How can you use ERP data to speed up order fulfillment?

For manufacturers, an ERP system allows quoting and estimating to be done using accurate data not only on costs, but also on what inventory is available and what production capacity is available to make the products. Customer orders placed are immediately viewable by procurement so they can order the right items, and by factory teams so they can schedule jobs.

Companies have long utilized Business Intelligence (BI) for demand forecasting and planning. However, with the advent of Data Science, precision has reached a point where algorithmic models can foresee a customer's next purchase. Leveraging purchase history, existing contracts, and newly won contracts of our B2B customer, these models enable us to predict the precise quantity and delivery date of items even before receiving a request for a quotation from the customer.

Real-time Inventory Tracking: Utilize ERP data to maintain up-to-date inventory levels, ensuring products are available for prompt order fulfillment. Order Automation: Automate order processing within the ERP system to reduce manual tasks and decrease order lead times. Demand Forecasting: Leverage historical sales data to forecast future demand accurately, enabling proactive order planning. Efficient Routing and Logistics: Use ERP data for optimizing order routing, carrier selection, and delivery routes to minimize transit times. Enhanced Communication: Implement ERP-driven notifications and alerts to keep customers informed about order status, fostering transparency and trust

ERP systems excel at delivering descriptive analytics of order history, sales trends, product mixes, and monthly trends to help understand what has happened. Adding predictive analytics through forecasting models, machine learning algorithms, and prescriptive analytics to recommend actions is helping to optimize inventory levels, production planning, and reduce costs. Effective analysis happens when it's built on a manufacturer's business model first. It is strengthened with cross-functional collaboration to identify key performance indicators that align with and drive results on shared goals. Gartner found that an analytics-driven demand-sensing approach helped deliver over 5% revenue growth and 7% lower inventory costs over three years.

The addition of process workflows could help us in this situation. Workflow dictates how an order must be automated through different stages like inventory reservation or Kanban-style pull manufacturing order.

Use ERP data to create simulations on flows. This way it is possible to predict bottlenecks and optimize flows in a model before changing the whole actual logistical setup.

Streamlining workflows and automating tasks helps reduce manual data entry, reduces the need for parallel processes, and improves communication and collaboration across shop floors. Using ERP data to map out the order fulfillment process and identify bottlenecks, errors, or inefficiencies is a great first step. Have a solid plan for integrating every aspect of operations into an ERP system to get the most value from your investment using APIs to streamline integration. Nearly every company with an ERP system uses data to trigger alerts, notifications, and reminders for your staff and customers, such as order confirmation, payment status, and tracking information. These steps will accelerate order fulfillment and delight customers.

ERP data is essential for monitoring and improving order fulfillment workflows at scale. Key metrics include order volume for tracking demand, order accuracy to reduce errors and costly returns, order cycle time that highlights bottlenecks, and order fulfillment rates to assure high levels of customer satisfaction. The manufacturers getting the most value from their ERP data realize they are competing with themselves to see how far they can improve each process to reduce wasted time and deliver products beyond customer expectations.

Some ERP vendors provide integrated Customer Relationship Management. CRM stores and analyzes data collected from customer interactions via multiple communication channels like email, phone, chat and social media. Business analytics enhanced with generative AI enables highly accurate sentiment analysis and gives a 360° profile view of every customer. An accurate and deep understanding of every customer's product, service and reward preferences empowers the business to have a personalized approach in recommending and fulfilling orders proactively and rewarding the customer's loyalty eventually.

Use Generative AI to enable the automation of process. It is game changing in this area of ERP and we are only scratching the surface. Take a look and see.