cases for AI. While AI should undoubtedly be a “big bet” at the strategic level, the path to successful implementation is not always clear-cut. Organizations should experiment broadly to discover where AI can provide the most significant benefits—in practice, making several “small bets” that add up to a big investment.
The key to unlocking AI’s potential lies in starting small, moving fast, and iterating. By building on existing ERP systems and leveraging the data they contain, companies can begin their AI journey with targeted applications that offer immediate value. For instance, anomaly detection tools utilizing machine learning can swiftly identify operational discrepancies, providing early warnings of potential issues. Conversational AI, when paired with ERP data, can offer plain-language insights into organizational performance, making complex information accessible to all levels of management. And advanced root cause analysis capabilities can elevate reporting from merely stating what is happening to explaining why it’s occurring, enabling more informed decision-making.
It’s crucial to understand that AI is not a monolithic solution but a diverse set of technologies and approaches. A successful pivot to AI can bring about harmony in operations, clarity in decision-making, and significant time savings across various business functions. As companies embark on this journey, they should remain flexible and open to discovering unexpected areas where AI can drive innovation and efficiency.
The resurgence of ERP technology represents a pivotal moment for businesses. The modern ERP is now a cornerstone of digital transformation, data integration, and advanced analytics—and as a result, the stakes for getting your ERP transformation right are higher than ever before. A move to a next-generation ERP ecosystem can drive operational efficiency, enhance decision-making, and provide a competitive edge.
You don’t have to do it alone. Spaulding Ridge, with its deep expertise in finance-led innovation and enterprise data, is well-positioned to help companies navigate the intricacies of modern ERP implementations. Our team of experts can provide valuable insights, tailored strategies, and hands-on support to ensure your ERP transformation delivers maximum value. Reach out to learn more about what a modern ERP system can do for you.
