METHOD AND SYSTEM FOR DETERMINING EFFICIENT INVENTORY LEVELS

Abstract: A system and method improves sales at point-of-sale locations (10) by monitoring on a per package consuer good (12) per point of sale basis sales, out-of-stock sales, and cut-line inventory. Hence, on a per packaged consumer good per point of sale basis, sales and out-of-stock sales can be compared (14) to determine if sales were lost to inadequate inventory. Moreover, comparing cut-line inventory to out-of-stock sales enables a determination of whether the lost sales were a result of inadequate ordering or failed shipments of ordered goods (16, 18, 20, 22).

Description: METHOD AND SYSTEM FOR DETERMINING EFFICIENT INVENTORY LEVELS BACKGROUND OF THE INVENTION Field of the Invention: The present invention relates to inventory control systems. More particularly, the present invention relates to a method and system for determining effect on sales of inventory levels. Brief Description of Prior Developments: Management of shelf space is a important consideration in maximizing sales in a retail environment. For example, providing ample facing space would make it easier for customers to locate products that they seek or to choose from among a variety of products. Retailers would generally like to provide customers with product variety while at the same time provide as much of a high volume product as necessary to prevent an out-of-stock condition wherein all of a particular product is sold out. From the retailer point of view, an out of stock condition may result in the sale of a competing product but not necessarily. Instead, a consumer seeking an out-of-stock product may choose to move to another retailer in search of the out-of-stock item. In such a case, the retailer may lose not only the sale of the product but also the sale of concomitant goods that the customer may otherwise have purchased. Even more damaging, consumers may be reluctant to return to the store for future purchases. In a consumer package goods environment, a retailer generally keeps the bulk of inventory on the shelves rather than in storage. When a particular packaged consumer good is not on the shelf, it is considered an out-of-stock condition. The stock imbalance will not be corrected until the next shipment from the supplier. Accordingly, the packaged consumer good may remain out-of-stock for several days or several weeks. If such out-of-stock conditions are recurrent for a particular good, it is generally an indication that additional shelf space is required for that good. As indicated, shelf space in a retail environment is a critical factor in driving product sales, particularly of packaged consumer goods. This shelf space factor in the sale of goods impels suppliers of packaged consumer goods to compete for limited shelf real estate. While product suppliers would like to have as much shelf space as possible, retailers generally have space constraints and must divide the shelf space among a variety of products and suppliers. Unless a retailer adds additional shelf space to a whole product category, gains in shelf space for one packaged consumer good generally comes at the price of a loss of shelf space for a competing consumer good. Hence, the challenges facing a retailer in determining product shelf space placement are many. They must balance consumer choice with product availability. They must balance overall sales with good supplier relations. In order for a retailer to increase the shelf space of a given packaged consumer good, convincing data must indicate that not increasing the shelf space may cause a risk such as lost sales and, accordingly, revenue. Thus, there is a need for a system and method for providing a retailer with the analytical tools necessary to determine the appropriate amount of inventory of a packaged consumer good and the appropriate amount of shelf space. SUMMARY OF THE INVENTION The present invention provides a system and method for improving inventory management and sales at point-of-sale locations by monitoring on a per packaged consumer good per point-of-sale basis sales, out-of-stock sales, and cut-line inventory. Hence, on a per packaged consumer good per point of sale basis, sales and out-of-stock sales can be compared to determine if sales were lost to inadequate inventory. Moreover, comparing cut-line inventory to out-of-stock sales enables a determination of whether the lost sales were a result of inadequate ordering or failed shipments of ordered goods. The system comprises a database of sales data maintained for a plurality of packaged consumer goods on a per point of sale basis, and corresponding out-of-stock sales data for the packaged consumer goods at each point of sale. Additionally, the database may contain cut-line inventory data for each packaged consumer goods at each point of sale. The system also comprises a memory having computer instruction that select sales data for a specified packaged consumer goods at a specified one of the points of sale and selects out-of-stock sales data for the specified packaged consumer good from the specified point of sale from said database. This data can be used to compare out-of-stock sales to sales for the specified consumer good at the specified point of sale. Hence, a deteπnination can be made whether the sales throughput for a particular packaged consumer good at a particular point of sale has been maximized. The system may also select cut-line inventory for the specified packaged consumer good at the specified point-of-sale so that cut-line inventory may be compared to out-of-stock sales to detemiine whether a supplier shipment problem has occurred that may be a cause of less than optimal sales. BRIEF DESCRIPTION OF THE FIGURES Other features of the invention are further apparent from the following detailed description of presently preferred exemplary embodiments of the invention taken in conjunction with the accompanying drawings, of which: Figure 1 is a block diagram representing data flow in accordance with aspects of the present invention; Figure 2 is an example graph of point-of-sail sales data for a packaged consumer good; Figure 3 is an example of a graph of point-of-sale sales data and corresponding out-of-stock sales data for a packaged consumer good; Figure 4 is an example of a graph of point-of-sale sales data, corresponding out-of-stock sales data, and corresponding cut- line sales data for a packaged consumer good; Figure 5 is an exemplary relationship diagram for a database to store data in accordance with the present invention; Figure 6 is schematic diagram representing a computer network system wherein aspects of the invention may be incorporated; and Figure 7 is a block diagram of a computer system for executing computer- readable instructions for carrying out methods in accordance with the present invention. DETAILED DESCRIPTION OF THE INVENTION OVERVIEW The system and method of the present invention provide an analytical framework for maximizing sales of packaged consumer goods. Sales of products are generally measured in terms of the number of goods sold. However, the number of goods sold depends on available inventory and when an out-of-stock condition is reached. In other words, if an out-of-stock condition is reached it is usually an indication that demand has outpaced supply. Such a condition may be rectified by determining the cause of the lack of inventory. For example, the lack of inventory may be due to insufficient ordering by the retailer. This can be rectified by devoting additional inventory space to the product. On the other hand, the lack of inventoiy may be caused by the supplier failing to ship adequate goods even though the retailer ordered sufficient inventory. The identification of the cause of the out-of-stock condition is crucial to correcting the condition to maximize potential sales of such goods. -EXEMPLARY OPERATING ENVIRONMENT Figure 1 provides a context diagram for the operation of the method and system of the present invention. Essentially, the system 10 receives an input 12 for inventoiy information for a particular product for a particular date range. The system 10 then analyzes inventory data (16, 18, 20, 22) provided by the retailer and the supplier and provides an output in the form of a graph or a report that provides sales information for the selected product over the selected date range. Figure 2 is an example of a graph of a type produced by system 10. As shown, curve 32 represents total sales of a selected packaged consumer good, here the good is TYLENOL 250 count packages. Dates are plotted along the abscissa and total sales in dollars are plotted along the ordinate. Notably, a various dates in the curve 32 the total sales reach intermediate term peaks (i.e. on 7/17/1999 sales peak at 32a, on 1/15/2000 sales peak at 32b, between 3/11 and 3/25/2000 sales peak at 32c, and on 7/15/2000 sales peak at 32d). Such peaks are indicative of increased sales activity of the packaged good on or shortly before the dates indicated. At other dates, such as in the region of about 10/23/1999 to about 1/1/2000, sales gradually ramp to the peak of 32e before declining. Each of these patterns are indicative of brisk sales of the packaged consumer good relative to sales during other date ranges. However, the graph does not indicate whether sufficient inventor}' was on hand to capture all potential sales. Figure 3 is a graph similar to the graph of Figure 3; however, this graph has overlaid out-of-stock (OOS) sales cuive 42 along with sales curve 32. The out-of- stock sales curve plots lost sales because of lack of inventory at particular dates. Out-of- stock sales figures are an attempt to estimate lost sales that resulted from an out-of-stock good. The estimate can be an estimate on a per store basis or across a number of stores. A per store estimate could be determined by examining historical sales data. Alternatively, the out-of-stock sales are determined from a projection based on all of a retailer's stores that carry a selected package consumer good. For example, OOS can be determined by taking the inverse of the percent of stores with the selected packaged consumer good in-stock multiplied by the total sales dollars (i.e., OOS sales = (100 - % in-stock)/100 * Total Sales in dollars). From this graphical illustration, it can be determined that certain sales figures would have been higher if the stock of the particular packaged consumer good had been available for purchase on or about a particular date. For example, at intermediate sales peak 32a, sales of TYLENOL 250 Count were nearly $120,000. This number is far greater than recent preceding sales or sales occurring shortly thereafter. On that basis, the sales may be considered highly successful. This short-term peak in sales may have been the result of a promotional or sales event. By considering the sales information alone, the promotion or event may be considered to have been successful. However, when out-of-stock sales are considered at intermediate peak 42a, it becomes apparent that the total sales could have been as much as $60,000 higher. Armed with the sales and out-of-stock information, subsequent similar promotions or sales events can be properly stocked. For example, subsequent intermediate peak 32b shows a greater sales volume (about $140,000). Notably, the out- of-stock sales are much more attenuated, illustrating that based on the previous out-of- stock sales lost adequate inventories were provided for this sale or promotional event. Similarly, the out-of-stock sales losses were much less at intermediate peaks 32c and 32d. Although the graphs illustrate that out-of-stock sales losses can be detected and compared to sales, the graph of Figure 3 does not provide an indication of the cause of the out-of-stock condition or lack of inventory. As such, a retailer may believe that proper inventoiy was ordered but that the supplier failed to provide adequate supplies. Figure 4 provides an additional curve to provide information about the cause of the inventory shortfall. Here, curve 52 illustrates the cut line inventory losses in dollars (i.e. sales inventory that was ordered by a retailer but not shipped as a result of, e.g., capacity constraints, excessive demand, and so on). Notably, at all of the intermediate peaks in out-of-stock sales lost (42a, 42b, 42c, 42d, 42e), curve 52 is zero, indicating that all ordered goods were shipped. Accordingly, the out-of-stock condition was a result of insufficient ordering of inventory rather than lack of shipments. The one exception is at cut peak 52a. In that case, the small amount of out-of-stock lost sales was likely due to lack of supplier shipments. Figure 5 provides an example of the structure of a relational database design that could be used to store the data necessaiy for use by the present invention. Such a relational database would store information collected from a number of sources. For example, the database would store information from a supplier indicative of packaged consumer goods supplied to a retailer. The database could also store information from one or more retailers indicative of inventory information from one or more retail outlets. The example database comprises three primary tables. PRODDESCR table 502 contains product infonnation such as Universal Product Code (UPC), Brand, Category, Size, which stores are selling the product, and so on. PRODDESCR table 502 contains information collected and maintained by the supplier. Logistics Table 504 also contains information maintained by the supplier such as units ordered, units shipped, units cut, and so on. Retail partner's provide data in the form of POLData (Partners On-Line) table 506 that contains retail partner data such as total sales, inventoiy, out of stock (OOS), and so on. After the data is compiled into the tables. Queries can be used to extract the information for reporting purposes. For example, SQL queries can be employed to derive the graphs shown in Figures 2-4 above. The following query is used to derive the data of Figure 2 where the Wk End Dates between "3/27/1999" and "7/1/2000", OPCO of "MCNEIL", Brand of "TYLENOL", and Size of "250 CT" are all user specified parameters that may be obtained through a variety of user interfaces: SELECT POLData. [Wk End Date], Sum(POLData. [Total Sales $]) AS [Total Sales $] FROM LOGISTICS RIGHT JOIN (PRODDESC INNER JOIN POLData on PRODDESC.UPC = POLData.UPC) ON (LOGISTICS.UPC = POLData.UPC) AND (LOGISTICS.WEDATE = POLData.[Wk End Date]) WHERE (((POLData.[Wk End Date]) Between #3/27/1999# AND #7/l/2000#) AND (((PRODDESC. [OPCO]) = 'MCNEIL')) AND ((((PRODDESC. [Brand]) = 'TYLENOL'))) AND ((((PRODDESC. [Size]) = '250 CT)))) GROUP BY POLData. [Wk End Date] ORDER BY POLData. [Wk End Date]. The following queiy can be used to derive the data for the graph of Figure 3: SELECT POLData.[Wk End Date], Sum(POLData. [Total Sales $]) AS [Total Sales $], SUM (POLData.[OOS $]) AS [OOS $] FROM LOGISTICS RIGHT JOIN (PRODDESC INNER JOIN POLData ON PRODDESC.LIPC = POLData.UPC) ON (LOGISTICS.UPC = POLData.UPC) AND (LOGISTICS.WEDATE = POLData. [Wk End Date]) WHERE (((POLData. [Wk End Date]) Between #3/27/1999# AND #7/l/2000#) AND (((PRODDESC. [OPCO]) = 'MCNEIL')) AND ((((PRODDESC. [Brand]) = 'TYLENOL'))) AND ((((PRODDESC. [Sizze]) = '250 CT')))) GROUP BY POLData. [Wk End Date] ORDER BY POLData. [ Wk End Date] . The following query can be used to derive the graph of Figure 4: SELECT POLData.[Wk End Date], Sum(POLData. [Total Sales $]) AS [Total Sales $], SUM (POLData. [Out_Of_Stock $]) AS [Out_Of_Stock $], Sum(LOGISTICS . [$Cut]) AS Cut_Line FROM LOGISTICS RIGHT JOIN (PRODDESC INNER JOIN POLData ON PRODDESC.UPC = POLData.UPC) ON (LOGISTICS.UPC = POLData.UPC) AND (LOGISTICS.WEDATE = POLData.[Wk End Date]) WHERE (((POLData. [Wk End Date]) Between #3/27/1999# AND #7/l/2000#) AND (((PRODDESC. [OPCO]) = 'MCNEIL')) AND ((((PRODDESC. [Brand]) = 'TYLENOL'))) AND ((((PRODDESC. [Size]) = '250 CT')))) GROUP BY POLData. [Wk End Date] ORDER BY POLData. [Wk End Date]; The above examples are illustrative for a single point of sale for a single retail outlet, such as a single WAL*MART or TARGET retail outlet. However, such a system can be expanded to encompass multiple such retailers and outlets by expanding the tables accordingly and modifying the queries accordingly to encompass multiple such points of sale. After the data is retrieved, as indicated in the graphs above, the data can be used to determine proper inventoiy level, lost sales, and so on. For example, a computer can be set up to automatically compare sales, out-of-stock, and cut-line inventoiy levels to determine whether sales for a predetermined period were maximized. If, for example, out-of-stock sales were within a predetermined percentage of sales (e.g., 10-25%), the condition could be flagged or a shipment alert generated, recommending that the store in question order additional inventory. Additionally, if cut-line inventory approaches a significant percentage of sales, the supplier can be alerted so that additional inventoiy can be routed to stores with a higher sell-through. Sales and inventoiy levels can be compared from similar promotions to automatically correct inventory orders for similar upcoming promotions based on past out-of-stock or cut-line conditions. It should be noted that the system described above can be deployed as part of a computer network, and that the present invention pertains to any computer system having any number of memory or storage units, and any number of applications and processes occurring across any number of volumes. Thus, the invention may apply to both server computers and client computers deployed in a network environment, having remote or local storage.. Figure 6 illustrates an exemplary network environment, with a server in communication with client computers via a network, in which the present invention may be employed. As shown, a servers 61 is interconnected via a communications network 64 (which may be a LAN, WAN, intranet or the Internet) with a number of client computers 62a, 62b, 62c, etc. In a network environment in which the communications network 64 is the Internet, for example, the servers 61 can be Web servers with which the clients 62 communicate via any of a nurήber of lαiown protocols such as hypertext transfer protocol (HTTP). Each client computer 62 and server computer 61 may be equipped with various application program modules, other program modules, and program data and with connections or access to various types of storage elements or objects. Thus, each computer 61 or 62 may have inventory, supply, and/or sales information associated therewith. Each computer 62 may contain computer-executable instructions that carry out the inventory program of the invention. It will be appreciated that the network connections shown are exemplary and other means of establishing a communications link between the computers may be used. The tables of Figure 5 can be stored in database 66 that is coupled to server 61. Client computers 62 may be retailer computer systems that collect, maintain, and forward data that is stored in database 66. Figure 7 provides a block diagram of an exemplary computing environment in which the computer-readable instruction of the invention may be implemented. Moreover, the invention was described herein in the context of flow chaits and computer-executable instructions that operate on a computer system 61, 62 (Figure 6). The further details of such computer systems are shown in Figure 7. Generally, computer-executable instructions are contained in program modules such as programs, objects, data stmctures and the like that perfomi particular tasks. Those skilled in the art will appreciate that the invention may be practiced with other computer system configurations, including multi-processor systems, network PCs, minicomputers, mainframe computers and so on. The invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. Figure 7 includes a general-purpose computing device in the fom of a computer system 62 (or 61), including a processing unit 722, and a system memory 724. The system memory could include read-only memory (ROM) and/or random access memory (RAM) and contains the program code 10 and data 712 for carrying out the present invention. The system further comprises a storage device 716, such as a magnetic disk drive, optical disk drive, or the like. The storage device 716 and its associated computer-readable media provides a non- volatile storage of computer readable instructions, data stmctures, program modules and other data for the computer system 720. A user may enter commands and information into the computer system 720 by way of input devices such as a keyboard 726 and pointing device 718. A display device 714 such as a monitor is connected to the computer system 720 to provide visual indications for user input and output. In addition to the display device 714, computer system 720 may also include other peripheral output devices (not shown), such as a printer. While the invention is susceptible to various modifications and alternative constructions, certain illustrated embodiments have been shown in the drawings and accompanying detailed description. It should be understood, however, that there is no intention to limit the invention to the specific constructions disclosed herein. For example, while the primary example used tliroughout was described in connection with content scheduling for an Internet web site, the present invention is by no means limited to such a system, but could be useful in any system wherein textual, graphic, or other infomiation is scheduled for compilation at various times. As such, the invention is intended to cover all modifications, alternative constructions, and equivalents falling within the scope and spirit of the invention.

Claims: Claims: What is claimed is: 1. A method for identifying inventoiy imbalance of a packaged consumer goods, comprising: inputting sales of a packaged consumer good at a point-of-sale; inputting out-of-stock sales of said packaged consumer goods at said point-of-sale; comparing sales of said packaged consumer good at said point of sale to said out-of-stock sales of said consumer package good at said point of sale whereby inventory imbalances can be indicated when out-of-stock sales reach a predetemiined percentage of sales. 2. The method as recited in claim 1 wherein the point of sale is a retail store. 3. The method as recited in claim 1 wherein the predetemiined percentage of sales is about 25%. 4. The method as recited in claim 1 further comprising comparing cut- line inventoiy to out-of-stock sales and indicating a supplier shipment problem when cut- line inventory is within a predetermined percentage of out-of-stock inventoiy. 5. The method as recited in claim 4 wherein said predetermined percentage of out-of-stock inventory is about 25%. 6. The method as recited in claim 1 wherein said out-of-stock sales are a function of available inventory at other points-of-sale locations for a selected retailer. 7. A computer-readable medium bearing computer-readable instmctions for identifying inventory imbalance of a packaged consumer goods, comprising: instruction for inputting sales of a packaged consumer good at a point-of- sale; instructions for inputting out-of-stock sales of said packaged consumer goods at said point-of-sale; instmctions for comparing sales of said packaged consumer good at said point of sale to said out-of-stock sales of said consumer package good at said point of sale whereby inventoiy imbalances can be indicated when out-of-stock sales reach a predetemiined percentage of sales. 8. The computer-readable medium as recited in claim 7 wherein the point of sale is a retail store. 9. The computer-readable medium as recited in claim 7 wherein the predetemiined percentage of sales is about 25%. 10. The computer-readable medium as recited in claim 7 further comprising comparing cut-line inventory to out-of-stock sales and indicating a supplier shipment problem when cut-line inventory is within a predetemiined percentage of out- of-stock inventory. 11. The computer-readable medium as recited in claim 10 wherein said predetemiined percentage of out-of-stock inventory is about 25%. 12. The computer-readable medium as recited in claim 7 wherein said out-of-stock sales are a function of available inventory at other points-of-sale locations for a selected retailer. 13. A system for improving sales at a point-of-sale location, comprising: a database comprising sales data from a plurality of packaged consumer goods at a plurality of points of sale, and out-of-stock sales data for said plurality of packaged consumer goods at said plurality of points of sale; a memory containing computer instmction that selects sales data for a specified one of said plurality of packaged consumer goods at a specified one of said plurality of points of sale and selects out-of-stock sales data of the specified one of said packaged consumer good from the specified one of the point of sale from said database whereby said out-of-stock sales can be compared to said sales for the specified consumer good at the specified point of sale. 14. The system as recited in claim 13 further comprising computer instmctions that compare the selected sales data to out-of-stock sales and generating a signal indicative of a need for additional inventory when out-of-stock sales are a predetermined percentage of sales of the specified packaged consumer good at the specified location. 15. The system as recited in claim 14 wherein the predetermined percentage of sales is about 25%. 16. The system as recited in claim 14 wherein the specified point of sale is a retail store. 17. The system as recited in claim 13 wherein said database further comprises cut-line inventory data from said plurality of packaged consumer goods at said plurality of points of sale. 18. The system as recited in claim 17 further comprising second computer instructions in a second computer memory, said second computer instmctions selecting cut-line inventory for the specified one of said packaged consumer goods at the specified one of said plurality of points-of-sale, and comparing the selected cut-line inventoiy to out-of-stock sales and indicating a supplier shipment problem when cut-line inventoiy is within a predetermined percentage of out-of-stock sales. 19. The computer-readable medium as recited in claim 18 wherein said predetemiined percentage of out-of-stock inventoiy is about 25%.

Inventors: CARREON VICTOR E, DAAS JEFFREY S, KROK DAVID C, LEH BRIAN, CARREON, VICTOR, E., DAAS, JEFFREY, S., KROK, DAVID, C., LEH, BRIAN
Applicants: JOHNSON & JOHNSON CONSUMER, JOHNSON & JOHNSON CONSUMER COMPANIES, INC.
Application year: 2001
Main classification: G06F
IPC codes: B65G61, G06Q10, G06Q50, G07G1