The Smart Forecaster
Pursuing best practices in demand planning, forecasting and inventory optimization
We are often asked what the difference is between these two important performance metrics for inventory planning. While they are both important for measuring how successful a business is in meeting demand, their meaning is very different. If not understood and incorporated into the strategic inventory planning process, inventory will be inefficiently allocated resulting in lower customer service and higher carrying costs. We’ve illustrated the difference in this 4 minute recording using Microsoft Excel.
Smart Operational Analytics automatically calculates historical service levels & fill rates across any item. To see how you calculate these and other operational metrics including inventory turns, supplier performance, and more register below to watch a five minute demonstration. The demo will show how our cloud platform continuously calculates and reports these metrics across thousands of items helping you identify opportunities for service level improvement and inventory reduction.
The three types of supply chain analytics are “descriptive”, “predictive”, and “prescriptive.” Each plays a different role in helping you manage your inventory. Modern supply chain software lets you exploit all three helping you to reduce inventory costs, improve on time delivery and service levels, while running a more efficient supply chain.
We just need to feed our demand histories into our new statistical methods, and we can start planning more effectively. Not quite: it’s about the technology and the process. You are investing in a new business process to develop forecasts for driving business strategy and inventory planning decisions.
No, not that kind of regime change: Nothing here about cruise missiles and stealth bombers. And no, we’re not talking about the other kind of regime change that hits closer to home: Shuffling the C-Suite at your company. In this blog, we discuss the relevance of regime change on time series data used for demand planning and forecasting.