Powerful AI: ERP Systems are necessary

We step deeper into the AI world – every day new apps and features might attract our attention. But the landscape of business operations is evolving at an unprecedented pace as well. Everything Digital became the first commandment of today’s world. Both digital and the AI integration across various business units transform how enterprises function, compete, and grow. With this transformation comes the need for IT platforms that can efficiently manage the increasing complexity of modern business processes. One such system is the Enterprise Resource Planning (ERP) system, which provides the backbone necessary to support the complex transactional nature of online businesses, the intricate supply chains spanning regions and continents, and the advanced analytics needed to thrive in an online-centric economy.

The Transactional Nature of Online Businesses

Online businesses must operate in a fast-paced environment characterized by high-volume transactions. These transactions are the foundation of online commerce, tracking everything like order placements, inventory updates, payment processing, and shipping logistics. Consider an online retailer like Amazon, which processes millions of customer orders daily. Each order includes a series of transactions such as product order, payment transaction, delivery promise, inventory adjustment, order fulfillment, and shipping. The seamless integration on the data layer will ensure visibility into customer satisfaction and business efficiency.

The complexity of these transactions requires robust systems that can handle vast amounts of data in real-time. ERP systems excel in this area, providing a centralized platform to manage all aspects of business operations. They ensure that every transaction, whether it’s a sales order or an invoice are accurately recorded and accessible across the enterprise. Such real-time visibility is essential for management: decisions on pricing or refilling inventory are supported by intelligent tools and algorithms to manage enterprise resources effectively and to maintain a competitive edge in the market.

Typically, online businesses operate across multiple channels—websites, mobile apps, social media platforms, and still physical stores. ERP systems enable seamless integration across these channels, ensuring consistency in pricing, inventory levels, and customer experiences. For instance, if a customer purchases a product online and chooses in-store pickup, the order management feature of an ERP system ensures that the inventory is updated in real-time, the product is reserved, and the customer receives timely notifications about their order status.

Tracking Products Along the Supply Chain

The pandemic showed us that supply chains have become complex and globalized. Shortages of raw materials and semi-finished goods caused major interruptions of product sales and deliveries. Today, supply chain functionalities of ERP systems sport effective tracking capabilities that glue the different sets of transactions together for full visibility. The systems do not only move products from point A to point B; they know at any point in time their location with visibility of cost, margin, and customer satisfaction.

The ERP systems play a critical role in capturing all transactional data points. They provide end-to-end visibility into the entire process, from sourcing raw materials to delivering finished products to customers. This visibility is crucial for several reasons:

1. Raw Material Sourcing: ERP systems help businesses manage relationships with suppliers, track the procurement of raw materials, and ensure that materials meet quality standards. They also enable businesses to forecast demand accurately, enabling real-time stocking of materials. For example, a manufacturer of electronic components might use an ERP system to track the sourcing of rare earth metals. The system can monitor supplier performance, track material costs, and ensure that the materials arrive on time to meet production schedules.

2. Manufacturing and Production: During the manufacturing process, ERP systems track the movement of materials through various stages of production. This includes work orders, monitoring production schedules, and ensuring that finished goods meet quality standards. ERP systems can also optimize production schedules, reduce waste, and improve overall efficiency. For instance, in a car manufacturing plant, the ERP system can track each component as it moves along the assembly line, and times the deliveries from OEM manufacturers to the production cycles.

3. Inventory Management is one of the most critical aspects of production planning. Is the inventory to high it requires capital that could be used elsewhere. If inventory is too low, then customer orders can’t be fulfilled. ERP systems can balance the optimal levels and allow business managers to maintain optimal stock levels. ERP systems can also predict demand trends from customers and plan inventory levels accordingly. For example, a fashion retailer might use an ERP system to track inventory across multiple warehouses and store locations, ensuring that popular items are always in stock while minimizing excess inventory.

4. Logistics and Delivery: ERP systems also manage the logistics of delivering products to customers. This includes coordinating with shipping carriers, tracking shipments in real-time, and ensuring that deliveries are made on time. ERP functionality can calculate delivery route optimization, predict potential delays, and provide customers with accurate delivery dates. A global logistics company might use an ERP system to track shipments across multiple countries, ensuring that customs regulations are met and that shipments arrive on time.

5. Billing and Payments: ERP systems streamline this process by automating invoicing, tracking payments, and managing accounts receivable. This ensures that businesses are paid promptly, and that cash flow is managed effectively. A wholesale distributor, for instance, uses an ERP system to stay current with their financials, always have full visibility on top and bottom line.

Transactional Data for Analytics and AI

Data is one of the most valuable assets a business can possess (“Data is the new oil.”). Every transaction within a business generates data that can be used for analysis, decision-making, and strategic planning. An ERP system as the single source of truth is central to collecting, storing, and managing all transactional data within its database.

However, data on its own is not enough. The true value of data lies in the insights it can provide when analyzed effectively. This is where AI, particularly supervised machine learning (ML), comes into play. By leveraging the transactional data collected by ERP systems, businesses can train ML models to recognize company-specific or business unit-specific trends and predictions of future outcomes developments.

1. Trend Analysis: Of course, before the advent of AI, the businesses calculated trends and predicted the future. BUT: with supervised Machine Learning, transactional data analysis became more intelligent and flexible. Actual data points feed into the AI models and make analytics more flexible than older “hard coded” analytical models. If Apple launches new products, the customer orders define the shipment orders from their production locations in China.

The question of which AI capability is being used isn’t easy to answer. In the Apple case, their algorithms are the best guarded company secret – and not accessible to anyone outside their firewalls. But one argument we can make: it’s NOT generative AI or any form of ChatGPT.

2. Demand Forecasting: By analyzing past and actual sales data, seasonal trends, and external factors like economic conditions, Business Intelligence [BI] can predict future demand with high accuracy. Business leaders can optimize inventory levels, reduce waste, and ensure that products are available when customers need them. For example, a grocery store chain might use BI to predict the demand for perishable goods like fresh produce, ensuring that they stock just the right amount to minimize spoilage and maximize sales.

3. Customer Segmentation: By analyzing transactional data, AI models within ERP systems can help segmenting their customers into different groups based on purchasing behavior, preferences, and demographics. As a result, laser-sharp marketing efforts can target customer groups with personalized ads for best results.

4. Pricing Strategies: AI can analyze market data, competitor pricing, and customer behavior to launch dynamic pricing strategies for optimal results. We know these strategies form airline, and train tickets: the closer you come to a target date the higher is the demand, and in result, the higher is the price. AI adjusts ticket prices dynamically based on real-time demand, seat availability, competitor pricing, and other factors.

The Future of ERP Systems in the AI Era

AI will continue to evolve within ERP systems. While hope and expectations for AI to deliver value to business are sky high, the software vendors are not there yet. Look at the big ones like SAP, Oracle, and Salesforce. They all put AI on each page of sales presentations – but it’s still a way to go to really help specific companies. There are AI models available for certain business scenarios, but these models must be trained with company-specific data to deliver value. In some environments, data lakes must be designed first and filled with data afterward. In other scenarios, existing data can be used to train ML models right away.

It’s still a long way for the software companies to exercise and operationalize the AI terms from the PowerPoint level to execution. But the software companies can’t do it without their customers. It must be a collaborative effort to extract business value from the AI capabilities.

ERP Systems as the Foundation of AI-Driven Business

When I teach my students at the Villanova School of Business about ERP, I make it transparent that we need both: ERP and AI. And this means that we need to understand both as well: ERP and AI. I don’t see that “sales orders” will disappear soon. And as long they don’t disappear, an ERP system is required to track and manage the orders. And the orders will provide fundamental insight into customer preferences and behaviors. This is not only valid for sales orders, but for any order type I mentioned earlier: production order, stock order, shipment and delivery order.

By providing an integrated ERP platform for transactional data, AI functionalities will enable businesses using that data to streamline operations, optimize supply chains, and make data-driven decisions. In an AI era, where data is the new currency and speed is the key to success, ERP systems are the bedrock for successful and innovative businesses.

Personally, I’m looking forward to see “old ERP companies” like SAP transforming its transactional databases into value-add scenarios for enterprises.