What will my on-hand inventory be next month, next quarter, at this time next year? When will I be at most risk of stocking out and what should I do about it? What should I order next and how much should I order? Should I accelerate orders or delay placing them? What will our replenishment spend be next month, next quarter, next year?
Knowing when to order, how much, and just what to do to avoid excess stock and stock-outs that are looming on the horizon requires diligence, strong business knowledge, fact-based math, and automation. Inventory planners bring the first two prerequisites but they are forced to rely on Excel spreadsheets and out-of-date and ERP systems that don’t scale and aren’t easy to use. This results in lots of manual effort to place orders and inevitably, mistakes will be made due to the sheer volume of items that need to be ordered on a daily basis. This leads to stockouts, lost sales, emergency production runs, and expensive expedites on one hand while contributing to too much inventory, excess, and obsolescence on the other. Problems reveal themselves too late resulting in a reactive process that compounds the issue further.
Smart Supply Planner (SSP™) is a native web order management and supply planning solution available on Smart’s Inventory Planning and Optimization Platform, Smart IP&O. It provides a fast, easy, and accurate way to predict what you’ll need to order and when.
Order suggestions are driven by Smart’s probabilistic forecasting that simulates daily demands and identifies optimal stocking parameters. You’ll anticipate when stockouts and excess stock are probable to occur enabling you to take corrective action before it becomes a problem. You’ll be able to predict when the next replenishment will arrive and can simulate how alternative planning parameters (reorder points, min/max, safety levels, and forecasts) impact supply planning, future on-hand stocking levels, and replenishment spend. You can then choose a feasible plan that best blends business objectives with your purchasing constraints.
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