The present invention relates generally to the field of merchandise and assortment planning, and more specifically to the use of systems and methods for facilitating assortment planning decisions.
In general, business models can involve buying merchandise and services for one price and selling it for another. In the process, sellers can incur spectacular costs marketing to prospective and existing customers, leasing stores, paying employees, buying and maintaining information technology, transporting, and, most importantly, buying and managing the merchandise itself.
Planning, at one level, is a strategic activity. Executives set business objectives and merchandise planners derive strategies to meet them: back to basics to reduce the style count, extended assortments with additional colors and styles, or new lines of business such as health & beauty. On another level, planning is tactical and operational. The plan influences how many styles and colors a merchant will carry. It influences how distributions are planned for stores. It influences when markdowns are expected to be taken for each style and color. It also influences which stores should carry each style.
One of the most important processes of such planning is assortment planning. Assortment planning provides answers to basic questions such as: Which product or service? How much of it? What colors? What sizes? What locations? Who is the target customer? When should it be offered? How long should it be offered? and so forth. Thus, the old adage, the right product, at the right place, at the right time, still holds true in today's marketplace, but with one important change. Sellers—whether traditional brick-and-mortar, e-commerce or a combination of the two—must have a compelling selection of merchandise for the right customer as well. Thus, an effective assortment planning process that provides the right products and services at the right locations at the right time is essential for successful modern business operation.
An effective assortment planning process is ever more necessary in retail environments and particularly in fashion retail environments. Retail environments and fashion retail environments often require that the business adjust to relatively fickle needs of the consumer.
Although assortment planning directly affects product selection, price, timing and micro-merchandising, it has often been de-emphasized due to hectic retail schedules. Extinguishing delivery fires and meeting marketing and financial planning obligations use valuable time, forcing companies to take the easy approach to merchandising: repeating assortment breadth and depth from previous seasons, creating store assortments based on store volume, and ranking items by sales volume alone.
Yet, to attract the right customer in today's increasingly competitive environment, assortment planning must focus on creating appropriate product breadth and depth of products based on the customer's desires and shopping patterns, taking into account lifestyles, climates, trends and more. Furthermore, assortment planning must present a compelling mix of products to illustrate the company's strategic vision.
In view of the foregoing, it would be beneficial to provide a method and system that provides efficient implementation of assortment planning decisions for merchandise. Moreover, it would be beneficial to provide a method and system that allows for more flexible assignments of products and stores to assortments.
The present invention relates to systems and methods for performing assortment definition/planning (i.e., matching the right articles with the right stores at the right times).
According to a first embodiment of the present invention, a method is provided for defining an assortment in a computerized assortment planning system for use in an operative execution system. The method includes assigning a plurality of articles to the assortment for one or more article validity periods, assigning a plurality of stores to the assortment for one or more store validity periods, and releasing the assortment to the operative execution system. Once released to the operative execution system, the articles and the stores are automatically added to and dropped from the assortment based on the validity periods.
According to another embodiment, a system is provided for defining an assortment for use in an operative execution system. The system comprises a central processing unit (CPU) and a storage device coupled to the CPU. The storage device has information stored therein for configuring the CPU to assign a plurality of articles to the assortment for one or more article validity periods, and to assign a plurality of stores to the assortment for one or more store validity periods. The storage device also has information therein for configuring the CPU to release the assortment to the operative execution system. Once released to the operative execution system, the articles and the stores are automatically added to and dropped from the assortment based on the validity periods.
According to yet another embodiment, a program product for defining an assortment for use in an operative execution system comprises machine-readable program code. The program code, when executed, causes one or more machines to perform method steps. The method steps include assigning a plurality of articles to the assortment for one or more article validity periods, assigning a plurality of stores to the assortment for one or more store validity periods, and releasing the assortment to the operative execution system. Once released to the operative execution system, the articles and the stores are automatically added to and dropped from the assortment based on the validity periods.
Other features and advantages of the present invention will become apparent to those skilled in the art from the following detailed description and accompanying drawings. It should be understood, however, that the detailed description and specific examples, while indicating preferred embodiments of the present invention, are given by way of illustration and not limitation. Many modifications and changes within the scope of the present invention may be made without departing from the spirit thereof, and the invention includes all such modifications.
Sales structure 14 represents the different sales channels used by enterprise 12. For example,
Referring again to
In contrast to conventional stores, department stores typically do not have inventory-managing character for consumer merchandise, because inventory management on an article or value basis usually takes place at the shop level. Nonetheless, the department store can represent an overreaching inventory management level for consumable materials, advertising materials, and additionals. Although the department store conventionally groups shops at a physical address, this is not a requirement. For example, different shops can exist at separate physical locations and still be assigned logically to the same department store. Unless otherwise specified below, the term “store” may refer to a conventional store, a department store, or any of the individual shops or departments unified by a department store.
Referring again to
Although the names and number of levels in article hierarchy 18 can be customized, one level in article hierarchy 18 must be defined as the “category” level. The category level may be selected to represent the independent presentation spaces in a store that are devoted to merchandise categories presented to consumers in a unified manner. In the department store context, for example, the category level in article hierarchy 18 may be selected to represent differentiated groupings of shops in the department stores such as confectionaries, menswear departments, and ladies wear departments. Alternatively, a lower level in article hierarchy 18 may be selected to represent the different independent presentation spaces for subgroups of merchandise (e.g., long-arm blouses, short-arm blouses, trousers) within each shop in a department store. Other criteria for selecting the category level may also be used.
In an exemplary embodiment, the level in article hierarchy 18 selected to be the category level has several additional properties that are unique to that level. One unique property of the category level is that stores can be assigned only to that level. In
Another unique property of the category level in article hierarchy 18 is that the assignment of articles (as described in detail below) to hierarchy 18 must be unique below the category level. That is, each article can be assigned only once to a node at or below a particular category node. By contrast, the same article can be assigned again to a different node at or above the category level (e.g., the division level).
Reference is now made to
According to an exemplary embodiment, the relationships between the various nodes in article hierarchy 18 may be as follows. The relationship between the nodes of each level above AM level 45 and the node(s) in the next lower level may be 1:n. That is, each node in TM level 44 may be assigned or linked to one or more child nodes in AM level 45, while each node in AM level 45 is linked to exactly one parent node in TM level 44. In contrast to the nodes above AM level 45, the relationships between the nodes in AM level 45 and the nodes in article level 46 may be n:m. That is, a single node in AM level 45 may be linked to one or more child nodes in article level 46, while each node in article level 46 may be linked to one or more parent nodes in AM level 45 so long as each parent node in AM level 45 is in a different category. Thus, in the embodiment illustrated in
After a theme structure has been defined for a company such as described above, one or more business types may be defined for each consumer theme (e.g., each shop in a department store) to further facilitate assortment definition and planning as described below. A business type definition may be a grouping of all stores of a consumer theme, grouped according to criteria level and capacity, using a standardized procedure. Hence, the business type may be defined for every reasonable combination of level type and capacity for a consumer theme. As such, business type definitions can be used to provide strategic grid spacing of stores according to presentation capacity and level, in consultation with division and sales, taking account of location-specific circumstances. The aim of the level type is to describe a CT/store (e.g., a shop in a department store) with regard to the level of the assortment (defined, for example, by price level, brands features, and so on). Thus, the level type of a CT/store is determined based on question such as, in which price categories, with which brands, and which special features is an assortment carried. The capacity type aims to describe a CT/store with regard to its capacity size expressed in, for example, a number of template display racks. Thus, the capacity of a CT/store is determined based on questions such as, how many articles can be carried, with which width and depth.
According to an exemplary embodiment, one or more business types (BT) may be defined for each consumer theme. An exemplary view 91 of a business type definition (with a rule set for capacity index) is shown in
After the business types have been defined, one or more layout modules may be assigned to each business type definition to facilitate assortment planning such as described below. The layout module provides a pictorial view of the areas in the stores of the selected business type that are available to sell a particular consumer theme. For example, separate regions of the stores may be shown as separate “blocks” on a computer screen, whereby their respective locations and sizes correspond to their actual locations and sizes in the stores. For example,
Referring again to the five segments of enterprise structure 10 described with reference to
In
A merchandise hierarchy may be formed for various reasons. For example, it may be formed to: (i) plan an assortment (as described in detail below), (ii) enable structured analyses in the information system and the planning of target and actual values at the MC level, and (iii) save common data (such as conditions) at superior levels to reduce storage space. According to an exemplary embodiment, the following information may be defined for each MC node: price, color, and size groups; validity periods; n characteristics, and status values. In this embodiment, colors may be saved hierarchically as main colors or single colors. The main colors can have various characteristic values, which represent the single colors. In this case, the single colors are variant-creating characteristics. Accordingly, a merchandise group hierarchy having this structure would allow for analysis of main colors, single colors, and attribute values.
The characteristics of articles in a merchandise hierarchy may be used for classification. Characteristics represent defined properties of an object, such as the color of a blouse. Characteristics help to differentiate objects from one another and find specific articles in the information system (e.g., list all articles with characteristic value “Red” of the “Color” characteristic). Characteristics can be either variant-creating (i.e., used in the definitions of the article variants) or purely informative. According to an exemplary embodiment, two or three-dimensional variant-creating characteristics can be defined for each MC node.
According to anther embodiment, below the MC level, and thus below the entire merchandise hierarchy, characteristic profiles may be defined to segment or specialize the merchandise hierarchy. This may be done to simplify the creation of new generic articles, variants, and single articles.
In this embodiment, a characteristic profile may be used to define the set of values for a characteristic that are permitted in that particular profile. For example, a characteristic profile called “Ladies' sizes, Germany” could define the sizes 34 to 48. Multiple characteristic profiles can be created for multiple merchandise groups. A characteristic profile can be assigned several times within the merchandise group hierarchy. Thus, every article that is assigned to a merchandise group can optionally be assigned to a characteristic profile. According to an exemplary embodiment, the relationship between characteristic-profiles and merchandise groups is n:m. That is, a single characteristic profile can be linked to multiple merchandise groups, and vice versa.
As persons skilled in the art will appreciate, the use of characteristic profiles provides several advantages. For example, characteristic profiles can be used to (i) group sets of colors and sizes, (ii) assign them to the relevant merchandise groups, and (iii) select the suitable profile when creating articles.
Returning again to
Turning now to
In accordance with an exemplary embodiment, assortment definition and planning can be performed for various types of merchandise such as fashion merchandise and regular (e.g., stackable, non-fashion, basic, etc.) merchandise. As persons skilled in the art will appreciate, assortment definition and planning for fashion may differ from assortment definition and planning for regular merchandise for various reasons. For example, assortment definition and planning for fashion generally involves: (1) a higher proportion of new articles; (2) shorter life cycles than the assortment planning horizon, and different, reduced possibilities for short-term replenishment; and (3) capacity use is subject to fluctuations within an assortment planning period. Thus, assortment definition and planning for different types of merchandise may be handled differently. In an exemplary embodiment, for example, assortment planning for regular merchandise may be performed at the theme module level and from month-to-month, while assortment planning for fashion may be performed at the consumer theme level and from season-to-season.
In the various embodiments discussed below, assortment definition and planning for an enterprise may be performed using both local assortments and global assortments. When a store or distribution center is first created, an assortment with the same name is also created. This may be referred to as a local assortment. When articles are listed for these local assortments, they can be managed in the respective store in a single step.
Assortments can also be defined which include several stores. These may be referred to as global assortments. Merchandise quantities can be planned for these global assortments, and thus for a group of stores, in the assortment planning processes described below. Articles that are listed for a global assortment can thus be managed for all assigned stores at one time.
With the foregoing in mind,
Global assortments such as assortment 118 may be classified according to assortment type. Assortment type refers to an assortment attribute that makes it possible to control the strategic direction of the assortment and its handling during assortment design/planning and procurement. In one embodiment, the possible values for the assortment type may be configured by the user. For example, assortments can express the following types: standard assortment-fashion; supplementary assortment-fashion; and regular (e.g., non-fashion) assortment.
In the illustrated embodiment, assortment 118 may also be characterized by one or more assortment dimensions 140. In general, assortment dimensions are attributes of an assortment that can be used during an assortment definition process to group retail sites together to design standardized assortments. That is, the assortment dimensions are used to group together retail sites with similar characteristics to form an assortment that applies to all stores in the group. Retail sites can be grouped differently for different assortment types, i.e., different dimensions can be used as grouping criteria. According to an exemplary embodiment, an assortment can be defined using up to three assortment dimensions. The respective value range or level of the assortment dimensions may be defined and configured by a user. The value range or level of an assortment dimension can be defined differently for each assortment type. By way of example, possible assortment dimensions may include the following retail site characteristics: capacity, price level/grade (high fashion, essential, basic) or sales for a certain group of merchandise, geographical region or location, climactic zone (warm weather, cold weather), demographics (urban, suburban), retail concept, and so on.
With the foregoing in mind, an exemplary assortment may comprise a plurality of retail sites (e.g., store consumer themes or shops in a department store) grouped by category (e.g., consumer theme) with regard to price level/grade and capacity type. Grouping stores by price level and capacity is equivalent to grouping stores by business type as discussed above. In this example, one assortment dimension is the capacity, which may be represented by the following values: “0” to “9” for assortments with type “standard assortment-fashion” and “supplementary assortment-fashion;” and “1” to “6” for assortments with type “regular assortment.” The other assortment dimension in this example is the price level/grade, which may be used only for assortment type “standard assortment-fashion” with the four values “1”—high-priced, “2”—mid-priced, “3”—low-priced, and “0” for exceptional cases (e.g., flagship stores and showpieces).
Referring again to the embodiment illustrated in
Referring once again to
According to an exemplary embodiment, each assortment version 144, 146 may represent one or more shelves 148 in each store assigned to assortment 118. Alternatively, each assortment version 144, 146 may represent one or more display racks (which in turn may comprise a plurality of shelves), or one or more layout modules (which in turn may comprise a plurality of display racks). If desired, a space optimization program (SOP) 150 may be used to determine the optimum layout of articles for each assortment version 144, 146.
In the embodiment illustrated in
As indicated in
Referring now to
Regardless of the source(s) of input information 158-162, classification engine 156 performs a classification algorithm that mines the input information to identify one or more dimensions 164 that may be suitable for characterizing the stores that are eligible for inclusion in the assortment. After completing this task, classification engine 156 provides the identified dimension information 164 to an assortment definition engine 166 along with the original input information (e.g., store information 158 and category information 160) or a subset thereof.
Assortment definition engine 166 uses the dimension information (possibly after approval by a user) and other input information (e.g., information 158-160) along with previous and existing store assignments and assortment information 168 to perform a matching process that clusters or groups stores into proposals for store-assortment assignments 170. The matching criterion is based on the similarity of dimension values of stores (e.g., as found by the classification algorithm) to the dimension values, which may be assigned manually to the assortment object. The proposed store-assortment assignments 170 may be presented to management for approval and release and/or used as inputs to one or more downstream processes without review. The foregoing process may be utilized to automatically generate proposals of suitable store groupings (e.g., by business type) for assortments as well as when to implement them.
With reference now to
This dimension information 164 is provided to assortment definition engine 166 along with store input information 158 and category input information 160. At the same time, assortment definition engine 166 also receives information regarding any previous and existing store assignments and assortments 168 that are based on similar dimension and category information. Using this data, assortment definition process 154 is able to provide a closed-loop system that allows for improved refinement over subsequent iterations. As explained above, assortment definition engine 166 performs a matching process and outputs a recommended store-assortment assignment 170. The end result of this process is that a particular input store is in the northeast region and is a high sales volume store for men's fashion, and therefore it is assigned to a certain assortment on this basis. Other stores located in different regions and/or having different sales volumes for the men's fashion category would be matched with similar stores and the results used to provide other proposed store-assortment assignments. In addition, this process may be performed for other categories besides men's fashion to create additional store-assortment assignments.
As persons skilled in the art will appreciate, the foregoing assortment decision process creates proposed store-assignment assortments that allow for more efficient assortment planning (i.e., matching the right articles with the rights stores at the right times). According to one embodiment, the proposed store-assortment assignments generated by process 154 may be presented to a user via an assortment definition graphical user interface (GUI) 224 such as shown in
To further illustrate the concepts described above, an example of how assortment definition process 154 may be used to define an assortment of stores for a particular category of articles (e.g., handbags) is provided with reference to
Next, stores may be assigned to the assortments (i.e., store clustering) using assortment definition process 154 described above. This is accomplished by analyzing, for every store, all historical sales data for handbags and classifying a capacity type according to the dimension definition. For example, if a particular input store has the capacity to display 100 handbags at a time, it might be classified as a type “5” store. According to an exemplary embodiment, this analysis may be performed automatically using automated classification engine 156 described above.
In addition to classifying each store by capacity, each store in the embodiment of
The result of considering all stores using the process discussed above is assignments of stores to assortments, which may be used as inputs to an assortment definition engine (e.g., engine 166 in
Referring again to the illustrated example, the stores assigned to Assortment 35 represents a group of similar stores for which it is logical to carry a similar set of articles. This set of articles may be determined in a different step and assigned to Assortment 35 to establish the desired article-assortment-store relation.
The assortment decision/planning process and system described above thus create new layout module versions which automatically become valid and later invalid after predetermined periods of time have elapsed and assigns articles (e.g., handbags) to this version according to the strategic target group (e.g., price level of “3”+capacity level of “5”). For example, an assortment layout module version may be defined to become valid after two months have elapsed and to become invalid after an additional two months have elapsed. After finalizing this plan, the layout module version is released, which means that the ordering process for the relevant articles is started (at least for those articles which are supplied by automatic replenishment).
As explained above, assortment planning for fashion merchandise and assortment planning for regular (e.g., non-fashion, stackable, basic, etc.) merchandise may be handled differently. For example, whereas the grouping—and thus the standardization—in assortment planning for fashion merchandise may be performed primarily using standard assortments from the business type definitions at the consumer theme level, the grouping for regular merchandise typically takes place at a deeper level in the theme structure, e.g., at or below the theme module. This difference is best illustrated in
As explained above, the assortments for regular merchandise are handled somewhat differently in the exemplary embodiment. In particular, assortments 188 and 189 comprising regular merchandise are linked to theme module (TM) level nodes 190 and 191, respectively. Moreover, two additional standard independent assortments 192 and 193 comprising regular merchandise may be assigned to one or more TM nodes (not shown) presently or to TM node 190 in the future. Similarly, another standard independent assortment 194 for regular merchandise may be assigned to another TM node (not shown) presently or assigned to TM node 191 in the future. As illustrated, each of the standard independent assortments 188, 189, 192, 193 and 194 for regular merchandise may comprise a layout module (LM), which in turn is defined by one or more display racks (DRs) of regular merchandise.
According to an exemplary embodiment, a store consumer theme is usually assigned to several assortments. Moreover, each store consumer theme typically has exactly one standard assortment (business type assortment), which is derived from the business type definition as described above. Because the standard assortment contains only fashion articles in this embodiment, business type assortments are not assigned any articles for consumer themes that have only regular merchandise theme modules. Instead, the regular merchandise articles are assigned to the store consumer theme via the assortments in the layout modules.
An illustration of the foregoing embodiment is illustrated in connection with
According to an exemplary embodiment, the grouping of stores by business type is sufficient to provide for a large majority (e.g., 95% or more) of the assortment planning for the stores in each group as a whole. That is, the stores of an enterprise are preferably sufficiently uniform when grouped by business type (i.e., the same consumer theme/capacity/level) that most or all of the necessary assortment planning for these stores can be accomplished at the business type level. Then, the assortment planning necessary to link the remaining small amount of articles (e.g., 5% or less) to the right stores at the right times can be accomplished using supplementary store assortments. For example, the remaining articles can be assigned using supplementary (global) assortments (e.g., for store-specific brand management) based on store capacity or, in some cases, using supplementary (local) assortments (e.g., for flagship stores).
Referring now to
In the illustrated embodiment, GUI 224 includes a header area 226, a table area 228, and a store selection area 250. Header area 226 shows selection criteria for the assortments and the associated store assignments which may be revised. Header area 226 includes a plurality of selection criteria fields including an assortment type field 230, an article hierarchy ID field 232, an article hierarchy node (e.g., a category) field 234, and a validity (or key) date field 236. All assignments of stores to assortments that are valid at the date provided in field 234 are shown in table area 228 (discussed in detail below). In most cases, the validity date entered in field 234 is chosen to be in the future because assortment definition process 154 typically defines the store assignment configuration which should be valid for instances of the next year.
Based on selection data entered into header area 290, all of the actual (i.e., current) and planned assignments of stores to assortments are presented in table area 228. In the illustrated embodiment, table area 228 includes an exception column 238, a plant (or store) column 240, an assortment column 241, a date from column 242, a date to column 244, a capacity type column 246, and a price level type column 248.
Exception column 238 shows the status of each assignment of a store to an assortment. Green indicates an assignment that has already been released to an operative execution system, i.e., the store-assortment assignment is actually in use. Yellow indicates an assignment that has been planned but not yet released. Red indicates an assignment that is incomplete. Assignments that are planned are not visible “outside” the planning system. After a planned assortment is approved and released to operative systems, it receives the status released and the yellow light in column 238 is replaced by a green light. From a planning standpoint, it may be important to know whether the assignments are already used operatively because, if so, changes should be limited. In the illustrated embodiment, operative (e.g., “actual”) assignments are shown in the left side columns of table area. If an operative assortment is being replaced by a new (planned) assignment, the new (planned) assignment is shown in the same row in the far right hand columns (see
Continuing with the description of table area 228, store column 240 shows the stores, including the technical name (e.g., unique ID) and the associated description. Assortment column 241 shows the actual/planned/incomplete assortment, including the technical name (e.g., unique ID) and the associated description. Date from column 242 and date to column 244 show the validity period for the assignment. Capacity column 246 shows the capacity type of the store, and price level column 248 shows the price level type of the store.
In the illustrated embodiment, GUI 224 may includes a plurality of buttons which may be selected (e.g., by clicking with a mouse) to invoke various functions associated with assortment definition. For example, GUI 224 may include a “Find Assortments” button that may be selected to launch the store matching process and (potentially) propose a new assortment for each store. If this proposal is found acceptable to the user and accepted, a new (planned) assortment is created and the old assignment is terminated.
Store selection area 250 shows all of the stores that match the selection criteria entered into fields 230-236 in header area 224 but have not yet been assigned to an assortment. In an exemplary embodiment, store selection area 250 includes a tree structure 252 that includes all of the eligible stores. In this embodiment, the stores may be dragged from tree 252 and dropped onto an assortment in table area 228 to create a new assignment manually.
With reference now to
As described above, one or more nodes in hierarchy 300 may be assigned (or linked) to an assortment for purposes of assigning a group of products to that assortment (and thus the stores in that assortment) during assortment planning. For example, subcategory node 312 may be assigned to a pair of assortments 316 and 318 to provide a group assignment of the products under node 312 to assortments 316 and 318. It may be desirable to assign a single node to two assortments, for example, when assortment 316 is for small stores and assortment 318 is for large stores. As another example, subcategory node 314 may be assigned to a pair of assortments 320 (for small stores) and 322 (for large stores) to assign the products under node 314 to assortments 320 and 322. After each of the foregoing assignments of a subcategory node to an assortment is made, one or more products beneath the subcategory node may be excluded (e.g., using a suitable GUI) from the assortment as explained above. Although not illustrated in
In addition to the assignments of products to assortments, it is also necessary to assign stores to the assortments so that the desired products are provided to the correct stores at the proper times. Typically, the assignment of the stores to the assortments is performed prior to assigning the products to the assortments using an assortment definition process such as described above in detail. In
In an exemplary embodiment, an additional link can be established to create a check or restriction on the types of products that are assignable to a particular store during assortment planning. More specifically, a particular node at one level (e.g., a category level) in an article hierarchy may be assigned to a store to indicate that only products below that node are assignable to that store. In
As persons skilled in the art will recognize, a restriction or check such as described above with reference to
According to various exemplary embodiments, a replenishment system that receives data regarding one or more articles may be used to replenish items. The data regarding the article may be received from any number of sources. For example, in one embodiment, data regarding one or more articles is received by the replenishment system from an assortment planning system. In another embodiment, data regarding one or more articles is received by the replenishment system from an article master data management system. In another embodiment, data regarding one or more articles is received by the replenishment system from a best seller/slow seller management system configured to periodically identify articles that are selling at a rate faster or slower than a rate determined by a planned sales curve. In another embodiment, data regarding one or more articles may be received by the replenishment system from a combination of these inputs and or additional inputs, including manual input by a user from a keyboard, mouse, or other input device.
The replenishment system uses received data regarding the articles to implement a replenishment process. In a first step, the replenishment system determines the articles that are to be included in the replenishment process. For example, in one embodiment, the replenishment system may be configured such that only data regarding articles associated with a particular predetermined “management type” is automatically forwarded to the replenishment system and included in the replenishment process. The management type may be, for example, a predetermined parameter included in data from either an assortment planning system or an article master data management system indicating whether a particular article is to be replenished using the replenishment process or another process and/or system. Accordingly, in one embodiment, all articles for which data is received by the replenishment system are automatically included in the replenishment process. In another embodiment, the articles to be included in the replenishment process are determined in response to user input designating which articles are to be included in the replenishment process, and data regarding these articles is then received by the replenishment system.
In another step (e.g., a second step), the replenishment system determines a supply channel for each article. For example, the replenishment system may determine whether an article is to be sourced directly from a vendor or from an existing supply in a particular warehouse. The replenishment system may also determine the particular routing of the article (e.g., cross-docking, direct delivery, etc.). In one embodiment, the supply channel for each article is determined according to data for each article from either an assortment planning system or an article master data management system indicating a particular supply channel. In another embodiment, the particular supply channel for each article may be determined by the replenishment system in response to user input designating a particular supply channel for each article.
In another step (e.g., a third step), the replenishment system determines the store in which each article is to be replenished. In one embodiment, the replenishment system determines the store in which each article is to be replenished according to a predetermined “business type” parameter. The business type parameter may be a parameter assigned by an assortment planning system which associates a particular article or group of articles with a particular store or grouping of stores based on, for example, a targeted price range or level for the article or group of articles to be replenished and the store or group of stores, and/or a particular capacity level or range associated with the article or group of articles and the store or group of stores. For example, in one embodiment, the replenishment system may receive the business type parameter from the assortment planning system indicating that a group of articles to be replenished using the replenishment process, such as “men's athletic socks,” is associated with a particular store or group of stores carrying products in a mid-level price range and at a high capacity level. The replenishment system then uses this data to determined the store or group of stores in which the article or group of articles is to be replenished. In another embodiment, the particular store in which the article is to be replenished may be determined by the replenishment system in response to user input designating a particular store for each article.
In another step (e.g., a fourth step), the particular method of replenishment is determined by the replenishment system. The replenishment method may be automatic replenishment, manual replenishment, etc. In one embodiment, the replenishment system may be configured such that only data regarding articles associated with a particular predetermined management type indicating automatic replenishment is automatically forwarded to the replenishment system and included in the replenishment process. In this embodiment, all articles for which data is received by the replenishment system are automatically determined as requiring automatic replenishment. In another embodiment, the particular method of replenishment may be determined by the replenishment system in response to user input designating a particular method of replenishment.
In another step (e.g., a fifth step), supply parameters are determined for each store in which the article or group of articles is to be replenished. The supply parameters may include, for example minimum and maximum supply quantities of the article for each store, as well as the validity period of each article for each store. The validity period of each article may be, for example, a range of dates during which an article or group of articles will be displayed and offered for sale at each particular store. In one embodiment, the replenishment system determines the supply parameters for each store in which the article or group of articles to be replenished according to supply parameter data received from, for example, an assortment planning system or article master data management system. In another embodiment, the supply parameters for each store may be determined by the replenishment system in response to user input designating a particular store for each article.
In another step (e.g., a sixth step), a requirement quantity is determined for each article. The actual determination of the requirement quantity depends on the supply parameters as well as sales data for each article or group of articles. Sales data for each article may include, for example, actual sales data (e.g., actual sales and supply of the article) and projected sales data for each article. Actual sales data may be provided to the replenishment system from, for example, a best seller/slow seller management system. Projected sales data may be supplied to the replenishment system in the form of, for example, a markdown profile for a particular article.
In another step (e.g., a seventh step), the replenishment quantity determined for each article by the replenishment system is reconciled against an available budget and with actual store capacity for each article or group of articles to determine whether actual funds and capacity are available to support the replenishment quantity for each article. For example, in one embodiment, the replenishment system may receive one or more budget parameters and/or one or more capacity parameters in the form of merchandised or assortment planning data from an assortment planning system or another system. The replenishment system may then reconcile the replenishment quantity with the budget parameter and the actual capacity parameter.
In another step (e.g., an eighth step), a supply quantity for each article is determined.
In another step (e.g., a ninth step), order optimization is performed.
In another step (e.g., a tenth step), a purchase order is transferred to a central warehouse or vendor according to the determined supply channel or supply source.
In this way, supplies for articles or groups of articles may be efficiently and automatically replenished according to planning and sales data from various sources. The use of actual and projected sales data in the determination of the requirement quantity allows for early identification and automatic replenishment of increased quantities of articles that are selling at rates faster than originally anticipated, as well as decreased replenishment quantities for articles that are selling at rates slower than originally anticipated. The use of actual store capacities in determining the quantity of an item to be automatically replenished ensures that quantities of particular articles are not procured beyond the capacity of a particular store or group of stores.
As noted above, embodiments within the scope of the present invention include program products comprising computer-readable media for carrying or having computer-executable instructions or data structures stored thereon. Such computer-readable media can be any available media that can be accessed by a general purpose or special purpose computer. By way of example, such computer-readable media can comprise RAM, ROM, EPROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to carry or store desired program code in the form of computer-executable instructions or data structures and which can be accessed by a general purpose or special purpose computer. When information is transferred or provided over a network or another communications connection (either hardwired, wireless, or a combination of hardwired or wireless) to a computer, the computer properly views the connection as a computer-readable medium. Thus, any such connection is properly termed a computer-readable medium. Combinations of the above are also to be included within the scope of computer-readable media. Computer-executable instructions comprise, for example, instructions and data which cause a general purpose computer, special purpose computer, or special purpose processing device to perform a certain function or group of functions.
In some embodiments, the present invention is described in the general context of method steps, which may be implemented in one embodiment by a program product including computer-executable instructions, such as program code, executed by computers in networked environments. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. Computer-executable instructions, associated data structures, and program modules represent examples of program code for executing steps of the methods disclosed herein. The particular sequence of such executable instructions or associated data structures represents examples of corresponding acts for implementing the functions described in such steps.
The present invention in some embodiments, may be operated in a networked environment using logical connections to one or more remote computers having processors. Logical connections may include a local area network (LAN) and a wide area network (WAN) that are presented here by way of example and not limitation. Such networking environments are commonplace in office-wide or enterprise-wide computer networks, intranets and the Internet. Those skilled in the art will appreciate that such network computing environments will typically encompass many types of computer system configurations, including personal computers, hand-held devices, multi-processor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, and the like. The invention may also be practiced in distributed computing environments where tasks are performed by local and remote processing devices that are linked (either by hardwired links, wireless links, or by a combination of hardwired or wireless links) through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.
An exemplary system for implementing the overall system or portions of the invention might include a general purpose computing device in the form of a conventional computer, including a processing unit, a system memory, and a system bus that couples various system components including the system memory to the processing unit. The system memory may include read only memory (ROM) and random access memory (RAM). The computer may also include a magnetic hard disk drive for reading from and writing to a magnetic hard disk, a magnetic disk drive for reading from or writing to a removable magnetic disk, and an optical disk drive for reading from or writing to removable optical disk such as a CD-ROM or other optical media. The drives and their associated computer-readable media provide nonvolatile storage of computer-executable instructions, data structures, program modules and other data for the computer.
Software and web implementations of the present invention could be accomplished with standard programming techniques with rule based logic and other logic to accomplish the various database searching steps, correlation steps, comparison steps and decision steps. It should also be noted that the word “component” as used herein and in the claims is intended to encompass implementations using one or more lines of software code, and/or hardware implementations, and/or equipment for receiving manual inputs.
It is important to note that the above-described preferred and alternative embodiments of the present invention are illustrative only. Although the invention has been described in conjunction with specific embodiments thereof, those skilled in the art will appreciate that numerous modifications are possible without materially departing from the novel teachings and advantages of the subject matter described herein. For example, although the stores in
This application claims the benefit of U.S. Provisional Application No. 60/551,221, filed Mar. 8, 2004 and entitled “Inventory Management,” and U.S. Provisional Application No. 60/563,284, filed Apr. 16, 2004 and entitled “Inventory Management,” both of which are hereby incorporated by reference.
Number | Name | Date | Kind |
---|---|---|---|
4752877 | Roberts et al. | Jun 1988 | A |
5015190 | Fowlkes, Jr. | May 1991 | A |
5315508 | Bain et al. | May 1994 | A |
5400253 | O'Connor | Mar 1995 | A |
5450317 | Lu et al. | Sep 1995 | A |
5615109 | Eder | Mar 1997 | A |
5758327 | Gardner et al. | May 1998 | A |
5832456 | Fox et al. | Nov 1998 | A |
5870716 | Sugiyama et al. | Feb 1999 | A |
5930771 | Stapp | Jul 1999 | A |
5953707 | Huang et al. | Sep 1999 | A |
5999914 | Blinn et al. | Dec 1999 | A |
6006196 | Feigin et al. | Dec 1999 | A |
6009407 | Garg | Dec 1999 | A |
6029139 | Cunningham et al. | Feb 2000 | A |
6064984 | Ferguson et al. | May 2000 | A |
6078891 | Riordan et al. | Jun 2000 | A |
6151582 | Huang et al. | Nov 2000 | A |
6167380 | Kennedy et al. | Dec 2000 | A |
6260024 | Shkedy | Jul 2001 | B1 |
6341351 | Muralidhran et al. | Jan 2002 | B1 |
6366890 | Usrey | Apr 2002 | B1 |
6493678 | Foster et al. | Dec 2002 | B1 |
6505093 | Thatcher et al. | Jan 2003 | B1 |
6507851 | Fujiwara et al. | Jan 2003 | B1 |
6510420 | Cessna et al. | Jan 2003 | B1 |
6578009 | Shinozaki | Jun 2003 | B1 |
6584447 | Fox et al. | Jun 2003 | B1 |
6597379 | Morris et al. | Jul 2003 | B1 |
6701299 | Kraisser et al. | Mar 2004 | B2 |
6711550 | Lewis et al. | Mar 2004 | B1 |
6725204 | Gusley | Apr 2004 | B1 |
6868528 | Roberts | Mar 2005 | B2 |
6910017 | Woo et al. | Jun 2005 | B1 |
6954736 | Menninger et al. | Oct 2005 | B2 |
6980966 | Sobrado et al. | Dec 2005 | B1 |
7006981 | Rose et al. | Feb 2006 | B2 |
7069232 | Fox et al. | Jun 2006 | B1 |
7080026 | Singh et al. | Jul 2006 | B2 |
7080030 | Eglen et al. | Jul 2006 | B2 |
7082408 | Baumann et al. | Jul 2006 | B1 |
7092896 | Delurgio et al. | Aug 2006 | B2 |
7092929 | Dvorak et al. | Aug 2006 | B1 |
7103560 | Fox et al. | Sep 2006 | B1 |
7117165 | Adams et al. | Oct 2006 | B1 |
7124098 | Hopson et al. | Oct 2006 | B2 |
7124984 | Yokouchi et al. | Oct 2006 | B2 |
7130811 | Delurgio et al. | Oct 2006 | B1 |
7137566 | Silverbrook et al. | Nov 2006 | B2 |
7139731 | Alvin | Nov 2006 | B1 |
7155402 | Dvorak | Dec 2006 | B1 |
7171376 | Ramakrishnan | Jan 2007 | B2 |
7197474 | Kitts | Mar 2007 | B1 |
7213037 | Rangadass | May 2007 | B2 |
7257544 | Rose et al. | Aug 2007 | B2 |
7310646 | Rangadass et al. | Dec 2007 | B2 |
7353195 | Inoue et al. | Apr 2008 | B2 |
7370364 | Dobbins et al. | May 2008 | B2 |
7386492 | Ginsburg et al. | Jun 2008 | B2 |
7386519 | Delurgio et al. | Jun 2008 | B1 |
7467098 | Razumov | Dec 2008 | B2 |
7523048 | Dvorak | Apr 2009 | B1 |
7552066 | Landvater | Jun 2009 | B1 |
7689460 | Natori et al. | Mar 2010 | B2 |
20010019778 | Gardaz et al. | Sep 2001 | A1 |
20010032130 | Gabos et al. | Oct 2001 | A1 |
20010039517 | Kawakatsu | Nov 2001 | A1 |
20010047293 | Waller et al. | Nov 2001 | A1 |
20010049634 | Stewart | Dec 2001 | A1 |
20020013731 | Bright et al. | Jan 2002 | A1 |
20020023500 | Chikuan et al. | Feb 2002 | A1 |
20020026296 | Lohmann et al. | Feb 2002 | A1 |
20020026368 | Carter, III | Feb 2002 | A1 |
20020035537 | Waller et al. | Mar 2002 | A1 |
20020042755 | Kumar et al. | Apr 2002 | A1 |
20020059108 | Okura et al. | May 2002 | A1 |
20020059122 | Inoue et al. | May 2002 | A1 |
20020066033 | Dobbins et al. | May 2002 | A1 |
20020072986 | Aram | Jun 2002 | A1 |
20020073114 | Nicastro et al. | Jun 2002 | A1 |
20020078159 | Petrogiannis et al. | Jun 2002 | A1 |
20020087532 | Barritz et al. | Jul 2002 | A1 |
20020099597 | Gamage et al. | Jul 2002 | A1 |
20020099678 | Albright et al. | Jul 2002 | A1 |
20020107713 | Hawkins | Aug 2002 | A1 |
20020116241 | Sandhu et al. | Aug 2002 | A1 |
20020120459 | Dick et al. | Aug 2002 | A1 |
20020120533 | Wiesenmaier | Aug 2002 | A1 |
20020123930 | Boyd et al. | Sep 2002 | A1 |
20020124109 | Brown | Sep 2002 | A1 |
20020133385 | Fox et al. | Sep 2002 | A1 |
20020138290 | Metcalfe et al. | Sep 2002 | A1 |
20020147630 | Rose et al. | Oct 2002 | A1 |
20020147668 | Smith et al. | Oct 2002 | A1 |
20020152128 | Walch et al. | Oct 2002 | A1 |
20020165834 | Delurgio et al. | Nov 2002 | A1 |
20020184116 | Tam et al. | Dec 2002 | A1 |
20030018513 | Hoffman et al. | Jan 2003 | A1 |
20030023500 | Boies et al. | Jan 2003 | A1 |
20030028393 | Coulston et al. | Feb 2003 | A1 |
20030028437 | Grant et al. | Feb 2003 | A1 |
20030046120 | Hoffman et al. | Mar 2003 | A1 |
20030046195 | Mao | Mar 2003 | A1 |
20030050852 | Liao et al. | Mar 2003 | A1 |
20030050869 | Bruynsteen | Mar 2003 | A1 |
20030061081 | Kellond et al. | Mar 2003 | A1 |
20030074269 | Viswanath | Apr 2003 | A1 |
20030083925 | Weaver et al. | May 2003 | A1 |
20030110052 | Capazario et al. | Jun 2003 | A1 |
20030126024 | Crampton et al. | Jul 2003 | A1 |
20030130883 | Schroeder et al. | Jul 2003 | A1 |
20030130905 | Foster et al. | Jul 2003 | A1 |
20030144916 | Mumm et al. | Jul 2003 | A1 |
20030149631 | Crampton et al. | Aug 2003 | A1 |
20030149674 | Good et al. | Aug 2003 | A1 |
20030154141 | Capazario et al. | Aug 2003 | A1 |
20030158791 | Gilberto et al. | Aug 2003 | A1 |
20030171978 | Jenkins et al. | Sep 2003 | A1 |
20030171979 | Jenkins | Sep 2003 | A1 |
20030171998 | Pujar et al. | Sep 2003 | A1 |
20030172007 | Helmolt et al. | Sep 2003 | A1 |
20030187665 | Boyd | Oct 2003 | A1 |
20030195791 | Waller et al. | Oct 2003 | A1 |
20030195810 | Raghupathy et al. | Oct 2003 | A1 |
20030200129 | Klaubauf et al. | Oct 2003 | A1 |
20030200148 | Razumov | Oct 2003 | A1 |
20030200150 | Westcott et al. | Oct 2003 | A1 |
20030208365 | Avery et al. | Nov 2003 | A1 |
20030216969 | Bauer et al. | Nov 2003 | A1 |
20030229502 | Woo | Dec 2003 | A1 |
20040002912 | Colon et al. | Jan 2004 | A1 |
20040010463 | Hahn-Carlson et al. | Jan 2004 | A1 |
20040098358 | Roediger | May 2004 | A1 |
20040122689 | Dailey et al. | Jun 2004 | A1 |
20040162763 | Hoskin et al. | Aug 2004 | A1 |
20040172321 | Vemula et al. | Sep 2004 | A1 |
20040177075 | Rangadass | Sep 2004 | A1 |
20040186765 | Kataoka | Sep 2004 | A1 |
20040186783 | Knight et al. | Sep 2004 | A1 |
20040210489 | Jackson et al. | Oct 2004 | A1 |
20040215662 | Rangadass | Oct 2004 | A1 |
20040220861 | Morciniec et al. | Nov 2004 | A1 |
20040254950 | Musgrove et al. | Dec 2004 | A1 |
20040267674 | Feng et al. | Dec 2004 | A1 |
20040267676 | Feng et al. | Dec 2004 | A1 |
20050004831 | Najmi et al. | Jan 2005 | A1 |
20050015303 | Dubin et al. | Jan 2005 | A1 |
20050021541 | Rangadass et al. | Jan 2005 | A1 |
20050055283 | Zarovinsky | Mar 2005 | A1 |
20050060270 | Ramakrishnan | Mar 2005 | A1 |
20050075915 | Clarkson | Apr 2005 | A1 |
20050075941 | Jetter et al. | Apr 2005 | A1 |
20050086122 | Cirulli et al. | Apr 2005 | A1 |
20050086125 | Cirulli et al. | Apr 2005 | A1 |
20050096122 | Nireki et al. | May 2005 | A1 |
20050096963 | Myr et al. | May 2005 | A1 |
20050102175 | Dudat et al. | May 2005 | A1 |
20050102192 | Gerrits et al. | May 2005 | A1 |
20050102227 | Solonchev | May 2005 | A1 |
20050165659 | Gruber | Jul 2005 | A1 |
20050171825 | Denton et al. | Aug 2005 | A1 |
20050189414 | Fano et al. | Sep 2005 | A1 |
20050197849 | Fotteler et al. | Sep 2005 | A1 |
20050197850 | Fotteler et al. | Sep 2005 | A1 |
20050197872 | Fotteler et al. | Sep 2005 | A1 |
20050197878 | Fotteler et al. | Sep 2005 | A1 |
20050197881 | Fotteler et al. | Sep 2005 | A1 |
20050197882 | Fotteler et al. | Sep 2005 | A1 |
20050197887 | Zuerl et al. | Sep 2005 | A1 |
20050197928 | Fotteler et al. | Sep 2005 | A1 |
20050205670 | Natori et al. | Sep 2005 | A1 |
20050209900 | Kettner et al. | Sep 2005 | A1 |
20050216371 | Fotteler et al. | Sep 2005 | A1 |
20050234762 | Pinto et al. | Oct 2005 | A1 |
20050235020 | Gabelmann et al. | Oct 2005 | A1 |
20050240469 | Rose et al. | Oct 2005 | A1 |
20060015415 | Najmi | Jan 2006 | A1 |
20060020512 | Lucas et al. | Jan 2006 | A1 |
20060036507 | Pujar et al. | Feb 2006 | A1 |
20060112099 | Musgrove et al. | May 2006 | A1 |
20060149634 | Pelegrin et al. | Jul 2006 | A1 |
20060265287 | Kubo | Nov 2006 | A1 |
20070027745 | Ouimet | Feb 2007 | A1 |
20070050272 | Godlewski et al. | Mar 2007 | A1 |
20070177211 | Eller et al. | Aug 2007 | A1 |
20080120206 | Weiler et al. | May 2008 | A1 |
20080319857 | Dobbins et al. | Dec 2008 | A1 |
20090099879 | Ouimet | Apr 2009 | A1 |
20090271245 | Joshi et al. | Oct 2009 | A1 |
20100320109 | Trumbauer et al. | Dec 2010 | A1 |
Number | Date | Country |
---|---|---|
2004-030343 | Jan 2004 | JP |
WO 9945450 | Sep 1999 | WO |
WO 0171635 | Sep 2001 | WO |
Number | Date | Country | |
---|---|---|---|
20050197872 A1 | Sep 2005 | US |
Number | Date | Country | |
---|---|---|---|
60551221 | Mar 2004 | US | |
60563284 | Apr 2004 | US |