How Two-Tier ERP With AI Can Address Today’s Business Challenges
Discover the flexibility and cost-saving potential of two-tier ERP systems with AI integration.
By combining the power of artificial intelligence and machine learning within two-tier ERP systems, companies can uncover new ways to optimize tasks such as document creation, compliance, demand forecasting, supplier sourcing, and more, says Achim Clemens and Akash Agrawal of SAP.
In the past few years, a perfect storm of consumer demand and connected supply chains has pushed companies to prioritize flexibility across everything they do. This challenge means thinking outside the box to balance meeting consumer attitudes and making production feasible.
With more and more customers opting for personalization and speed, major manufacturing companies are questioning whether their traditional enterprise resource planning (ERP) platforms address their needs. However, the growth of artificial intelligence (AI) and machine learning offers an opportunity to update their approach, making software development more accessible and efficient for enterprise organizations – especially those managing global operations.
ERP platforms will play a crucial role in this business transformation, and two-tier ERP systems can help unlock the flexibility and scalability needed for success. Combining the strengths of two-tier ERP with a rich set of AI integrations can go a step further, addressing areas like inventory management, demand forecasts, and more across the organization.
The Business Case for Two-tier ERP
Sprawling supplier networks have created a new reality for today’s businesses. Not only are they managing operations in multiple markets, but they’re also tasked with ensuring each location has access to up-to-date data to comply with local regulations.
With a two-tier ERP, a company’s headquarters can use a customized tier 1 ERP that handles core business functions like finance, human resources, and procurement. In comparison, subsidiaries or smaller business units use less resource-intensive tier 2 ERP that suits their needs specific to each location. While the ERPs are technically “separate,” information flows from the tier 2 system to tier 1, creating a single source of accurate data for the entire enterprise.
By implementing two-tier ERP, companies can help address critical use cases across their operations, with AI adding another layer of efficiency.
Saving Costs Through Customization
Two-tier ERP is a perfect solution for companies operating in multiple countries that need a platform tailored to the needs of specific markets. Many large-scale enterprises are still relying on a legacy tier 1 ERP that has been customized over many years, with potentially hundreds of different customizations added for different use cases. While this legacy tier 1 application may be a foundational piece of the business’ operations, implementing the same system in smaller markets with different needs would be costly and cumbersome.
A flexible tier 2 platform can solve this problem. Companies can ensure accurate data flows from subsidiaries to tier 1 ERP by tailoring the ERP tech to the local language and currency. Configuring the tier 2 to local regulations also avoids the issue of managing international compliance.
These small steps offer some immediate opportunities for cost savings that could go a long way. However, implementing AI and machine learning can take things a step further without creating additional bloat on the system. In fact, by adopting the two-tier approach, one company reduced its customization footprint by over 90%, which helped it handle solution updates 18 times quicker.
AI can play a key role in that speed, eliminating the need for manual data entry and intervention at certain tier 2 locations by automating repetitive tasks within the specific ERP – such as creating accounts payable documents – to generate cost savings. Trained on the business activity at each location, AI can also generate personalized insights, sales forecasts, and supplier performance reports. Based on those insights, the same company is also using machine learning to predict financial results.
Customizing two-tier ERP with relevant AI capabilities can elevate the platform from a flexible solution to a powerful, data-driven one that can identify key moments for cost-savings across the enterprise.
See More: Ready or Not, the Shift Is Here: Trends Driving ERP Decision-making
Meeting Specific Business Needs
Companies operating in multiple countries may also have business activity that spans multiple industries – requiring a solution tailored to those verticals. Some subsidiaries may even have a completely different business model. Those locations focused on different industries or serving a niche market need features that the tier 1 ERP simply won’t have.
To help scale its business both nationally and globally, one company decided to replace its on-premise ERP and consolidate its platform in select countries. Knowing that its core business in Europe differed from other markets, it turned to two-tier ERP to address deeper insights and accelerate operations. Doing so helped the company handle tasks ranging from cash and receivables management to invoicing, booking, and revenue recognition. These integrated workflows not only increased productivity and transparency but also improved speed and customer service.
AI can analyze large volumes of data in markets with specific business needs to evaluate market trends and competitor pricing. By integrating external data sources into two-tier ERP, such as third-party applications or market databases, AI can aggregate data from these sources to identify patterns or trends specific to the business that they may not have spotted otherwise.
These personalized recommendations are tailored to the company’s unique requirements and preferences in that market, whether recommending inventory levels or identifying nearby suppliers when needed. Altogether, this information can help the business optimize its pricing in real-time and even forecast future trends based on customer activity to remain competitive.
Standardizing Processes and Compliance
In a global business without an integrated or standardized ecosystem of subsidiaries, growth can be slow and expensive. Managing multiple ERPs across countries presents an even bigger challenge: ensuring standard processes and compliance.
But with the two-tier approach, companies can rely on a single scalable, cloud-based data system that connects back to a core ERP. This ensures access to real-time data throughout the entire operation, allowing subsidiaries to stay agile and offer a consistent customer experience.
In organizations with a widespread subsidiary network, tasks like creating customer invoices may need to be done manually, and tasks like running global inventory levels could be time-consuming. Two-tier ERPs can ensure that data flows between sources smoothly, ensuring cross-business visibility, managing compliance, and speeding up reporting tasks. For one business, it helped reduce the time for monthly enterprise-wide inventory reporting from 6-8 hours to just 20 minutes.
AI can help ensure that this increased speed does not sacrifice quality. Algorithms can continuously monitor data moving through ERP tech to ensure that it complies with local regulations and industry guidelines, spotting anomalies, unauthorized transactions, and more. Natural language processing (NLP) AI can extend these capabilities to documents, analyzing legal contracts and other policy documents to check that each partner throughout the network meets the necessary standards.
Adapting ERP Systems for Market Needs
A two-tier ERP approach offers the flexibility, customization, and cheaper maintenance and upgrade costs that a legacy tier 1 ERP can’t provide. In a business environment where quick adaptation determines who will be successful and who will fall behind, multinational corporations should consider how they can adapt their ERP to different markets to better address their needs and uncover opportunities that they otherwise couldn’t pursue.
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