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On Demand Webinars
On Demand Webinar – “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? Join the webinar to learn how new probabilistic predictive modeling techniques help you discover and understand trade-offs between service levels and inventory investments leading to reduced inventory and improved customer service.
On Demand Webinar – You manage thousands of parts, millions in inventory across many locations. How do you get a handle on material management? Where do you start? Join our discussion with Chris Haefner, Manager of Material Management at Minnesota’s Metro Transit, the nation’s 15th largest transit agency.
On Demand Webinar – Phillip Slater, Spare Parts Management Specialist and Founder of SparePartsKnowHow.com, surveyed hundreds of storerooms over a period of years. Phillip was able to differentiate between the high and low performing companies and identified seven practices that high performers execute better and more consistently than everyone else. The result of this work is the definitive identification of best practice for spare parts inventory management. Our webinar will explain clear actions you can take to improve your spare parts inventory management results.
Academic Articles & White Papers
White Paper: What 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.
International Journal of Forecasting: A new approach to forecasting intermittent demand for service parts inventories
We address the problem of forecasting intermittent (or irregular) demand, i.e. random demand with a large proportion of zero values. This pattern is characteristic of demand for service parts inventories and capital goods and is difficult to predict. We forecast the cumulative distribution of demand over a fixed lead time using a new type of time series bootstrap.
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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!