3 Ways Your Wholesaler ERP System is Failing You

  • Despite the helpful features and functionalities, ERP systems have shortcomings in a few critical areas

  • AI technologies are able to act as an ERP optimizer to leverage your existing system

The supply chain is the world’s most complex logistics challenge, where efficiency and accuracy are critically important to ensure goods are accessible to consumers when needed. Enterprise Resource Planning (ERP) systems play a key role for wholesale distribution companies in this process, serving (among other things) as the inventory management software that attempts to ensure that the right products are available in the right quantities at the right time and place. However, despite the promise of seamlessly managing inventory operations, ERP systems fall short in several key areas, opening up wholesalers to vulnerability, disruptions, and lost profits.

Understanding Wholesaler ERP Systems

An ERP system offers several business functions in a single platform, providing real-time visibility and control over inventory operations. In the world of supply chain management, ERPs allow wholesalers to track, manage, and purchase their inventory across multiple locations.

There are several ERP solutions to choose from that are tailored for the wholesale distribution industry. Each system comes with its own unique features and functionalities designed to address specific needs within the supply chain, including inventory management. With so many options, wholesalers can select an ERP system that specifically aligns with their requirements, challenges, and budget.

Key Wholesaler ERP Inventory Functions

ERP systems offer various functions to enhance inventory management efficiency and accuracy:

  • Real-Time Inventory Tracking: ERP systems enable businesses to monitor inventory levels in real-time across various locations, warehouses, and distribution centers. Real-time visibility allows for more informed decision-making, such as identifying dead stock or excess inventory and taking corrective actions.
  • Demand Forecasting and Planning: By analyzing historical data, ERP systems assist in forecasting demand, typically using a moving average or simple exponential smoothing to calculate a monthly demand or “usage” number.
  • Inventory Replenishment: Wholesaler ERP systems calculate inventory levels for each SKU based on factors such as lead times, demand history, and service-level targets. They then create suggested POs to vendors as well as transfers from the distribution centers to branches.

Common Failures in Wholesaler ERP Systems

Despite the helpful features and functionalities, ERP systems have shortcomings in a few critical areas, leading to inventory management inefficiencies that hurt the bottom line.

1. Late and Inadequate Response to Sharp Changes in Supply and Demand

Today’s business climate demands agility and quick action considering volatile market conditions and unforeseen disruptions. ERP systems struggle to adapt quickly to sudden changes in supply and demand, and when faced with a surge in demand or a delay due to a supply chain disruption, they often fail to provide timely insights or recommendations — often not catching up to the change for several months. This leaves businesses scrambling to react effectively. This lack of ERP agility can result in dead stock, excess inventory and missed sales opportunities, impacting customer satisfaction and profitability.

2. Failure to Account for Lost Customers

A common blind spot of many ERP systems is the inability to account for lost customers in demand forecasting and inventory planning. Customer churn changes demand, which is often overlooked in ERPs and leads to inaccurate demand forecasts.  Thrive studies across many wholesalers have shown that wholesalers have a heavy concentration of stocked SKU’s that sell to only 1 or 2 customers.  Without accounting more quickly for lost customers, businesses overstock or understock certain products — leading to increased carrying costs or stockouts. Incorporating lost customer data into demand forecasting models is crucial for improving forecast accuracy and optimizing inventory levels.

3. Inaccurate Min/Max Suggestions for Low-Selling SKUs

A significant challenge in wholesale inventory management is dealing with low-selling SKUs, which often lead to dead stock. ERP systems cannot accurately forecast demand for low-selling items, leading to excess inventory levels or lost sales that reduce profitability (and potentially customers). Since high volume SKU’s (eg A and B items) account for the majority of sales, buyers naturally prioritize high-selling SKUs over low-selling ones, further exacerbating the problem. As a result, businesses are left with stagnant inventory (from C and D items) that takes up valuable warehouse and branch space and hampers cash flow. A smarter dynamic non-forecast based method for low-selling SKUs is essential for mitigating the consequences of dead stock.

While ERP systems serve as crucial tools in inventory management, they have shortcomings that require ERP integrations such as AI technologies to supplement their functionality. In the fast-paced world of supply chain management, wholesalers cannot solely rely on their ERP system. Those that do run the risk of dealing with considerable consequences — dead stock, overstock, lost sales, disappointed customers, and a negative reputation. By leveraging advanced AI technologies such as those offered by Thrive Technologies, wholesalers can enhance the responsiveness, accuracy, and efficiency of their inventory management practices.

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