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Tag Archives: Lead Time Forecasting

Why Lead Time impacts your Inventory Optimization and How To Fix It

What is Lead Time? Why Is it Important?

Lead Time is the length of days between when an order is placed and the date the goods are available for use. The largest impact to lead time accuracy is found by comparing expected receipt date to actual receipt date for each purchase order. In simple terms, the variance is calculated as the absolute value of the difference [expected or requested receipt date – actual receipt date] for each line on the purchase order. These variances in days across multiple purchase orders establish the need for lead time accuracy testing and lead time forecasting.

What is the Impact When Supplier Lead Time is Not Accurate?

Suppliers provide an estimate of lead time, but these numbers are not always accurate. The differences between your expected receipt date and actual receipt date can become expensive from the resulting unplanned over stocks, out of stocks, and deflated consumer opinions. Lead time tracking and lead time forecasting are mission critical to the success of your supply chain. Lead Time Forecasting, like Demand Forecasting, should use a set of math algorithms to calculate the correct lead time days to use in planning purchase orders. Also, like Demand Forecasting, the Lead Time Forecast should move up and down according to changes in market, business influences and seasonality of product.
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Seasonal Index Lessons from History

Reviewing Seasonal Indexes is critical for an accurate demand forecast. Seasonal Indexes, also called seasonal multipliers, are used to adjust the demand forecast by multiplying the product base forecast by a multiplier. The effect will raise or lower the demand forecast for the time period, often a week or month. The results are often used to help calculate the inventory needed to support sales. Holidays like Easter, seasons like springtime, and events like the Super Bowl that repeat based on some factor of time are frequently better serviced with a seasonal index applied across the year.

Problems with Seasonality

The problem with seasonality is that it can change each year, and your current fiscal year may not map back to your seasonal index. Sales from the last seasonal event may impact your base demand forecast to create inaccuracy. Easter is in a different month and fiscal week this year. How did you account for the differences when purchasing Easter inventory for this year? Next year, Easter is again in a different month and will be several weeks different from this year. Thanksgiving is a holiday that based on the time of year can add or subtract a whole weekend of December holiday shopping. There are two issues that need to be reviewed and adjusted: the current year fiscal week seasonal index values and the base demand forecast. Read More

Inventory Optimization: Putting it in to Practice

We’re wrapping up an informative series on inventory optimization today: we’d like to give you some advice on actually putting it all in to practice. If you haven’t been with us throughout the month, the series has included:

What’s the Payoff?

What are the aims of Inventory Optimization? We argue that Inventory Optimization aims to improve your margins through a net reduction of acquisition and carrying costs. So what does this look like? Read More

The 3 Most Ignored (and Profitable) Factors in Inventory Optimization
When is the last time your Inventory Optimization (IO) program saw the inside of a warehouse, the bed of a truck, or a container floating across the ocean? Most inventory optimization programs overlook the harsh realities of replenishment and logistics. How does your program stack up?

Note: We’re in week four of our series on inventory optimization.

Oft-Overlooked Inventory Optimization Factors

While it’s true that inventory optimization is largely a math equation, the devil (and the profit) is in the details. Most solutions talk about carry cost, acquisition cost, and profits because it sounds good and seems impressive, but what is really happening under the hood of your IO solution? Read More

As we discussed in part one of our Lead Time Forecasting series, time is money and an accurate lead time forecast is critical for your business.  Lead Time forecasting is considered the time from when a Purchase Order is placed until the goods are ready and available to sell or ship off the shelf.  This week we take a look at how a lead time forecasting impacts your customers

Does Lead Time ruin your Customer-Centric Sales Environment?

Are you like the many retailers focused on delivering a customer-centric experience?  Amazon.com leads the industry in providing a true customer-centric experience that is focused on delivering the best possible customer experience and believe that by delivering this experience its business will continue to grow.  Based on the customer-centric model, let’s take look at how an inaccurate lead time forecast can have a real impact on your customers’ experience.
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Lead Time Forecasting: Are Your Shelves Overstocked or Out-of-Stock?

Time is money – making lead time forecasting critical for your business. Over the next three weeks we will take a deeper look at lead times and the impact they have on today’s retail market supply chain.

A lead time of 60 days or more can become the largest influence in your safety stock due to variations in the actual lead times for receipted goods. The variations between actual lead times and also the differences between actual and expected lead times will need to be offset with the use of additional safety stock which lowers your profit margins significantly.

Do you find yourself looking at what inventory you have on the shelf while you wait for the slow boat to cross the Pacific? Do your suppliers provide an estimated lead time that quickly comes and goes and leaves you with overstock or out-of-stock? A recent study of a Top 100 North American Retailer showed lost sales of over a million dollars in gross margin due to inaccuracy in their lead time planning.

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