Abstract:
The present invention relates to a unified, user driven, business-to-business pricing tool covering all price setting processes. The pricing tool utilizes a multi-dimensional, multi-level workbook which allows the user to select and edit chosen parameters at any level or dimension. The pricing tool allows edited parameters to be set at a high level and inherited throughout the workbook. Optimization and analytical tools may then be used throughout the workbook whereby the edited parameters are incorporated into the optimization and analysis. A price triangulation module is included whereby preferred business segmentation and selected business pricing goals and constraints may be incorporated into the optimization at any said level or dimension.

Description:
PRIORITY AND INCORPORATION BY REFERENCE  
       [0001]     This application claims priority of U.S. Provisional Patent Applications No. 60/800,640, filed May 15, 2006 and No. 60/825,902, filed Sep. 16, 2006, which are hereby fully incorporated by reference. 
     
    
     BACKGROUND OF THE INVENTION  
       [0002]     The present invention relates to business-to-business price setting and management systems. More particularly, the present invention relates to systems and methods for providing a robust, interactive, user-friendly price setting tool.  
         [0003]     Many businesses rely upon careful pricing in order to stay competitive and still realize a profit. Successful price setting may be the difference between a company&#39;s solvency and demise. Through proper pricing, market dominance may be obtained and held, even in very competitive markets.  
         [0004]     Setting an optimal price for a product and market segment is very challenging as it needs to address several drivers and constraints, including: historical negotiated prices, win ratios at different price points, competitive prices, minimum price constraint, etc.  
         [0005]     Price setting professionals are often forced to pick one primary driver (e.g. historical prices) to set price as they lack a comprehensive solution that can incorporate multiple data points into the price setting process.  
         [0006]     The price setting process needs to output multiple price points, including list price, negotiated target price, approval price levels, and price floors.  
         [0007]     Additionally, each market segment (e.g. geography, industry or company size or type) can have its own set of prices or price adjustments.  
         [0008]     The complexity of addressing multiple price drivers, price points and segments across thousands of products requires a large diversion of time and man-hours of officials within a company. The loss in productivity due to price setting is often enormous. Most companies cannot invest adequate amount of time to the price setting process resulting sub-optimal prices which in turn leads to lower profits and shareholder value.  
         [0009]     Traditionally, teams of marketing specialists, or the truly gifted businessperson, were needed to devise successful pricing schemes. Often such pricing suggestions were not competitive and too costly to generate.  
         [0010]     With the advent of computers, automated pricing became a reality. However, such pricing schemes often did not have the desired level of utility, intuitiveness, and functionality as to be of any great improvement over more traditional methods of price setting. Furthermore, such automated price setting systems were unable to incorporate multiple drivers (or data points) to guide the price setting process and yet be interactively editable.  
         [0011]     For the typical business, the above systems are still too inaccurate, unreliable, costly and intractable in order to be utilized effectively for price setting. Businesses, particularly those involving large product sets, would benefit greatly from the ability to have accurate and efficient price setting tools available that allows for instant simulations and interactivity of pricing scenarios.  
         [0012]     It is therefore apparent that an urgent need exists for an improved system and method for price setting and optimization that is both accurate and efficient. This solution would replace price setting techniques with a more helpful system; thereby increasing the realization of business goals, standardization of deal negotiations and decreased waste.  
       SUMMARY OF THE INVENTION  
       [0013]     To achieve the foregoing and in accordance with the present invention, a method and system for Price Setting and Optimization are provided. Such a system is useful for a business to set product prices in order to effectuate business goals. Such an analysis may be utilized by the business for price management.  
         [0014]     The instant systems allow sales managers and other client users to set optimal price points at any level or dimension of the business across including products, customers, customer segments and geography. Selected parameters may be set while the remaining terms are optimized to give a desired result.  
         [0015]     The instant invention enables a business user to select a preferred business segment for analysis. The user may adjust selected prices as desired. As prices are adjusted, the resulting business impact is simulated in real time. Users may simulate price, revenue, margin and win ration impact at any level and dimension of the selected business segment.  
         [0016]     The pricing tool utilizes a multi-dimensional workbook which allows the business user to specify a worksheet corresponding to a desired business segment (e.g. product hierarchy, geography, industry and/or sales channel). Worksheets are used to analyze historical price and sales data, edit desired price points and view simulated results—all in one worksheet. The pricing tool allows the user to set or edit parameters (e.g. target prices, or approval prices) at any level of the business and inherited down throughout the worksheet, e.g. a price change applied at a product family gets inherited down to each product belonging to the product family. Optimization and analytical tools may then be used to analyze the effects of changed parameters at any level of the worksheet. Edited parameters are incorporated into the optimization and analysis at all levels.  
         [0017]     The pricing tool incorporates a price triangulation module which may be used to balance results of the optimization with additional analysis to arrive at final prices. An effective business to business price setting tool must allow the business user to create a useful business segmentation structure and to incorporate pricing goals and constraints into the overall process. The instant price triangulation module incorporates business goals and constraints into the price setting process.  
         [0018]     Optimization may be performed at any selected segment and for any level or dimension of said segment. Business goals and constraints are incorporated into all dimensions and levels of the workbook.  
         [0019]     The invention allows the user to set up a novel workspace whereby prices and policies may be set on worksheets at any level or dimension of the business hierarchies (e.g., product, customer, and organization).  
         [0020]     These and other features of the present invention will be described in more detail below in the detailed description of the invention and in conjunction with the following figures.  
     
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0021]     In order that the present invention may be more clearly ascertained, one embodiment will now be described, by way of example, with reference to the accompanying drawings, in which:  
         [0022]      FIG. 1  shows a block diagram illustrating the price setting and optimization system in accordance with an embodiment of the present invention;  
         [0023]      FIG. 2  shows a block diagram illustrating the optimization and triangulation system for the price setting and optimization system of  FIG. 1 ;  
         [0024]      FIG. 3  shows a block diagram illustrating the manager module for the price setting and optimization system of  FIG. 1 ;  
         [0025]      FIG. 4  shows a flow chart illustrating the process of price setting for the price setting and optimization system of  FIG. 1 ;  
         [0026]      FIG. 5  shows a flow chart illustrating the process of planning business goals for the price setting and optimization system of  FIG. 1 ;  
         [0027]      FIG. 6  shows a flow chart illustrating the process of optimization for the price setting and optimization system of  FIG. 1 ;  
         [0028]      FIG. 7  shows a flow chart illustrating the process of receiving optimization input for the price setting and optimization system of  FIG. 1 ;  
         [0029]      FIG. 8  shows a flow chart illustrating the process of price optimization for the price setting and optimization system of  FIG. 1 ;  
         [0030]      FIG. 9  shows a flow chart illustrating the process of triangulating pricing for the price setting and optimization system of  FIG. 1 ;  
         [0031]      FIG. 10  shows a flow chart illustrating the process of managing goals for the price setting and optimization system of  FIG. 1 ;  
         [0032]      FIG. 11  shows a flow chart illustrating the process of generating product pricing for the price setting and optimization system of  FIG. 1 ;  
         [0033]      FIG. 12  shows a flow chart illustrating the process of generating market pricing for the price setting and optimization system of  FIG. 1 ;  
         [0034]      FIG. 13  shows a flow chart illustrating the process of generating channel pricing for the price setting and optimization system of  FIG. 1 ;  
         [0035]      FIG. 14  shows a flow chart illustrating the process of setting channel prices for the price setting and optimization system of  FIG. 1 ;  
         [0036]      FIG. 15  shows a flow chart illustrating the process of generating consumer pricing for the price setting and optimization system of  FIG. 1 ;  
         [0037]      FIG. 16  shows a flow chart illustrating the process of generating deal terms for the price setting and optimization system of  FIG. 1 ;  
         [0038]      FIG. 17  shows a flow chart illustrating the process of pricing execution for the price setting and optimization system of  FIG. 1 ;  
         [0039]      FIG. 18  shows a flow chart illustrating the process of performance tracking for the price setting and optimization system of  FIG. 1 ;  
         [0040]      FIG. 19  shows a price waterfall diagram illustrating the management of pricing in an implementation of the price setting and optimization system of  FIG. 1 ;  
         [0041]      FIG. 20  shows a worksheet interface implementing the price setting and optimization system of  FIG. 1 ;  
         [0042]      FIG. 21  shows a triangulation diagram generated by an implementation of the price setting and optimization system of  FIG. 1 ;  
         [0043]      FIG. 22A  illustrates a computer system, which forms part of a network and is suitable for implementing the price setting and optimization system of  FIG. 1 ;  
         [0044]      FIG. 22B  illustrates a block diagram of a computer system and network suitable for implementing price setting and optimization system of  FIG. 1 .  
     
    
     DETAILED DESCRIPTION OF THE INVENTION  
       [0045]     The present invention will now be described in detail with reference to several embodiments thereof as illustrated in the accompanying drawings. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. It will be apparent, however, to one skilled in the art, that the present invention may be practiced without some or all of these specific details. In other instances, well known process steps and/or structures have not been described in detail in order to not unnecessarily obscure the present invention. The features and advantages of the present invention may be better understood with reference to the drawings and discussions that follow.  
         [0046]     To facilitate discussion,  FIG. 1  shows a block diagram illustrating the Price Setting and Optimization System  100  in accordance with an embodiment of the present invention. The instant systems allow sales managers and other client users to change and optimize selected parameters at any level or dimension of the price setting tool. Selected parameters may be set while the remaining terms are optimized to give a desired result.  
         [0047]     The instant invention enables a business user to select a preferred business segment for analysis. A business segment can be a combination of one or more of the following dimensions: product group (e.g. product family), geography, industry and sales channel. The user may adjust selected parameters (e.g. list price, target price, approval prices and floor prices) as desired. As parameters are adjusted, the resulting business impact is simulated in real time. Users may simulate price, revenue, profit and margin impact at any level or dimension of the selected business segment.  
         [0048]     Price Setting and Optimization System  100  includes a Deal Term Generator  110 , coupled to a Negotiator  120  and an Executor  130 . Deal Term Generator  110  includes a Planner  111 , Optimizer  112 , and Deal Manager  113 . Deal Term Generator  110  receives business goals, and feedback from performance tracking. Deal Term Generator  110  is enabled to generate business to business price setting. Price setting may include suggesting deal terms and product pricing, channel pricing, market pricing and customer pricing.  
         [0049]     Planner  111  provides for the setting of business goals. These business goals are then tied to pricing actions. Planner  111  receives feedback information from Executor  130 . Additionally, Planner  111  may provide elasticity models. The Planner  111  may be coupled to Optimizer  112 . Planner  111  provides Optimizer  112  with pricing actions, pricing constraints, statistical information, and elasticity models. It should be noted that the elasticity modeling utilized by Price Setting and Optimization System  100  is purposeful left unspecified such that various models may be utilized as needs dictate. For example, in some embodiments linear programming may be utilized. Alternatively, in some embodiments Bayesian shrinkage modeling may be utilized. Alternate modeling may be utilized as is well known by those skilled in the art. In some embodiments, rule or constraint based optimization may be utilized rather than elasticity based optimization.  
         [0050]     Optimizer  112  provides optimization of the pricing and deal terms by applying the modeling to the pricing constraints, as provided by Planner  111 . In some embodiments, Optimizer  112  may include industry standard values for variables and constraints, such as price sensitivity and product attributes. Additionally, in some embodiments these industry standards may be modified by the user to reflect business knowledge. One advantage of the present invention is that it utilizes standard business knowledge, thereby providing more closely tailored pricing optimizations to business realities. Additional mathematical or specialized knowledge is not required for effective price setting that confirms to specific business goals.  
         [0051]     Optimizer  112  may, in some embodiments, be coupled to Manager  113 . Manager  113  provides the generation of list prices and deal terms (target prices, approval prices and floor prices). Manager  113  utilizes the optimized price outputs of Optimizer  112  in order to provide generate the optimal prices and deal term suggestions. These deal term suggestions may then be output to Negotiator  120  in order to facilitate negotiations and pricing at various stages of business to business interactions. Additionally, Negotiator  120  may incorporate approval routing and alerts triggered by deal terms (e.g. a negotiated price which is below the approval price level or floor price). In some embodiments Manager  113  may provide output in multiple formats in order to further facilitate deal negotiations. Such outputs may include pricing waterfall diagrams, charts, spreadsheet outputs, or any output beneficial for business use, as is well known by those skilled in the art.  
         [0052]     In some embodiments, Manager  113  may be enabled to provide “what if” scenarios to the user. In these circumstances, possible scenarios may be input into Planner  111 . Then Manager  113  may provide likely results of these possible scenarios. In this way, potential volatilities of the market or unexpected events may be considered for business to business interactions. This ability has significant repercussions for risk analysis and business planning.  
         [0053]     In some embodiments, Negotiator  120  is a sub component of Deal Manager  113 . Alternatively, Negotiator  120  may receive output from Deal Manager  113 . Negotiator  120  outputs customer specific price quotes, price agreements and/or contracts. In some embodiments Negotiator  120  may be an included automated component of Price Setting and Optimization System  100 . In alternate embodiments, Negotiator  120  may be human facilitators who engage in business to business price negotiations. Moreover, in some embodiments Negotiator  120  may be a hybrid system of automated components which provide boiler plate deals and human elements if there are breakdowns of negotiations. The field decisions made by Negotiator  120  are, in some embodiments, driven by the outputs of Manager  113  to ensure profitability, or the optimization of one or more of the business goals set in the Planner  111 . Negotiator  120  may additionally present deal guidance to a human agent to facilitate negotiations.  
         [0054]     Negotiator  120  may be coupled with Executor  130  to execute the business to business price agreements created. Executor  130  may be an integrated system that ties pricing seamlessly with enterprise pricing systems. In this way, effectuation of pricing is streamlined for enhanced efficiency. Executor  130  may, in some embodiments, provide performance tracking and subsequent feedback to the Deal Term Generator  110 , and specifically to the Planner  111 . Such performance tracking feedback may be utilized by Planner  111  to statistically modify the modeling to provide increased accuracy of subsequent price settings.  
         [0055]      FIG. 2  shows a block diagram illustrating the optimization and triangulation system for the price setting and optimization system of  FIG. 1 . In some embodiments, the Optimizer  112  receives input from Price Goal Generator  201 , Profit Goal Generator  202 , Price Constraints Generator  203 , Relative Price Sensitivity Generator  204  and Elasticity Model Generator  205 . In some embodiments Price Goal Generator  201 , Profit Goal Generator  202 , Price Constraints Generator  203 , Relative Price Sensitivity Generator  204  and Elasticity Model Generator  205  are components of the Planner  111 . The Optimizer  112  may utilize the received information in order to generate optimized prices as well as estimations of volume impact, revenue impact and profit impact. In some embodiments, Optimizer  112  may be coupled to Triangulator  210  and Manager  113 .  
         [0056]     Triangulator  210  may be enabled to analyze the pricing information generated by Optimizer  112 . Triangulator  210  may then generate list prices, target prices, approval prices and floor prices. Target prices, approval prices and floor prices (also called deal terms) provide guidance for negotiations of business to business deals. Target prices are the desired price for the negotiation. Approval prices are not as high as the target prices, and require approval from management through a workflow system. Approval prices are not automatically approved, but rather trigger approval workflows, where one or more people are required to approve the price before it can be submitted. Floor prices are the minimum prices that may be considered at deal negotiations. The Triangulator  210  may output its information to the Negotiator  120  for deal negotiation guidance. In some embodiments, the Triangulator  210  may provide output to the Manager  113 . In such embodiments the Manager  113  may then provide a comprehensive guidance scheme, including pricing recommendations, alerts and policies to the Negotiator  120 . Manager  113 , as discussed above, may include human actors, automated components, or a combination of both human and machine actors.  
         [0057]     The results from Negotiator  120  (e.g. customer quotes, price agreements and/or contracts) may be then output to Order Processor  220  and Performance Tracker  230 . Order Processor  220  and Performance Tracker  230  are components of Executor  130  in some embodiments. Order Processor  220  may be enabled to streamline downstream processes of packaging, invoicing and additional standard order processes as is well known to those skilled in the art. Performance Tracker  230  tracks performance and provides feedback for the tracked performance. In some embodiments, Performance Tracker  230  may receive information from Negotiator  120  and Order Processor  220  in order to compile performance tracking data.  
         [0058]     Results from Performance Tracker  230  may then be output to Elasticity Model Generator  205  for tuning of the elasticity models in order to generate tailored and accurate elasticity models. Such modification of models may include linear adjustments or statistical methods of modification.  
         [0059]      FIG. 3  shows a block diagram illustrating the pricing factors of the Manager  113  for the Price Setting and Optimization System  100  of  FIG. 1 . Manager  113  provides management of pricing for every level of business to business price setting processes. The components of  FIG. 3  provide pricing factors for optimization by Price Setting and Optimization System  100 . However, the pricing factors as detailed in  FIG. 3  are exemplary in nature. Individual businesses will have unique organizational structures.  
         [0060]     A General Manager  301  oversees all other components and may be coupled to Product Line Director  302 , Business Manager  304 , Regional Managers  305 , Product Regional Managers  307  and Sales Representative  309 . Product Line Director  302  is coupled to a plurality of Product Line Managers  303  and provides direction of Product Line Managers  303 . Product Line Managers  303  manage the various product lines of a particular business. Product Line Managers  303  are coupled to Business Manager  304 , which provides oversight of Product Line Managers  303  and Regional Managers  305 .  
         [0061]     The plurality of Regional Managers  305 , each provide regional management. Regional Managers  305  receive direction from Sales Operation Manager  306 . Sales Operation Manager  306  manages the sales operation for the business. The plurality of Product Regional Managers  307  manage the products of each region. Said management includes directing of Sales Manager  308 . Likewise Sales Manager  308  provides oversight of Sales Representative  309 . Ultimately, a vast plethora of pricing factors are generated by the components of  FIG. 3 . Each pricing factor may be arranged into a pricing waterfall in order to illustrate the bearing these factors have upon the optimized price setting.  
         [0062]      FIG. 4  shows a flow chart illustrating the process of price setting, shown generally at  400 , for the price setting and optimization system of  FIG. 1 . The process begins at the planning step  410 , where business goals and pricing actions are planned. This step may, in some embodiments, occur within Planner  111 . For step  410 , standard business goals may be included, such as maximization of profits; however, additional goals may be included as is deemed necessary. Such goals may include a certain sales volume, certain revenue, a change in market share or any additional desired business goal. Additionally, Step  410  may include planning goal constraints, such as a sales constraint for an inventory deficient product. Moreover, in some embodiments, business knowledge may be included at step  410  in order to provide more efficient price setting.  
         [0063]     Next, at step  420 , price setting occurs. This step may be performed at Optimizer  112 . Alternatively, in some embodiments step  420  may be performed in Optimizer  112  and Triangulator  210 . At step  420 , optimized pricing and triangulation occurs in order to set the prices.  
         [0064]     Then, at step  430 , goals are managed. This step occurs at the Manager  113 . The managed goals are then output to Negotiator  120  for negotiation at step  440 . Then at step  450 , pricing is executed at the Executor  130 . The process then ends.  
         [0065]      FIG. 5  shows a flow chart illustrating the process of planning, where planning includes the planning of business goals for the price setting and optimization system of  FIG. 1 , shown generally at step  410 . This process begins at step  511 , where business goals are set. As previously discussed, the business goals may include business standards and may be modified as needed to meet any desired result. Then, at step  512 , the business goals set at step  511  are tied to pricing actions. The process then ends by proceeding to step  420  of  FIG. 4 .  
         [0066]      FIG. 6  shows a flow chart illustrating the process of price setting for the price setting and optimization system of  FIG. 1 , shown generally at  420 . The process begins from step  410 . The process then progresses to step  601 , where a decision is made whether to optimize. Triangulation is independent of but complementary to optimization. Optimization does not have to be run in order to use Triangulation. However, if optimization is performed, then triangulation is a very useful way of setting the best price that balances the optimal price as determined by a set of assumptions and constraints with other relevant data points such as competitive prices. If Optimization is desired then the process proceeds to step  610  where optimization input is received. Optimization input is received from Planner  111  as the result of the process illustrated at step  410 . Additional optimization input may be received from components Triangulator  210 , Profit Goal Generator  202 , Price Constraints Generator  203 , Relative Price Sensitivity Generator  204  and Elasticity Model Generator  205 . Triangulator  210 , Profit Goal Generator  202 , Price Constraints Generator  203 , Relative Price Sensitivity Generator  204  and Elasticity Model Generator  205  may provide industry standards, and in some embodiments may be modified by user&#39;s business knowledge for enhanced accuracy.  
         [0067]     Then, at step  620 , prices are optimized by utilizing the optimization input received from step  610 . Optimization, as previously discussed, may utilize performance feedback as well as elasticity modeling and business goals and constraints in order to yield optimum pricing. In some embodiments, optimization may be rule based instead of elasticity based.  
         [0068]     These optimums, at step  630 , may then be triangulated in order to yield business to business deal suggestions for enhanced negotiations. Triangulation of prices may occur at the Triangulator  210 . In some embodiments, triangulation may include user defined constraints, and rules. For example, in some embodiments, the user may define the target price to be a minimum of 10% greater than variable costs, but not more than 75% of the historical pricing. In such a way the Triangulator  210  may compile all rules and optimize pricing according to the business goals to generate triangulated pricing. In some embodiments the Triangulator  210  may provide an integrated display of optimizations, sales history and constraints in order to provide a context rich backdrop for the user to define the floor, approval and target pricing. The process then ends by proceeding to step  430  of  FIG. 4 .  
         [0069]     If at step  601  optimization is not desired the process goes directly to step  630  where triangulation is performed. As discussed above triangulation of prices may occur at the Triangulator  210 . In some embodiments, triangulation may include user defined constraints, and rules. For example, in some embodiments, the user may define the target price to be a minimum of 10% greater than variable costs, but not more than 75% of the historical pricing. In such a way the Triangulator  210  may compile all rules and optimize pricing according to the business goals to generate triangulated pricing. In some embodiments the Triangulator  210  may provide an integrated display of optimizations, sales history and constraints in order to provide a context rich backdrop for the user to define the floor, approval and target pricing. The process then ends by proceeding to step  430  of  FIG. 4 .  
         [0070]      FIG. 7  shows a flow chart illustrating the process of receiving optimization input for the price setting and optimization system of  FIG. 1 , shown generally at  610 . The process begins at step  711  where price goals are inputted. Price goals may exist to conform to competitor pricing, promotional advertised pricing, manufacturer demands, or for any other reason.  
         [0071]     Then at step  712 , profit goals may be inputted. Typically profits are maximized for. However, in some circumstances businesses may require other goals to take precedence over profit, such as expanding market dominance through increased volume sales. In such circumstances the business may desire that some base level of profit be maintained to support the business and appease investors&#39;; however some profit may be willingly sacrificed in favor of dominating the marketplace. Thus the present invention allows for powerful, strategic business price management.  
         [0072]     At step  713 , price sensitivity is inputted. Business to business customers may have varying sensitivity to pricing for various products. In some embodiments, the price of the product may be linearly correlated with price sensitivity. Also, in some embodiments, type of product may play a substantial role in price sensitivity. Statistically or empirically derived standard price sensitivity may be provided. Additionally, in some embodiments, the user may be able to modify these price sensitivity values utilizing business knowledge. Moreover, in some embodiments, these price sensitivity values may be unique within every negotiation. This is due to inconsistency of price perception from one consumer to another. As such the present invention, in some embodiments, may be enabled to have variable price sensitivities dependent upon customers.  
         [0073]     Then in step  714 , pricing models are input. Models may be elasticity models or alternate models, such as rule based. In some embodiments, the user may select the model to be used by the Optimizer  112 . In some embodiments, a default model may be provided. Additionally, in some embodiments, when performance tracking data is received, the model may be modified to better fit actual performance. Such modifications may be statistical in nature, however any suitable method may be utilized as is well known in the art. Moreover, in some embodiments, model selection may be automated by the Deal Term Generator  110 . In these embodiments the model may be chosen as to provide best-fit to the received performance tracking feedback. Alternatively, models may be selected in response to product types sold, region, economic climate, or any multitude of variables which provide for accurate modeling selection. The process then ends by proceeding to step  620  of  FIG. 6 .  
         [0074]      FIG. 8  shows a flow chart illustrating the process of price optimization for the price setting and optimization system of  FIG. 1 , shown at  620 . The process begins from process  610  of  FIG. 6 . Then the process continues at step  821  where the optimized prices are generated. The price generation is performed by the Optimizer  112 , and utilizes the inputted optimization information from process  610 .  
         [0075]     Then, at step  822 , an estimation is generated for the impact that the optimized prices will have upon revenue by utilizing the inputted optimization data. At step  823  an estimation is generated for the impact that the optimized prices will have upon product sales volume by utilizing the inputted optimization data. At step  824  an estimation is generated for the impact that the optimized prices will have upon profit by utilizing the inputted optimization data. It should be noted that steps  822 ,  823  and  824  may be performed in parallel or any order.  
         [0076]     The data generated from steps  822 ,  823  and  824  may be useful for business planning and production planning. Additionally, this data may be important for the compliance with defined constraints and goals inputted at process  610 . After steps  822 ,  823  and  824  have all completed the process ends by proceeding to step  630  of  FIG. 6 .  
         [0077]      FIG. 9  shows a flow chart illustrating the process of triangulating pricing for the price setting and optimization system of  FIG. 1 , shown at  630 . The process begins from process  620  at  FIG. 6 . Then at step  938  an inquiry is made whether the triangulation is to be performed in an automated fashion. If so then, at step  931 , target prices are generated. At step  932  approval prices are generated. At step  933  floor prices are generated. In some embodiments, Steps  931 ,  932  and  933  are performed in parallel. The generation of floor, approved and target pricing may be effectuated by statistical optimization methods. Alternatively, in some embodiments, the generation of the prices may be based upon a rule based constraint scheme. After target, approval and floor prices are generated the process end by proceeding to step  430  of  FIG. 4 .  
         [0078]     Else, if at step  938  the triangulation is not automated, then the process proceeds to step  939  where a context rich interface is generated for the user to effectuate the price settings. Then, at step  931 , target prices are generated. At step  932  approval prices are generated. At step  933  floor prices are generated. In these embodiments the Triangulator  210  provides an interface for the user where multiple sources of relevant data are displayed, thereby creating the context rich environment for the price setting. This environment may include the optimized price, historical price, constraint data, win probability, active contracts, and additional information as is beneficial for effectuating the price generation. After target, approval and floor prices are generated the process ends by proceeding to step  430  of  FIG. 4 .  
         [0079]      FIG. 10  shows a flow chart illustrating the process of managing goals for the price setting and optimization system of  FIG. 1 , shown at  430 . The process begins from process  420  from  FIG. 4 . Then, at step  1031 , product parameters are generated. At step  1032  market parameters are generated. At step  1033  channel parameters are generated. At step  1034  customer parameters are generated. Lastly, at step  1035  the deal term parameters are generated. In this fashion the price waterfall may be constructed for each pricing element. Additionally, these price settings may be utilized to create comprehensive deal suggestions for the Negotiator  120 . The process end by progressing to step  440  of  FIG. 4 .  
         [0080]      FIG. 11  shows a flow chart illustrating the process of generating product parameters for the price setting and optimization system of  FIG. 1 , shown at  1031 . The process  1031  as illustrated is intended as exemplary; individual businesses will vary in the process of generating product parameters for the price setting and optimization system. This process begins from step  420  of  FIG. 4 . Then at step  1131  product attribute multipliers are set. At step  1132  product list prices are set. At step  1133  product volume breaks are set. At step  1134  product lifecycle adjustments are set. At step  1135  product bundle prices are set. At step  1136  service prices are set. Again, these values may be set by automated means by utilizing output from the optimizer, historical data and statistical methods. Also, in some embodiments, the user may configure the set values. Alternatively, in some embodiments, an automated system may set the values and the user may be able to tune the values as is desired. The process then ends by proceeding to step  1032  of  FIG. 10 .  
         [0081]      FIG. 12  shows a flow chart illustrating the process of generating market parameters for the price setting and optimization system of  FIG. 1 , shown at  1032 . The process  1032  as illustrated is intended as exemplary; individual businesses will vary in the process of generating market parameters for the price setting and optimization system. The process begins from step  1031  of  FIG. 10 . At step  1231  industry price adjustments are set. At step  1232  geography price adjustments are set. At step  1233  competitive price adjustments are set. At step  1234  promotion prices are set. Again, these values may be set by automated means by utilizing output from the optimizer, historical data and statistical methods. Also, in some embodiments, the user may configure the set values. Alternatively, in some embodiments, an automated system may set the values and the user may be able to tune the values as is desired. The process then ends by proceeding to step  1033  of  FIG. 10 .  
         [0082]      FIG. 13  shows a flow chart illustrating the process of generating channel parameters for the price setting and optimization system of  FIG. 1 , shown at  1033 . The process  1033  as illustrated is intended as exemplary; individual businesses will vary in the process of generating channel parameters for the price setting and optimization system. The process begins from step  1032  of  FIG. 10 . At step  1331  channel prices are set. At step  1332  channel margins are set. At step  1333  channel incentives are set. At step  1334  channel promotions are set. Again, these values may be set by automated means by utilizing output from the optimizer, historical data and statistical methods. Also, in some embodiments, the user may configure the set values. Alternatively, in some embodiments, an automated system may set the values and the user may be able to tune the values as is desired. The process then ends by proceeding to step  1034  of  FIG. 10 .  
         [0083]      FIG. 14  shows a flow chart illustrating the process of setting channel parameters for the price setting and optimization system of  FIG. 1 , shown at  1331 . The process begins from step  1032  of  FIG. 10 . At step  1431  introductory stock prices are set. At step  1432  end user prices are set. Again, these values may be set by automated means by utilizing output from the optimizer, historical data and statistical methods. Also, in some embodiments, the user may configure the set values. Alternatively, in some embodiments, an automated system may set the values and the user may be able to tune the values as is desired. The process then ends by proceeding to step  1032  of  FIG. 10 .  
         [0084]      FIG. 15  shows a flow chart illustrating the process of generating consumer parameters for the price setting and optimization system of  FIG. 1 , shown at  1034 . The process  1034  as illustrated is intended as exemplary; individual businesses will vary in the process of generating consumer parameters for the price setting and optimization system. The process begins from step  1033  of  FIG. 10 . At step  1531  product/consumer prices are set. At step  1532  product/consumer target prices are set. Again, these values may be set by automated means by utilizing output from the optimizer, historical data and statistical methods. Also, in some embodiments, the user may configure the set values. Alternatively, in some embodiments, an automated system may set the values and the user may be able to tune the values as is desired. The process then ends by proceeding to step  1035  of  FIG. 10 .  
         [0085]      FIG. 16  shows a flow chart illustrating the process of generating deal term parameters for the price setting and optimization system of  FIG. 1 , shown at  1035 . The process  1035  as illustrated is intended as exemplary; individual businesses will vary in the process of generating deal term parameters for the price setting and optimization system. The process begins from step  1034  of  FIG. 10 . At step  1631  suggested deal terms are set. At step  1632  deal terms envelope and approval levels are set. The envelope is defined by the floor pricing and the target pricing generated by the Triangulator  210 . At step  1633  the deal terms rules are set. Again, these values may be set by automated means by utilizing output from the optimizer, historical data and statistical methods. Also, in some embodiments, the user may configure the set values. Alternatively, in some embodiments, an automated system may set the values and the user may be able to tune the values as is desired. The process then ends by proceeding to step  440  of  FIG. 4 .  
         [0086]      FIG. 17  illustrates a flow chart illustrating the process of executing prices for the price setting and optimization system of  FIG. 1 , shown at  450 . The process begins from step  440  of  FIG. 4 . At step  1710  orders are processed. Processing orders includes generating invoices, shipping products and the multitude of actions required to complete a typical business order as is well known by those skilled in the art. At step  1720  performance is tracked. Then the results of the performance tracking are outputted to the Planner  111  for further tuning of the elasticity model, at step  1730 . The process then ends.  
         [0087]      FIG. 18  shows a flow chart illustrating the process of performance tracking for the price setting and optimization system of  FIG. 1 , shown at  1720 . The process begins from step  1710  of  FIG. 17 . At step  1821  price realization is tracked. At step  1822  win ratios are tracked. Win ratios refer to the percentage of the time the deal negotiations are successful. At step  1823  the impact on revenue is tracked. At step  1824  the impact on volume is tracked. At step  1825  the impact on profit is tracked. The process then ends by progressing to step  1730  of  FIG. 17 .  
         [0088]      FIG. 19  shows a price Waterfall Diagram  1900  illustrating the management of pricing in an implementation of the price setting and optimization system of  FIG. 1 . The elements illustrated in Waterfall Diagram  1900  are exemplary; particular waterfall elements may vary dependent upon business. The Price Setting and Optimization System  100  is configured to work with the waterfall defined for the business.  
         [0089]     Pricing components found in Product Pricing  1910  include Base Price  1911 , Product Lifecycle Adjustment  1912 , Product Attribute Adjustment  1913 , Product Bundle Adjustment  1914 , Product Package Adjustment  1915 , List Price  1916 , Volume Discount  1917 , and COGS  1918 . Pricing components found in Market Pricing  1920  include Regional, Industry or Channel Adjustment  1921 , Regional, Industry or Channel Price  1922 , Promotional Discount  1923 , and Rebates  1924 . Pricing components found in Negotiated Pricing  1930  include Negotiated Discount  1931 , Manufacturers Adjustment  1932 , Shipping Charge  1941 , Shipping Cost  1942 , and Payment Cost  1943 , Invoice Price  1933 , Pocket Price  1934 , and Pocket Margin  1935 . Pricing components found in Channel Pricing  1950  include Introductory Stock Price  1951  and Distributor Promotions  1952 .  
         [0090]      FIG. 20  shows a Worksheet Interface  2000  implementing the price setting and optimization system of  FIG. 1 . In some embodiments, the present invention is a series of multidimensional spreadsheets. Each spreadsheet is embodied in a Pricing Worksheet  2001 . Certain cells in the Pricing Worksheet  2001  may be edited (e.g. list price or deal terms), others are non-alterable (e.g. historical prices or revenue). The present invention enables an editable, multidimensional spreadsheet that may be analyzed while being modified. Additionally, in some embodiments, changes made to the spreadsheet propagate through the spreadsheet to provide this cohabitation of edit ability and analytics.  
         [0091]     In some embodiments, all Worksheets  2001  in a given workbook are aware of the edits made to other Worksheets  2001  in the same workbook. Thus, if several different policies that determine the calculation of a price are edited via different Worksheets  2001 , the calculation will reflect all of the applicable policy changes made in the workbook.  
         [0092]     Moreover, in some embodiments, the modification to the spreadsheet may be enabled to provide instant simulations of alternate scenarios. Such functionality provides a powerful tool to the business user in terms of business planning capability. The present invention thus empowers the user to create highly configured Pricing Worksheet  2001  to suit specific needs and reflect expert business knowledge. Pricing Worksheet  2001  displays and allows configuration of prices and policies, sales analysis, goals and constraints, and cell information of the spreadsheet.  
         [0093]     Plan Tab  2002  illustrates a functionality window for displaying and enabling configuration of price constraints, volume constraints and business goals.  
         [0094]     Analysis Tab  2003  illustrates a functionality window for displaying and enabling configuration of analysis. Such analysis may be displayed as a bar chart, line chart, min/max chart, trend chart, scatter chart, price brand chart or waterfall chart.  
         [0095]     Price Tab  2004  illustrates a functionality window for displaying and enabling configuration of price triangulation and deal guidance.  
         [0096]     Optimize Tab  2005  illustrates a functionality window for displaying and enabling configuration of elasticity modeling, business to business price optimization, win probability, average price elasticity optimization and average pricing optimization.  
         [0097]     Simulate Tab  2006  illustrates a functionality window for displaying and enabling configuration of simulations of price impact, margin impact and business impact.  
         [0098]     Details Tab  2007 , labeled inspect, illustrates a functionality window for displaying and enabling configuration of inspection of cells within the spreadsheet, audit trails and comments.  
         [0099]     Statistics Tab  2008  illustrates a functionality window for displaying and enabling configuration of statistical analyses, including trending.  
         [0100]     Data Selection Tab  2009  illustrates a functionality window for displaying and enabling configuration of price types (list prices, target prices, approval prices, volume discounts or any price adjustments), business dimensions (e.g. product hierarchy, geographies, industries) and business measures. Rows, columns, and/or cells in a Worksheet  2001  may be selected in order to drive other tools, such as charts or mass-edit operations. (e.g. revenue, profit, margin, win ratios).  
         [0101]     Workbook Tab  2010  illustrates a functionality window for displaying and enabling configuration of printing and exporting.  
         [0102]     Pricing Organizer Tab  2011  illustrates a functionality window for displaying and enabling configuration of approval routing and administration of Pricing Worksheet  2001 . In some embodiments, the Organizer  2011  provides a view of workbooks that supports searching and sorting.  
         [0103]     Pricing Templates Tab  2012  illustrates a functionality window for displaying and enabling configuration of price templates and industry templates for the Pricing Worksheet  2001 .  
         [0104]      FIG. 21  shows a Triangulation Display  2100  generated by an implementation of the price setting and optimization system of  FIG. 1 . Historical Pricing  2101  is provided by the performance tracking. Historical Pricing  2101  provides a range of values from highest to lowest price as well as the average or median value. Optimized Price  2102  is generated by the Optimizer  112 . Win Probabilities  2103  provides the probability of a successful deal within a price range. Competitors Pricing  2104  provides a comparison to competitor&#39;s pricing. Competitors Pricing  2104  provides the maximum, minimum, individual competitive prices as well as the median value. Marginal Cost  2105  provides a basis for the minimum profitable sales price. Pricing lower than Marginal Cost  2105  will be sold at less than cost. Maximum price Constraint  2106  are constraints imposed due to market considerations. Often a business will not want to increase pricing above a pre determined level in order to avoid alienation of customers and for competitive reasons. Margin Goal  2107  is provided by the Optimizer  112  in response to planned goals. Finally, Triangulated Pricing  2108  are the triangulated floor, approval and target pricing for the product.  
         [0105]     Triangulation Display  2100  provides a context rich backdrop for setting of floor, approval and target prices by the user. Such a diagram, in conjunction with the user&#39;s specialized business knowledge, and the ability to make interactive modifications and analytics simultaneously provides for a powerful business strategy tool.  
         [0106]      FIGS. 22A and 22B  illustrate a Computer System  2200 , which is suitable for implementing embodiments of the present invention.  FIG. 22A  shows one possible physical form of the Computer System  2200 . Of course, the Computer System  2200  may have many physical forms ranging from a printed circuit board, an integrated circuit, and a small handheld device up to a huge super computer. Computer system  2200  may include a Monitor  2202 , a Display  2204 , a Housing  2206 , a Disk Drive  2208 , a Keyboard  2210 , and a Mouse  2212 . Disk  2218  is a computer-readable medium used to transfer data to and from Computer System  2200 .  
         [0107]      FIG. 22B  is an example of a block diagram for Computer System  2200 . Attached to System Bus  2220  are a wide variety of subsystems. Processor(s)  2222  (also referred to as central processing units, or CPUs) are coupled to storage devices, including Memory  2224 . Memory  2224  includes random access memory (RAM) and read-only memory (ROM). As is well known in the art, ROM acts to transfer data and instructions uni-directionally to the CPU and RAM is used typically to transfer data and instructions in a bi-directional manner. Both of these types of memories may include any suitable of the computer-readable media described below. A Fixed Disk  2226  may also be coupled bi-directionally to the Processor  2222 ; it provides additional data storage capacity and may also include any of the computer-readable media described below. Fixed Disk  2226  may be used to store programs, data, and the like and is typically a secondary storage medium (such as a hard disk) that is slower than primary storage. It will be appreciated that the information retained within Fixed Disk  2226  may, in appropriate cases, be incorporated in standard fashion as virtual memory in Memory  2224 . Removable Disk  2218  may take the form of any of the computer-readable media described below.  
         [0108]     Processor  2222  is also coupled to a variety of input/output devices, such as Display  2204 , Keyboard  2210 , Mouse  2212  and Speakers  2230 . In general, an input/output device may be any of: video displays, track balls, mice, keyboards, microphones, touch-sensitive displays, transducer card readers, magnetic or paper tape readers, tablets, styluses, voice or handwriting recognizers, biometrics readers, or other computers. Processor  2222  optionally may be coupled to another computer or telecommunications network using Network Interface  2240 . With such a Network Interface  2240 , it is contemplated that the Processor  2222  might receive information from the network, or might output information to the network in the course of performing the above-described Price Setting and Optimization Price Setting and Optimization System  100 . Furthermore, method embodiments of the present invention may execute solely upon Processor  2222  or may execute over a network such as the Internet in conjunction with a remote CPU that shares a portion of the processing.  
         [0109]     In addition, embodiments of the present invention further relate to computer storage products with a computer-readable medium that have computer code thereon for performing various computer-implemented operations. The media and computer code may be those specially designed and constructed for the purposes of the present invention, or they may be of the kind well known and available to those having skill in the computer software arts. Examples of computer-readable media include, but are not limited to: magnetic media such as hard disks, floppy disks, and magnetic tape; optical media such as CD-ROMs and holographic devices; magneto-optical media such as optical disks; and hardware devices that are specially configured to store and execute program code, such as application-specific integrated circuits (ASICs), programmable logic devices (PLDs) and ROM and RAM devices. Examples of computer code include machine code, such as produced by a compiler, and files containing higher level code that are executed by a computer using an interpreter.  
         [0110]     Although the present invention has been described in considerable detail with reference to exemplary embodiments, modifications and variations may be made to the disclosed embodiments while remaining within the subject and spirit of the invention. Therefore, the spirit and scope of the appended claims should not be limited to the description of the versions contained herein.