Guest Commentary: Finally, A New Way to Look at Inventory Optimization

Finding the balance between overstocks and lost sales is necessary for operational growth and health. With so many flavors of inventory optimization applications available, why do so many companies still struggle with inventory inefficiencies? It’s because traditional inventory applications fall short in three key areas:

  1. They assume that all demand is smooth and normally distributed
  2. They only consider safety stock for the existing supply chain structure
  3. They do not simulate real-world behavior or enable what-if analysis

There is a new way to approach inventory modeling and policy design that enables companies to analyze and properly categorize demand, factor all aspects of inventory for both existing and new supply chain structures and simulate real-world behavior to enable true “what-if” capabilities. Together, these capabilities provide a prescription for the right levels of working capital across a continuously-changing business. So let’s look at the three advantages of looking at inventory optimization in this new, holistic manner.

Advantage 1: Understanding Demand
Simply stated, safety stock is your insurance against variability in the supply chain. One of the biggest sources of variability in the supply chain is demand, and demand can be highly unpredictable, occurring in patterns from fast to slow, smooth to erratic, intermittent to consistent (Image 1). Despite this fact, most inventory optimization tools assume that all demand is “normal,” leading to either too much inventory or stock-outs and lost sales.

Image 1: Different Patterns of Demand

Image 1: Different Patterns of Demand

Intelligently adapting to widely-varying demand behaviors is the key to better safety stock results. Comprehensive multi-echelon inventory optimization technology can actually act as a guard against inventory variability. This is achieved by analyzing and classifying the underlying demand patterns into categories (Image 2), then applying the appropriate inventory optimization algorithm to set the proper reorder points and quantities required to meet the user-defined service targets. Of course, this is all done automatically using advanced algorithms.

Image 2:   Image 2: Example of classification of varying demand patterns

Image 2: Example of classification of varying demand patterns

Advantage 2: Covering all Aspects of Inventory for Both Existing and New Supply Chain Structures
There are multiple types of inventory held throughout the supply chain, including cycle stock, pre-build stock and work-in-progress (WIP), so why do most inventory applications only focus on safety stock?  And why can’t most applications consider alternative supply chain structures? The answer is that most inventory applications do not include network optimization capabilities.

Network optimization is the technology required to consider the optimal flow of products throughout the supply chain and inherent cycle stock given the trade-offs between a host of variables including transportation modes and facility locations. Multi time-period network optimization is the technology required to determine when products need to be pre-positioned to accommodate seasonality or capacity constraints. Working with a combined network and inventory optimization solution, planners can evaluate all aspects of inventory including safety stock, cycle stock, pre-build stock and WIP.  This integration also enables analysts to consider completely new supply chain structures such as the opening/closing of distribution centers or manufacturing locations, then immediately evaluate the optimal inventory requirements for these new potential networks.

Advantage 3: The Power of Adding Simulation to Inventory Optimization
Although companies can identify millions of dollars in annual cost savings through right-sizing inventory levels, optimization technologies have limitations to how well they can predict operational performance under the stress of real-world day-to-day variability such as transportation delays, production lead times and demand. The only way to truly test the effects of these multiple levels of variability is to use discrete event simulation. Simulation can digitally “run the clock” to fill each order and schedule each shipment to provide detailed performance metrics such as on-time deliveries, stock-outs or capacity bottlenecks. Once an inventory strategy has been chosen using optimization, simulation is an excellent method to test it further, providing validation that the new inventory policies work as intended.

A New Weapon for Supply Chain Excellence
Finding the balance between overstocks and lost sales isn’t easy. Fortunately, new tools are available to allow companies to analyze and properly categorize demand, consider all aspects of inventory for both existing and new supply chain structures and simulate real-world behavior. These capabilities give companies the resources they need to finally conquer the inventory challenge and achieve a healthier overall business.

Toby Brzoznowski is the Executive Vice President of LLamasoft, Inc. Toby has over 20 years of experience in building and growing businesses, focused on process improvement and analysis technologies. His expertise has been applied to bringing new and advanced technologies into mainstream use at global Fortune 500 businesses. In the last decade, Toby has been involved in the start-up of three technology companies. He is a graduate of the University of Michigan and a frequent presenter at supply chain and strategic sourcing events.

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