WO2003054759A2

WO2003054759A2 - Local market optimization

Info

Publication number: WO2003054759A2
Application number: PCT/IB2002/005588
Authority: WO
Inventors: Kevin Blackmore
Original assignee: Accenture Services Limited
Priority date: 2001-12-21
Filing date: 2002-12-23
Publication date: 2003-07-03
Also published as: AU2002353398A1; EP1459231A1; CA2499567A1

Description

LOCAL MARKET OPTIMIZATION

FIELD OF THE INVENTION

[01] This invention relates to marketing and sales methods and, in particular, to a system and method for inventory selection by making optimal product purchasing and allocation decisions.

BACKGROUND OF THE INVENTION

[02] A product retailer typically needs to make numerous purchasing, allocation, and presentation decisions in the marketing cycle of a particular commodity or product. Factors affecting such decisions may relate to seasonal activity, for example, or to the amount of store space available for allocation to a particular product category or line of products.

[03] Marketing allocation decisions made in the present state of the art typically result from a process of analyzing a particular store as a member of a cluster group of stores, and not by analyzing the store as an individual entity. Moreover, product assortment determinations within the particular store, which may be referred to as 'store cataloguing,' are usually made using only the historical performance of the store and the store size. Accordingly, as stores may be grouped according to grade or class, the stores in a particular grade or class grouping will usually be stocked with similar product assortments. However, because customer demographics typically vary from store to store, and customer purchasing patterns vary even for stores in the same grade or class, allocation decisions which direct that the same product assortment be stocked for stores in the same grade or class may result in acceptable sales in some stores but may result in undesirable quantities of unsold inventory in other stores.

[04] Thus, there is a particular need for a system and method for aiding retail purchasers and planners in making purchasing and allocation decisions while taking into account the demographics of the local consumer groups. BRIEF SUMMARY OF THE INVENTION

[05] Advantages of the present invention include the ability to customize a retail strategy and store sales plan to a specific store based on the store's sales trends and consumer demographics.

J06] The invention also allows a user to easily and efficiently view and modify sales plan and store plan information based on one or more of a plan period, division, department, zone, cluster, grade, and segment.

[07] A system and method is provided for optimizing product purchase and allocation decisions in a marketing environment. The method includes deteπnining local store opportunity by identifying demographic consumer groups within cluster groups of stores, and taking into account the shopping and purchasing characteristics of the consumer groups. Product offer is thus also tailored to the requirements of the local customers rather than only to the historical performance of the store or to the size and layout of the facility, as is conventionally done. Local store parameters are modeled, using empirical data archived in the system and data input by a client accessing the system, to derive a sales plan which reflects overall market conditions, and a store sales and space plan which reflects sales activity at the local store. The data are analyzed as a function of division, department, store cluster, and market segment. Differences identified from analysis of the sales plan, and the store sales and space plan, are evaluated and may be reconciled using the experience and knowledge of the retail purchaser/planner. The process produces an allocation plan, a grade plan, a density plan, and a range width plan, which parameters are applied to a local store model, with the result that product assortment can vary among stores in the same class or grade so as to optimize product offering or selection for each local store.

BRIEF DESCRIPTION OF THE DRAWINGS [08] The invention description below refers to the accompanying drawings, of which:

[09] Fig. 1 is a basic block diagram of a computer system in which the method of the present invention may be advantageously employed; [10] Fig. 2 is a generalized flow diagram of the method of the present invention;

[11] Fig. 3 is a flow diagram showing in greater detail a local store opportunity determining step of the flow diagram of Fig.2;

[12] Fig. 4 is an illustration of a local store customer group identification step of the flow diagram of Fig.2;

[13] Fig. 5 is an illustration of a customer group shopping determination step of the flow diagram of Fig. 2;

[14] Fig. 6 is an illustration of a customer group purchasing determination step of the flow diagram of Fig. 2;

[15] Fig. 7 is a generalized flow diagram illustrating the formulation of a sales plan and a store sales and space plan at a local store parameter modeling step in the flow diagram of Fig. 2;

[16] Fig. 8 is an illustration of a preferred user interface showing a first sales plan screen;

[17] Fig. 9 is an illustration of a preferred user interface showing a second sales plan screen;

[18] Fig. 10 is an illustration of a preferred user interface showing a third sales plan screen;

[19] Fig. 11 is an illustration of a preferred user interface showing a fourth sales plan screen;

[20] Fig. 12 is an illustration of a preferred user interface showing a first store plan screen;

[21] Fig. 13 is an illustration of a preferred user interface showing a second store plan screen; [22] Fig. 14 is an illustration of a preferred user interface showing a local store analysis screen;

[23] Fig. 15 is an illustration of a preferred user interface showing a third store plan screen;

[24] Fig. 16 is an illustration of a preferred user interface showing a fourth store plan screen;

[25] Fig. 17 is an illustration of a preferred user interface showing a store plan review screen;

[26] Fig. 18 is an illustration of a preferred user interface showing a first plan reconciliation screen;

[27] Fig. 19 is an illustration of a preferred user interface showing a second plan reconciliation screen;

[28] Fig. 20 is an illustration of a preferred user interface showing a grade plan screen;

[29] Fig. 21 is an illustration of a preferred user interface showing a plan density screen; and

[30] Fig.22 is an illustration of a preferred user interface showing a range width screen.

DETAILED DESCRIPTION OF THE INVENTION

[31] The methods of the present invention may be embodied in a computer system, such as a computer system 10 shown in Fig. 1. The computer system 10 includes a central processor unit 11, a system memory 13 and a system bus 15 which couples various system components, including the system memory 13, to the central processor unit 11. The system bus 15 may comprise one of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, or a local bus using any of a variety of bus architectures. The structure of the system memory 13 is well known to those skilled in the art and may include a basic input/output system (BIOS) stored in a read only memory (ROM), and one or more program modules, such as operating systems, application programs, and program data, stored in random access memory (RAM).

[32] The computer system 10 may also include a variety of interface units and drives for reading and writing data. In way of example, the computer system 10 may include a hard disk interface 17 and a removable memory interface 19, coupling a hard disk drive 21 and a removable memory drive 23, respectively, to the system bus 15. The removable memory drive 23 may include a magnetic disk drive or an optical disk drive. The drives for reading and writing data, and their associated computer-readable media, such as a floppy disk 25, provide nonvolatile storage of computer readable instructions, data structures, program modules and other data for the computer system 10. It should be understood that, although only one hard disk drive 21 and one removable memory drive 23 are shown for clarity of illustration, the computer system 10 may include several of either or both such drives. Furthermore, the computer system 10 may include additional drives for interfacing with other types of computer- readable media.

[33] A user can interact with the computer system 10 using a number of input devices. In the illustration provided, a serial port interface 27 couples a keyboard 29 and a pointing device 31 to the system bus 15. The pointing device 31 may be implemented as a mouse, a track ball, a pen device, or other such similar device. Of course, one or more other input devices (not shown) such as a joystick, a game pad, a satellite dish, a scanner, a touch sensitive screen, or the like, may be connected to the computer system 10.

[34] The computer system 10 may include additional interfaces for connecting still more devices (not shown) to the system bus 15. A universal serial bus (USB) interface 33 couples a video or digital camera 35 to the system bus 15. An IEEE 1394 interface 37 may be used to couple additional devices (not shown) to the computer system 10. Furthermore, the IEEE 1394 interface 37 may be configured to operate with particular manufacture interfaces, such as FireWire developed by Apple Computer and i.Link developed by Sony Corporation. Input devices may also be coupled to the system bus 15 through a parallel port, a game port, a PCI board, or any other interface used to couple and input device to a computer.

[35] The computer system 10 may also include a video adapter 39 coupling a display device 41 to the system bus 15. The display device 41 may include a cathode ray tube (CRT), a liquid crystal display (LCD), a field emission display (FED), a plasma display, or any other device that produces an image that is viewable by the user. Additional output devices, such as a printing device (not shown), may be connected to the computer system 10.

[36] Sound can be recorded and reproduced with a microphone 43 and a speaker 45. A sound card 47 may be used to couple the microphone 43 and the speaker 45 to the system bus 15. One skilled in the art will appreciate that the particular device connection configuration is shown for illustration purposes only, and that several of the peripheral devices could be coupled to the system bus 15 via alternative interfaces. For example, the video camera 35 could be connected to the IEEE 1394 interface 37, and the pointing device 31 could be connected to the USB interface 33.

[37] The computer system 10 can operate in a networked environment using logical connections to one or more remote computers or other devices, such as a server, a router, a network personal computer, a peer device or other common network node, a wireless telephone, or a wireless personal digital assistant The computer system 10 includes a network interface 49 that couples the system bus 15 to a local area network (LAN) 51. Networking environments are commonplace in offices, enterprise-wide computer networks, and home computer systems.

[38] A wide area network (WAN) 53, such as the Internet, can also be accessed by the computer system 10. A modem unit 55 is shown connected to the serial port interface 27 and to the WAN 53. The modem unit 55 may be located within or external to the computer system 10, and may comprise any type of conventional modem, such as a cable modem or a satellite modem. The LAN 51 may also be used to connect to the WAN 53 via a router 57 in accordance with conventional practices. [39] It will be appreciated by one skilled in the relevant art that the network connections shown are exemplary and that other ways of establishing a communications link between computers can be used. The existence of any of various well-known protocols, such as TCP/IP, Frame Relay, Ethernet, FTP, HTTP, and the like, is presumed, and the computer system 10 can be operated in a client-server configuration to permit a user to retrieve web pages from a web-based server. Furthermore, any of various conventional web browsers can be used to display and manipulate data on web pages.

[40] The operation of the computer system 10 can be controlled by a variety of different program modules. Examples of program modules are routines, programs, objects, components, and data structures that perform particular tasks or implement particular abstract data types. The present invention may also be practiced with other computer system configurations, including hand-held devices, multiprocessor systems, microprocessor-based, or programmable consumer electronics, network PCS, minicomputers, mainframe computers, personal digital assistants, and the like. Furthermore, 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. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.

[41] The method of the present invention can be described with reference to the generalized flow diagram of Fig. 2 in which an initial customer and retail strategy is developed, at step 61. As can be appreciated by one skilled in the relevant art, a merchandiser needs to consider both local strategies and product strategies when deciding which products to stock in the local store. In considering product strategies, for example, the corporate direction and strategy can be taken into account so as to identify the product growth areas, the focus, and the 'hot' products. In considering local strategies, the merchandiser may take into account the local product strengths, the local market, and the characteristics of the local customers. That is, the analysis considers which customer groups patronize the local store and what products are they most likely to purchase. Additionally, the local market is evaluated to identify its strength, catchment size, opportunity, and market share.

[42] The initial retail strategy may be developed by taking into account, i) the produces) and local store strategy needed to deliver growth, ii) the role played by each business unit and business category, and iii) the role played by each store format and store channel. Additional factors that may be used in developing the initial retail strategy relate to the needs of current customers, the potential for new customers, and the objective of increasing sales. An analytical model utilized in the disclosed method may use strategy, customer information, and internal-performance to determine store format, store layout, and space allocations.

[43] A local store opportunity is determined, at step 63. This operation may include determining customer demand, that is, determining who the customers are, what the customers purchase, and how the purchases are made. The local competitive position of the store is evaluated, as is the store performance in terms of sales and return per foot (RPF).

[44] The local store parameters are modeled, at step 65. Local store market conditions are represented by local store parameters in the analytical model, by which the local store market conditions can be used by the retail purchaser/planner to drive the product offer. The format of the store is assessed to determine, for example, how the layout of the store and the location of the entrances may influence the customer traffic patterns. Assessing the layout and location of entrances can be done on the basis of establishing which products are presented in the primary and the secondary locations in the local store. For a food retailer, for example, the preferred practice is to place fresh produce near the main entrance, while for department stores, cosmetics are usually placed near the main entrance. The process of assessment also takes into account the products purchased by the local customers. For example, an apparel retailer might decide that, for a particular cluster of stores, childrenswear has low priority and should be displayed at the back of a store's top floor. However, a particular local merchant might experience a strong demand for childrenswear and would move the display to a more favorable area in the local store.

[45] At this stage, consideration may also be given as to whether the space, or capacity, for the various products and merchandise should be increased, decreased, or maintained at the same level. Once the modeling parameters have been determined, a query is made, at decision block 67, as to whether the store model has been optimized and yields acceptable sales figures. This query is addressed by the retail purchaser/planner who draws upon his experience in the relevant art to render a judgment on likely sales. The determination may be based on the derived space allocations for the various products and merchandise, and on projected indicators, such as revenue, RPF, margin, footfall, and return on inventory. If sales and allocation figures provided by the store model are not optimal or acceptable to the retail planner/purchaser, the appropriate parameters are adjusted, at step 73, as explained in greater detail below, and operation returns to decision block 67.

[46] Once the store model parameters have been adjusted to produce sales and allocation data acceptable to the retail purchaser/planner, the parameters are applied to the local store model, at step 69, to produce a revised retail strategy, at step 71. The revised retail strategy, utilizing the adjusted store model parameters, is intended to- insure that: i) the correct styles of merchandise are provided for the local customers, ii) a profitable allocation of space for the identified products and merchandise is provided in the store, iii) the proper breadth of merchandise is stocked in the space provided, and iv) the merchandise is stocked to the proper quantities to meet the anticipated needs of the local store customers.

[47] The process of determining local store opportunity, at step 63 above, can be described in greater detail with reference to the flow diagram of Fig. 3 in which local store customer groups are identified, at step 81. The identification of local store customer groups can be expressed in terms of customer parameters 91, listed in Fig. 4, as is known in the relevant art, and then further analyzed. For example, a customer value distribution 93 may be segmented into 'peripheral,' 'browser,' 'core,' 'occasional,' and 'gold,' as functions of average basket value and frequency of visit. Customer demographics may be grouped into a set of demographic profiles 95, and customer purchases can be grouped into a set of purchase behavior profiles 97. The set of demographic profiles 95 represents groups of customers having similar demographic characteristics, and the set of purchase behavior profiles 97 represents groups of customers who purchase similar types of products.

[48] With reference back to Fig. 3, when local store customer groups have been identified, a determination is made as to the locations in which the customer groups make their respective purchases, at step 83. An example of such a determination is illustrated in Fig. 5 in which a set of four customer groups 101 have been identified and labeled as 'stylish single,' 'mothers with a mission,' 'student enclaves,' and 'budgeting families.' Associated with each customer group in the set of customer groups 101 is a graphic showing the distribution and densities of a respective customer group. The geographic locations of the set of customer groups 101 can be plotted along two coordinate axes to form a graph 103 having, for example, a horizontal axis indicating spending level (e.g., 'value' to 'affluent') and a vertical axis indicating style preference (e.g., 'traditional' to 'fashion').

[49] The purchasing characteristics of a particular customer group can then be determined, at step 85 (Fig. 3). This information can be provided in tabular form, as shown in Fig. 6. For example, the parameters listed in a Demographics and Lifestyle table 111 for one of the customer groups in the set of customer groups 101 may be given as 'Age: 35 - 50,' 'Family: busy husband,' and 'Home: detached house.' Characteristics and patronage parameters can be similarly listed, as shown in a Usage & Attitude table 113. Additional information using some of the customer parameters 91, above, here denoted as 'value,' product,' and 'channel' are listed in a purchasing behavior table 115 to provide the requisite information for step 85, above.

[50] In a preferred embodiment, the generalized process performed by the computer system 10 in modeling local store parameters, generally denoted as step 65 in Fig. 2, follows the steps shown in the flow diagram of Fig. 7. A Sales Plan formulation is initiated at operation 130, where the retail purchaser/planner, or client, decides on planned sales within market segments for a specified period. The Sales Plan formulation preferably focuses on the strategic element of the financial planning process, where the client decides on planned sales, within market segments, for a specified planning period. A Store Plan foπnulation is initiated at operation 140, where the client calculates planned sales per cluster group, and calculates planned sales within a combination of market segments and cluster groups. In a preferred embodiment, the Store Plan formulation focuses on historical data, where the client calculates planned sales, initially as a function of cluster groups and subsequently as a function of both the cluster groups and market segments.

[51] A Gap Analysis is performed at various levels between the Sales Plan foπnulation and the Store Plan formulation, at operation 139. The Gap Analysis is run so that the Sales Plan formulation may be adjusted as required to more closely conform to the Store Plan formulation. The Sales Plan 161 is typically derived using relevant overall market parameters and conditions, and incorporates an understanding of the retailer's strategy. Using the Sales Plan 161 exclusively, the retailer would specify essentially the same allocation of merchandise to stores in the same cluster group. In comparison, the Store Plan 163 is primarily based on actual local store sales parameters and activities and is more likely to reflect differences in stores found in the same cluster group. Accordingly, allocations made in accordance with the results of the Store Plan 140 would differ among stores in the same cluster group.

[52] By way of example, the Sales Plan 161 may have been derived using a projection that sales in a Menswear category would increase by four percent, where the four percent figure results from a ten percent sales increase in a Casualwear category and a one percent decrease in a Foπnalwear category. The Sales Plan 161 is applicable to a cluster of stores which includes a 'Store A' and a 'Store B.' Store A may be undergoing a re-development in the Menswear category, with the expectation that Menswear sales will most probably fall by ten percent during this re-development period. Meanwhile, the Menswear category in Store B may have been enlarged and the competition may have decreased with the result that the overall Menswear sales increased by fifteen percent and Store B has become very strong in Formalwear. As a result of these differences, the Store Plans derived for Stores A and B will not necessary align with their respective, similar, Sales Plans. Where a Store Plan does not align with a Sales Plan, a Gap Analysis and reconciliation process are performed so as to adjust the Sales Plan for a particular store in accordance with the Store Plan formulation.

[53] In one prefeired embodiment of the disclosed method, a reconciliation process includes a process of working detail store estimates, such as for cotton, linen, and silk shirts, back up to higher-level budgets, such as casual Menswear and formal Menswear budgets, for example. At this level, the retail purchaser/planner may analyze the data to determine if the gap, or non-alignment between the Store Plan and the Sales Plan, is acceptable, whether the estimated impact at the Store level is realistic, and what the options are for minimizing the gap. Such options may include 'pushing' the formal Menswear elsewhere, and re-timing or re-scheduling the Store sales activities.

[54] A Range-Width Plan 155 is formulated, at operation 150. Here, the range width of the assortment by local market is calculated at a lower level of detail. Also calculated are sales by grade, style, and footage per store and per store group to produce a Grade Review 151 and a Density Review 153. As is understood in the relevant art, the product offer in a store is referred to as the 'range' of the product, the number of styles, colors, and sizes of the product is referred to as the 'range width,' and the quantity of the product purchased or on display is referred to as the 'range depth.' Taking, for example, the range of Formal Mens Wear, the range width for a small store may include shirts that are either black, white, or blue and round neck, with mostly short sizes. For a large store, the range width may also include shirts that are green and orange with selections of v-neck and round neck in larger sizes. The small store may have a range depth of five units for each color, while the large store may have a range depth of twenty units for each color. [55] Calculating the Range-Width Plan 155 at a lower level of detail means progressively working down through the hierarchy either in terms of sales or of units. Using Menswear sales as an example, this might break down to range widths of a forty percent share of casual Menswear and a sixty percent share of formal Menswear. The casual Menswear might further break down at a lower level of detail into a thirty percent share for casual Shirts, a twenty percent share for casual Trousers, a ten percent share for casual Jackets, and a forty percent share for casual Accessories. The casual Shirts may then be further broken down into a thirty percent share for plain Cotton Casual Shirts, a thirty percent share for Print Cotton Casual Shirts 30%, a twenty percent share for Linen Casual Shirts, and a twenty percent share for Silk Casual Shirts.

[56] These calculation are determined by: p reviewing the previous season's historical sales for like products and like stores, ii) reviewing the strategic intention of the Store executives in the present season, which asks 'Where is the focus and direction?' or 'What are the products and the customers?' iii) reviewing the customer strategy, which asks 'Which customers do we focus on?' or 'What do the customers want to buy?' or 'How many of the customers shop in each store?' and iv) reviewing the market, which asks 'What is the view on what is fashionable or popular?' or 'Which of the customers are influenced by fashion trends?' This process of reviewing allows the retail purchaser/planner to make a prediction on likely sales based on personal experience.

[57] Using the results of the operation 150, the computer system 10 produces key output data including a Sales Plan 161 and a Store Plan 163, at operation 160. The Sales Plan 161 is provided as a planned sales allocation for the year for each Department and Market Segment combination. The Store Plan 163 may be provided as a planned sales allocation for each Department, Cluster, and Market Segment combination.

[58] The Sales Plan 161 and the Store Plan 163 are reconciled, at operation 165, to produce a Final Allocation Plan 167. The Final Allocation Plan 167 is further analyzed to produce a set of Final Allocation Outputs including a Grade Plan 171, a Density Plan 173, and a Range-Width Plan 175, at operation 170. The Grade Plan 171 includes rationing planned Department/Cluster sales between each Cluster/Grade and Market Segment combination. The Density Plan 173 details the number of zones, and the number of styles within zones, for each store for each department. As understood in the relevant art, a zone is a measure of selling space. For example, an 'S-shaped hanging rack' is the equivalent of two zones of space, and a 'small rectangular table' is the equivalent of one zone of selling space. The Range Width Plan 175, which includes the purchase quantities for a selected number of product categories, preferably details the average total buy projected for each style/store combination.

[59] Sales Plan formulation, at operation 130, is described in greater detail below with additional reference to Figs. 8 through 11, which are representations of the display screens utilized by a client accessing the computer system 10 in a preferred embodiment. It should be understood that various planning tools currently available in the relevant art, in alternative to the specific methodology described below, can be used to produce the requisite information described in the disclosed method.

[60] In Fig. 8, Plan Sales by Division (i.e., by business unit) or Divisional Sales Values, are entered in a first Sales Plan screen 200, at step 131. When accessing the first Sales Plan screen 200, the client can enter a planned sales figure for each Division for a selected planning period.

[61] By way of example, the client may select 'Menswear' from a 'Division' list 201, and select a time period denoted by the code 'SS02' from a 'Plan Period' list 203. The plan period code represents any range of dates to which the information refers. The client inputs a planned sales figure for the Menswear Division to a 'Planned Sales for Division' entry field 205. The value in the entry field 205 may be edited, by clicking on an 'Edit' button 207 and, optionally, on a 'Cancel' button 211. The client can define a new plan period by selecting, activating, or selecting a 'Define New Plan Period' button 213 as is well-known in the relevant art. When an 'OK' button 209 is clicked, such as by using a computer mouse, the Planned Sales figure in the entry field 205 is saved to a processing system database (not shown), such as may be resident in the hard disk drive 21 or in the removable memory drive 23, or which may comprise a remote database accessible via the network interface 49 or the modem unit 55. The data in the entry field 205 corresponds to the Divisional Sales Value parameter, derived at step 131 in Fig. 7. The client then proceeds to the next screen, at step 133, by clicking on a 'Sales by Department' link 215.

[62] A second Sales Plan screen 220, shown in Fig. 9, provides for the allocation of planned sales between departments. The client specifies a Division and selects a ^• planning period, and can re-allocate Divisional planned sales among selected Departments within the specified Division. Continuing with the above example, the client would select 'Menswear' from a 'Division' list 221, and 'SS02' from a 'Plan Period' list 223. The planned Divisional sales for the Menswear Division, previously input to the entry field 205 of the first Sales Plan screen 200, will be retrieved from the processing system database and will be displayed in a 'Planned Sales for Division' field 225 of the second Sales Plan screen 220.

[63] Relevant Departments will be displayed in 'Department' fields 227, along with respective percentage allocations for the Division/Department from the previous year in 'Last Year's Sales % Participation' fields 229. The client can then allocate the Divisional planned sales among selected Departments, by percentage, in multiple 'Sales Plan %' entry fields 231. The data in the entry fields 231 corresponds to the Sales Value by Department parameter, derived at step 133 in Fig. 7. The percentage allocation values in the fields 231 can be edited by the client, if desired. Total sales figures can be calculated and displayed in 'Total' fields 233. The client clicks an 'OK' button 235 to save the percentage allocation values in the fields 231 and the sales total in the field 225 to the processing database. The client then proceeds to the next screen, at step 135, by clicking on a 'Sales by Division/Segment link 237.

[64] A third Sales Plan screen 240, shown in Fig. 10, provides for the allocation of Divisional planned sales between market segments. The client specifies the Division and planning period, and can re-allocate Divisional planned sales among selected Market Segments within the specified Division. In the example, the client would continue by selecting 'Menswear' from a 'Division' list 241, and 'SS02' from a 'Plan Period' list 243. The planned Divisional sales for the Menswear Division, previously input to the entry field 205 of the first Sales Plan screen 200, is retrieved from the processing system database and displayed in a 'Planned Sales for Division' field 245 of the third Sales Plan screen 240. Relevant Market Segments will be displayed in 'Segment' fields 247, along with respective percentage allocations for the Division/Segment from the previous year in 'Last year's sales % participation' fields 249.

[65] The client can then allocate the Divisional planned sales among selected Market Segments, by percentage, in multiple 'Sales Plan %' entry fields 251. The data in the entry fields 251 corresponds to the Sales Value by Division and Market Segment parameter, derived at step 135 in Fig.7. The percentage allocation values in the fields 251 can be edited by the client, if desired. Total sales figures will be calculated and displayed in 'Total' fields 253. The client clicks an 'OK' button 255 to save the percentage allocation values in the fields 251 and the sales total in the field 245 to a database. The client then proceeds to the final Sales Plan screen, at step 137, by clicking on a 'Review Sales by Department/Segment' link 257.

[66] In a fourth Sales Plan screen 260, shown in Fig. 11 , the chent specifies a Division and a Department within the specified Division. The computer system 10 then allows the client to review departmental planned sales among selected Market Segments within the specified Division. Referring to the example provided above, the client selects 'Menswear' from a 'Division' list 261, selects 'SS02' from a 'Plan Period' list 263, and selects 'Ties' from a 'Department' list 265. The planned Divisional sales for the Tie Department, previously input to one of the entry fields 231 of the second Sales Plan screen 220, will be retrieved from the processing system database for display in a 'Planned Sales for Department' field 267 of the fourth Sales Plan screen 260. Relevant market segments will be displayed in 'Segment' fields 269, along with respective percentage allocations for the Division/Segment from the previous year in 'Division/Segment Sales % Allocation' fields 271. The total values are provided in 'Total' fields 275.

[67] The client can then either accept the Divisional allocation amounts previously entered, ^• or re-allocate the departmental plan sales among the market segments using percentage amounts, at step 137. The segment percentage allocations in the fields 271 can be edited by the client after clicking an 'Edit' button 279. Total sales figures will be calculated and displayed in 'Total' fields 275. The chent clicks an 'OK' button 277 to save the percentage allocation values in the fields 273 and the sales total amounts in the fields 275 to the processing system database. The data in the fields 273 corresponds to the Sales Value by Department and Market Segment parameter, derived at step 137 in Fig. 7. By clicking on a 'Divisional Store Sales' link 281, the client can go on to store plan formulation, at operation 140, using display screens shown in Figs. 12 through 17.

[68] Divisional plan sales for each Division/Store combination are allocated using a first Store Plan screen 300, shown in Fig. 12, at step 141. The following series of parameters may be entered or, if values have been entered previously, the parameters can be edited. The parameters include i) the number of zones for each business unit in a store, ii) the cluster to which the store belongs, and iii) the replenishment grades for the stores included in the analysis. When accessing the first Store Plan screen 300, the client selects a Division in a 'Division' list 301, and selects the planning period in a 'Plan Period' list 303. In the present example, the client would again select 'Menswear' from the list 301, and 'SS02' from the list 303. This action retrieves all relevant stores for display in a column of 'Store' fields 305. Additionally, previously-entered values for planned sales, zones, clusters, and grade allocations, if any, are displayed in 'Planned Sales' fields 307, 'Zones' fields 309, 'Cluster' fields 311, and 'Grade' fields 313, respectively. The data in the fields 311 corresponds to the Store Sales Value by Division and Cluster parameter, derived at step 141 in Fig.7. [69] Once these values are acceptable to the client, he can leave the planned sales values, number of zones, cluster, and grade allocations as they appear on the first Store Plan screen 300, or review the entries by moving to a second Store Plan screen 320, shown in Fig. 13, via a 'Review Sales by Division/Cluster' link 317. It should be understood that the allocation values appearing in the first Store Plan screen 300 are independent of the amount allocated in the 'Planned Sales for Division' field 245 in the third Sales Plan screen 240, above.

[70] Alternatively, the client could have entered Divisional planned sales by amount, in the column 307, for each of the stores displayed in the 'Store' fields 305. The allocations entered by the client are independent of the amounts allocated in the 'Planned Sales for Division' entry field 205 in the first Sales Plan screen 200, above. The chent can also specify the number of zones for each Division or business unit in the store, select a Cluster to which, the store belongs, and allocate a replenishment grade for the selected store, within the Division. To assist in making these decisions, the client may utilize a Local Store Analysis feature by clicking on either a 'View' button 315 or on a 'Local Store Analysis' link 319. Either action will bring the client to a Local Store Analysis screen 340, shown in Fig. 14, at step 143, as described in greater detail below.

[71] When the client has opened the second Store Plan screen 320, in Fig. 13, he can select the Division in a 'Division' list 321, and the planning period in a 'Plan Period' list 323. The Planned Store Sales previously entered in the 'Planned Sales' fields 307 of the first Store Plan screen 300 are summed for the selected Division and displayed in a 'Planned Store Sales for Division' entry field 325. When accessing the second Store Plan screen 320, the client can review calculated Divisional Planned Sales between Store Clusters, where the relevant Store Clusters are displayed in 'Cluster' fields 327. The percentage allocation a particular cluster represents (i.e., the sum of clusters allocated divided by the number of stores) is provided in a 'Store Plan %' field 329. The total value represented for each Cluster (i.e., Divisional Sales multiplied by the percentage allocation) is provided in a 'Total' field 331. [72] If the client wishes to utilize the Local Store Analysis feature as an aid in making the above evaluations, he may click on a 'View' button 333, which takes him to the Local Store Analysis screen 340. In the Local Store Analysis screen 340, the chent selects the Division in a 'Division' list 341, the Department in a 'Department' list 343, and selects the planning period using a 'From' field 345 and a 'To' field 347. By chcking on a 'Query' button 349, the chent can display the relevant stores and their previous data. Alternatively, the client may, from the second Store Plan screen 320, click on a 'Rework My Allocation' button 335 to return to the first Store Plan screen 300, or click on a ' Sales by Department/Cluster' link 337 to move to a third Store Plan screen

360, shown in Fig. 15, at step 145.

[73] In the third Store Plan screen 360, the client selects the Division in a 'Division' list

361, the Plan Period in a 'Plan Period' list 363, and a Cluster in a 'Cluster' list 365. Continuing with the example, the client would select 'Menswear' from the list 361, and 'SS02' from the list 363, and 'Cluster B' from the list 365. The planned sales entered for the Store Division combination in a 'Planned Store Sales for Division/Cluster' window 367 will then be summed and displayed in a 'Store Plan' column 369 along with the relevant Departments and the Division/Department allocation, by default. The client can then elect to accept the default allocation, or he can re-allocate the Planned Sales for the respective Division, Planning Period, and Cluster combination, by percentage, between the Departments, in the 'Store Plan' column 369. The data entered in the column 369 corresponds to the Store Sales Value by Department and Cluster parameter, derived at step 145 in Fig. 7. The selected allocation is then saved to the processing system database via an OK' button 371.

[74] By chcking on a 'Sales by Division/Cluster/Segment Unk 373, the client can elect to proceed to a fourth Store Plan screen 380, shown in Fig. 16, to allocate divisional planned sales for each Cluster between Market Segments. The client selects the Division in a 'Division* list 381, the Plan Period in a 'Plan Period' list 383, and the Cluster in a 'Cluster' list 385. The Planned Sales for Clusters allocated in a 'Planned Store Sales for Division/Cluster' entry field 386 are summed for each Cluster Group and displayed along with the relevant Segments and the Division/Segment allocation. The chent can choose to accept these default allocations, or re-allocate the planned sales for the particular Division, Plan Period, and Cluster combination, by percentage, between the respective Segments, appearing in a 'Store Plan %' column 387. The total value is calculated and displayed in a 'Total' column 391. The data in the column 387 corresponds to the Store Sales Value by Division, Cluster, and Market Segment parameter, derived at step 147 in Fig. 7. Data is saved to the processing system database by clicking on an 'OK' button 393.

[75] The client can then review the data entries by clicking on a 'Review Department/Cluster/Segment' link 395 to bring up a Store Plan Review screen 400, shown in Fig. 17. The client selects the Division in a 'Division' list 401, the Plan Period in a 'Plan Period' list 403, the Cluster in a 'Cluster' list 405, and a Department in a 'Department' list 407. Continuing with the example provided, the chent would select 'Menswear' from the list 401, select the planning period 'SS02' from the list 403, select 'Cluster B' from the list 405, and select 'Ties' from the list 407.

[76] The Department/Cluster allocation is displayed in a 'Planned Store Sales for Department/Cluster' window 409. Additionally, the relevant Market Segments are listed in a 'Segment' column 411, and the relevant allocations are listed in a 'Department/Segment % Allocation¹ column 413. The chent can elect to accept the listed allocations, or re-edit the percentages with respect to the Cluster group using the 'Allocation for Cluster' column 414. The data entered in the column 414 corresponds to the Store Sales Value by Department, Cluster, and Market Segment parameter, derived in at step 149 in Fig. 7. Values are displayed in a 'Total' column 415. The data is saved to the processing system database by clicking on an 'OK' button 417. The chent may at this point elect to proceed to the reconciliation operation 165 (in Fig. 7), by clicking on a 'Reconcile Plan Department/Cluster' link 419.

[77] The Gap Analyses operation 139, in Fig. 7, functions to compare the Sales Value by Department parameter, from the field 231 (Fig. 9), and the Store Sales Value by Department and Cluster, from the field 369 (Fig. 15), above. The operation 139 also functions to compare the Sales Value by Department and Market Segment, from the field 273 (Fig. 11), with the Store Sales Value by Department, Cluster, and Market Segment, from the field 414 (Fig. 17), above. The Range Width Plan Foπnulation operation 150 is completed at this stage. The Sales Plan 161 and the Store Plan 163 are produced by the operation 160.

[78] A first Plan Reconciliation screen 420, shown in Fig. 18, provides for a comparison of planned sales allocation from the Sales Plan 161 and the Store Plan 163 for Department/Cluster combinations. The client selects a Division from a 'Division' list 421 and a Plan Period from a 'Plan Period' list 423. The chent clicks a 'Fetch Department' button 425 to populate a 'Department' column 433 of a Sales table 431, and a 'Department' column 443 of a Store table 441, using data from the processing database. The allocation of the Divisional sales by value, for each Department, will be displayed in a 'Plan Sales' column 435 for the Sales Plan 161. For the Store Plan 163, the allocation of the Divisional sales by value are displayed in a 'Plan Sales' column 447 for each Department listed in the 'Department' column 443 and associated Cluster listed in a 'Cluster' column 445. The client has the option of clicking on a 'Rework My Sales Plan' button 439, or a 'Rework My Store Plan' button 449, which returns the client to the beginning of the respective plan.

[79] To exit the first Plan Reconciliation screen 420, the client can click on a 'Reconcile Plan Department/Cluster/Segment' link 427 to bring up a second Plan Reconciliation screen 450, shown in Fig. 19. By using the second Plan Reconciliation screen 450, the client can reconcile the Sales Plan and the Store Plan according to Department/Cluster/Segment. The client specifies the Division from a 'Division' list 451, the selected planning period from a 'Plan Period' list 453, and the Market Segment from a 'Segment' list 455. The client can click a 'Fetch Departments' button 457 to populate a 'Department' column 463 of a Sales table 461, and a 'Department' column 473 of a Store table 471, with data obtained from the processing database.

[80] The allocation of Divisional sales by value, for each Department/Segment combination are displayed for the Sales Plan 161. For the Store Plan 163, the allocation of the Divisional sales by value, for each Department/Segment, are also displayed. The client has the option of clicking on either a 'Rework My Sales Plan' button 465 or a 'Rework My Store Plan' button 475 to return to the beginning of the respective plan. If the data presented in the Sales table 461 and the Store table 471 are acceptable, the client uses a 'Review Sales by Segment/Cluster/Grade link 479 to bring up a Grade Plan screen 480, shown in Fig. 20.

[81] Sales are reviewed by Segment/Cluster/Grade, at operation 170. The client selects the Division from a 'Division' list 481, the planning period from a 'Plan Period' list 483, the Cluster from a 'Cluster' list 485, and the Department from a 'Department^, list 487. The Department/Cluster sales are displayed in a 'Planned Sales for Department/Cluster' window 489 for the selected parameters. The client can then click a 'Fetch Grade Participation and Calculate Sales' button 491 which may initiate the sequence of events described below.

[82] The number of stores assigned to a particular Grade are counted, for each Grade. The participation percentage for each Grade is calculated and displayed in a Grade Plan table 493. The planned sales for the Department/Cluster are divided by the participation percentage and displayed in the Grade Plan table 493. The client can then click on a 'Ration Sales by Segment' button 495 to provide the sales percentage for each Department/Cluster/Segment and to allocate the total for each Grade among the percentages in the Grade Plan table 493. The client then has the option of i) clicking on a 'Rework My Allocation' button 497 which returns the process to the Store Plan Review screen 400 where changes can be inputted, or ii) clicking on a 'Review Density Relationship for Number of Zones' link 499 to bring up a Plan Density screen 500, shown in Fig. 21.

[83] In the Plan Density screen 500, the density relationship for the number of zones is reviewed, in operation 170. The client specifies the Division from a 'Division' list 501 to bring back the Grade data and the Footage data for each Division/Store combination in a Store/Zones/Grade table 503. The client then specifies the selected planning period in a 'Plan Period' list 505 and clicks a 'Fetch Departments' button 507. This action returns the relevant Departments and the Division/Department allocation by plan period. The client next selects a store, in a 'Select Store' list 509, which action initiates calculation of the parameters in a 'Zones per Department' column 511. In a preferred embodiment, each parameter may be determined by multiplying the zones per store by the respective percentage allocation. Subsequently, the client may enter the number of styles within a zone in a respective 'Styles per Zone' column 513 entry (i.e., styles per zone multiplied by zones per department). This data can be edited by the client, or retained as presented.

[84] A user, by clicking on a 'Review Range Width by Cluster/Grade' link 515 in the Plan Density screen 500, may access a Range Width screen 520, illustrated in Fig. 22. The client specifies the Division from a 'Division' list 521, the selected planning period from a 'Plan Period' list 523, the Cluster from a 'Cluster' list 525, and the Department from a 'Department' list 527. The Department/Cluster allocation is displayed in a 'Planned Store Sales for Department/Cluster' Window 529. The client can click on a 'Fetch Stores/Grades' button 531 to populate a 'Store' column 533 and a 'Grade' column 535 with data from the processing database, for each store from 'Divisional Store Sales.' The corresponding Store Plan 163 for each store can be found by multiplying the Planned Sales for each store by the percentage allocation of Division to Department.

[85] The entries in a 'Zones per Department' column 537 are planned densities assigned to each Department/Store combination appearing in the Plan Density screen 500. The entries in a 'Styles per Zone' column 539 are also taken from the Plan Density screen 500. The entries in an 'Average Total Buy' column 541 are found by dividing the Store Plan 163 by the number of styles and multiplied by styles per zone. The chent can click on a 'Rework My Allocation' button 543 to be taken back to review the Density in the Plan Density screen 500. The client can click on a 'Graph Store Optimized Buy' button 545 to plot the average buy per store of a Department, grouped by Grade. [86] It should be appreciated by those of skill in the relevant art that, on each illustrated screen, additional buttons or hyperlinks may be active to allow the user to navigate directly to the various screens, regardless of whether each hyperlink or button is specifically numbered and referenced on each screen.

[87] While the invention has been described with reference to a preferred embodiment, it will be understood by those skilled in the relevant art that various changes may be made and equivalents may be substituted for elements thereof without departing from the scope of the invention. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the invention without departing from the essential scope thereof. Therefore, it is intended that the invention not be Umited to the particular embodiment disclosed as the best mode contemplated for carrying out this invention, but that the invention will include all embodiments falling within the scope of the appended claims.

Claims

WHAT IS CLAIMED IS:

1. A method for making product purchase and allocation decisions in a marketing environment, said method comprising the steps of: developing an initial retail strategy; determining local store opportunity based upon said initial retail strategy, said local store opportunity including a determination of a customer group, a determination of purchase characteristics of said customer group, and a determination of how purchases are made by said customer group; modeling store parameters to produce a local store model based on said local store opportunity; and specifying a revised retail strategy based on said local store model.

2. The method of claim 1 wherein said step of developing an initial retail strategy comprises the steps of: taking into account product and local store strategy directed to produce growth in sales; and taking into account the format of said local store.

3. The method of claim 1 wherein said step of modeling store parameters comprises the steps of: assessing the layout of said local store; and assessing the locations of entrances in said local store.

4. The method of claim 1 further comprising the step of repeating said step of modeling store parameters if said local store model does not comprise an acceptable store model.

5. The method of claim 1 further comprising the step of applying said local store model to the product purchase and allocation decisions if said local store model comprises an acceptable store model.

6. The method of claim 1 wherein said step of modeling store parameters comprises the steps of: specifying a sales value for a selected business unit for a selected planning period to produce a divisional sales value; allocating said divisional sales value among departments to produce a sales value by department; allocating said divisional sales value among a selected set of stores to produce a divisional store sales value; allocating said divisional store sales value among departments to produce a store sales value by department and cluster; and comparing said sales value by department with said store sales value by department and cluster.

7. The method of claim 6 further comprising the step of revising said divisional store sales value in response to said step of comparing said sales value by department with said store sales value by department and cluster.

8. The method of claim 1 further comprising the step of formulating a range width plan including purchase quantities for a plurality of product categories.

9. The method of claim 8 wherein said step of formulating a range width plan comprises the steps of generating a grade review and generating a density review.

10. The method of claim 1 further comprising the steps of providing a sales plan based on relevant market parameters and providing a store sales and space plan based on local store parameters.

11. The method of claim 10 further comprising the step of reconciling said sales plan with said store sales and space plan to produce a final allocation plan.

12. The method of claim 11 wherein said step of reconciling comprises the step of revising said divisional store sales value.

13. The method of claim 11 further comprising the steps of producing a grade plan, producing a density plan, and producing a range-width plan.

14. The method of claim 1 wherein said step of modeling store parameters comprises the steps of: specifying a sales value for a selected business unit for a selected planning period to produce a divisional sales value; aUocating said divisional sales value among market segments to produce a sales value by division and market segment; aUocating said divisional sales value among departments to produce a sales value by department; allocating said sales value by department among market segments to produce a sales value by department and market segment; aUocating said divisional sales value among a selected set of stores to produce a divisional store sales value; allocating said divisional store sales value among departments to produce a sales value by department and cluster; allocating said store sales value by department and cluster among market segments to produce a store sales value by department, cluster, and market segment; and comparing said sales value by department and market segment with said store sales value by department, cluster, and market segment.

15. The method of claim 14 further comprising the step of revising said divisional store sales value in response to said step of comparing said sales value by department and market segment with said store sales value by department, cluster, and market segment.

16. The method of claim 14 further comprising the steps of: allocating said divisional store sales value among store clusters to produce a store sales value by division and cluster, and allocating said store sales value by division and cluster among market segments to produce a store sales value by division, cluster, and market segment.

17. A computer-readable medium having computer-executable instructions for performing steps comprising: receiving a local store determination based upon an initial retail strategy, said local store determination including an identification of consumer groups demographics, and an identification of and shopping purchasing characteristics of said consumer groups; modeling store parameters to produce a local store model based on said local store opportunity; and producing a revised retaU strategy based on said local store model.

18. The computer-readable medium of claim 17 wherein said instructions for performing the step of modeling store parameters includes computer-executable instructions for performing steps comprising: receiving a sales value by department produced by allocation of a divisional sales value among departments; receiving a store sales value by department and cluster produced by allocation of a divisional store sales value among departments; and comparing said sales value by department with said store sales value by department and cluster.

1 . The computer-readable medium of claim 17 wherein said instructions for performing the step of modeling store parameters includes computer-executable instructions for performing steps comprising: receiving a sales value by department and market segment produced by allocation of a sales value by departments among market segments; receiving a store sales value by department, cluster, and market segment produced by allocation of a store sales value by department and cluster among market segments; and comparing said sales value by department and market segment with said store sales value by department, cluster, and market segment.

20. A computerized marketing analysis system for assisting a user in making product purchase and allocation decisions in a marketing environment, said computerized analysis system comprising: a computer system for storing, displaying, and processing marketing information; software for configuring said computerized marketing analysis system within said computer system, said software implementing in said computer system the steps of: receiving a local store determination based upon an initial retail strategy, said local store determination including an identification of consumer groups demographics, and an identification of and shopping purchasing characteristics of said consumer groups; modeling store parameters to produce a local store model based on said local store opportunity; and producing a revised retail strategy based on said local store model.

21. The computerized marketing analysis system of claim 20 wherein said software further implements in said computer system the steps of: receiving a sales value by department produced by allocation of a divisional sales value among departments; receiving a store sales value by department and cluster produced by allocation of a divisional store sales value among departments; and comparing said sales value by department with said store sales value by department and cluster.

22. The computerized marketing analysis system of claim 20 wherein said software further implements in said computer system the steps of: receiving a sales value by department and market segment produced by allocation of a sales value by departments among market segments; receiving a store sales value by department, cluster, and market segment produced by aUocation of a store sales value by department and cluster among market segments; and comparing said sales value by department and market segment with said store sales value by department, cluster, and market segment.