The Smart Forecaster

Pursuing best practices in demand planning, forecasting and inventory optimization

The Right Forecast Accuracy Metric for Inventory Planning

The Right Forecast Accuracy Metric for Inventory Planning

Traditional forecasting accuracy metrics aren’t applicable when the goal is to optimize inventory. It’s “service level accuracy” that matters because just setting a service target doesn’t mean you’ll actually achieve it. Poor accuracy here has extremely costly implications. The right way to measure accuracy for inventory planning is to focus on the accuracy of the service level projection. This blog explains why and details how to calculate the metric.

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Infrequent Updates to Inventory Planning Parameters Costs Time, Money, and Hurts Service

Infrequent Updates to Inventory Planning Parameters Costs Time, Money, and Hurts Service

Inventory planning parameters such as safety stock levels, reorder points, Min/Max settings, lead times, order quantities, and DDMRP buffers directly impact inventory spending and ability to meet customer demand. Ensuring that these inputs are optimized regularly will dramatically improve customer service levels and will reduce the amount of unnecessary inventory spending.

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5 Demand Planning Tips for Calculating Forecast Uncertainty

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.

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Excess Inventory Hurts Customer Service!

Excess Inventory Hurts Customer Service!

Many companies adopt a “customer first, better to have the inventory and not need it” approach to inventory planning. While well intentioned, this approach often ignores the role that diminishing returns and opportunity costs play in inventory management impacting the organizations ability to quickly respond to demand.

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Want to Optimize Inventory? Follow These 4 Steps

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.

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Managing Demand Variability

Managing Demand Variability

Anybody doing the job knows that managing inventory can be stressful. Common stressors include: Customers with “special” requests, IT departments with other priorities, balky ERP systems running on inaccurate data, raw material shortages, suppliers with long lead times in far-away countries where production often stops for various reasons and more. This note will address one particular and ever-present source of stress: demand variability.

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Assessing How Suppliers Influence Your Inventory Costs

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.

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Getting “Halfway There” with Demand Planning

Getting “Halfway There” with Demand Planning

Demand planning takes time and effort. It’s worth the effort to the extent that it actually helps you make what you need when you need it. But the job can be done well or poorly. We see many manufacturers who stop at the first level when they could easily go to the second level. And with a little more effort, they could go all the way to the third level, utilizing probabilistic modeling to convert demand planning results into an inventory optimization process.

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The Advantages of Probability Forecasting

The Advantages of Probability Forecasting

Most demand forecasts are partial or incomplete: They provide only one single number: the most likely value of future demand. This is called a point forecast. Usually, the point forecast estimates the average value of future demand. Much more useful is a forecast of full probability distribution of demand at any future time. This is more commonly referred to as probability forecasting and is much more useful.

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Beware of Simple Rules of Thumb for Managing Inventory

Beware of Simple Rules of Thumb for Managing Inventory

Managing inventory requires executives to balance competing goals: high product availability versus low investment in inventory. Executives strike this balance by stating availability targets and budget constraints. Then supply chain professionals translate these “commander’s intentions” into detailed specifications about reorder points and order quantities.

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Worst Practices in Forecasting

Worst Practices in Forecasting

Companies launch initiatives to upgrade or improve their sales & operations planning and demand planning processes all the time. Many of these initiatives fail to deliver the results they should. Has your forecasting function fallen short of expectations? Do you struggle with “best practices” that seem incapable of producing accurate results?

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The Trouble With Turns

The Trouble With Turns

In our travels around the industrial scene, we notice that many companies pay more attention to inventory Turns than they should. We would like to deflect some of this attention to more consequential performance metrics.

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Managing the Inventory of Promoted Items

Managing the Inventory of Promoted Items

In a previous post, I discussed one of the thornier problems demand planners sometimes face: working with product demand data characterized by what statisticians call skewness—a situation that can necessitate costly inventory investments. This sort of problematic data is found in several different scenarios. In at least one, the combination of intermittent demand and very effective sales promotions, the problem lends itself to an effective solution.

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