The Brains behind the Supply Chain – ERP driven by AI

Artificial intelligence isn’t just a buzz word any more.  The potential of AI to enhance business processes by being embedded in ERP systems, is more than a vision, it has become ready for rapid implementation.

When AI or machine learning is embedded into ERP the productivity and the quality of customer service can be dramatically improved by optimizing the integration of data and processes between suppliers, manufacturers, distributors, retailers, and customers.

Here are five benefits that can be experienced by empowering ERP with AI capabilities:

Eliminate tedious tasks – Already used by call center agents to recommend answers to clients’ questions and make upsell and cross-sell suggestions, chat bots can also eliminate valuable time and money wasted on trivial supply chain related tasks.  According to a recent study businesses estimate they spend on average 6500 hours during the work year doing manual, paper-based processes including chasing invoice exceptions, discrepancies and errors. Chatbots can be used to respond to internal and external inquiries regarding invoices and payment requests. Amazon already communicates with customers using automated messages.

Reduce shipping costs – Global supply chain managers can use sensors to track the exact location of ships, containers, and trucks while using AI to route packages more efficiently.  Jack Levis, director of process management for United Parcel Service (UPS) says that for every mile that its drivers in America are able to reduce their daily route, the firm saves around $50m a year. Tools like shock-detecting sensors can make them aware of potential damage to cargo. Maersk technicians are able to see the precise location and operational details of 270,000 refrigerated containers full of perishable commodities.

Manage inventory better – AI systems can automate the labor-intensive task of finding items while identifying inventory and order patterns to reveal which items are selling and should be restocked first.  Lowe’s LoweBot that was deployed in 11 stores throughout the San Francisco Bay Area used a searchable computer display, advanced voice recognition, and laser-based sensors (similar to technology used in autonomous vehicles) to find the exact location of products inside the store, and also to make demand forecasts for new purchases.  AI can also be used to determine how to lay out a new warehouse, improve an existing warehouse, add equipment, update picking methods, or optimize staff for a busy season.

Deliver products more quickly – The last step of the sales process can be the most important for customer satisfaction.  Delivery planning requires some amount of machine learning optimization to categorize product that would require immediate delivery over others, then orders have to be grouped together based on distance, time and load capability.  Machine learning models can be deployed to find the most often ordered products and have those sections placed adjacent or having it in a separate warehouse would reduce the time and effort required by the packer. Amazon late last year was granted a patent for what it calls “anticipatory shipping,” a method to start delivering packages even before customers have clicked “buy” by having products located in warehouses closer to their predicted final destination.

Optimize procurement – Today, according to Gartner procurement technology vendors are using AI technologies to further increase automation and efficiency. By analyzing historical trends and business risk data, finance and procurement professionals can derive suggested discount rates on invoices, optimize cash flow, and create the optimal balance between buyers and suppliers. AI agents operate on behalf of the buyers and sellers to locate potential deals, automatically and anonymously negotiate towards the best terms based on the parameters set and market conditions.  By analyzing data for hidden patterns procurement could identify which departments are likely to overspend next month, which suppliers may be likely to face challenges next year and where materials prices are headed over the longer term to help decide which suppliers to choose.

But being armed with AI is not enough. To optimize the supply chain ERP systems must be open so that they can be easily integrated with partner, supplier, and customer systems to provide automatic communications while also gathering the necessary data to gleam powerful insights.  They also need to be highly flexible to adjust to the fast pace of market and technological changes.

ERP with real-time visibility into business operations enables organizations to make more informed decisions to adapt quickly to changes in the marketplace. By automating labor intensive error prone tasks employees can be more responsive to customers, while having more time for more creative and strategic tasks.  In addition ERP provides the glue along the customer journey so by optimizing each step companies can experience a tremendous boost in productivity.

With the huge opportunity to increase profitability and customer satisfaction, it’s only a matter of time before AI is an expected and necessary part of managing the supply chain using ERP systems.