Data Science predictive modeling techniques to control
trade-offs between service levels and inventory investments.
“Don’t stock too much and don’t run out!” This directive is issued by many CEOs – a crisp and clear message that seems impossible to accomplish. How much is enough? What will demand be for each of our thousands of products? How wrong will our forecast be, and how important is it that we don’t run out? How do we formulate the plan and make it so? This is largely the point of your Inventory Planning process but how well is it working for you?
Probability forecasting and scenario analysis are quickly becoming the approaches of choice for optimizing inventory levels. By leveraging these predictive modeling techniques you can discover and understand trade-offs between service levels and inventory investments. This will help you develop a consensus inventory plan that is continuously updated to reflect real-time changes in demand, supply, and business priorities.
The live technology demonstration will highlight critical functions:
- Develop and refresh demand forecasts and stocking policies at any time
- Share collaborative inventory plans and develop consensus within a few clicks
- Continuously compare proposed inventory policies across many metrics
- Upload results to your ERP system within a click of a button
Contact Us Today for More Information
If you request a demo, one of our specialists will show you how Smart can help, using your own inventory data!