Abstract:
Methods for managing hedging scenarios associated with a retail commodity. The method includes enabling the creation of a risk profile associated with a user and the commodity. Based on the risk profile, the method includes selecting hedging scenario(s) associated with purchasing a quantity of the commodity. The method also includes determining a user cost associated with purchasing the hedging scenarios using a time-based price of the commodity and outputting the costs. In some embodiments the time-based price is historic. The method can include enabling the user to purchase a hedging scenarios. Some embodiments include accepting a commodity consumption pattern, adjustments to the pattern, what-if cases, costs to the provider of the hedging scenarios. The costs (and savings) to the user can be determined based on the accepted consumption patterns (and adjustments) what-if cases, and provider costs. Systems and programs for managing such hedging scenarios also provided.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
       [0001]    This application claims priority from Provisional Patent Application No. 60/900,928 entitled “MANAGEMENT AND DECISION MAKING TOOL FOR COMMODITY PURCHASES WITH HEDGING SCENARIOS,” filed Feb. 12, 2007, by Fell et al., which is incorporated herein as if set forth in full. 
     
    
     COPYRIGHT NOTICE 
       [0002]    A portion of the disclosure of this patent document contains material to which a claim for copyright is made. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent file or records, but reserves all other copyright rights whatsoever. 
       TECHNICAL FIELD 
       [0003]    Embodiments of the disclosure relate generally to computer-implemented management and decision making tools. More particularly, this application relates to a system and method implementing management and decision making tools for retail commodity purchases under various hedging scenarios. 
       BACKGROUND 
       [0004]    Making a decision to purchase a retail commodity can be a very difficult process, particularly if a large quantity or volume of the commodity is to be purchased but that commodity tends to fluctuate in an unpredictable manner. For example, as the price of oil continues to fluctuate globally and fluidly, fuel prices at the pump can change from location to location on a daily or even hourly basis. In such a volatile market, it is extremely difficult for fleet managers and consumers alike to make sound decisions on where, how much, when, or even what fuel grade to buy and the terms on which to buy the commodity. 
       SUMMARY 
       [0005]    One object of the disclosure is to provide a new way to facilitate the decision making process of retail commodity purchases. This object can be achieved in a computer-implemented management and decision making tool that can be adaptive, interactive, and easy-to-use. More specifically, embodiments of the management and decision making tool (MDMT) disclosed herein can be implemented with a plurality of functions that offer additional analytics to support the purchase decision, by a consumer, a fleet manager, a financial manager, or anyone who is authorized to purchase the retail commodity for commercial or other purposes. 
         [0006]    In one embodiment, the MDMT uses estimated forward retail gasoline prices, along with historical or predicted consumption of fuels, to determine estimated fuel costs for an upcoming period. The fuel costs thus estimated can be compared with fuel costs estimated under various hedging strategies or scenarios. The MDMT estimates the savings that could be realized by implementing a “Pricelock” on a hedging strategy and presenting the results to a user or users via a user interface (in some embodiments the user interface can be a Web browser application running on the user&#39;s computer). Each time the user selects a different hedging strategy, the potential savings can be dynamically changed to reflect the selection. The MDMT can be used to drive both initial and additional purchases. 
         [0007]    The management and decision making tool disclosed herein can be configured to implement a comprehensive solution (also referred to as the Pricelock system) for price protection on retail commodities. Embodiments of the Pricelock system can be found in U.S. patent application Ser. No. 11/705,571, filed on Feb. 12, 2007, by Fell et al., entitled “METHOD AND SYSTEM FOR PROVIDING PRICE PROTECTION FOR COMMODITY PURCHASING THROUGH PRICE PROTECTION CONTRACTS,” which is incorporated herein as if set forth in full. 
         [0008]    Various embodiments provide a number of advantages. Some embodiments allow a consumer to select from a number of standard hedging scenarios and to see the savings such choices might cause in the future (or would have caused in the past). In some embodiments, the savings may be based on estimates of, or actual, commodity consumption patterns. These patterns may be adjusted by the user, in some embodiments, for changes in the consumer&#39;s expected consumption patterns. Some embodiments allow what-if cases to be studied in view of the hedging scenarios. Such what-if scenarios can “shock test” the purchasing decision with hypothetical exogenous events. Comparison shopping of the various hedging scenarios is enabled by some embodiments. Various embodiments enable more informed commodity decision purchases and eliminate, or at least reduce, uncertainty from commodity purchase decisions. Some embodiments enable the development of a risk profile associated with the commodity and adjust the displayed hedging scenarios based upon the risk profile. Embodiments can also be adaptive, interactive, and easy to use. Various embodiments save the consumer and the price protection service provider time, effort, and expense in reaching an agreement regarding which hedging scenario to execute. 
         [0009]    Other objects and advantages of the present disclosure will become apparent to one skilled in the art upon reading and understanding the detailed description of the embodiments described herein. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS  
         [0010]    A more complete understanding of the disclosure and the advantages thereof may be acquired by referring to the following description, taken in conjunction with the accompanying drawings in which like reference numbers generally indicate like features and wherein: 
           [0011]      FIG. 1  illustrates one embodiment of a method of calculating and displaying estimated future commodity costs. 
           [0012]      FIG. 2  illustrates one embodiment of a method of calculating and displaying estimated hedged commodity costs. 
           [0013]      FIG. 3  illustrates one embodiment of a system for managing hedging scenarios associated with a retail commodity and making decisions pertaining thereto. 
           [0014]      FIG. 4  illustrates a screenshot of a one embodiment of graphical user interface for managing hedging scenarios associated with a retail commodity and making decisions pertaining thereto. 
           [0015]      FIG. 5  illustrates another screenshot of a one embodiment of graphical user interface for managing hedging scenarios associated with a retail commodity and making decisions pertaining thereto. 
           [0016]      FIG. 6  illustrates another screenshot of a one embodiment of graphical user interface for managing hedging scenarios associated with a retail commodity and making decisions pertaining thereto. 
           [0017]      FIG. 7  illustrates yet another screenshot of a one embodiment of graphical user interface for managing hedging scenarios associated with a retail commodity and making decisions pertaining thereto. 
           [0018]      FIG. 8  illustrates another screenshot of a one embodiment of graphical user interface for managing hedging scenarios associated with a retail commodity and making decisions pertaining thereto. 
       
    
    
     DETAILED DESCRIPTION  
       [0019]    The disclosure and the various features and advantageous details thereof are explained more fully with reference to the non-limiting embodiments that are illustrated in the accompanying drawings and detailed in the following description. Descriptions of well known starting materials, processing techniques, components and equipment are omitted so as not to unnecessarily obscure the disclosure in detail. Skilled artisans should understand, however, that the detailed description and the specific examples, while disclosing preferred embodiments, are given by way of illustration only and not by way of limitation. Various substitutions, modifications, additions or rearrangements within the scope of the underlying inventive concept(s) will become apparent to those skilled in the art after reading this disclosure. 
         [0020]    Before discussing specific embodiments, an embodiment of a hardware architecture for implementing certain embodiments is described herein. One embodiment can include a computer communicatively coupled to a network (the Internet in some embodiments). As is known to those skilled in the art, the computer can include a central processing unit (“CPU”), at least one read-only memory (“ROM”), at least one random access memory (“RAM”), at least one hard drive (“HD”), and one or more input/output (“I/O”) device(s). The I/O devices can include a keyboard, monitor, printer, electronic pointing device (such as a mouse, trackball, stylist, etc.), or the like. In various embodiments, the computer has access to at least one database over the network. 
         [0021]    ROM, RAM, and HD are computer memories for storing computer-executable instructions executable by the CPU. Within this disclosure, the term “computer-readable medium” is not limited to ROM, RAM, and HD and can include any type of data storage medium that can be read by a processor. In some embodiments, a computer-readable medium may refer to a data cartridge, a data backup magnetic tape, a floppy diskette, a flash memory drive, an optical data storage drive, a CD-ROM, ROM, RAM, HD, or the like. 
         [0022]    The functionalities and processes described herein can be implemented in suitable computer-executable instructions. The computer-executable instructions may be stored as software code components or modules on one or more computer readable media (such as non-volatile memories, volatile memories, DASD arrays, magnetic tapes, floppy diskettes, hard drives, optical storage devices, etc. or any other appropriate computer-readable medium or storage device). In one embodiment, the computer-executable instructions may include lines of complied C++, Java, HTML, or any other programming or scripting code. 
         [0023]    Additionally, the functions of the disclosed embodiments may be implemented on one computer or shared/distributed among two or more computers in or across a network. Communications between computers implementing embodiments can be accomplished using any electronic, optical, radio frequency signals, or other suitable methods and tools of communication in compliance with known network protocols. 
         [0024]    As used herein, the terms “comprises,” “comprising,” “includes,” “including,” “has,” “having” or any other variation thereof, are intended to cover a non-exclusive inclusion. In some embodiments, a process, process, article, or apparatus that comprises a list of elements is not necessarily limited only those elements but may include other elements not expressly listed or inherent to such process, process, article, or apparatus. Further, unless expressly stated to the contrary, “or” refers to an inclusive or and not to an exclusive or. In some embodiments, a condition A or B is satisfied by any one of the following: A is true (or present) and B is false (or not present), A is false (or not present) and B is true (or present), and both A and B are true (or present). 
         [0025]    Additionally, any examples or illustrations given herein are not to be regarded in any way as restrictions on, limits to, or express definitions of, any term or terms with which they are utilized. Instead these examples or illustrations are to be regarded as being described with respect to one particular embodiment and as illustrative only. Those of ordinary skill in the art will appreciate that any term or terms with which these examples or illustrations are utilized will encompass other embodiments which may or may not be given therewith or elsewhere in the specification and all such embodiments are intended to be included within the scope of that term or terms. Language designating such nonlimiting examples and illustrations includes, but is not limited to: “for example”, “for instance”, “e.g.”, “in one embodiment”. 
         [0026]    Within this disclosure, the term “commodity” refers to an article of commerce—an item that can be bought and sold freely on a market. It may be a product which trades on a commodity exchange or spot market and which may fall into one of several categories, including energy, food, grains, and metals. Currently, commodities that can be traded on a commodity exchange include, but are not limited to, crude oil, light crude oil, natural gas, heating oil, gasoline, propane, ethanol, electricity, uranium, lean hogs, pork bellies, live cattle, feeder cattle, wheat, corn, soybeans, oats, rice, cocoa, coffee, cotton, sugar, gold, silver, platinum, copper, lead, zinc, tin, aluminum, titanium, nickel, steel, rubber, wool, polypropylene, and so on. Note that a commodity can refer to tangible things as well as more ephemeral products. Foreign currencies and financial indexes are examples of the latter. For example, positions in the Goldman Sachs Commodity Index (GSCI) and the Reuters Jefferies Consumer Research Board Index (RJCRB Index) can be traded as a commodity. What matters is that something be exchanged for the thing. New York Mercantile Exchange (NYMEX) and Chicago Mercantile Exchange (CME) are examples of a commodity exchange. Other commodities exchanges also exist and are known to those skilled in the art. 
         [0027]    In a simplified sense, commodities are goods or products with relative homogeneousness that have value and that are produced in large quantities by many different producers; the goods or products from each different producer are considered equivalent. Commoditization occurs as a goods or products market loses differentiation across its supply base. As such, items that used to carry premium margins for market participants have become commodities, of which crude oil is an example. However, a commodity generally has a definable quality or meets a standard so that all parties trading in the market will know what is being traded. In the case of crude oil, each of the hundreds of grades of fuel oil may be defined. For example, West Texas Intermediate (WTI), North Sea Brent Crude, etc. refer to grades of crude oil that meet selected standards such as sulfur content, specific gravity, etc., so that all parties involved in trading crude oil know the qualities of the crude oil being traded. Motor fuels such as gasoline represent examples of energy-related commodities that may meet standardized definitions. Thus, gasoline with an octane grade of 87 may be a commodity and gasoline with an octane grade of 93 may also be a commodity, and they may demand different prices because the two are not identical—even though they may be related. Those skilled in the art will appreciate that other commodities may have other ways to define a quality. Other energy-related commodities that may have a definable quality or that meet a standard include, but are not limited to, diesel fuel, heating oils, aviation fuel, and emission credits. Diesel fuels may generally be classified according to seven grades based in part on sulfur content, emission credits may be classified based on sulfur or carbon content, etc. 
         [0028]    Historically, risk is the reason exchange trading of commodities began. For example, because a farmer does not know what the selling price will be for his crop, he risks the margin between the cost of producing the crop and the price he achieves in the market. In some cases, investors can buy or sell commodities in bulk through futures contracts. The price of a commodity is subject to supply and demand. 
         [0029]    A commodity may refer to a retail commodity that can be purchased by a consuming public and not necessarily the wholesale market only. One skilled in the art will recognize that embodiments disclosed herein may provide means and mechanisms through which commodities that currently can only be traded on the wholesale level may be made available to retail level for retail consumption by the public. One way to achieve this is to bring technologies that were once the private reserves of the major trading houses and global energy firms down to the consumer level and provide tools that are applicable and useful to the retail consumer so they can mitigate and/or manage their measurable risks involved in buying/selling their commodities. One example of an energy related retail commodity is motor fuels, which may include various grades of gasoline. For example, motor fuels may include 87 octane grade gasoline, 93 octane grade gasoline, etc as well as various grades of diesel fuels. Other examples of an energy related retail commodity could be jet fuel, heating oils, electricity or emission credits such as carbon offsets. Other retail commodities are possible and/or anticipated. 
         [0030]    While a retail commodity and a wholesale commodity may refer to the same underlying good, they are associated with risks that can be measured and handled differently. One reason is that, while wholesale commodities generally involve sales of large quantities, retail commodities may involve much smaller transaction volumes and relate much more closely to how and where a good is consumed. The risks associated with a retail commodity therefore may be affected by local supply and demand and perhaps different factors. Within the context of this disclosure, there is a definable relationship between a retail commodity and the exposure of risks to the consumer. This retail level of the exposure of risks may correlate to the size and the specificity of the transaction in which the retail commodity is traded. Other factors may include the granularity of the geographic market where the transaction takes place, and so on. For example, the demand for heating oil No. 2 in January may be significantly different in the Boston market than in the Miami market. 
         [0031]      FIG. 1  is a flow diagram representing a simplified process  100  of calculating and graphically displaying estimated forward retail fuel costs, according to one embodiment. At step  101 , a user (a manager in some embodiments) inputs predicted fuel consumption in gallons by fuel type and location. This step can be implemented to allow as much granularity as possible. Step  101  can be configured to provide granularity per location, quantity, fuel type or grade, and time period. 
         [0032]    As to the location, the user may be allowed to input by retail station, zip code, MSA, county, state, country, etc. Input data then can be aggregated to the county level for pricing against NYMEX data. In some embodiments, if a user inputs fuel consumption in a number of locales, those zip codes can be rolled into their appropriate counties and the gallon consumption is compiled accordingly. 
         [0033]    As to quantity, the user may be allowed to enter the number of gallons per locale, per time period. The time period may be months, weeks, days, or any other duration. 
         [0034]    As to grade, the user may be allowed to enter the specific fuel type and/or grade (unleaded or diesel in some embodiments). In some embodiments, the fuel can be 87 octane unleaded gasoline. 
         [0035]    As to time period, the user may enter the time month by month or other time period as may be desired. In some embodiments, the time period may coincide with the time periods associated with an exchange&#39;s forward contract pricing. 
         [0036]    Step  101  can be implemented to use user inputs as estimates or obtain historical consumption data from historical feeds. In some embodiments, such data may originate at one or more transactional data aggregators such as Wright Express, WEX, or other fuel or credit card provider, fleet or logistics systems, or the like. A database can be being configured to automatically be populated with the historical consumption data. 
         [0037]    Step  102  can be optionally implemented to provide the user the ability to adjust the predicted fuel inputs to account for anticipated or potential variance from historical consumption patterns, particularly in the case where historical consumption data is used to populate the database as forward consumption patterns might differ from the historical data or estimate. Step  102  can be executed manually by the user or through a wizard program implementing the Pricelock “interview” process. The wizard program, which in one embodiment is implemented as a software module of the MDMT, can operate to analyze the existing data, ask the user which components of the predicted fuel consumption need to be modified (in some embodiments, these components can include specific location consumption changes, an overall volume increase of 10%, a new location, etc.), and display or highlight those fields requiring modification(s). 
         [0038]    Step  103  can be implemented to calculate estimated forward gasoline prices on a location, time, and grade basis and present them graphically over time. Embodiments which estimate forward gasoline prices are found in U.S. patent application Ser. No. 11/705,571, filed on Feb. 12, 2007, by Fell et al., entitled “METHOD AND SYSTEM FOR PROVIDING PRICE PROTECTION FOR COMMODITY PURCHASING THROUGH PRICE PROTECTION CONTRACTS,” which is incorporated herein as if set forth in full. Step  103  can be implemented to provide the user with the ability to selectively change the estimated forward gasoline prices and manually override certain estimated forward retail prices by desired locations and time periods. Step  103  can also be implemented to provide the user with the ability to import, or otherwise input, forward gasoline price estimates from other sources. In some embodiments, if a fleet card provider offers estimates for future fuel prices, these estimates could be displayed to the user and used in the corresponding analysis. 
         [0039]    Step  104  can be implemented to calculate the total estimated fuel cost based on user inputs from steps  101  and  102  such as price, usage at the location(s) over specific time periods, utilizing output data that can be graphically represented in step  103  to sum the total retail gasoline prices in numeric form, based on locations, volume, and specified time. 
         [0040]    Step  105  can be implemented to allow the user to adjust the total estimated fuel costs, take into consideration user selected event(s), and utilize underlying data obtained/generated so far. This can allow the user to add sensitivities to the total estimated fuel costs. Embodiments implementing sensitivity analysis are described in U.S. patent application Ser. No. 11/705,571, filed on Feb. 12, 2007, by Fell et al., entitled “METHOD AND SYSTEM FOR PROVIDING PRICE PROTECTION FOR COMMODITY PURCHASING THROUGH PRICE PROTECTION CONTRACTS,” which is incorporated herein as if set forth in full. 
         [0041]      FIG. 2  is a flow diagram representing process  200  of calculating and graphically displaying estimated forward retail fuel costs with various hedging scenarios, according to some embodiments. Steps  201  and  202  can be essentially the same as steps  101  and  102  described above. 
         [0042]    At step  203 , based on the estimated fuel consumption data from step  201  or  202 , available hedge positions and associated Pricelock pricing can be presented to the user. Step  203  can be implemented in many ways. In some embodiments, available hedge positions and associated Pricelock pricing can be presented as hedging scenarios or risk profiles. In some embodiments a risk profile may be built for the user. In some embodiments, a set of pre-defined options may be presented to the user. 
         [0043]    In some embodiments, the user may select a “risk profile” or a hedge position corresponding to a desired coverage. After the selection is made, the user (a fleet manager in some embodiments) can be taken through a series of questions relating to various considerations such as 1) risk tolerance; 2) available cash resources; 3) interest in financing prepayment of fuel; 4) willingness to ‘push’ drivers to affinity and/or preferred stations, etc. 
         [0044]    Additionally, step  203  can be implemented to consider product definition variables including, but not limited to, the amount of total gasoline purchases to “lock”, the percentage of gasoline desired to be purchased at affinity and/or preferred stations, a tolerance above the “lock” price that would deplete a virtual reserve tank (which may be referred to as the Pricelock Gasoline Tank in some embodiments). The Pricelock Gasoline Tank may be representative of the amount of fuel, in gallons and dollars, that can be pre-purchased and locked in at a certain price per gallon. 
         [0045]    Independent of steps  201 ,  202 , and  203  (i.e., pre-user input), step  204  can be implemented to calculate matrices of available lock prices and insurance/hedge costs per gallon. Due to constantly changing gasoline prices, consumption patterns, and forward contract prices, these matrices may be priced dynamically and continuously. 
         [0046]    According to one embodiment, inputs  250  can be a multi-dimensional matrix of strike prices for all available locations (the approximately 4000 counties in the United States in some embodiments) for that day, provided by a hedging partner, along with the hedge cost per gallon (HCPG) charged by the hedging partner. The HCPG is the lock insurance cost according to one embodiment. Based on inputs  250 , step  204  may operate to generate Pricelock matrices, which may include fuel type, locations, lock insurance costs, lock strike prices, Pricelock markup, affinity/preferred discount percentage and term (duration). Step  204  can be implemented to provide a separate multi-dimensional analysis table for each fuel/time. In one embodiment, step  204  can be implemented to display Pricelock lock prices by product type (including a preference to purchase from affinity retailers along with a preference to lock at a 10% tolerance above lock price in some embodiments) and optionally in price per gallon. In one embodiment, step  204  can be implemented to graphically display, via a national map, a Pricelock Lock Price matrix (location, grade, time) for lock prices and insurance/hedge costs. 
         [0047]    Step  205  can be implemented to apply Pricelock matrices (step  204 ) to the predicted fuel consumption (step  201  or  202 ) to calculate the estimated fuel cost under different hedging scenarios (chosen by the user at step  203 ). In some embodiments, if the user chooses to “pricelock” in unleaded gasoline over a 3-month period, with a lock price of $3.20, a purchase tolerance of $0.05 (meaning that the Pricelock Gasoline Tank may only be depleted when the price of retail gasoline is $3.25 in some embodiments) and does not wish to participate in affinity discounts, the Pricelock matrix for unleaded gasoline may have a “lock price” calculated for this product mix (which can reflect a composite of the various components described above with reference to step  204 ) for each county. This “lock price” by county can be multiplied by the number of gallons by county (entered by the user in step  201 ) to calculate a total pre-purchase amount. 
         [0048]    Step  206  can be implemented to calculate the savings by comparing the estimated fuel costs with and without hedging. More specifically, the estimated fuel cost generated in step  105  of process  100  (which can be used as a baseline cost) may be compared with the estimated hedged cost generated in step  205  of process  200 . 
         [0049]    Step  207  can be implemented to represent both the baseline and the hedged estimated fuel costs graphically or numerically. Step  207  can be implemented to dynamically change the graphical representation of costs/savings to reflect hedging choices the user makes. In some embodiments, if the user (a fleet manager in some embodiments) chooses to “lock in” only 50% of the fleet&#39;s anticipated fuel consumption over a prescribed period, the savings can be dynamically and correspondingly calculated and represented to facilitate the user to compare costs and make informed decisions. 
         [0050]    Additionally, step  207  can be implemented to allow the user to adjust the savings based on external factors such as cost of funds (internal hurdle rates in some embodiments) and interest rates. This can be a useful feature in cases where a user chooses to utilize a financing partner to facilitate the pre-purchase of fuels. Step  208 , in some embodiments, can be implemented to adjust the estimated savings based on various what-if cases. These what-if cases can include, in some embodiments, hurricanes, wars, political changes, supply disruptions, interest rate changes, and various world events. 
         [0051]    As one skilled in the art can appreciate, embodiments disclosed herein can be implemented and/or augmented in many ways. In some embodiments, the management and decision tool can be further implemented to provide a theoretical historical savings analysis based on actual transactional data on fuel consumption and historical data on Pricelock lock prices. The results of this theoretical analysis can show a customer (in some embodiments, the customer can be a commercial fleet, a business, a governmental agency, etc.) how much savings “would have” been realized if they “would have” purchased fuel over some historical period of time. 
         [0052]    Theoretical historical savings analysis (comparing retail commodity purchases with hedged purchases in some embodiments) may consider the following consumer inputs: a) consumer consumption patterns by fuel grade, location and time period; b) Pricelock and/or other sources of transactional data of actual historical retail prices; and c) actual transactional data from one or more fuel card providers (which, in some embodiments, can be WEX, Voyager, etc.) if the consumer is an existing fuel card customer. 
         [0053]    The theoretical historical savings analysis may operate to combine inputs a, b and c in various ways to estimate commodity costs, by month, by fuel grade without utilizing the Pricelock functionality as described above. Moreover, the consumer can have the ability to modify inputs a, b, and c, and estimated costs if desired. 
         [0054]    For the estimate of the hedged position, the theoretical historical savings analysis may (based on the product choices defined by the consumer in step  205  in some embodiments), access the Pricelock pricing matrices from the beginning of a historical period defined by the consumer. The theoretical historical savings analysis can then provide a historical comparison between fuel costs estimated based on the consumer inputs and the Pricelock lock prices over the historical period of time or over some period of interest. 
         [0055]    The above-described analyses could be applied to historical consumption and historical market data, and using a matrix of historical strike prices and HCPG, and a backward looking “historical” pricing model, an analysis can be performed that shows a consumer what the savings “could have been” if they had purchased a fuel hedge. Similarly, if the customer is using Pricelock hedging and actual consumption is known, the benefit can be calculated in a similar manner. 
         [0056]      FIG. 3  illustrates price protection system  300  which consumer  302  can use to manage hedging scenarios and make decisions associated with purchasing a retail commodity. In some embodiments, system  300  includes consumer computer  304 , price protection service provider server  306 , financial institution computer  308 , and network  310 . Consumer computer  304  can include user input/output devices such as display  305  and can be any time of device capable of presenting graphical user interfaces (GUIs) (to be discussed more with reference to  FIGS. 4-9 ) to user  302  such as a PC, a laptop, a personal digital assistant, a mobile phone, etc. Server  306  can be any type of device capable of serving GUIs to consumer computer  304  and receiving matrices of available lock prices and insurance/hedge costs. Computer  308  can be any type of device capable of sending the matrices of available lock prices and insurance/hedge costs to price protection service provider  306 . In various embodiments, computer  306  can be part of the Pricelock system and can include CPU  314 , removable media device  316 , hard drive  318  or other type of long term memory, and can host MDMT including GUI  320  and interview wizard  322 . 
         [0057]    Network  310  can serve to allow the computers  304 ,  306 , and  308  to communicate with each other. In various embodiments, user  302  can use system  300  to obtain information about available price protection services. The consumer can use a client, web browser, etc. executing on consumer computer  304  to request from price protection service server  306  a GUI  320  which can contain the information about available price protection services. Server  306  can respond by sending consumer computer  304  requested GUI  320  via network  310  which can be the Internet, a WAN, a LAN, a wireless network, etc. Consumer computer  304  can display GUI  320  on display  305  and enable user  302  to navigate through the various pages, screens, etc. of GUI  320 . User  302  may also use GUI  320  via system  300  to select price protection services as disclosed herein. In some embodiments, system  300  includes fuel card provider  323  which can supply historic consumption data relevant to user  302 . System  300  can include information service provider  325  which can provide data regarding the commodity market. In some embodiments information service provider  325  can be Reuters or Bloom berg although many other information service providers are available and within the scope of the disclosure 
         [0058]    Embodiments of price protection service system  300  are described in U.S. patent application Ser. No. 11/705,571, filed Feb. 12, 2007, by Fell et al., entitled “METHOD AND SYSTEM FOR PROVIDING PRICE PROTECTION FOR COMMODITY PURCHASING THROUGH PRICE PROTECTION CONTRACTS,” which is incorporated herein as if set forth in full. 
         [0059]    With reference now to  FIG. 4 , screenshot  400  of one embodiment of GUI  320  is illustrated. Screenshot  400  can represent a screen from which user  302  can navigate to various features of the GUI. Screenshot  400  shows welcome tab  402 , lock-in tab  404 , account creation tab  406 , and account management tab  408 . Lock-in tab  402  can include a display  410  of the current lock price for 87 octane grade of a retail commodity which can be selected by user  302  using elements  412 . In this example the retail commodity is unleaded gasoline. User  302  can select between a local or national current lock price  410  with selection elements  413 . Lock-in tab  402  can also include a button or other element  414  to allow a consumer to navigate to a screen represented by screenshot  500  (of  FIG. 5 ) on which user  302  can begin to purchase a price protection service. In some embodiments, lock-in tab  402  (or other tabs or screens) can include a news display area  416  wherein news relevant to the commodity can be displayed. 
         [0060]    Regarding tab  404 , lock-in tab  404  can allow user  302  to navigate to screen  500 .  FIG. 5  shows screenshot  500  of one embodiment of GUI  320 . Screenshot  500  can correspond to account creation tab  404  and can include different areas  502  and  504 . In areas  502  and  504 , respectively, a consumer can determine possible savings associated with purchasing a price protection service and define a price protection service to purchase. Possible savings area  502  can include input elements  506  and  508  and results display  510 . In elements  506  and  508  user  302  can input how many miles they drive in a year (or some number of miles which they desire to input) and a price for a gallon of gasoline which they desire to enter respectively. In some embodiments, this price may be a price which user  302  believes will prevail during the period of interest to the user. GUI  320  can be configured in various embodiments to calculate the fuel cost associated with inputs  506  and  508 , compare it to the price user  302  would pay in accordance with various price protection services, and display resulting savings in display  510 . 
         [0061]    Price protection service definition area  504  of  FIG. 5  can display the current lock price  410  (adjusted for national or local results with elements  413  in some embodiments) and sub-area  512  in which user  302  can define the price protection service which they desire. Service definition sub-area  512  can include input element  514 , display elements  516 , input element  518 , display element  520 , and button  522 . Input  514  can allow user  302  to select, or input, the length of the service plan they desire. Display  516  may display a price (to user  302  in some embodiments) associated with obtaining the price protection service. In some embodiments, the price in display  516  can be on a price-per-gallon basis. Input element  518  can allow user  302  to input a desired quantity of the commodity which they desire to purchase via the price protection service. GUI  320  can be configured to use the information as displayed by elements  413 ,  514 ,  516 , and  518  in service definition area  504  to compute a cost for obtaining the price protection service defined by the information in area  504  and display it in result display element  520 . Button  522 , in some embodiments, may allow user  302  to navigate to a screen represented by screenshot  600  (of  FIG. 6 ) with which the service may be purchased. 
         [0062]      FIG. 6  illustrates screenshot  600  of one embodiment of GUI  320  for price protection system  300  (of  FIG. 3 ). Screenshot  600  can correspond to account creation tab  406  and can include two areas  602  and  604 . Purchase finalization area  602  can reflect information (in some embodiments, current lock price  410 , local/national selection  413 , length of protection  514 , service price  516 , and commodity amount  518 ) displayed or entered on tabs  400  and  500 . In some embodiments such information may be modified on tab  600 . Purchase finalization area  602  can include elements such as element  603  which can allow users to select various options associated with the purchase. In some embodiments, element  603  can relate to a carbon offset which can be associated with purchasing amount  518  of the commodity Many other options are available and can be represented on screen  600 . GUI  320  can be configured to use information from tabs  402 ,  404 , and  406  to calculate fuel costs, price protection service costs, carbon offset fee costs, and total costs  610  for the price protection service(s) defined by user  302  and display these totals in displays  604 ,  606 ,  608 , and  610 . As shown by  FIG. 6 , area  604  can include tabs  601 ,  701 , and  801 . In some embodiments, tab  601  can include area  612  for a consumer with an existing account on system  300  to log in.  FIG. 6  shows that tab  601  can include area  614  for a consumer (who may happen to be new to the system  300 ) to create an account. 
         [0063]    In various embodiments, selection of tab  701  may allow a consumer to navigate to a portion of GUI  320  with which user  302  can pay for the selected price protection service. In various embodiments clicking on either buttons  616  or  618  of  FIG. 6  (to login or create an account) may also allow the user to navigate to tab  701 . Tab  701 , as depicted by  FIG. 7 , can include elements allowing a user to pay for their purchase using a credit card, electronic funds transfers, etc. In some embodiments, tab  701  can include an element  704  which can enable a consumer to obtain a loan to pay the full, or a portion of, the up-front cost  610  of the service. Examples of payment options are disclosed in U.S. patent application Ser. No. ______ (Attorney Docket No. PRICE1170-1), entitled “SYSTEM AND METHOD FOR ENABLING HEDGING CUSTOMERS TO LOCK FORWARD POSITIONS WITH CUSTOMER-FRIENDLY PAYMENT OPTIONS,” by Fell et al, filed February ______, 2008, which is incorporated herein as if set forth in full. In this manner, user  302  can choose not to expend any funds up-front. Button  706  can be included in tab  701  to enable user  302  to submit the terms of the service (defined as described herein) and the terms of payment to system  300  of  FIG. 3  for acceptance by system  300 . System  300  (of  FIG. 3 ) can verify the financing information from tab  701  and confirm that the requested price protection service is available, and return receipt  800  (of which an embodiment is shown in  FIG. 8 ) to user  302  via GUI  320 . 
         [0064]    In some embodiments, GUI  320  can present more than one type of hedging scenario to user  302 . Such hedging scenarios can include: purchasing the commodity at a retail price; purchasing the commodity at current lock price  410 , purchasing the commodity at lock price  410  plus a mark-up, purchasing the commodity at lock price  410  minus a mark-down, purchasing the commodity within a symmetric price collar about lock price  410 , or purchasing the commodity within an asymmetric collar about lock price  410 . In some embodiments, a collar can be a financial structure including a put and a call associated with the commodity. When the collar is symmetric, the put and the call can be equidistant from the at-the-money point. When the collar is asymmetric, the put and the call can be different distances from the at-the-money point. 
         [0065]    For each hedging scenario, GUI  320  can display the projected resulting savings based on a comparison between the forward retail price(s) and purchasing according to the corresponding hedging scenario. System  300  can be configured to calculate these projected resulting savings. GUI  320  can include input elements (or displays as the case may be) for information related to the hedging scenarios. Such information can include, but is not limited to: price protection service period, retail price of the retail commodity, a locale, the current retail price, current lock price  410 , a desired mark-up, a desired mark-down, an upper collar limit, and a lower collar limit. In some embodiments, GUI  320  can also include a series of buttons corresponding to the displayed hedging scenarios. GUI  320  can be configured such that clicking on one of buttons indicates that user  302  has selected the corresponding hedging scenario for purchase. GUI  320  can navigate user  302  to a portion of GUI  320  similar to that illustrated in  FIG. 7  (with the appropriate items of information filled in automatically in some embodiments) so that user  302  can review and purchase the selection if desired. 
         [0066]    Although embodiments have been described in detail herein, it should be understood that the description is by way of example only and is not to be construed in a limiting sense. It is to be further understood, therefore, that numerous changes in the details of the embodiments and additional embodiments will be apparent, and may be made by, persons of ordinary skill in the art having reference to this description. It is contemplated that all such changes and additional embodiments are within scope of the following claims and their legal equivalents.