Abstract:
A computer implemented sales transaction tool and associated method of use is disclosed. This includes at least one processor configured to receive sales transaction information and programmed to provide the following functionality: a series of control functions that can be selectively activated by input to the processor for creating at least one subset of the sales transaction information, a plurality of graphical representations that are generated based on the selected subset of sales transaction information, and displaying at least one graphical representation of the plurality of graphical representations on an electronic display associated with the processor. Graphical representations of sales transaction information may include a slope and scatter diagram of sales transaction information, a waterfall chart, waterfall transactional analysis, a time series chart, a price sensor, a margin sensor, a break-even analysis graph and a bubble chart. There are graphical representations to evaluate opportunity of moving low margin products to average margins of comparable products and determining value for products having a single customer.

Description:
BACKGROUND OF INVENTION 
       [0001]    A major problem facing all businesses today is the ability to be able to identify the value derived from each customer. There is a interdependence between volume and margin and most organizations have a difficult time determining how a change in volume can affect the margin until after the fact and numerous sales have been made at a particular price. This creates a tremendous problem since it is very difficult for an organization to stay profitable in a dynamically changing sales environment. Moreover, once a lower price has been offered to a customer, a course correction to obtain a reasonable margin is very difficult without losing the customer altogether. Another major issue is being able to analyze the enormous volume and complexity of price and cost elements and being able to relate this information back to the individual sales order. It is very difficult to maintain profitability if the individual components that contribute to the final transaction price are not known. 
         [0002]    An important function of operating a business is being able to ascertain an individual customer&#39;s contribution to price changes and estimate the theoretical impact of a price change on the sales volume. It is also important to be able to identify cost and margin drivers associated with sales transactions. Another important issue is low margin products and whether it is possible to move the price of these products upward so that these products enjoy at least an average pocket margin of comparable products in a selected peer group. Another important issue is the process of providing an exclusive product to a single customer and determining whether the return on these sales makes sense from a business perspective. A major problem is the ability to dynamically ascertain the relationship between sales volume, margin, revenue and a particular customer or predetermined group of customers. There is a significant need to be able to determine what prices need to be raised, along with a projected loss of volume, in order to obtain a desired range of margin. Another issue is the ability to be able to ascertain the plant gate pocket price, which is the gross sales price minus all cost elements, with the exception of raw material costs, in relationship to cumulative quantity. 
         [0003]    Although there are tools to analyze profit such as the PROFIT ANALYZER™ manufactured by Vendavo, Inc., having a place of business at 1029 Corporation Way, Palo Alto, Calif. 94303, these tools seem to lack the ability to collectively look at the elements forming the price in a side-by-side comparison. 
         [0004]    The present invention is directed to overcoming one or more of the problems set forth above. 
       SUMMARY OF INVENTION 
       [0005]    In an aspect of this invention, a sales transaction tool is disclosed. This sales transaction tool includes at least one processor, such as a computer and/or data processor, that receives sales transaction information, a series of control functions that can be selectively activated by input to the at least one processor for creating at least one subset of the sales transaction information, a plurality of graphical representations that are generated based on the selected subset of sales transaction information, and at least one electronic display for displaying at least one graphical representation of the plurality of graphical representations. 
         [0006]    In another aspect of this invention, a sales transaction tool is disclosed. This sales transaction tool includes at least one processor that receives sales transaction information, a series of control functions that can be selectively activated by input to the at least one processor for creating at least one subset of the sales transaction information, wherein the series of control functions includes at least one of a product-type control, a time period-type control, a predetermined grouping of customers, a predetermined market, and a plurality of graphical representations that are generated based on the selected subset of sales transaction information, wherein the plurality of graphical representations includes at least one of a graphical representation of gross sales price information minus predetermined cost elements versus quantity, a slope and scatter diagram of sales transaction information, a price and margin solver, a time series chart, a price sensor, a margin sensor and a break-even analysis graph, waterfall analysis of sales transaction information, a low volume analysis tool for estimating opportunity of moving low margin products to average margins of comparable products, a single customer analysis tool for determining value with a single customer, and a transactional waterfall bubble chart, and at least one electronic display for displaying at least one graphical representation of the plurality of graphical representations. 
         [0007]    In still another aspect of this invention, a method for utilizing a sales transaction tool is disclosed. The method includes receiving sales transaction information with at least one processor, selectively activating a series of control functions by input to the at least one processor for creating at least one subset of the sales transaction information, generating a plurality of graphical representations based on the at least one selected subset of sales transaction information, and displaying at least one graphical representation of the plurality of graphical representations on at least one electronic display. 
         [0008]    In still another aspect of this invention, a method for utilizing a sales transaction tool is disclosed. The method includes receiving sales transaction information with at least one processor, selectively activating a series of control functions by input to the at least one processor for creating at least one subset of the sales transaction information, wherein the series of control functions includes at least one of a product-type control, a time period-type control, a predetermined grouping of customers, and a predetermined market, generating a plurality of graphical representations based on the at least one selected subset of sales transaction information, wherein the plurality of graphical representations includes at least one of a graphical representation of gross sales price information minus predetermined cost elements versus quantity, a slope and scatter diagram of sales transaction information, a price and margin solver, a time series chart, a price sensor, a margin sensor and a break-even analysis graph, waterfall analysis of sales transaction information, a low volume analysis tool for estimating opportunity of moving low margin products to average margins of comparable products, a single customer analysis tool for determining value with a single customer, and a transactional waterfall bubble chart, and displaying at least one graphical representation of the plurality of graphical representations on at least one electronic display. 
         [0009]    These are merely some of the innumerable aspects of the present invention and should not be deemed an all-inclusive listing of the innumerable aspects associated with the present invention. These and other aspects will become apparent to those skilled in the art in light of the following disclosure and accompanying drawings. 
     
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         [0010]    For a better understanding of the present invention, reference may be made to the accompanying drawings in which: 
           [0011]      FIG. 1  illustrates an exemplary screen display (graphical user interface) of the present invention showing a main front page viewed by a user for performing fishtail analysis and for generating a slope and scatter chart utilizing controls to selectively acquire data; 
           [0012]      FIG. 2  illustrates an exemplary display (graphical user interface) for selecting and disabling various sales transaction analysis tools associated with the present invention; 
           [0013]      FIG. 3  illustrates an exemplary display (graphical user interface) for managing data files and acquiring information regarding the system associated with the present invention; 
           [0014]      FIG. 4  illustrates graphical information available through the slope and scatter chart illustrated in  FIG. 1  and associated with the present invention; 
           [0015]      FIG. 5  illustrates an exemplary display (graphical user interface) for generating a time series chart, break-even analysis and price and/or margin sensors associated with the present invention; 
           [0016]      FIG. 6  illustrates an exemplary display (graphical user interface) displaying associated subfunctions available with the price and/or margin sensors shown in  FIG. 5  and associated with the present invention; 
           [0017]      FIG. 7  illustrates an exemplary display (graphical user interface) for generating fishtail analysis and associated histograms associated with the present invention; 
           [0018]      FIG. 8  illustrates an exemplary display (graphical user interface) for generating a transactional waterfall aggregate browser associated with the present invention; 
           [0019]      FIG. 9  illustrates an exemplary display (graphical user interface) for generating low volume analysis including tables and graphical representations associated with the present invention; 
           [0020]      FIG. 10  illustrates an exemplary graphical display of low volume product analysis of annual sales versus a particular product identification, e.g., stock keeping unit (“SKU”), in predetermined time units, e.g., quarters, associated with the present invention; 
           [0021]      FIG. 11  illustrates an exemplary display (graphical user interface) for generating single customer analysis including tables and graphical representations associated with the present invention; and 
           [0022]      FIG. 12  illustrates an exemplary display (graphical user interface) for generating a transactional waterfall bubble chart including graphical representations associated with the present invention. 
       
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
       [0023]    In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the invention. However, it will be understood by those skilled in the art that the present invention may be practiced without these specific details. For example, the invention is not limited in scope to the particular type of industry application depicted in the figures, a particular type of software language, or to particular conventions regarding software designations. In other instances, well-known methods, procedures and components have not been described in detail so as not to obscure the present invention. A processor referred to in this Application can be a single processor or a whole series of processors. An illustrative, but nonlimiting, application for this technology includes the chemical industry. An illustrative, but nonlimiting source of the data/information from custom built multi-cube information from SAP® via the Business Warehouse™ system. SAP® is a federally registered trademark of SAP America, Inc., having a place of business at 3999 West Chester Pike, Newtown Square, Pa. 19073. An illustrative, but nonlimiting, mechanism for receiving data and performing computations can include EXCEL®. EXCEL® is a federally registered trademark of Microsoft Corporation, having a place of business at One Microsoft Way, Redmond, Wash. 980526399. 
         [0024]    Referring now to the drawings, initially to  FIG. 1 , where  FIG. 1  is a sample screen display of a main graphical user interface, which is indicated by numeral  10 . This screen display  10  is reached after going through login security. Illustrative, but nonlimiting, examples of login security may include activation of macros, provision of a password and/or userid followed by verification of the password, the userid, and/or the computer domain. 
         [0025]    There is a control section that is generally indicated by numeral  12 . The first section in the control section  12  is for selecting a particular sales region. Under the heading of “region”  14 , there are several inputs that the user can utilize to select sales transaction data associated with a sales information. Illustrative, but nonlimiting examples include: a drop-down input  20  to select a predetermined sales organization; a drop-drop down input  22  to select a predetermined geographic region; a drop-drop down input  24  to select a predetermined country to which the product will be shipped; and a drop-down input  26  to provide a predetermined primary sales representative. 
         [0026]    A second section in the control section  12  is for selecting a particular product. Under the heading of “product”  16 , there are several inputs that the user can utilize to select sales transaction data associated with product information. Illustrative, but nonlimiting examples include: a drop-down input  28  to select a predetermined product, e.g., product performance identification; a drop-drop down input  30  to select a predetermined subtype or subcomponent of product, e.g., higher level material; and a drop-down input  32  to provide a predetermined different version or category of the same product, e.g., price reference material; and a drop-down input  34  to provide a predetermined packaged quantity also known as “material group package”, e.g., drum, bulk vessel, isocontainers, tank trucks, rail cars, bags, and so forth. 
         [0027]    A third section  18  in the control section  12  is for selecting a particular time period and/or distribution channel  18 . Under the heading of “period and distribution channel”  18 , there are several inputs that the user can utilize to select sales transaction data associated with period and sales distribution information. Illustrative, but nonlimiting examples include: a drop-down input  36  to select a predetermined three month period, e.g., quarter; a drop-drop down input  38  to select a predetermined month; a drop-drop down input  40  to select a predetermined year; and a drop-down input  42  to select a predetermined customer group. 
         [0028]    There is also special control section to allow the user to select specific sales transaction information that is generally indicated by numeral  48 . Illustrative, but nonlimiting examples include: a drop-down input for a first predetermined customer group  50 ; a drop-down input for a second predetermined customer group  52 ; a drop-down input for a third predetermined customer group  54 ; and a drop-down input for a fourth predetermined customer group  56 . 
         [0029]    Also, under special controls  48  are a series of drop-down inputs for a predetermined segment of a market. Illustrative, but nonlimiting examples include: a drop-down input for a particular industry  58 ; a drop-down input for a particular market  60 ; a drop-down input for a particular segment of a market  62 ; and a drop-down input for a particular sub-segment of a market  64 . 
         [0030]    Other special controls  48  for other criteria can be available. Illustrative, but nonlimiting examples include: a drop-down input for a sub-group of a predetermined product  66 ; a drop-down input for a predetermined affiliation  68 , which is a connection to other predetermined groupings of sales transaction data; and a drop-down input for a second predetermined packaged quantity or material group package  70 , e.g., drum, bulk vessel, isocontainers, tank trucks, rail cars, bags, and so forth. There is also a drop-down input for a predetermined plant or facility  72 . 
         [0031]    There are a series of click-on inputs that can be utilized to exclude any of the inputs from either the control section  12  or the special control section  48 , which are indicated by numeral  37 . After all of the controls for filtering the sales transaction data through the control section  12  or special control section  48  have been selected, pushbutton  46  provides for execution of the selected controls to provide the selected sales transaction data to graphical representation tools described below. There is a pushbutton  44  that allows the user to reset the previously selected input provided through the control section  12  or special control section  48 . 
         [0032]    A first illustrative, but nonlimiting, graphical representation tool for analyzing data includes a fishtail analysis that is generally indicated by numeral  76 . This may include a plot of plant gate pocket price “PGPP” indicated by numeral  78  versus cumulative quantity  80 . Plant gate pocket price “PGPP” is defined as a gross sales price minus costs with the exception of raw material cost. The vertical lines, indicated by numeral  82 , reflect various data collection points, e.g., manufacturing sites, terminals, warehouses, and so forth). The horizontal line, indicated by numeral  84 , indicates a variable cost of raw materials based on market related prices. The plot indicated by numeral  86  is the plant gate pocket price “PGPP” of the selected customer and/or material combination. The distance between data points indicates the quantity of product that is sold. Also, this fishtail analysis provides combined margin plots for different packaging types or different periods to directly compare differences, changes and/or trends, e.g., drummed material versus bulk material. 
         [0033]    A pushbutton  88  provides a freeze function for chart comparison. This allows comparison of identically selected controls throughout different periods of time, e.g., current month versus previous month. There is also a pushbutton  90  that erases the previously acquired frozen chart. Moreover, there is a click-on input  92  to provide full cost information in the fishtail analysis  76  and a click-on input  94  that will hide the full cost information in the fishtail analysis  76 . 
         [0034]    A second illustrative, but nonlimiting, tool for analyzing data includes a slope and scatter plot that is generally indicated by numeral  96 . This is a plot of a variety of factors indicated by numeral  98  on the slope and scatter plot provided by drop-down input indicated by numeral  118 . Illustrative, but nonlimiting examples of the various factors  118  include: a cash cost of accounts receivables (“CoC A/R”)/unit; allocated transaction/unit; average plant gate pocket price “PGPP”/unit; cash cost of inventory for a value of investment (“CoC Consignment”)/unit; commissions/unit; a cost to serve (“C2S”)/unit; duties and/or tariffs/unit; early payment discount (EPD)/unit; fixed costs/unit; a second imputed discount/unit; internal shipping costs/unit; net invoice/unit; last leg of freight charges/unit; net price/unit; discounts printed on an invoice/unit; packaging cost/unit; profit margin/unit; pocket margin/unit; variable costs/unit; small quantity upcharge/unit; target price/unit; top quartile price/unit; transactional corrections/unit; variable margin/unit; gross invoice/unit; and volume rebates/unit. These factors  98 , provided by drop-down input  118 , include a variety of waterfall elements described below. 
         [0035]    The slope and scatter plot  96  includes the factors  98  plotted versus quantity indicated by numeral  100 . There is a click-on input  102  for creation of a linear graph and a click-on input  104  for creation of a logarithmic graph. The quantity  100  can be in a variety of units  120 , e.g., tons, U.S. Dollars, Euros, and so forth. There is a click-on input  101  to display customer names as labels and a click-on input  103  to the hide the customer names. 
         [0036]    There is a data input for range  106 , a data input for a lower limit  108  and a data limit for a higher limit  110 . There is a pushbutton  112  to provide an input from the range  106 , the lower limit  108  and the higher limit  110  to provide range selection to adjust probability ranges for quantity scaling on the X axis and or regression analysis. The limits  108  and  110  will exclude values falling outside of the limits and are indicated by numerals  111  and  113 , respectively, on the slope and scatter chart  96 . The range  106  can allow the user to determine the percentage of data points falling within the limits  108  and  110 . A pushbutton input  114  allows data from various sources, e.g., marketing account representatives, to appear in different colors. There is a pushbutton input  122  that allows the user to suppress the appearance of zeros on the slope and scatter plot  96 . This is a helpful function in a variety of situations, e.g., customer pick-up, volume rebate levels. 
         [0037]    A customer function  116  assists the user in identifying the party that is receiving the sale of the goods. This is utilized in providing an appropriate view for analysis. Illustrative, but nonlimiting examples of the customer function  116  include, but are not limited to: a negotiating party; a sold-to party; a shipping party; and a global parent. An output variable for the slope and scatter plot  96  allows analysis of all pricing elements. This is preferably performed along the Y axis. 
         [0038]    As shown in  FIG. 4  and generally indicated by numeral  190 , there is an ability for the user to click on a customer from a listing  192  to located a particular account on the slope and scatter chart  96  as well as the fishtail analysis  76 , shown in  FIG. 1 . Clicking a data point on the slope and scatter chart  96  can create an account waterfall chart  194 . A click on a waterfall element  191  will yield a respective run chart over the transactions during the period chosen. 
         [0039]    There is a pushbutton icon  193  to close the waterfall chart  194 . Clicking on a waterfall element on the account waterfall chart  194  will create a series chart  195 . There is a pushbutton icon  196  to close the series chart  195 . The user can click on the scatter plot  96  to create a transactional waterfall chart  197 . There is a pushbutton icon  198  to close the transactional waterfall chart  197 . 
         [0040]    Referring again to  FIG. 1 , a price and margin solver is an additional tool that is indicated by numeral  124 . This includes an equation  126  representing the slope and scatter plot  96  indicated by numeral  109 . The upper limit  110  is shown on the slope and scatter plot  96  by numeral  113  and the lower limit  108  is shown by numeral  111 . 
         [0041]    The desired target quantity can be changed through data input  128 . The result target is generated and indicated by data output  130 , which depends on the type of factor indicated by numeral  118 . The conformance with the target is indicated by data output  132  as range of values both positive and negative. The distance from the trend line is indicated by numeral  134 , and the distance from the lower confidence limit is indicated by numeral  136 . When the values are outside of these limits, the output can turn another predetermined color, e.g., red, to provide this as an indication. 
         [0042]    There is a header menu indicated by numeral  140 . Located with the header menu  140  is a star browser  142  that allows the user to navigate between the different tools for sales transaction analysis. As shown in  FIG. 2 , the star browser  142  provides a “pages” function  144  that displays a list of various tools for analysis, which includes: a fish and scatter chart  152 ; a time series chart  154 ; a water graph  156 ; low volume analysis  158 ; a single customer analysis  160 ; a bubble chart  162 ; and a waterfall query  164 . 
         [0043]    There is a control function  146  that allows the user to switch off one or more of the analysis tools. This includes: disabling a time series chart  166 ; disabling a water graph  168 ; disabling low volume analysis  170 ; disabling single customer analysis  172 ; disabling a bubble chart  174 ; disabling special controls  176 ; and provide an automatic filter in a new waterfall  178 . 
         [0044]    A file management function is indicated by numeral  148  in  FIG. 3 . This file management function  148 , provides a data file creation feature  180  so that waterfall numbers can be separately analyzed in a pivot table. There is a CE Star Template function  150  that provides information about the version  182  of the star browser  142 . This may include a version identification, date of release, file name, and so forth. There is also a function to determine the last date when sales transaction data was provided to the system  184 . 
         [0045]    A time series chart is indicated by numeral  200  in  FIG. 5 . There is an average top quartile price (“TCP”) indicated by numeral  204 , an average bottom quartile price (“BCP”) indicated by numeral  206  and an average price plot indicated by numeral  208 . The time series chart  200  provides a general overview of a gross price  202  and provides fine tuning of the navigation of a price sensor and margin sensor that is generally indicated by numeral  210 . When the user clicks on two points on the average price plot  208 , a corresponding price sensor  212  and corresponding margin sensor  214  will be generated. 
         [0046]    The price sensor  212  includes a first portion  216 , where the price has decreased by a predetermined percentage, e.g., one percent (1%) or more, a second portion  218 , where the price has changed by less than a predetermined percentage, e.g., one percent (1%), and a third portion  220 , where the price has increased by a predetermined percentage, e.g., one percent (1%) or more. The price sensor  212  provides comparisons between last and actual month based on revenue. 
         [0047]    As shown in  FIGS. 5 and 6 , clicking on the first portion  216  generates a customer list  270  having a customer  272 , e.g., sold-to-party, a price for a first predetermined period  274 , e.g., month, a price for a second predetermined period  276 , e.g., month, a variable margin for a first predetermined period  278 , e.g., month, and a variable margin for a second predetermined period  279 , e.g., month. Also, clicking on the second portion  218  generates a customer list  280  having a customer  282 , e.g., sold-to-party, a price for a first predetermined period  284 , e.g., month, a price for a second predetermined period  286 , e.g., month, a variable margin for a first predetermined period  288 , e.g., month, and a variable margin for a second predetermined period  289 , e.g., month. Moreover, clicking on the third portion  220  generates a customer list  290  having a customer  292 , e.g., sold-to-party, a price for a first predetermined period  294 , e.g., month, a price for a second predetermined period  296 , e.g., month, a variable margin for a first predetermined period  298 , e.g., month, and a variable margin for a second predetermined period  299 , e.g., month. 
         [0048]    The margin sensor  214  includes a first portion  222 , where the margin has decreased by a predetermined percentage, e.g., one percent (1%) or more, a second portion  224 , where the margin has changed by less than predetermined percentage, e.g., one percent (1%) and a third portion  226 , where the margin has increased by a predetermined percentage, e.g., one percent (1%) or more. Clicking on the first portion  222  generates a customer list  270  having a customer  272 , e.g., sold-to-party, a price for a first predetermined period  274 , e.g., month, a price for a second predetermined period  276 , e.g., month, a variable margin for a first predetermined period  278 , e.g., month, and a variable margin for a second predetermined period  279 , e.g., month. Also, clicking on the second portion  224  generates a customer list  280  having a customer  282 , e.g., sold-to-party, a price for a first predetermined period  284 , e.g., month, a price for a second predetermined period  286 , e.g., month, a variable margin for a first predetermined period  288 , e.g., month, and a variable margin for a second predetermined period  289 , e.g., month. Moreover, clicking on the third portion  226  generates a customer list  290  having a customer  292 , e.g., sold-to-party, a price for a first predetermined period  294 , e.g., month, a price for a second predetermined period  296 , e.g., month, a variable margin for a first predetermined period  298 , e.g., month, and a variable margin for a second predetermined period  299 , e.g., month. 
         [0049]    The user can click on any two points in the average price plot indicated by numeral  208  and a corresponding price sensor  212  display will be generated to provide a price comparison and a corresponding margin sensor  214  display will be generated to provide a margin comparison. The price sensor  212  and the margin sensor  214  will detail lists of increasing or decreasing price/margin customers. The source code algorithms utilized to drill down points on a graph to other graphical images or information throughout this patent application is contained in Appendix A and incorporated herein by reference. 
         [0050]    A break-even analysis tool is generally indicated by numeral  250 . This tool involves a graphical representation of percentage of volume change  252  versus percentage of price change percent  254 , which is indicated by plot  256 . This break-even analysis tool  250  provides insight as to how much volume is required to break even if the price is cut. There is a data input  260  that allows the user to select a particular customer, all customers, or a predetermined subset thereof. The responsiveness of demand to price changes is illustrated in the break-even analysis tool  250 . 
         [0051]    Depending on the user&#39;s selections under controls  12  and special controls  48  in  FIG. 1 , the break-even analysis tool  250  measures the theoretical responsiveness or change in quantity demanded of a product  252 , which is illustrated along the Y axis, to a change in price in this same quantity demanded of this predetermined product  254 , which is illustrated along the X axis. As an assumption for this break-even analysis, all cost terms are assumed to remain static. The X axis  254  provides a hypothetical change in price in percent with a positive value being a price increase and a negative value being a price decrease. The Y axis  252  provides a hypothetical loss or gain in sales volume in percent. The break-even analysis tool  250  explores the theoretical impact on sales volume after a change in price. Each data point on the plot  256  represents a hypothetical break-even value for absolute pocket margin. The calculation is based on the selection, provided by the user, through controls  12  and special controls  48  in  FIG. 1  so that if a particular time interval, e.g., month, is selected, all projections are calculated based on the average gross sales price and absolute pocket marking for this same time interval, e.g., month. This would allow the user to determine if there is a hypothetical increase in price, what sales could be lost to generate the same pocket margin during the same time interval, e.g., month. 
         [0052]    Another sales analysis tool is a waterfall analysis that is activated through control  156  shown on  FIG. 2 . The waterfall graphical analysis is generally indicated by numeral  300  on  FIG. 7 . In this illustrative, but nonlimiting, embodiment there is a first transactional waterfall  302 . The first transactional waterfall  302  is associated with a first histogram of variable margin or pocket margin per unit  306 . There is a filtering and histogram control indicated by numeral  305 . Illustrative, but nonlimiting, input that can be provided to the filtering and histogram control  305  includes, but is not limited to: a first sales organization  314 ; a first segment detail  316 ; a second segment selection  318 ; a second segment detail  320 ; a customer  322 ; a first calculated predetermined period, e.g., quarter  324 ; a second calculated predetermined period, e.g., month  326 ; size of a material handling group  328 ; and a material handling container, e.g., starting bin  330 . The size  328  and starting bin  330  can be customized by the user. The utilization of the filtering and histogram control  305  generates a second transactional waterfall  304  and a second histogram  308 . There are a percentage of transactions  310  and a percentage of volume  312  found on both a first histogram  306  and a second histogram  308 . 
         [0053]    The first transactional waterfall  302  and the second transactional waterfall  304  provide a graphical representation of currency/quantity in relationship to all of the contributing factors that are generally indicated by numeral  342 . This is helpful to prevent cost leakage. These factors  342  can include a target price  344 , e.g., list price, base price; an invoice gross  352 , e.g., a sales order price, which is the price at which a customer places an order directly related to the price of every real time sales transaction/order item in the system. There is a first imputed discount  346 , which is the difference between a target price  344  and the invoice gross  352 , e.g., a sales order price. Also, these factors  342  include a top quartile price  348 , e.g., which is the top 25% of all prices determined by predetermined market segment during a predetermined time period, e.g., quarter, for a particular product identification, e.g., stock keeping unit (“SKU”). Also, a second imputed discount  350 , which is the difference between the top quartile price  348  and the invoice gross  352 , e.g., a sales order price. Moreover, these factors  342  include: a small quantity upcharge (“SQU”)  354 ; discounts printed on an invoice (on-invoice discounts)  356 ; an invoice net  358 , e.g., invoice price appearing on invoice document; a volume rebate  360 , which are accruals for rebates on a transaction level based on preexisting agreements; transactional corrections  362 , which are credit and debit memorandums entered into the system based on a reference document; allocated corrections  364 , which are credit and debit memorandums that are not based on a reference document and manually allocated to a predetermined period; and early payment discount(s) (“EPD”)  366  that is typically based so that the customer could always apply for an early payment discount, or a predetermined percentage of customers would apply for an early payment discount. 
         [0054]    The net price  368  is the invoice gross  352 , e.g., a sales order price minus the small quantity upcharge (“SQU”)  354 , discounts printed on an invoice (on-invoice discounts)  356 , invoice net  358 , e.g., invoice price appearing on invoice document, volume rebate  360 , transactional corrections  362 , allocated corrections  364 , and early payment discount(s) (“EPD”)  366 . 
         [0055]    There are a number of other contributing factors  342  that are utilized to arrive at margin values. These include a variable cost of raw materials  370 , which is based at the manufacturing plant or other location of origin for the raw materials; packaging cost  372 , which is an additional cost of packaged goods for a predetermined packaged unit, e.g., stock keeping unit (“SKU”); a last leg of freight charges  374 , which is the freight charges from the last facility e.g., terminal, warehouse, to a customer. The variable margin is indicated by numeral  376  and includes the net price  368  minus the variable cost of raw materials  370 , packaging cost  372 , and a last leg of freight charges  374 . 
         [0056]    Remaining contributing factors  342  include a cash cost of accounts receivables  378  (“CoC A/R), which is calculated from invoiced amount and a WACC of ten percent (10%) utilizing actual payment days. “WACC” is defined as (Cost of equity) (Equity/Capital)+(Cost of debt (1−tax rate)) (Debt/Capital). There is also a cash cost of inventory for a value of investment  380  (“CoC Consignment”). An internal shipment cost  382  provides freight costs between terminals and warehouses accumulated for multiple legs of travel. This includes resupplies. A cost to serve (“C2S”) is indicated by numeral  384 , which includes an allocated cost of selling, overhead, other distribution and research and development (“SG&amp;A”). Commissions, which include service fees and compensation paid to sales agents, are indicated by numeral  386 . Duties, which includes custom charges for internal or external deliveries is indicated by numeral  388 . The pocket margin  390  is calculated by taking the variable margin indicated by numeral  376  minus a cash cost of accounts receivables  378 , a cash cost of inventory  380 , an internal shipment cost  382 , a cost to serve (“C2S”)  384 , commissions  386 , and duties  388 . 
         [0057]    There is a calculation of a fixed costs  392 , which is a cost of labor and maintenance for a predetermined period of time; energy costs  394 ; and finally a profit margin  396 , which is the pocket margin  390  minus the fixed costs  392  and the energy costs  394 . 
         [0058]    The user clicking on any of the contributing factors  342  will trigger a run chart, as shown in  FIG. 8 , which is generally indicated by numeral  400 . There is a pushbutton  402  that closes the run chart  400 . When the user clicks on one of the contributing factors on the run chart  400  will trigger a waterfall graph  401  for that respective sales order and/or transaction. If additional details are required, an additional pushbutton icon  403  is available. 
         [0059]    Another sales analysis tool is low volume analysis that is activated through control  158  shown on  FIG. 2 . The low volume analysis is generally indicated by numeral  410  on  FIG. 9 . In this illustrative, but nonlimiting, embodiment there is a table  411  for particular product identifications, e.g., stock keeping units (“SKUs”) in decreasing order according to net sales  413  and grouped according to quadrants  412 . Net sales  413  provides both a monetary amount  415  and a percentage of total  417 , and sales quantity  414  provides a weight  419  and a percentage of total  421 . An average sales/quantity  416  is also provided. For each quadrant the specific average pocket margin  418  and profit margin  420  is determined along with a potential benefit  422 , which is the difference of pocket margin  418  and profit margin  420  times the quantity sold  414 . Preferably, but not necessarily, this is calculated for those particular product identifications, e.g., stock keeping units (“SKUs”) that have margins falling below its quadrant&#39;s average value. This low volume analysis is very helpful for businesses with a complex product portfolio with numerous grades, material codes, and so forth to single out underperforming sales with a meaningful, business related dataset utilized during an appropriate, predetermined time period. 
         [0060]    The low volume analysis tool  410  can then generate a graphical representation  430  of net sales  442  versus a time period  444 , e.g., quadrant; there is a switch  446  that allows the user to go between a material name and a material key. A table of material based analysis is shown on table  450 . This includes a column for: material identification  452 , e.g., I.D.; a time period  454 , e.g., quadrant  454 ; a material subgroup  456 , e.g., higher level material; a sum of net invoice  458 ; a sum of billing quantity  460 ; a sum of pocket  462 ; a sum of profit margin  464 ; an average price per weight  466 , e.g., EUR/ton; an average pocket margin  468 ; an average profit margin  470  and an opportunity  472 . When the user double clicks on a particular material name  457  within the column for a material subgroup  456 , e.g., higher level material, a listing of customers who purchased this product during a predetermined time period can be analyzed. 
         [0061]    Moreover, the low volume analysis tool  410  can also generate a graphical analysis  480  of annual sales  482  versus particular product identifications  484 , e.g., stock keeping units (“SKUs”), as shown in  FIG. 10 . This is broken down by predetermined time units, e.g., quarters, with a first quartile  486 , a second quartile  488 , a third quartile  490 , and a fourth quartile  492 . 
         [0062]    Still another sales analysis tool is single customer analysis that is activated through control  160  shown on  FIG. 2  and provides a sanity check on exclusively manufactured materials utilized by primarily one customer. The single customer analysis is generally indicated by numeral  500  on  FIG. 11 . In this illustrative, but nonlimiting, embodiment there is a graphical output for total average pocket margin  502  and total average profit margin  504 . As a general principle, it is desired that margins and values for these single customers should exceed the average due to the additional labor, longer equipment downtime and additional plant maintenance required. The ability to ascertain the success or failure of capturing sufficient value is shown in a bar graph of average pocket margin  506  and a bar graph of average profit margin  508 . The dashed line  505  is average pocket margin and dashed line  507  is average profit margin for all products being analyzed. Single customer analysis  500  should be applied for businesses with a highly complex material/customer mix with numerous grades or material codes, to single out underperforming sales. As with any sales transaction analysis tool, a meaningful, business-related dataset within an appropriate predetermined time period improves the accuracy of the results. 
         [0063]    There is a table of values within predetermined columns of dependency on a particular customer. These predetermined columns of dependency include a predetermined percentage  510 , e.g., one hundred percent (100%), of an entire production of a product goes to a single account, a first range of predetermined percentages  512 , e.g., ninety (90%) to one hundred percent (100%), of the production of a product goes to a single account; a second range of predetermined percentages  514 , e.g., seventy (70%) to ninety percent (90%), of the production of a product goes to a single account; a third range of predetermined percentages  516 , e.g., fifty (50%) to seventy percent (70%), of the production of a product goes to a single account; and a fourth range of less than a predetermined percentage  518 , e.g., fifty (50%), of the production of a product goes to a single account. This is for: average pocket margin  520 ; average profit margin  522 ; number of products  524 ; percentage of quantity  526 ; percentage of sales  528 ; opportunity (profit)  530  and risk (profit)  532 . Opportunity is defined as additional potential value if margins can be raised to at least overall average (which can be achieved through either cutting costs or increasing prices to compensate for additional costs and services). Risk is defined as an estimate of potential loss, e.g., if entire sales disappeared or production is ceased. 
         [0064]    The average pocket and profit margins  502  and  504  can belong to individual single customer dependence ranges based on the number of particular product identifications, e.g., stock keeping units (“SKUs”) in an individual single customer dependence range. The contribution to total sales is found in percentage of billing quantity and net sales. The general expectation is that high individual single customer dependence (“SCD”) ranges generate margins significantly above average, and SCD ranges to the right edge show margins around average or slightly below as shown in the bar graph of average pocket margin  506  and the bar graph of average profit margin  508 . 
         [0065]    There is an input  540  to select either a material key or a higher level material. A detail table is generally indicated by numeral  550  and can utilize the “Furey” scale. There is a listing of: materials  552 ; quantity in weight  554 , e.g., tons; net sales  556 ; total return based on pocket margin  558 ; relative percentage of pocket margin  560 ; total return based on profit margin  562 ; relative percentage of total profit margin  564 ; total opportunity  566 ; and total risk  568 . The materials  552  and quantity in weight  554  are both in terms of a particular product identification, e.g., stock keeping units (“SKUs”). A double click on a particular material name or key  570  will display a listing of customers who purchased this particular product during the predetermined time period. 
         [0066]    Finally, another sales analysis tool is a transactional waterfall bubble chart that is activated through control  162  shown on  FIG. 2 . The transactional waterfall bubble chart is generally indicated by numeral  600  on  FIG. 12 . There is a pushbutton icon  602  to remove the color coding and a pushbutton icon  604  that allows the transactional waterfall bubble chart  600  to be created based on a listing of menu items  606 . There is a color code  608  that indicates various items, e.g. countries, and associated color for that particular menu item. The listing of menu items  606  includes a value for the X axis  610 . Illustrative, but nonlimiting examples of values for the X axis  610  include in drop-down entry format: pocket margin; last leg freight; packaging costs; volume rebates; cash cost of accounts receivables (“CoC A/R”); total freight; profit margin; and variable margin. The listing of menu items  606  includes a value for the Y axis  612 . Illustrative, but nonlimiting examples of values for the X axis  612  include in drop-down entry format: invoice gross; net price; target price; and top quartile price. The listing of menu items  606  includes: a data entry for a bubble size  614 ; a drop-down value for invoiced net or billing quantity  616 ; a drop-down input  618  for per unit, total or percentage as type of figures on X axis; a drop-down input  620  for per unit or total as type of figures on Y axis; a data input for bubble color  622 ; and a drop-down input for customer grouping  624 , e.g., market sub-segment, ship-to country, primary sales representative, country (geographic region), material packaging grouping, plant, sales organization, and a sort field. 
         [0067]    The various examples shown above illustrate a novel sales transaction, analysis and reporting tool and associated method of use. A user of the present invention may choose any of the above embodiments, or an equivalent thereof, depending upon the desired application. In this regard, it is recognized that various forms of the subject invention could be utilized without departing from the spirit and scope of the present invention. 
         [0068]    Other aspects, objects and advantages of the present invention can be obtained from a study of the drawings, the disclosure and the appended claims. Thus, there has been shown and described several embodiments of a novel and non-obvious invention. As is evident from the foregoing description, certain aspects of the present invention are not limited by the particular details of the examples illustrated herein, and it is therefore contemplated that other modifications and applications, or equivalents thereof, will occur to those skilled in the art. The terms “have,” “having,” “includes” and “including” and similar terms as used in the foregoing specification are used in the sense of “optional” or “may include” and not as “required.” Many changes, modifications, variations and other uses and applications of the present construction will, however, become apparent to those skilled in the art after considering the specification and the accompanying drawings. All such changes, modifications, variations and other uses and applications which do not depart from the spirit and scope of the invention are deemed to be covered by the invention, which is limited only by the claims that follow.