Supply Chain Inventory Optimization
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Implementation Engineers helps organizations optimize inventory to improve material availability, service levels, and working capital while reducing excess, obsolete, and poorly positioned stock through expert inventory optimization services.
We evaluate inventory at the item, location, supplier, and network level to determine what inventory is needed, where it should be positioned, how much should be held, and how it should be replenished based on demand, variability, lead time, criticality, service requirements, and operational risk.
IE goes beyond inventory analysis to implement the planning parameters, policies, processes, system changes, management routines, and accountability required to sustain improved inventory performance. For complex environments, we can also apply AI and advanced optimization to predict future requirements and dynamically optimize inventory decisions as conditions change as part of AI inventory optimization.
What We Implement
Inventory Segmentation & Strategy
Apply the right inventory strategy to the right materials.
IE segments inventory based on factors such as demand, usage, variability, lead time, criticality, supply risk, value, and service requirements through inventory segmentation.
Rather than managing every item with the same rules, we establish differentiated inventory strategies based on how each category contributes to operations and customer service.
Inventory Policy & Parameter Optimization
Align inventory levels with actual demand and supply conditions.
IE evaluates and optimizes safety stock, Min/Max levels, reorder points, order quantities, lead times, safety time, and replenishment frequency as part of inventory policy optimization and safety stock optimization.
We identify outdated or inappropriate planning parameters and establish policies that better balance material availability, inventory investment, and operating risk.
Excess & Obsolete Inventory Reduction
Release working capital trapped in inventory that is no longer needed.
IE identifies excess, slow-moving, and obsolete inventory and determines the underlying causes of accumulation through excess inventory reduction and obsolete inventory management.
We develop disposition strategies while correcting the planning, purchasing, master-data, and governance issues that created the excess inventory so the problem does not simply return.
Material Availability & Shortage Reduction
Improve service without solving shortages by adding inventory everywhere.
IE analyzes shortages and stockouts to determine whether the underlying causes involve inventory policies, demand signals, supplier performance, inaccurate lead times, planning parameters, inventory accuracy, or replenishment processes as part of stockout reduction.
We implement targeted solutions that improve availability of the materials that matter most while avoiding unnecessary increases in overall inventory.
ERP / MRP & Master Data Optimization
Make sure system-generated inventory decisions reflect reality.
IE improves the master data and planning parameters that drive ERP and MRP inventory recommendations.
This can include lead times, safety stock, reorder points, lot sizes, inventory classifications, supplier data, demand inputs, material locations, and other parameters required for more reliable planning and replenishment.
Inventory Visibility & Performance Management
Give teams the information needed to actively manage inventory.
IE implements KPIs, dashboards, exception reporting, ownership, and management routines around inventory performance.
Teams gain visibility into shortages, excess and obsolete inventory, service levels, inventory turns, parameter exceptions, and other measures needed to identify issues and take action.
AI-Enabled Inventory Optimization
Use predictive intelligence to anticipate requirements and dynamically position inventory.
For complex inventory environments, IE and Vooban can implement AI and advanced optimization models that incorporate historical consumption, forecasted demand, maintenance or production requirements, lead times, criticality, supply constraints, and other operating variables.
Instead of relying solely on historical averages and static inventory parameters, AI can help predict what will be needed, when it will be needed, and where it should be positioned—allowing organizations to improve availability while reducing unnecessary inventory.
Why Inventory Optimization Matters
More Inventory Doesn’t Necessarily Mean Better Availability
Organizations can carry millions of dollars in inventory and still experience shortages of the materials that operations or customers actually need.
The issue is often not the total amount of inventory. It is what inventory is being held, where it is positioned, and how inventory decisions are being made.
Outdated planning parameters, inaccurate demand signals, unreliable supplier lead times, poor master data, inconsistent replenishment policies, and limited visibility can create excess inventory in one area while critical materials remain unavailable somewhere else.
The result is higher working capital, expediting, material shortages, production disruption, excess and obsolete stock, and lower service levels through working capital optimization.
Inventory optimization creates a more deliberate connection between demand, supply, risk, service, and working capital.
And as supply chains become more complex, AI provides another level of capability—using forward-looking demand and operating data to anticipate inventory requirements rather than reacting after shortages occur.
IX® in Action | Gold Mining
Optimizing Inventory to Improve Material Availability and Reduce Working Capital
A gold producer in Brazil was struggling to maintain the inventory required to keep operations running reliably. The organization managed approximately 14,000 active inventory items through a Min/Max replenishment system that applied a standard 30-day lead time across materials despite significant differences in demand, criticality, and supply requirements.
The result was a significant imbalance in inventory performance. Critical spare parts were frequently unavailable when operations needed them, while the organization simultaneously carried approximately $13 million in obsolete inventory.
Implementation Engineers worked with the organization to redesign its inventory-management approach, establish differentiated inventory policies, optimize replenishment parameters, strengthen ERP processes, and recover value from obsolete stock.
What We Implemented
- Inventory Segmentation & Policy: Established differentiated inventory policies for capital spares, critical spares, spare parts, and consumables based on their operational requirements.
- Min/Max Optimization: Redesigned Min/Max replenishment processes, including supporting procedures, roles, and responsibilities.
- Obsolete Inventory Recovery: Classified non-moving stock, developed a structured clear-out plan, and supported the disposition and sale of obsolete inventory.
- ERP & Process Improvement: Updated inventory process flows, ERP functionality, reporting, and management tools to support improved inventory decisions.
- Inventory Management & Sustainment: Trained stakeholders to appropriately stratify, manage, and maintain inventory over time.
- Performance Management: Defined critical inventory measures and KPIs to provide greater visibility and sustain improved performance.
$3.5M
in revenue recaptured from obsolete inventory
10%
reduction in inventory
21-day
reduction in purchasing lead time
The transformation allowed the organization to move away from a one-size-fits-all approach to inventory management and establish more disciplined policies based on actual material and operational requirements. By addressing excess and obsolete inventory while improving replenishment processes, IE helped the client release working capital while strengthening material availability for operations.
Frequently Asked Questions
What is supply chain inventory optimization?
Supply chain inventory optimization is the process of determining the right inventory levels, positioning, and replenishment strategies based on demand, variability, lead time, criticality, and risk to improve availability and service while reducing excess and working capital.
How can a company reduce inventory without creating shortages?
By segmenting inventory, optimizing policies and parameters for each category, addressing root causes of shortages, and implementing targeted solutions for critical materials rather than across-the-board cuts.
Which inventory parameters should be optimized?
Key parameters include safety stock, Min/Max levels, reorder points, order quantities, lead times, safety time, and replenishment frequency.
How does inventory segmentation improve inventory performance?
Segmentation applies differentiated strategies based on demand, variability, criticality, and risk so high-impact items receive appropriate protection while lower-risk items do not tie up unnecessary capital.
What causes excess and obsolete inventory?
Common causes include outdated planning parameters, inaccurate demand signals, unreliable lead times, poor master data, inconsistent replenishment policies, and lack of governance that allows accumulation to continue.
How can AI improve inventory forecasting and positioning?
AI can incorporate historical consumption, forecasted demand, lead times, criticality, and constraints to predict future requirements and dynamically position inventory, improving availability while reducing unnecessary stock.