The technology described in this patent document relates generally to a markdown optimization, and more specifically to computer-implemented systems and methods for optimizing a clearance plan for an item or items for sale.
One of the largest business problems that retailers face is how to liquidate inventory during the clearance period while maximizing profit yet still following certain business rules and limitations. In retail practice this problem is referred to as markdown optimization. The goal of markdown optimization is to determine which products to mark down, how much to mark them down, when to mark them down, and in which markets or stores. These recommendations can be based on factors such as inventory levels, base sales volume, price elasticity, local preferences, and local demand. Such a series of price decreases devised for a particular item or set of items are typically called a price schedule and are used by retailers to guide them in decreasing or eliminating inventory during the clearance period.
In accordance with the teachings herein, computer-implemented systems and methods are provided for markdown optimization. For example, a system and method can be configured to identify for an item an optimal markdown plan containing a markdown price for the item. Also, the method and system can be configured to identify for an item an optimal delay plan. For an item, a delay cost and a markdown spend are calculated, and a comparison is performed of the item's delay cost with respect to the item's markdown spend. The comparison is used to determine whether to mark down an item based upon the item's determined markdown price.
As another example, a system and method can be configured to identify markdown prices for items offered by a first entity. This includes identifying for each item an optimal markdown plan containing a markdown price for the item, with the optimal markdown plan being optimal with respect to one or more user-specified objectives. Also, for each item an optimal delay plan is identified, with the optimal delay plan being optimal with respect to the user-specified objectives and also satisfy an additional constraint of delaying a first markdown until a subsequent budget period. For each item, a delay cost and a markdown spend are calculated, and a comparison of the item's delay cost is performed with respect to the item's markdown spend. The comparison is to be used by a second entity to determine whether to mark down an item based upon the item's determined markdown price.
Based upon the input by the users 32, the markdown optimization system 34 establishes weekly prices (or prices at some other time interval) in the clearance period so as to maximize expected revenue for one or more items (e.g., products for sale). Within the system 34, pricing can be done at any level of an item hierarchy and at any level of a product location hierarchy.
The users 32 may interact with a markdown optimization system 34 in a number of ways, such as over one or more networks 36. Server(s) 38 accessible through the network(s) 36 may host the markdown optimization system 34. One or more data stores 40 can store the data to be analyzed by the markdown optimization system 34 as well as any intermediate data or markdown plans generated by the system 34.
The delay constraint 60 that can be used when creating a markdown plan allows for further optimization of the markdown plan's effectiveness in satisfying the business objectives of an organization. The optimal markdown plan identified at 58 is modified to take into account the delay constraint 60. The system additionally makes use of the user-specified objectives (e.g., business rules) when modifying the markdown plan to include the delay constraint 60. The system uses these inputs to identify the optimal delay plan at 66. The delay plan refers to the modified markdown plan that results from the markdown optimization system integrating the delay constraint into the markdown planning.
The markdown optimization system compares the optimal markdown plan and the optimal delay plan to determine the delay cost. The delay cost is the expected opportunity loss between the optimal markdown plan and the optimal delay plan. For instance, the delay cost could be expressed as the difference in the revenue expected to be generated under the optimal markdown plan and the revenue expected to be generated under the optimal delay plan. The delay cost is used to express the objective value difference between the two plans.
The markdown optimization system compares the delay cost with the markdown spend, as shown at 68. Markdown spend refers to the reduction in value of the inventory on hand at the beginning of the markdown period due to the planned markdown. In other words, if a markdown of 25% is planned for an item that normally would retail for $89.99 and there are 210 units on hand at the beginning of the markdown period, then the markdown spend would be represented by the equation:
Markdown Spend=210*(25%*$89.99)=$4,724.48
where the amount $4724.48 in this example equals the revenue that can no longer be realized on the inventory on hand once the markdown is put in place.
The markdown optimization system uses the markdown spend figure to compute a ratio of delay cost to markdown spend for a given item. The items analyzed are sorted based on this ratio, in decreasing order. The ratio then is used to determine whether a given markdown should be put in place for the period studied. For example, an organization may impose a budget constraint on markdown spend for a given period. The items, having already been ranked based on the ratio of delay cost to markdown spend, will be chosen based on the markdown spend that is calculated for each. Thus, for example, if the organization imposing a budget on markdown spend set the budget at $5,000, and the item listed in the above example had the highest ratio of delay cost to markdown spend of the items analyzed, then the item would be chosen to be marked down, since the markdown spend figure is below the budget for the period. Alternatively, if the budget for the period were $4,000, then the item listed above would not be chosen, even if it did have the highest ratio of delay cost to markdown spend. Instead, the markdown optimization system would look at the markdown spend figure of the item with the second-highest ratio or give a partial markdown for the current item depending on the business preferences.
It also is possible that more than one item might be chosen to be marked down. For example, if the markdown budget for the period in the above example had been $10,000, then the item above, if it had the highest ratio of delay cost to markdown spend, would be chosen for inclusion. There would be a significant portion remaining of the markdown budget for the period, though, so the markdown optimization system would examine the markdown spend figure of the item with the second-highest ratio of delay cost to markdown spend. If the markdown spend figure for the item with the second-highest ratio is less than or equal to $5,275.52 (which is $10,000 less the $4,724.48 markdown spent on the item with the highest ratio), then that item also would be chosen for a markdown. If not, the markdown optimization system would continue to examine the markdown spend figures of the items in the list until either the entire markdown budget for the period had been allocated or there were no more items in the list.
Items that are chosen to be marked down in a given period have their markdown prices included in the price schedule 70. The price schedule 70 is used to set the prices for the items analyzed.
The location hierarchy 86 includes information that is intended to better represent the way in which organizations structure their operations. For example, the entire organization could constitute the top level of the hierarchy, while the next level could be defined by region, country, or state. Further, within that level, there could be further sub-levels. For example, if the first level is the organization and the second level is a country (e.g., the United States), then the third level could be each of the 50 states or a region within the United States, such as the Northeast or Midwest. At the bottom level of the hierarchy would be the individual establishments that make up the organization.
When the item hierarchy and the location hierarchy are combined, the resulting set of item data can be very large. This problem is a very difficult optimization problem and it often is impossible to solve if the product and/or location scopes are large, which is very typical for a large retailer, for instance. For this reason, a two-step optimization algorithm is applied. First, using as inputs the business rules 54 and the user-specified objectives 56, the markdown optimization system identifies the optimal markdown plan at 58. Business rules may include, for example, limits on discount amounts, limits on the frequency of discounts, and limits on the dates of discounts. The optimal markdown plan is devised by the markdown optimization system to satisfy the business rules 54 and the user-specified objectives 56, but it is generated without regard to any budget constraint for the markdowns. The budget constraint is ignored and weekly optimal prices are calculated for each product/location pair i independently.
For solving the markdown problem, it is noted that the goal of markdown optimization is to find weekly optimal prices, called a price schedule, for combinations of a product and a location, each called a product/location pair, in order to maximize expected revenue. Expected revenue from a group of product/location pairs in the clearance period can be mathematically represented as:
where:
N=number of product/locations to be priced
T=number of weeks in the clearance period
pi,t=price of product/location pair i in week t
si,t=expected sales units of product/location pair i in week t at price pi,t
The expected sales for a product/location pair in a given week depend on the available inventory and forecasted demand for that week. Forecasted demand depends on base forecast (forecast without any price reduction), price, and how elastic the demand of the product at that location is. This relationship can be mathematically represented by the equation
where
Ii,t=inventory of product/location pair i at the beginning of week t
pi,0=list price of product/location pair i
βi=price response coefficient of product/location pair i
αi,t=base forecast at list price for product/location pair i in week t
In the above forecast demand equation, a typical log-linear demand model is assumed, but other demand models may be used as well. Weekly prices of each product/location pair (pi,1, pi,2, . . . pi,T) follow business rules. Some examples of these business rules include: weekly prices must be non-increasing; weekly prices are to be chosen from a given set of admissible price points; limits on frequency of price changes (e.g., maximum number of price changes can be taken, minimum weeks between two consecutive markdowns); and, limits on dates of price changes (e.g., pre-determined dates that cannot take markdowns, dates by which a markdown must have been taken).
Now let Ri be the expected optimal revenue obtained by solving the problem for product/location pair i, and consider the optimization problem with an additional constraint that no price change can be given in week 1 (in other words, pi,1=pi,0). Let the optimal expected revenue of the second problem be Ri′.
Mathematically it is evident that Ri≧Ri′ and the difference di=Ri−Ri′ is the cost of delaying a price change in week 1. This difference will be zero if there was no price change recommended in week 1 in the original optimization problem because the additional “no price change in the first week” constraint will be redundant in the second problem and hence the expected revenues Ri and Ri′ will be the same. In the other cases the difference will be positive and is a measure of how important it is to give the price change in the first week. Economically speaking, if one delays a price change that was recommended in week 1 then one is expected to lose di. In other words d1 is the additional expected revenue if the price change for product/location i is not delayed.
The optimization in its simplest form can be described as, given a clearance horizon of T periods, choosing prices p1, p2, . . . , pT from {P1, P2, . . . , PK} such that the revenue derived is maximized and the business rules are met. Expressed mathematically, this would take the form:
where:
where:
As the first step of the two-step optimization algorithm does not consider any budget constraints for the markdowns, the second step of the two-step optimization algorithm is to choose the markdowns to be implemented in such a way as to satisfy a budget constraint imposed on the markdown plan. Thus, the second step 66 of the algorithm identifies the optimal delay plan, which involves including the delay constraint 60 in the optimization modeling done by the markdown optimization system. As with the optimal markdown plan identified at 58, the optimal delay plan satisfies business rules and user-specified objectives, in addition to satisfying the delay constraint 60. Once the optimal delay plan is identified, the markdown optimization system, at 68, compares the delay cost with the markdown spend budgeted for the period of the analysis. This allows the markdown optimization system to rank the optimized markdowns against one another to produce a sorted list. The sorted list is used to choose the most beneficial markdowns that may be implemented within the constraints of the markdown spend budgeted for the period. The markdown optimization system then includes the chosen markdowns in the price schedule 70 it outputs, which will be used to set the prices for the items analyzed by the markdown optimization system.
If at 132 the method determines that the IVR of the current plan is not less than the IVR of the optimal plan, or after the optimal plan has been updated at 134, the method determines at 136 if the current price plan also is a delay plan. If the current price plan is also a delay plan, then the method will determine at 138 whether the current price plan is better than the best delay plan. If the current price plan is better than the best delay plan, then the method updates the best delay plan with the current price plan at 140.
If at 136 the method determines that the current plan is not a delay plan, and if the current plan is not determined to be better than the best delay plan at 138, the method determines at 142 if there are other feasible plans (after the best delay plan is updated at 140). If there are other feasible plans, the method generates at 144 the next feasible plan, which the method sets as the current plan 146. The method then returns to evaluate the current plan at 126, and then reiterates the steps after that point. If the method determines at 148 that there are no other feasible plans, then the method outputs the optimal plan and the best delay plan, as depicted at 148 and the method then ends at 150.
It should be understood that, similar to the other processing flows described herein, one or more of the steps and the order in the flowchart may be altered, deleted, modified and/or augmented and still achieve the desired outcome. For example,
After the above optimization problems are solved and the delay costs (di's) are calculated, the markdown optimization system then decides which price changes should be delayed to the next week. This decision depends on the value of di's as well as how much markdown spend each product/location pair i consumes in week 1, which are represented by the term bi. This is an optimization problem called a knapsack problem in the operations research literature. From the perspective of computational complexity, the knapsack problem is an NP-hard problem. Mathematically the problem can be formulated as
where xi are binary decision variables representing if product/location pair i's price change should be approved or delayed. In other words, if xi=1 then the price change for product/location i will be approved for week 1 and if xi=0 then it will be delayed until next week. Finding the optimal solution to the knapsack problem is not trivial. A slightly different version of this problem is solved where the constraint xiε{0, 1} is replaced (relaxed) by 0≦xi≦1. Here, xi can take any number between 0 and 1 (inclusive). When applied to the markdown optimization problem, the use of the relaxed value set corresponds to partial approval of a markdown. For example, if xi is 0.7, that means approve the price change with 70% of the optimized markdown. For example, if the current price is 30 and the markdown price is 20 dollars then the approved markdown will be 0.7×(30−20)=7 dollars and the clearance price will be 30−7=23 dollars.
Note that this relaxation assumes that di is linear with the price discount which is not true, however it is a very good approximation. The use of the relaxed value set allows the generation of the optimal solution to be trivial. For each product/location pair i, the system takes the ratio di/bi and sorts the resulting ratios from largest to the smallest, picking markdowns in this order until the budget is filled completely.
At 214, the interface shows the output of the method described above with respect to
Additional details regarding the results of the analysis are displayed in the interface at 216. For each product, the ending inventory predicted by the modeling process is displayed, under both the optimal plan and the best delay plan. The method also generates a predicted amount of total revenue that the organization would derive from sales of each product during the period of the analysis. The difference between the total revenue generated for a product under the optimal plan and the total revenue generated for that product under the best delay plan is referred to as the delay cost for that product. The markdown spend in the first week of the optimal plan also is displayed by the interface. The markdown spend refers to the change in the retail value of the inventory based on the markdown in the first week of the analytical period compared to the value of that inventory under the delay plan. The delay cost is then divided by the markdown spend to produce the ratio that will be used by the markdown optimization system to determine the relative merits of the price schedules for the various products. Finally, the interface depicts at 216 the inventory value at risk (IVR), both with and without pooling. Inventory pooling refers to the ability of a user to define sub-groups among locations within which inventory risk can be pooled where one or more products have common pricing strategies in more than one location. This allows the system to model an aggregated inventory target for locations in the same subgroup, thereby replacing the requirement that locations meet inventory targets individually. Because this is a less restrictive manner of modeling, a better optimal plan may be achieved.
Within the example graphical interface, a user will enter details about the new clearance plan. The first phase of defining a new plan involves specifying a plan type and plan goals. Next, the user enters settings that pertain to plan dates and pricing options. After entering these details, the user indicates what he or she would like to do next with the new clearance plan.
Plan Type and Goals
The clearance plan type and plan goals are entered by the user in the Choose a Markdown Plan type and goals section of the Create Plan dialog box, according to the following steps:
1. The user selects the plan type—optimized, manual, or baseline—from the drop-down list.
2. If the user is creating an optimized plan, he or she enters a primary plan goal from the Primary goal drop-down list. The user can select to maximize revenue and margin, to maximize net revenue and net margin, or to minimize inventory at risk.
3. If the user selected Minimize Inventory at Risk as the primary plan goal, he or she select a secondary plan goal from the Secondary goal drop-down list. The user can select to maximize revenue and margin or to maximize net revenue and net margin.
4. If the user is creating an optimized or a manual plan, he or she enters a target inventory level to reach by the end of the plan. This is the value that is used to determine the amount of inventory that exceeds plan goals, or at-risk inventory. The user enters a numeric value in the first box, then selects % or Units from the drop-down list to specify whether the number represents a percentage of the beginning inventory level or a number of inventory units. When a user indicates a number of units, this refers to the total number of units of inventory for each product multiplied by the number of locations that are included in the plan.
Note that the net revenue goal is available only when at least one of the following metrics is greater than zero: cost of capital rate, markdown cost, or markdown unit cost. Also, when a secondary goal is entered for an optimized plan, the system optimizes so that the following conditions are met: the primary goal is attained and, for outcomes where the primary goal is attained, the secondary plan goal is maximized.
Plan Dates and Pricing Options
The user also enters details that pertain to dates and pricing options in the Set plan details section of the Create Plan dialog box:
1. The user enters the start and end dates for the clearance plan in the Start date and End date boxes, respectively. The default length of a plan is 16 plan periods.
2. For an optimized or a manual plan, the user enters the dates on which markdowns are allowed. The user may indicate that markdowns can occur on all available markdown dates during the clearance plan by selecting All dates allowed. Also, the user may indicate that markdowns can be made only on a subset of markdown dates by selecting Select dates. The Select Date dialog box appears.
3. For an optimized or a manual plan, the user enters the desired unit salvage value percentage in the Unit salvage value for end date box. This value is used to calculate the margin that is generated by a plan. Valid entries are greater than or equal to 0 and less than 100. Note that discounted prices must fall between the salvage value and the last regular price of a product.
4. To set prices for each product to the same value at all locations in an optimized plan, the user selects Activated from the Uniform price or discount schedule dropdown list. To leave this feature inactive, the user selects Not activated. Note that when the user selects this option for products with different initial prices, new prices must be based on a discount percentage grid rather than a grid of actual prices.
5. To force at least one markdown for each product in an optimized plan, the user may select Activated from the Force at least one markdown drop-down list. To leave this feature inactive, the user selects Not activated.
Next Step Selection
To complete the new plan definition, the user indicates what to do next with the plan in the Select next step section of the Create Plan dialog box. The options that are available depend on the type of plan that the user creates.
For an optimized plan, the user can save the plan by selecting Save and run optimization. First, the user specifies from the drop-down list when he or she wants the plan to be optimized, choosing from the options: Now, Overnight, After next data load, and Later (i.e., upon request). Second, the user can set the optimized plan to become the active plan by selecting Make optimized solution the Active Plan. If the user selects this option, he or she can also activate these options: pre-approve first markdown for plan, which automatically sets the status for the first set of markdowns to approved and automatically optimize plan with new data, which optimizes a plan each time that new data is added to the system. For an optimized or a manual plan, the user can view the Plan Details window immediately by selecting Open Markdown Plan Details page. The Plan Details window opens when the user closes the Create Plan dialog box.
For a baseline plan, the Save and run evaluation option is selected automatically. The user specifies from the drop-down box when he or she wants the plan to be evaluated, choosing from the options: Now, Overnight, After next data load, and Later (i.e., upon request). Next, the user can set the evaluated plan to become the active plan by selecting Make evaluated solution the Active Plan. If the user selects this option, he or she can also activate these options: pre-approve first markdown for plan, which automatically sets the status for the first set of markdowns to approved and automatically evaluate plan with new data, which evaluates a plan each time that new data is added to the system.
When the user has completed his or her entries in the Create Plan dialog box, he or she clicks OK to create the plan. If the user selected Open Markdown Plan Details page in the Select next step section, then the Plan Details window appears. Alternatively, the user may click Cancel to cancel the creation of the plan.
Within the Plan Details window, there are two tabs—the Active Plan tab and the Alternative Plan tab. These tabs may be considered to be displaying two versions of a clearance plan. The Active Plan tab displays the version of a plan that is ready for execution or that is currently being implemented. The Alternative Plan tab displays the version of the plan with any alternative settings that the user might have made. The alternative version of a plan functions as a workspace for that plan, enabling the user to review potential changes before committing to them. If the user decides that an alternative plan is preferable to an active plan, then he or she can select to make that version of the plan the active plan.
The user can perform the following tasks on the Active Plan tab:
The user can perform the following tasks on the Alternative Plan tab:
The Typical Work Flow for Clearance Plans
After a clearance plan has been created, and even while a plan is in progress, the user can review and modify the details for that plan. At this point, the products, locations, and time frame for a clearance plan have been defined. Now the user can focus on the price schedule for a clearance plan. While the types of merchandise and locations included can vary widely between clearance plans, there is a basic work flow that the user usually will follow when working with a clearance plan. In general, the user completes the following steps when he or she works with a new clearance plan in the system:
1. Open the Plan Details window. The user can modify most settings for a clearance plan in this window.
2. Set a price schedule for the products that are included in a plan on the Alternative Plan tab in the Plan Details window. The type of clearance plan dictates how the user controls pricing for products that are in a clearance plan:
3. The user then reviews the performance of the alternative plan. Depending on the results, the user may repeat Steps 2 and 3 until he or she is satisfied with the settings for the alternative plan.
4. If the user decides that the alternative plan is preferable to the active plan, replace the active plan with the alternative plan.
5. The user approves tentative price changes on the Active Plan tab so that price changes can be implemented. The user may approve a subset of pending price changes, or he or she can approve all pending price changes.
6. For an ongoing plan, the user can perform these tasks:
Note that the tasks in this last step are repeated periodically over the duration of a clearance plan.
When a user creates a clearance plan, he or she might select some settings that perform one or more of the above steps automatically. For example, if the user selects the Open Markdown Plan Details page option when he or she creates a plan, he or she then begins to work with a plan in Step 2. If the user selects the Make optimized solution the Active Plan option, then he or she begin to work with a clearance plan in Step 6.
Open the Plan Details Window
To work with a clearance plan, the user needs to view the plan in a Plan Details window. If the user selected Open Markdown Plan Details page during plan creation, then this window appears automatically. To view the Plan Details window for a group plan, the user completes the following steps:
1. If necessary, the user opens the Markdown Groups window by selecting Markdown Groups from the View menu.
2. The user selects the group name for the plan that he or she wants to view.
3. By pressing ENTER or selecting Open Group Plan from the Menu drop-down list that is located in the top-right corner of the Markdown Groups window, the user may access the Plan Details window for this group.
Note that the user can also double-click the group name in the list to open the Plan Details window.
Alternatively, to view the Plan Details window from a product list window, the user may complete the following steps:
1. Display the list of products that are included in a clearance plan by selecting the correct product list view. If the user has not yet activated a plan, then he or she selects Inactive Plans from the Show drop-down list. If the user has activated a plan, then he or she selects Active Plans from the Show drop-down list.
2. Select one or more of the products that are in the desired clearance plan.
3. Open the Plan Details window by pressing ENTER or by selecting Open Plan from the Menu drop-down list that is located in the top-right corner of the product list window.
The top of the Plan Details window displays information about the plan, including group name and description, number of products in the plan, number of product-location combinations, number of days on active clearance, and the date that the plan was last modified. There are two sections at the top of the Active Plan and Alternative Plan tabs. The user can view summary information about a plan and make changes to plan settings in these sections.
The Dates and Inventory Units section displays the following items about a plan:
The Optimization/Evaluation section displays settings for plan optimization or evaluation. The user can use this section to change the settings for a plan, if desired. The Optimization/Evaluation section displays these items about a plan: plan status (the status of the plan for the currently displayed plan tab), date that the status occurred, plan type, plan goal(s), unit salvage value percentage, target inventory level, the setting of the “Force at least one markdown” option, and a message area that indicates optimization or evaluation errors, as well as when there is new data in the system.
Setting a Price Schedule for an Alternative Plan
The list of scheduled markdowns for a clearance plan is displayed in the Price Schedule section in the Plan Details window. The user can expand this section by clicking the right arrow to the left of the Price Schedule label. For a new plan, the user works on the Alternative Plan tab to create a preliminary price schedule. For an existing plan, the user modifies the price schedule by using the Alternative Plan tab. The steps to create a preliminary price schedule or to modify an existing price schedule depend on the type of clearance plan the user is working with—optimized or manual. Each column in the Price Schedule table represents a plan period in the clearance plan. Each row provides information about price changes for a clearance plan. For plans with more than one product, the cells in this table might be displayed as a range.
Metrics Displayed in the Price Schedule Table
Setting the Price Rules
The Price Rules tab of the Plan Rules dialog box controls settings for the logistics of markdowns in a plan. The user can enter values for the following settings:
Selecting the List of Possible Markdowns
The user may use the Price Points, Percentage Discount, or Percentage Off with Price Endings tab to select the pricing grid that the system uses for optimization. Each tab displays available markdowns in a different format:
Optimizing a Plan
When the user works with an optimized plan, he or she enables the system to calculate an optimal set of price changes. The resulting price schedule is selected so that plan goals are met while adhering to the existing business constraints. To optimize an alternative plan, the user selects Optimize and the appropriate time from the Menu drop-down list that is located in the top-right corner of the Plan Details window. He or she chooses whether to optimize a plan now, overnight, or after the next data load. If the user selects Optimize→Now, a dialog box appears to let him or her know that calculations are in progress.
When optimization is complete, the following actions occur:
Editing a Price Schedule Manually
To edit the price schedule manually, a user completes the following steps:
1. The user clicks in the cell that he or she wants to edit and enters a value.
2. If a value that the user enters is not within the pricing rules for a plan, the user receives a warning and enters a new value for the cell.
If there are products that have subproducts, such as a box of tiles that can be sold by the box or as individual tiles, the user also can set prices for those subproducts. By default, a subproduct has the same discount percentage as the product that it is associated with. The user sets alternative prices for subproducts in the Price Changes view of the product list.
Resetting a Plan
If the user decides to reset the alternative plan settings, he or she selects Reset Plan from the Menu drop-down list that is located in the top-right corner of the Plan Details window. The Reset Plan dialog box appears.
Evaluating a Plan
After entering price changes for a plan, the user evaluates the plan against the goals that he or she specified during plan creation. To evaluate an alternative plan, the user selects Evaluate from the Menu drop-down list that is located in the top-right corner of the Plan Details window. A dialog box appears to let the user know that calculations are in progress. When evaluation is complete, the following actions occur:
The table below lists errors that may occur during evaluation:
The user can modify the rules for a plan by using the Plan Rules dialog box. Select Plan Rules from the Menu drop-down list that is located in the top-right corner of the plan window.
Reviewing the Performance of a Clearance Plan
While examples have been used to disclose the invention, including the best mode, and also to enable any person skilled in the art to make and use the invention, the patentable scope of the invention is defined by claims, and may include other examples that occur to those skilled in the art. Accordingly the examples disclosed herein are to be considered non-limiting. As an illustration, a markdown optimization system can be configured as disclosed herein to provide for a solution for the markdown pricing problem which is significantly complex because of, among other things, the large number of product/location combinations and nonlinear objective and constraints as well as because product/location groups are not optimized independently.
The systems' and methods' data (e.g., associations, mappings, etc.) may be stored and implemented in one or more different types of computer-implemented ways, such as different types of storage devices and programming constructs (e.g., data stores, RAM, ROM, Flash memory, flat files, databases, programming data structures, programming variables, IF-THEN (or similar type) statement constructs, etc.). It is noted that data structures describe formats for use in organizing and storing data in databases, programs, memory, or other computer-readable media for use by a computer program.
The systems and methods may be provided on many different types of computer-readable media including computer storage mechanisms (e.g., CD-ROM, diskette, RAM, flash memory, computer's hard drive, etc.) that contain instructions for use in execution by a processor to perform the methods' operations and implement the systems described herein.
The computer components, software modules, functions, data stores and data structures described herein may be connected directly or indirectly to each other in order to allow the flow of data needed for their operations. It is also noted that a module or processor includes but is not limited to a unit of code that performs a software operation, and can be implemented for example as a subroutine unit of code, or as a software function unit of code, or as an object (as in an object-oriented paradigm), or as an applet, or in a computer script language, or as another type of computer code. The software components and/or functionality may be located on a single computer or distributed across multiple computers depending upon the situation at hand.
It should be understood that as used in the description herein and throughout the claims that follow, the meaning of “a,” “an,” and “the” includes plural reference unless the context clearly dictates otherwise. Also, as used in the description herein and throughout the claims that follow, the meaning of “in” includes “in” and “on” unless the context clearly dictates otherwise. Finally, as used in the description herein and throughout the claims that follow, the meanings of “and” and “or” include both the conjunctive and disjunctive and may be used interchangeably unless the context expressly dictates otherwise; the phrase “exclusive or” may be used to indicate situation where only the disjunctive meaning may apply.
This application claims priority to and the benefit of U.S. Application Ser. No. 60/922,772 (entitled Markdown Optimization Systems And Methods and filed on Apr. 10, 2007), of which the entire disclosure (including any and all figures) is incorporated herein by reference.
Number | Name | Date | Kind |
---|---|---|---|
5195172 | Elad et al. | Mar 1993 | A |
5319781 | Syswerda | Jun 1994 | A |
5627973 | Armstrong et al. | May 1997 | A |
5652842 | Siegrist, Jr. et al. | Jul 1997 | A |
5712989 | Johnson et al. | Jan 1998 | A |
5767854 | Anwar | Jun 1998 | A |
5799286 | Morgan et al. | Aug 1998 | A |
5926820 | Agrawal et al. | Jul 1999 | A |
5946662 | Ettl et al. | Aug 1999 | A |
5953707 | Huang et al. | Sep 1999 | A |
5963910 | Ulwick | Oct 1999 | A |
5999908 | Abelow | Dec 1999 | A |
6009407 | Garg | Dec 1999 | A |
6014640 | Bent | Jan 2000 | A |
6023684 | Pearson | Feb 2000 | A |
6029139 | Cunningham et al. | Feb 2000 | A |
6041267 | Dangat et al. | Mar 2000 | A |
6078892 | Anderson et al. | Jun 2000 | A |
6115691 | Ulwick | Sep 2000 | A |
6151582 | Huang et al. | Nov 2000 | A |
6175876 | Branson et al. | Jan 2001 | B1 |
6182060 | Hedgcock et al. | Jan 2001 | B1 |
6226623 | Schein et al. | May 2001 | B1 |
6236977 | Verba et al. | May 2001 | B1 |
6237138 | Hameluck et al. | May 2001 | B1 |
6249768 | Tulskie et al. | Jun 2001 | B1 |
6263315 | Talluri | Jul 2001 | B1 |
6275812 | Haq et al. | Aug 2001 | B1 |
6286005 | Cannon | Sep 2001 | B1 |
6321133 | Smirnov et al. | Nov 2001 | B1 |
6321206 | Honarvar | Nov 2001 | B1 |
6397224 | Zubeldia et al. | May 2002 | B1 |
6456999 | Netz | Sep 2002 | B1 |
6470344 | Kothuri et al. | Oct 2002 | B1 |
6484179 | Roccaforte | Nov 2002 | B1 |
6502077 | Speicher | Dec 2002 | B1 |
6526526 | Dong et al. | Feb 2003 | B1 |
6546135 | Lin et al. | Apr 2003 | B1 |
6553352 | Delurgio et al. | Apr 2003 | B2 |
6560501 | Walser et al. | May 2003 | B1 |
6581068 | Bensoussan et al. | Jun 2003 | B1 |
6584447 | Fox et al. | Jun 2003 | B1 |
6611829 | Tate et al. | Aug 2003 | B1 |
6640215 | Galperin et al. | Oct 2003 | B1 |
6728724 | Megiddo et al. | Apr 2004 | B1 |
6735570 | Lacy et al. | May 2004 | B1 |
6750864 | Anwar | Jun 2004 | B1 |
6898603 | Petculescu et al. | May 2005 | B1 |
6901406 | Nabe et al. | May 2005 | B2 |
6907382 | Urokohara | Jun 2005 | B2 |
6970830 | Samra et al. | Nov 2005 | B1 |
7039594 | Gersting | May 2006 | B1 |
7085734 | Grant et al. | Aug 2006 | B2 |
7089266 | Stolte et al. | Aug 2006 | B2 |
7092896 | Delurgio et al. | Aug 2006 | B2 |
7092929 | Dvorak et al. | Aug 2006 | B1 |
7130811 | Delurgio et al. | Oct 2006 | B1 |
7133876 | Roussopoulos et al. | Nov 2006 | B2 |
7133882 | Pringle et al. | Nov 2006 | B1 |
7171376 | Ramakrishnan | Jan 2007 | B2 |
7236949 | Natan et al. | Jun 2007 | B2 |
7240019 | Delurgio et al. | Jul 2007 | B2 |
7249031 | Close et al. | Jul 2007 | B2 |
7251615 | Woo | Jul 2007 | B2 |
7302400 | Greenstein | Nov 2007 | B2 |
7302410 | Venkatraman et al. | Nov 2007 | B1 |
7346538 | Reardon | Mar 2008 | B2 |
7370366 | Lacan et al. | May 2008 | B2 |
7379890 | Myr et al. | May 2008 | B2 |
7440903 | Riley et al. | Oct 2008 | B2 |
7536361 | Alberti et al. | May 2009 | B2 |
7617119 | Neal et al. | Nov 2009 | B1 |
7689456 | Schoeder et al. | Mar 2010 | B2 |
7752067 | Fotteler et al. | Jul 2010 | B2 |
20020013757 | Bykowsky et al. | Jan 2002 | A1 |
20020046096 | Srinivasan et al. | Apr 2002 | A1 |
20020072953 | Michlowitz et al. | Jun 2002 | A1 |
20020099678 | Albright et al. | Jul 2002 | A1 |
20020107723 | Benjamin et al. | Aug 2002 | A1 |
20020116237 | Cohen et al. | Aug 2002 | A1 |
20020123930 | Boyd et al. | Sep 2002 | A1 |
20020169654 | Santos et al. | Nov 2002 | A1 |
20020169655 | Beyer et al. | Nov 2002 | A1 |
20020178049 | Bye | Nov 2002 | A1 |
20030023598 | Janakiraman et al. | Jan 2003 | A1 |
20030028437 | Grant et al. | Feb 2003 | A1 |
20030050845 | Hoffman et al. | Mar 2003 | A1 |
20030078830 | Wagner et al. | Apr 2003 | A1 |
20030083924 | Lee et al. | May 2003 | A1 |
20030083925 | Weaver et al. | May 2003 | A1 |
20030088458 | Afeyan et al. | May 2003 | A1 |
20030097292 | Chen et al. | May 2003 | A1 |
20030110072 | Delurgio et al. | Jun 2003 | A1 |
20030110080 | Tsutani et al. | Jun 2003 | A1 |
20030120584 | Zarefoss et al. | Jun 2003 | A1 |
20030126010 | Barns-Slavin | Jul 2003 | A1 |
20030126136 | Omoigui | Jul 2003 | A1 |
20030167098 | Walser et al. | Sep 2003 | A1 |
20030172145 | Nguyen | Sep 2003 | A1 |
20030208402 | Bibelnieks et al. | Nov 2003 | A1 |
20030208420 | Kansal | Nov 2003 | A1 |
20030220830 | Myr | Nov 2003 | A1 |
20030229502 | Woo | Dec 2003 | A1 |
20030236721 | Plumer et al. | Dec 2003 | A1 |
20040093296 | Phelan et al. | May 2004 | A1 |
20040111388 | Boiscuvier et al. | Jun 2004 | A1 |
20040199781 | Erickson et al. | Oct 2004 | A1 |
20050033761 | Guttman et al. | Feb 2005 | A1 |
20050066277 | Leah et al. | Mar 2005 | A1 |
20050096963 | Myr et al. | May 2005 | A1 |
20050197896 | Viet et al. | Sep 2005 | A1 |
20050198121 | Daniels et al. | Sep 2005 | A1 |
20050256726 | Benson et al. | Nov 2005 | A1 |
20050256753 | Viet et al. | Nov 2005 | A1 |
20050262108 | Gupta | Nov 2005 | A1 |
20060047608 | Davis et al. | Mar 2006 | A1 |
20060069598 | Schweitzer et al. | Mar 2006 | A1 |
20060074728 | Schweitzer et al. | Apr 2006 | A1 |
20060143030 | Wertheimer | Jun 2006 | A1 |
20060248010 | Krishnamoorthy et al. | Nov 2006 | A1 |
20070055482 | Goodermote et al. | Mar 2007 | A1 |
20070174119 | Ramsey et al. | Jul 2007 | A1 |
20070288296 | Lewis | Dec 2007 | A1 |
20080077459 | Desai et al. | Mar 2008 | A1 |
20080208719 | Sharma et al. | Aug 2008 | A1 |
20090271241 | Pratt | Oct 2009 | A1 |
Number | Date | Country |
---|---|---|
1413955 | Apr 2004 | EP |
WO 0111522 | Feb 2001 | WO |
2007002841 | Jan 2007 | WO |
Number | Date | Country | |
---|---|---|---|
60922772 | Apr 2007 | US |