Predictive Analytics & AI

optimizing-inventory

Optimizing Inventory Levels

Inventory optimization is a challenge that every company faces when it comes to the challenge of matching its supply volume to customer demand. The optimization of inventory levels has been found to have a major impact on the profitability of an organization. Furthermore, the amount of inventory held also has a major impact on available cash. Also, since working capital is at a premium, it’s important for companies to keep their stock levels as low as possible and to have a high turnover in terms of inventory sales.

Our solution to inventory optimization is based on mathematical modelling and operational research where variables such as the unit holding cost, lost sales cost per unit of unsatisfied demand etc. can be used along with the stochastic demand estimated to estimate the optimal base stock level for minimizing the total expected cost per order cycle for each individual Stock Keeping Unit (SKU). In addition, simulation can be used to verify and validate the accuracy of the models thus developed mitigating the risk of the models performing badly in real world scenarios.

The potential use cases for Predictive Analytics and AI are many and a few of them are as follows.

Customer Segmentation
Predicting Churn / Attrition
Detecting Fraud / Outliers
Making Product Recommendations
Optimizing Inventory Levels
Demand Forecasting
Developing Chat Bots for Customer Engagement