Smart eLearning Platform: Best practices for Demand Forecasting, and Inventory Planning.
On Demand Webinars
Probabilistic Inventory Optimization: Achieving Service and Inventory Targets in Uncertain Times
On Demand Webinar
Smart Software, preents a webinar underlining the importance of precise demand prediction and efficient stock level optimization in today’s dynamic business landscape. With continued supply chain disruptions, rising interest rates, and increasingly volatile demand, traditional forecasting methods often overlook the uncertainties of the current economy. However, Probabilistic Forecasting emerges as a preeminent methodology, offering superior accuracy and reliability.
Planning for Intermittent Demand: Optimizing Inventory Using Probabilistic Modeling
On Demand Webinar
How do you plan the right inventory levels when you have intermittent demand, the seemingly random, highly sporadic usage pattern that is especially prevalent with spare parts? Most parts and materials planning organizations rely on traditional forecasting approaches, rule of thumb methods, and “planned” maintenance schedules to determine stocking requirements. This Video will discuss these approaches, why they often fail, and how new probabilistic forecasting methods can make a big difference to your bottom line.
10 Questions That Reveal Your Company's Inventory Policy
On Demand Webinar
Do you know how your organization sets its inventory planning policies and the degree to which you actually apply them? And that they’re doing the job? Demand planning, forecasting, and inventory planning need to be well-defined processes that are understood and accepted by everybody involved. Please watch our video featuring Greg Hartunian, CEO of Smart Software, who will review the top 10 questions you should ask to reveal your company’s true planning policy. Doing so will demystify your planning process and help you identify major opportunities for financial savings and process improvement.
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 important is it that we don’t run out? 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.
Spare Parts Planning at Metro Transit of Minneapolis/St. Paul
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.
Best Practices for Spare Parts Management with Phillip Slater
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.
Smart Software Corporate Profile
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