Probabilistic vs. Deterministic Order Planning
Consider the problem of replenishing inventory. To be specific, suppose the inventory item in question is a spare part. Both you and your supplier will want some sense of how much you will be ordering and when. And your ERP system may be insisting that you let it in on the secret too.
Assessing How Suppliers Influence Your Inventory Costs
Software for inventory optimization is most often used to crank out the analytical results you need to run your day-to-day business, such as Reorder Points (also known as Mins) and Order Quantities. This specialized software helps you find the sweet spot that balances inventory costs against item availability during routine operations.
Increasing Revenue by Increasing Spare Part Availability
Let’s start by recognizing that increased revenue is a good thing for you, and that increasing the availability of the spare parts you provide is a good thing for your customers. But let’s also recognize that increasing item availability will not necessarily lead to increased revenue. If you plan incorrectly and end up carrying excess inventory, the net effect may be good for your customers but will definitely be bad for you. There must be some right way to make this a win-win, if only it can be recognized.
Four Useful Ways to Measure Forecast Error
In this video, Dr. Thomas Willemain, co-Founder and SVP Research, talks about improving Forecast Accuracy by measuring Forecast Error. We begin by overviewing the various types of Error Metrics: Scale-dependent error, Percentage error, Relative error, and Scale-free error Metrics. While some error is inevitable, there are ways to reduce it, and forecast metrics are necessary aids for monitoring and improving forecast accuracy. Then we will explain the special problem of intermittent demand and divide-by-zero problems. Tom concludes by explaining how to assess forecasts of multiple items and how it often makes sense to use weighted averages, weighting items differently by volume or revenue.
Redefine Exceptions and Fine Tune Planning to Address Uncertainty
In a perfect world, Just in Time (JIT) would be the appropriate solution for inventory management. But as the saying goes “everyone has a plan until they get punched in the mouth.” One enormous punch in the mouth for the global supply chain was Suez Canal Blockage that held up $9.6B in trade costing an estimated $6.7M per minute.
Coping with Surging Demand During the Rebound
Many of our customers that saw demand dry up during the pandemic are now seeing a significant demand surge. Other customers in critical industries like plastics, biotech, semiconductors and electronics saw demand surges starting as far back as last April. For suggestions about how to cope with these situations, please read on.
Why pick arbitrary Service Level Targets?
Learn how to select automatically the optimal Targets @scale minimizing total costs for your business. The Smart Inventory Optimization app calculates all the key metrics to expose those tradeoffs.
Maximize Machine Uptime with Probabilistic Modeling
If you both make and sell things, you own two inventory problems. Companies that sell things must focus relentlessly on having enough product inventory to meet customer demand. Manufacturers and asset intensive industries such as power generation, public transportation, mining, and refining, have an additional inventory concern: having enough spare parts to keep their machines running.
This technical brief reviews the basics of two probabilistic models of machine breakdown. It also relates machine uptime to the adequacy of spare parts inventory.
What is the difference between Demand planning and Inventory optimization ?
The Smart Demand Planning app (SDP) provides demand forecasts. The SDP forecasting engine is also the core of the Smart Inventory Optimization app (SIO), which stress-tests various inventory policies using a number of demand scenarios to find optimal inventory policy settings.
Want to Optimize Inventory? Follow These 4 Steps
Service Level Driven Planning (SLDP) is an approach to inventory planning based on exposing the tradeoffs between SKU availability and inventory cost that are at the root of all wise inventory decisions. When organizations understand these tradeoffs, they can make better decisions and have greater variability into the risk of stockouts. SLDP unfolds in four steps: Benchmark, Collaborate, Plan, and Track.
Six Tips for New Demand Planners
If you are a new professional in the field of inventory management, you face a very steep learning curve. There are many moving parts in the system you manage, and much of the movement is random. You may find it helpful to take a step back from the day-to-day flow to think about what it takes to be successful. Here are six suggestions that you may find useful; they are distilled from working over thirty five years with some very smart practitioners.
Automatic Forecasting for Time Series Demand Projections
In this video tutorial Dr. Thomas Willemain, co–Founder and SVP Research at Smart Software, presents Automatic Forecasting for Time Series Demand Projections, a specialized algorithmic tournament to determine an appropriate time series model and estimate the parameters to compute the best forecasts methods.
Four Ways to Optimize Inventory
Inventory optimization has become an even higher priority in recent months for many of our customers. Some are finding their products in vastly greater demand; more have the opposite problem. In either case, events like the Covid19 pandemic are forcing a reexamination of standard operating conditions, such as choices of reorder points and order quantities.
Forecast Using Leading Indicators – Regression Analysis:
In this Video Tutorials Dr. Thomas Willemain, co–Founder and SVP Research, presents Regression Analysis, a specialized statistical modeling technique to improve the accuracy of the forecasts. These videos explain with examples how to use Regression Analysis and the various scenarios where this technique makes a good choice.
5 Demand Planning Tips for Calculating Forecast Uncertainty
Those who produce forecasts owe it to those who consume forecasts, and to themselves, to be aware of the uncertainty in their forecasts. This note is about how to estimate forecast uncertainty and use the estimates in your demand planning process. We focus on forecasts made in support of demand planning as well as forecasts inherent in optimizing inventory policies involving reorder points, safety stocks, and min/max levels.