Method and System For Determining Time-Phased Product Sales Forecasts and Projected Replenishment Shipments For A Retail Store Supply Chain

Abstract

A time phased forecasting and replenishment system (20) for retail organizations which can be used for inventory management and financial management. One or more computers (28) create time phased plans for one or more retail facilities, such as various types of retail stores (23) and / or various types of suppliers (24). The system calculates projected sales for each product at each facility and calculates projected replenishment shipments between facilities and suppliers a specified number of weeks into the future. The calculated forecasts and replenishments are done in ways that account for the unique needs of retail organizations, and allow efficient processing and storage of the large data volumes typical in many retail organizations.

Description

RELATED APPLICATION DATA[0001]This application is a divisional of application Ser. No. 10 / 620,110, filed Jul. 15, 2003, which application is a continuation-in-part of application Ser. No. 09 / 536,335, filed Mar. 25, 2000, now U.S. Pat. No. 6,609,101, which claims the benefit of provisional application Ser. No. 60 / 126,454, filed Mar. 26, 1999, all of which applications are incorporated herein in their entireties.FIELD OF THE INVENTION[0002]The present invention relates to a computer-implemented method and system for simulating the business of retail organizations for the purposes of better managing inventories and finances at both retail organizations and / or suppliers. More particularly, the invention is a method and system for forecasting product sales in a retail store supply chain and determining replenishment shipments to various entities in the supply chain.BACKGROUND[0003]The typical retail organization uses a reorder point system to manage inventories at the store-level. These ...

AI Technical Summary

Benefits of technology

The system enables accurate and efficient forecasting and replenishment planning, improving inventory management and financial projections by addressing the unique challenges of retail store supply chains, such as holiday sales and promotional demands, while reducing computational complexity and costs.

Problems solved by technology

However, these systems are designed to meet the needs of a manufacturing organization, and have not proved suitable for a retailer's needs.

These systems are not able to process the large data volumes typical of most retail organizations.

Additionally, manufacturing systems are not designed to deal with fundamental retailing needs such as promotional replenishments, holiday forecasting, shelf configurations, fast easy-to-use displays of information appropriate for large volumes of data, and product groupings where several products are treated as one for the purposes of forecasting and replenishment.

Systems designed for tens of thousands of stock keeping locations could theoretically be made to work for a hundred million stock keeping locations, but as a result of limitations in computing resources and time available to complete the computing operations this has not been achieved in actual practice.

Additionally, using systems not designed to economically process this amount of data would force the retailer to purchase significantly more computer processing power than would be needed with a system designed for these volumes (assuming such a system existed).

Similarly, a return to the normal display after the Christmas season would cause a decrease in the projected replenishment shipments some number of days before the planned return to the normal shelf arrangement.

Unfortunately, current time-phased planning systems do not provide capabilities for handling changes in shelf arrangements and showing their resultant impact on the replenishment schedules.

Consequently, any planned replenishment shipments calculated without accounting for these shelf changes would be inaccurate, and therefore could not be used to plan product needs at suppliers or suppliers, or to show accurate financial projections of inventory levels at the stores and the suppliers.

For this reason, current time-phased planning systems do not provide capabilities for dealing with changes in shelf configurations in a retail store.

It is not efficient for retailers to forecast the sales of packs, and also forecast the sales of cartons.

Nor is it efficient to plan the replenishment of packs and also the replenishment of cartons, and then add the two numbers together (accounting for the number of packs per carton).

For this reason, current time-phased planning systems do not provide capabilities for handling products sold in several different configurations, but purchased in only one of these configurations.

Unfortunately, this leaves the store with too little inventory during the week of Easter, and too much inventory the week after.

For this reason, current time-phased planning systems do not provide capabilities for correctly representing holiday sales at a retail store.

However, current time-phased planning systems do not contain the specialized logic needed to plan replenishments for promotions.

Additionally, this product must arrive in enough time to allow store employees to set up the display, and also give them time to get an emergency shipment if something were to go wrong and their initial distribution were delayed or otherwise not shipped.

Retailers are in a difficult position if a promotion begins and they do not have the quantity of product to support the promotion, and so they need this sort of back-up plan.

For this reason, current time-phased planning systems do not provide capabilities for initial distribution shipments.

However they do not allow safety stock to be used simultaneously for one type of demand (non-promotional demands for example) and safety time to be used for other types of demands (promotional demands for example on the same product).

This forces retailers to use an approach that is not well suited to their business, or to create other systems to compensate for the limitations in the existing systems.

Unfortunately, the current forecasting and replenishment systems do not use this early sales history to re-project the promotional forecast, and then re-project the planned replenishments during the promotion period.

As a result, this early marketplace information is not used to its full potential to ship the right quantities of product to the correct stores, resulting in overstocks at some stores, and out of stocks at other stores.

However, browser-based DRP systems designed for use in a LAN, on the Internet or in other networks do not provide the speed and functionality required in a retail store supply chain.

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