Signs Predictive Analytics Aren’t Used to Determine Buffer Inventory

Accurately calculating buffer inventory must include multiple real-world factors, such as:

• Demand Behavior and Variation

• Replenishment-Lead-Time Behavior and Variation

• Target Service Level

• Reorder Quantity / Reorder Multiple

• Replenishment Cycle

• Probability of Cancellation

Does your company’s current buffer-inventory calculation include all these factors? Generally speaking, the answer is “no”; therefore, your company is at risk for missing on-time delivery or carrying too much inventory.

Your company may use an industry standard buffer-inventory calculation knowing it doesn’t include all the real-world factors listed above; therefore, you likely modify the formula’s result based on your experience and intuition.

Subjective techniques may not withstand the audit scrutiny of internal and/or legislative controls, such as US Sarbanes-Oxley. Every inventory-position change affects financial statements, cash flow, and off-balance-sheet obligations. Understandably, shareholders and stakeholders rightly expect such changes to be the result of an objective and repeatable process, not a subjective, intuitive modification.

Neither internal nor legislative controls require an inventory-position process to be correct, providing optimal performance. But as a supply-chain professional, your processes are always under the microscope: sales may focus on service level, finance on inventory performance, and transportation on minimal expediting.

Because of this intense scrutiny on all aspects of your supply-chain performance, companies need objective, correct predictive analytics for inventory optimization. As we’ve considered, industry standard buffer-inventory calculations are not predictive analytics.

Predictive Analytics to Accurately Determine Buffer Inventory Does Exist

Right Sized Inventory (RSI) is a commercially-available Monte-Carlo inventory-simulation model for every inventory item in every location. RSI provides patented, affordable, cloud-based predictive-analytics optimization software that simulates real- world client environments, predicts optimum inventory levels at the item-by-item level, and enables our clients to realize better business outcomes by eliminating inventory imbalances and quantifying risk. We can interface with your ERP or other inventory system. Enhance your inventory-planning system and realize better business outcomes by deploying the most advanced and comprehensive predictive-analytics inventory-optimization tool on the market.

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