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There’s a reason 87% of organizations surveyed by APQS call inventory management a focus area for their supply chains in 2022. It’s been a tough couple of years, with almost half (46%) or those surveyed missing their business goal targets in 2021, APQC found.  

The inherent challenges of managing inventory got even harder as supply chain disruptions have endured, turning up the heat in volatility, uncertainty, and constraints.  

But that doesn’t mean you have to be content just to mitigate the impact of these headwinds. By leveraging advanced inventory management techniques such as advanced vendor-managed inventory (VMI) and multi-echelon inventory optimization (MEIO), you can not only regain control of your inventory, but make it work harder for you, delivering even greater value. 

As you become a mature user of a well-designed supply chain planning software, you can leverage its advanced features to redefine your holistic inventory network strategy. For example, you can better understand where to position buffer in your network and maximize the balance of inventory of finished goods vs raw material and semi-final goods.   

Here are some key things you can do at mature levels of inventory management: 

Multi-echelon Inventory Optimization (MEIO)  

The “echelons” of multi-echelon inventory optimization are nodes of your supply chain network, such as your  suppliers or your component manufacturers. MEIO takes managing inventory to the next level by optimizing the ideal location and size of inventory levels for all locations (echelons) while considering all the dependencies, costs, constraints and sources of demand and supply variability across the entire network. An effective MEIO solution suggests the right levels of inventory at each stage of the supply chain by managing and optimizing inventory balance across multiple echelons and locations in parallel. 

Optimize all the “Moving Parts” 

One of the biggest challenges of effective inventory management is taking into account all the factors, such as cost, service level, and segmentation, that influence outcomes. You should be able to integrate any level of costing data, including: 

  • Customer service costs 
  • Supply chain management costs such as direct manufacturing costs and transportation  
  • Sourcing costs including COGS & procurement costs 
  • and many more.  

This means you can perform cost-to-serve analysis—logic that determines the optimal service level versus working capital using inventory/service trade-offs—at any level of detail, including family and individual items/SKU.  

Advanced Automation 

You can tap techniques including AI and machine learning to automate tasks such as identifying root causes, then sending alerts or augmenting decision-making around the finding. That frees supply chain talent up for more value-adding activities. APQC found 24% of organizations they surveyed call automation and digitization a top focus area in their supply chain planning.  

Optimized Safety Stock Calculations 

Use of technologies such as machine learning help you move beyond static and traditional inventory target calculations. You can use machine learning to determine optimal safety stock calculations and deliver recommended actions and alerts. According to Gartner’s “The Rise of the Ecosystem—and 4 More Supply Chain Predictions,” by 2026, more than 50% of supply chain organizations will use machine learning (ML) to augment decision-making capability. 

Advanced VMI: A particularly exciting opportunity to maximize the value you can get from inventory comes in advanced VMI.  

One avenue is creating virtual inventories for your customers based on channels. For example, John Galt Solutions’ customer Randa Apparel & Accessories, a major global fashion manufacturer, created a virtual supply chain network featuring a virtual warehouse for each retailer (e.g., channel) that models its product lanes, inventory flows, customers’ destinations and other elements. Channels can also be ecommerce, distribution center, regional distribution centers, stores, transfers, etc. Randa uses the Atlas Planning Platform to model multi-channel distribution using multiple demand streams to manage inventory at every node (DC, regional DC’s, stores, etc.) in the supply chain network.   

Advanced VMI functionality also means you can evolve your processes to support end-to-end collaboration and enrich the customer experience. VMI enables you to see item and location consumption and inventory data, and is a key enabler to reducing inventory and improving customer service within the value chain. 

Experimentation and Innovation 

When you reach advanced stages of inventory management, you can discover new ways to leverage inventory for competitive advantage, such as Amazon has done with cutting delivery times. A digital supply chain twin facilitates advanced experimentation such as simulations and what-if scenarios, so you can see the potential impact of proposed inventory strategies. 

One outcome of the chaos of the last few years is that supply chains are now seen as a key enabler of strategy. “The supply chain is no longer just an efficient maker and mover of goods; it’s now a principal driver of business growth,” Kris Timmermans, global supply chain and operations lead at Accenture, told Supply & Demand Chain Executive.  

Smarter inventory management is one of the most powerful levers to drive supply chain results. Find out how the Atlas Planning Platform helps you unlock the full power of your supply chain.