Earl F Dulaney, Age 691985 N Bridgeport Dr, Fayetteville, AR 72704

2001004, Nov 29, 2001

May 18, 2001

09/860416

Matthew Waller - Fayetteville AR, US
Earl Dulaney - Fayetteville AR, US

G06F017/60

705/010000, 705/028000

The present invention optimizes inventory and inventory investment utilization based upon inventory holding cost and lost sales, economic profit, unit sales, sales revenue, or gross margin with or without considering investment constraints. The invention assimilates relevant data for each particular item to be evaluated. The data to be collected include store-level point-of-sale data, frequency of replenishment, lead time, investment available, number of units per order lot, cost to the retailer of one unit of SKU, price retailer receives for one unit of SKU, the inventory holding cost factor, and the unit cost of a lost sale. The system evaluates these variables when determining the optimal solution for an unconstrained or constrained investment. The invention also includes a process through which multiple parties can collaborate on the solution. The participants can adjust the permissioned data, optimization parameters, and constraints to reoptimize to meet their objectives.

2002003, Mar 21, 2002

Sep 28, 2001

09/967586

Matthew Waller - Fayetteville AR, US
Earl Dulaney - Fayetteville AR, US

G06F017/60

705/037000

The present invention is a method for an economic bidding process which enables retailers to generate competition for merchandising space or inventory investment between suppliers of items in branded, replenished categories. This process enables a retailer's acquisition, evaluation, and comparison of economic bids from multiple suppliers through the merchandise optimization and collaboration technology also disclosed. In the economic bidding process the use of the same set of data, financial metrics, and economic model by all parties facilitates comparison of bids based on a wide variety of variables, as opposed to comparison based on cost alone as in traditional bidding. Suppliers can propose bids, and retailers evaluate them, based on an economic picture that is larger than cost alone. Hence, the bidding process enabled by the present invention is termed an “economic” bidding process.

2003019, Oct 16, 2003

Dec 11, 2000

09/735041

Matthew Waller - Fayetteville AR, US
Earl Dulaney - Fayetteville AR, US
Milan Milatovic - Fayetteville AR, US
David Johnson - Alexandria VA, US

G06F017/60

705/010000

The present invention involves a system, method and article of manufacture that first garners user input criteria necessary to analyze and communicate a redistribution of product demand whenever a new target product is added to, or an existing target product is deleted from, a product assortment. In the invention's preferred embodiment, the user is provided with a graphical user interface to facilitate acceptance of required user input criteria, and then passes such garnered information to a user selectable redistribution demand processing model, which analyzes and processes the user's input criteria to develop and communicate a demand redistribution product set for focus products affected by said target product's deletion or addition.

6341269, Jan 22, 2002

Dec 30, 1999

09/475612

Earl F. Dulaney - Fayetteville AR
Matthew A. Waller - Fayetteville AR

Mercani Technologies, Inc. - Fayetteville AK

G06F 1760

705 22, 705 7, 705 8, 705 28

The present invention relates to inventory management systems and processes at the retail, wholesale and/or distributor level. The present invention particularly involves a system, method and article of manufacture that optimizes inventory and merchandising shelf space utilization based upon cost and lost sales, with or without considering physical space constraints. In an exemplary embodiment, the system includes a bank of memory, a processor, an input and an output, and a computer program. The system optimizes inventory or store facings using various data and extrapolated computations. The system optimizes inventory using facing optimization which is an approach to shelf inventory management that minimizes the sum of expected annual cost of lost sales and expected annual inventory holding cost. The process of facing optimization requires the assimilation of relevant data for each particular item to be evaluated. The data to be collected include store-level point-of-sale (a. k. a.