Improve Forecast Accuracy, Eliminate Excess Inventory, & Maximize Service Levels
Smart Software’s Inventory Planning and Optimization Platform (Smart IP&O™) offers a single, easy to use, and scalable native cloud platform for collaborative demand planning, forecasting, and inventory optimization.
Specializing in intermittent demand planning, Smart IP&O extends beyond traditional forecasting by leveraging probability modeling to drive inventory strategy and consensus demand planning.
Smart IP&O predicts continuously, leveraging field-proven models to forecast demand and lead times, predict excess and out-of-stocks, monitor inventory performance, and optimize planning parameters.
Smart IP&O seamlessly returns accurate forecasts and optimized stocking policies to your ERP system to reduce inventory, increase service levels, and ensure alignment between your inventory policy and business strategy.
How Smart IP&O Can Help
Smart IP&O Application Suite
Testimonials
“Smart IP&O allowed us to transform our manually maintained stocking levels to a service level-based model that drove significant improvements in fill rates while optimizing total inventory on hand. The accurate forecasts of stocking levels provided fact-based data that allowed us to strategically phase the consolidation effort where warehouse space was at a premium.”
“Whatever the request, we need to meet our next day service commitment – Smart enables us to risk adjust our inventory, to be sure we have the products and parts on hand to achieve the service levels our customers require.”
“Smart is the only one out there that has really licked the intermittent demand modeling challenge. We get accurate information and more importantly at the lowest dollar. Without Smart, I think we would have seen a continued growth in our inventory and not necessarily gotten any greater benefit for service.”
Industry Focus
Spare Parts
Industrial Equipment
Manufacturing
Transportation
Pursuing best practices in demand planning, forecasting and inventory optimization
Ten Tips that Avoid Data Problems in Software Implementation
Once a customer is ready to implement software for demand planning and/or inventory optimization, they need to connect the analytics software to their corporate data stream.This provides information on item demand and supplier lead times, among other things. We extract the rest of the data from the ERP system itself, which provides metadata such as each item’s location, unit cost, and product group.
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Riding the Tradeoff Curve
In the supply chain planning world, the most fundamental decision is how to balance item availability against the cost of maintaining that availability (service levels and fill rates). At one extreme, you can grossly overstock and never run out until you go broke and have to close up shop from sinking all your cash into inventory that doesn’t sell.
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Reveal Your Real Inventory Planning and Forecasting Policy by Answering These 10 Questions
In this blog, we review 10 specific questions you can ask to uncover what’s really happening with the inventory planning and demand forecasting policy at your company. We detail the typical answers provided when a forecasting/inventory planning policy doesn’t really exist, explain how to interpret these answers, and offer some clear advice on what to do about it.
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AUTOMATED STATISTICAL ANALYSIS DRIVES INVENTORY MANAGEMENT
Inventory managers struggle with the conflicting priorities of customer satisfaction and cost control. The featured article shows how to harness customer demand data to craft optimal inventory policies:
Measure current inventory policy performance: service levels, fill rates, inventory turns, and ordering costs.
Identify improvement goals: Assessing tradeoffs between inventory investment and the risk of running out.
Find the optimal balance point: Setting reorder points and order quantities that will achieve the results you require and much more in this article.
What Do You Need to Know About Forecasting and Planning Service Parts?
This paper describes Smart Software’s patented methodology for forecasting demand, safety stocks, and reorder points on items such as service parts and components with intermittent demand, and provides several examples of customer success.