What’s Wrong with Modern Supply Chains?
Feb 07, 2020
Technological advancements and globalization have transformed the world into a communal village, where global citizens, along with businesses, partake in the global arena. Even though technology and globalization have affected radical transformations across different fields, the supply chain has remained relatively static and resistant to change. This has created a mismatch between capacity and the current management needs of the modern supply chain. The complex nature of the globally-interconnected supply chain requires the adoption of an advanced supply chain control tower to automate the supply chain and address demand planning inaccuracies and lack of procurement and inventory management capabilities.
Supply Chain of organizations (Source: shutterstock.com)
Demand Planning Inaccuracy
One of the main issues with the modern supply chain is the demand planning inaccuracy due to the disconnect between Enterprise Resource Planning systems (ERPs) and the systems managing customer data. The disconnect between ERP data and customer data impedes demand planning because demand forecasting requires accurate, up-to-date, and extensive historical sales data and this divide between ERPs and customer data leads to the implementation of inappropriate planning. Subsequently, demand planning and supply chain management based on inaccurate forecast undermines the ability of businesses to capitalize on increases in demand and exposes businesses to the possibility of incurring losses. This is because businesses can overstock to cater to a false increase in demand forecasted in the foreseeable future leading to losses as overstocks expire in warehouses. For example, Walgreens’ demand planning in 2014 based on an inaccurate forecast led to a loss of $1 billion1.
Lack of Inventory Management Capacity
Another problem in the modern supply chain is the mismatch between the volume of inventory and procurement and the capacity to manage the large volumes effectively. In the modern supply chain, current procurement and inventory management techniques are ‘beyond human capacity’ leading to expirations, overstocks, stock-outs, and wastage such as excess cross-warehouse movements. Today, supply chain organizations must set PAR levels for every SKU in every point of storage where the SKU is being stored and then they must add reorder quantities for each SKU. All of this translates to setting millions of parameters and making sense of all this data is overwhelming for even the best supply chain professional. This overwhelming amount of data is what leads businesses to amass waste, however, incidents of overstocks, stockouts, and expirations, and other types of wastage can be eradicated by increasing the supply chain’s capacity to manage procurement and inventory. The fact that current procurement and inventory are beyond human capacity implies that automation of the modern supply chain is the most viable alternative to enhance capacity. Lack of capacity for managing procurement and inventory in the modern supply chain highlights why a business needs to use ERP systems and modules with advanced software to enable automation and lead to a truly modern supply chain. Automation of the modern supply chain will enhance the dependability of demand forecasts and the accuracy of demand planning, decreasing overstocks, stock-outs, and wastage, with an increase in profitability.
Businesses can eliminate demand planning inaccuracies by using Seeloz’s Artificial Intelligence to manage their supply chain. Seeloz’s Supply Chain Automation Suite (SCAS) can automate parts of a supply chain organization and have a profound effect on their business. This technology enhances automation of the supply chain by injecting a layer of smartness into operations across distribution, outlets, warehouses, and production plants. Our AI provides the tools to organize, monitor, and manage the entire supply chain. To address demand planning inaccuracies, businesses can use our tools to enhance the connection between ERP data and customer data and enable extensive incorporation of historical sales data in demand forecasting. Ultimately, incorporation of historical sales data will enhance control over inventory, shipment, and expirations.
For automation, SCAS correlates all supply and demand variables to offer businesses with a 360-degree visibility of the past, current, and future performance. Subsequently, SCAS recommends actions to improve operations of the supply chain in the future. It is important to note that SCAS was designed to enable the supply chain to operate autonomously under human supervision as it fulfills the needs of consumers. To address capacity issues in the management of procurement and inventory, businesses use our Autonomous Procurement and Inventory (API) feature, which autonomously sets the PAR level and reorder points for every SKU in each warehouse. This is important because it allows demand planners and distribution planners to reduce overstocks, stock-outs, and expirations. For example, SCAS will enable ERPs to communicate with systems, such as Warehouse Management System (WMS) and Transport Management System (TMS), at different levels simultaneously. Autonomous communication allows ERP to place a delivery order to WMS. The WMS alerts an employee to deliver the products to the dock as the ERP signals TMS to schedule a vehicle to pick the products and deliver to the customer. The high-level automation offered by Seeloz reduces the manpower required to collect, analyze, and adopt the forecasts in decision making. This module undertakes data collection and analysis, delivering the forecast to relevant parties for execution, leading to improved flexibility and agility to changes in demand. Seeloz’s SCAS has proven to reduce expirations by 80%, overstock and stock-outs by 50% and an increase in profitability by 40%.
These results and the supply chain transformation Seeloz provides is only the tip of the iceberg for what will be an AI revolution within the supply chain space. Wait too long and you could possibly be left in the dust.
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