Abstract:
Expense data is accessed for one or more expense types. An initial average expense is computed for one or more of the expense types and the computed average expenses are presented to a user. A user selection is received of an item corresponding to an expense type, and expense data for the item is entered. An updated average expense is computed for the expense type associated with the item based upon the expense data for the item.

Description:
TECHNICAL FIELD  
       [0001]     This disclosure relates to a self-adjusting context aware expense system.  
       BACKGROUND  
       [0002]     Businesses typically desire to lower expenses in order to stay competitive. Rigorous, unilateral cost cutting measures or the establishment of absolute cost ceilings may yield acceptable results in the short term. However, in the mid to long term, such measures have the potential to lower employee satisfaction and productivity, thus endangering the competitiveness of businesses.  
         [0003]     One technique for cost cutting is the unilateral setting of maximum allowed amounts for target costs. The unilateral cost ceiling may be set globally, or regional variations may be allowed. For example, cost ceilings may be set globally for certain travel expenses such as hotel rooms and meal costs. The ceilings may be uniform or may vary by geographic region such as country, state/province, or city. The ceilings may be set without due consideration of actual costs and without consideration of the quality of the goods and services purchased. Also, once set, the cost ceilings are not updated with sufficient regularity to reflect changes in costs due to factors such as inflation, deflation, and seasonal variations. Also, the cost ceilings do not account for specials that may be offered from time to time by the suppliers of goods and services.  
         [0004]     Employees may become demoralized by the setting of unrealistic cost ceilings. Further, the setting of a static cost ceiling provides no incentive for an employee to seek further measures to reduce costs. Thus, short term cost cutting results may be achieved, but further benefits will not be realized in the mid to long term. Also, static cost ceilings do not provide management with effective reporting tools to track the expense activity, set appropriate cost guidelines, and motivate employees to look for further cost cutting opportunities.  
       SUMMARY  
       [0005]     Implementations described below provide techniques for enabling a business to minimize expenses in the short term, while minimizing negative side effects in the mid to long term. A self-adjusting and context-aware method and system are disclosed to drive down expenses while also minimizing the negative side effects from the expense minimization. The system may be used in the context of various expenses encountered by a business or by an individual. For example, the system may be used to track and encourage the lowering of travel expenses, overhead expenses, administrative expenses, business development expenses, training expenses, recruiting expenses, entertainment expenses, and acquisition/purchasing expenses for purchasing goods and services, among others. A single system may be used to monitor the various expenses, or separate systems may be used as desired. The system may be integrated with existing purchasing, portal, and expense tracking systems, e.g., by proposing a modular, add-on system structure and business process.  
         [0006]     The expense behavior of one expense producing party is quantified relative to the dynamically computed average expense behavior of a group of expense producing parties. For example, the average price of a specific service or asset may be computed based upon purchases made within in a specific geographic region, within a specific period of time (e.g., the last three weeks). The price may be computed for all employees or for certain employees, groups of employees, or organizations within the business. The average price is continually computed and updated as new data is received.  
         [0007]     Since the average costs for assets or services are derived from real-life transactions, these averages can be used as automatically self-adjusting, realistic target limits for cost cutting measures. This helps to minimize frustration among employees that would otherwise be caused by unrealistic cost cutting demands based on incorrect cost target data or false estimates of costs. At the same time, fraud may be detected by, for example, deploying software agents to search for specific patterns or exceptions in the available data pool.  
         [0008]     Cost saving behavior is incentivized and rewarded. For example, when an employee acquires the service or asset for a lower amount than its current average price, the employee may be credited with a “point” for each dollar saved. Accumulated points may then be turned into a benefit, as typically selected the company. Benefits may include, for example, bonus payments, additional holidays, additional time off, or perks such as reserved parking privileges. The reward system may be implemented similarly to mileage programs of air carriers or point programs of hotel chains.  
         [0009]     A “specific reporting” feature of the system allows management to gain granular insights into where costs are saved within the organization. This reporting feature also allows cost saving employees to gain positive visibility within the organization, thus motivating others to follow suit.  
         [0010]     In one implementation, expense producing parties are able to share ratings of the received services or assets to provide not only cost-savings-driven metrics, but also quality-driven metrics. Data on where and how assets have been acquired are typically made available to all internal parties, so as to ensures re-use of well-proven purchasing sources as well as encouraging expense producing parties to find new, even better deals in order to gather “points”. The quality driven metrics may be combined with the cost savings metrics in order to provide a best value purchase to the organization.  
         [0011]     In another implementation, providers of goods and services are able to preemptively offer their specific goods and services to purchasing parties, thus shortening the latency of the system detecting sound opportunities. For example, a service provider may offer a “special” price for a given service if purchased during a specific period of time or in a specific quantity.  
         [0012]     Also, contextual data may be incorporated to account for factors that typically affect the pricing of assets or services such as, for example, seasons, special events, special locations, etc.  
         [0013]     By allowing enterprise applications to access the continually gathered data, a variety of additional benefits can be realized such as, for example, better cost forecasting and planning, faster and more effective purchasing processes, and sharing of current and anticipated demand data with providers, among other business benefits.  
         [0014]     According to one general aspect, expense data is accessed for one or more expense types. An initial average expense is computed for one or more of the expense types and the computed average expenses are presented to a user. A user selection is received of an item corresponding to an expense type, and expense data for the item is entered. An updated average expense is computed for the expense type associated with the item based upon the expense data for the item.  
         [0015]     Implementations may include one or more of the following features. For example, the expense data may be provided. The expense data may include, for example, an expense type, an expense amount, an expense date and an expense location. Ratings data may be provided and associated with the expense data. The presentation to the user may be based at least in part on the ratings data. Context data may be provided and associated with the expense data. The presentation to the user may be based at least in part on the context data. The context data may include special events data, weather data, local data, and an specific expense limit. Also, user data may be provided and associated with the expense data. The presentation to the user may be based at least in part on the user data. The user data may include a user preference, a user purchase history, and a user reward point total. Service data may be provided and associated with the expense data. The presentation to the user may be based at least in part on the service data. The service data may include an offer, a special offer, and a local standard cost. The expense data may be reported to the user, and may include exception reporting and forecasting based upon the expense data.  
         [0016]     The expense data may be accessed, for example, by pulling the expense data from a data store. The expense data may include travel expense data and may be accessed from a travel expense application. The expense data may include asset purchasing data and may be accessed from an asset purchasing application.  
         [0017]     The expense data may be analyzed to determine cost savings. A difference may be calculated between the expense data for the item and the initial average expense for the expense type associated with the item, and a reward may be provided to the user based upon the calculated difference. A difference may be calculated between the expense data for the item and the initial average expense for the expense type associated with the item, a number of points may be assigned corresponding to the difference and the points may be associated with the user. A reward may be provided to the user based upon the number of points.  
         [0018]     In another general aspect, an apparatus may include a smart expense application running on a host device. The smart expense application is configured to access expense data in a database, compute initial average expense data based upon the accessed expenses data, present the initial average expense data to the client device, display the initial average expense data to a user, receive a user selection to order an item comprising an expense, receive expense data for the item, and compute an updated average expense upon the expense data for the item.  
         [0019]     Implementations may include one or more of the following features. For example, the smart expense application may be further configured to access the expense data in an application, to access user data, to access service data, and to access context data. The smart expense application may be further configured to interface with other applications.  
         [0020]     The smart expense application may be configured to calculate a difference between the expense data for the item and the initial average expense for the expense type corresponding to the item and assign a number of points corresponding to the difference. The smart expense application may be further configured to provide a reward to the user based upon the number of points.  
         [0021]     The details of one or more implementations are set forth in the accompanying drawings and the description below. Other features will be apparent from the description and drawings, and from the claims. 
     
    
     DESCRIPTION OF DRAWINGS  
       [0022]      FIG. 1  is a diagram of a self-adjusting context aware expense system.  
         [0023]      FIG. 2  is an exemplary set of expense data that may be used by the system of  FIG. 1 .  
         [0024]      FIG. 3  is an exemplary flow diagram of a method for reducing expenses using the system of  FIG. 1 . 
     
    
     DETAILED DESCRIPTION  
       [0025]      FIG. 1  shows an example of a self-adjusting context aware expense system  100 . The system  100  includes a smart expense application  105  configured to interact with a user  110 . The smart expense application  105  typically is a software application running on a general purpose computer. In one implementation, the smart expense application  105  may reside on a host computer in a client/host architecture. The user  10  may include a client computer in a client/host architecture. In another implementation, the smart expense application  105  may reside on a client computer, which may be the same client computer employed by the user  110  or may be a different client computer in communication with the user  110 .  
         [0026]     A client computer or a host computer may include one or more general-purpose computers (e.g., personal computers), one or more special-purpose computers (e.g., devices specifically programmed to communicate with each other and/or the client system or the host system), or a combination of one or more general-purpose computers and one or more special-purpose computers. Other examples include a mobile device, including a mobile phone or a personal digital assistant (PDA), a workstation, a server, a device, a component, other physical or virtual equipment, or some combination of these capable of responding to and executing instructions. The client computer and the host computer may include devices that are capable of establishing peer-to-peer communications. The client computer and the host computer may be arranged to operate within or in concert with one or more other systems, such as, for example, one or more LANs (“Local Area Networks”) and/or one or more WANs (“Wide Area Networks”).  
         [0027]     The client computer may communicate with the host computer over a communications link. A communications link typically includes a delivery network that provides direct or indirect communication between the client computer and the host computer, irrespective of physical separation. Examples of a delivery network include the Internet, the World Wide Web, WANs, LANs, analog or digital wired and wireless telephone networks (e.g., Public Switched Telephone Network (PSTN), Integrated Services Digital Network (ISDN), and Digital Subscriber Line (xDSL)), radio, television, cable, or satellite systems, and other delivery mechanisms for carrying data including, for example, a wired, wireless, cable or satellite communication pathway.  
         [0028]     An example of the smart expense application  105  is a software application loaded on a client computer or a host computer for commanding and directing communications enabled by the client computer or the host computer. Other examples include a program, a piece of code, an instruction, a device, a computer, a computer system, or a combination of these for independently or collectively instructing a computer to interact and operate as described. The smart expense application  105  may be embodied permanently or temporarily in any type of machine, component, physical or virtual equipment, storage medium, or propagated signal capable of providing instructions to the client computer and the host computer.  
         [0029]     As shown, the smart expense application  105  is configured to access travel expense report data. In one implementation, the travel expense report data is part of the travel expense application  115 . The travel expense application  115  may be a separate software application for maintaining travel expense data. In another implementation, the travel expense report data may be contained in a separate database, or the travel expense application  115  may be simply a database of travel expense report data. Travel expense reports, by their nature, contain detailed information about costs that were actually incurred. The information may include expense type, location and time. The smart expense application  105  typically is configured to compute the average costs for each expense type and location within a specific time period, using the accessed travel expense data.  
         [0030]     In other implementations, the smart expense application  105  may be configured to access additional expense data or different expense data altogether. For example, the smart expense application  105  may be configured to access computer equipment purchasing data from external sources in addition to or in place of accessing travel expense data. The travel expense application  115  may be eliminated or supplemented with other applications  160 , including applications that provide different expense data.  
         [0031]     The smart expense application  105  may compute average costs for various expense types and store the average expense data  120  in a database or other data store. The smart expense application may, for example, read, write, or modify the average expense data  120 . Similarly, the smart expense application  105  may read, write, or modify user data  125 , service data  130 , and context data  135 . Service providers, suppliers, and manufacturers  150  may provide data to the smart expense application  105  or may cause data to be stored in a database or other data store for later use. The smart expense application  105  may communicate with a travel reservation application  140  and with a travel agent  145 . A reporting function  155  may be provided for reporting items to management.  
         [0032]     Referring now to  FIG. 2 , an example of travel expense report data  200  is shown. The travel expense report data  200  may be contained as a record within the travel expense application  115 . The data  200  includes an expense type  205 , a description  210  of the expense, an expense amount  215 , a currency type  220 , an expense date  225 , an expense location  228  including a city  230 , state  235 , and country  240 , and a user identity  245  of the person incurring the expense.  
         [0033]     In the example of  FIG. 2 , the data  200  may be organized according to expense type  205  and location  228 . In particular the data  200  includes three entries  255   a ,  255   b , and  255   c  for hotel expense data  255  in New York, N.Y., three entries  260   a ,  260   b , and  260   c  for dinner expense data  260  in New York, N.Y., four entries  265   a ,  265   b ,  265   c , and  265   d  for lunch expense data  265  in New York, N.Y., three entries  270   a ,  270   b , and  270   c  for hotel expense data  270  in Denver, Colo., and three entries  275   a ,  275   b , and  275   c  for dinner expense data  275  in Denver, Colo.  
         [0034]     The smart expense application  105  may compute the average costs  250  for an expense type  205 , location  228 , and date  225 . As shown in  FIG. 2 , the average price  257  of a hotel room in New York, N.Y., USA in November 2002 for one night is $183.00. The average price  257  is computed using the hotel expense data  255 . The average price  262  of a dinner in New York, N.Y., USA in November 2002 is $49.00, and is computed using the dinner expense data  260 . The average price  267  of a lunch in New York, N.Y., USA in November 2002 is $32.00, and is computed using the lunch price data  265 . The average price  272  of a hotel room in Denver, Colo., USA in November 2002 for one night is $119.00, and is computed using the hotel price data  270 . Finally, the average price  277  of a dinner in Denver, Colo., USA in November 2002 is $27.00 and is computed using the dinner price data  275 .  
         [0035]     Referring to  FIGS. 1 and 2 , as new expense data is entered, the smart expense application  105  computes the average costs. The averages costs  250  may be saved as average expense data  120  in a database or other data store. The average expense data  120  may be stored locally on the same computer or computers with the smart expense application  105 , or may be stored remotely from the smart expense application  105 . The smart expense application  105  may continually compute the average costs, periodically computer the average costs, or compute the average costs when a certain event occurs, such as the addition of new data or by a user entered command. The average expense data  120  may include average expense data for the various types of expenses managed by the smart expense application  105 . The average expense data  120  may include averaged data by one or more of location, time, season, or user or user group.  
         [0036]      FIG. 3  illustrates an exemplary process  300  using the system  100  of  FIG. 1 . In the process  300 , the user  110  first connects to the smart expense application  105  prior to making travel arrangements (step  305 ). The user  110  then inputs information such as a travel destination and departure time, and may also input a start location and return time (step  310 ). Other data such as arrival times also may be input.  
         [0037]     A decision is made as to whether specific data may be retrieved (step  315 ). If not, the information such as user identity, destination, departure time, start location and return time are sent to a travel agent  145  for booking (step  320 ).  
         [0038]     If specific data may be retrieved (step  325 ), then the smart expense application  105  will present the known, specific average expense data  250  to the user  110 , so that the user  110  may review the data and become familiar with the specific cost structures at the chosen travel destination and time.  
         [0039]     The smart expense application  105  may access user data  125 . The user data  125  may be stored locally on the same computer or computers with the smart expense application  105 , or may be stored remotely from the smart expense application  105 . In one implementation, the user data  125  may contain information such as a job profile, title or category, user preferences, travel history, and expense savings points accumulated by the user. Based on the user data  125  and the average expense data  120 , the smart expense application  105  will also propose the currently known and available, most affordable, yet well-rated specific options, e.g. food and hotel options, for the chosen travel destination and time. The smart expense application  105  may have access to real-time service availability checks. For example, by accessing the travel reservation application  140 , real time information such as hotel, flight, car rental, and restaurant availability information may be obtained and presented to the user  110 .  
         [0040]     Service ratings for the goods or services may be retrieved (step  330 ). Service ratings for goods or services may be submitted after thee goods are purchased or the services are rendered. The smart expense application  105  may store these service ratings in various locations. For example, the service ratings may be stored as part of service data  130  or as part of context data  135 . The service data  130  and/or the context data  135  may be stored locally on the same computer or computers with the smart expense application  105 , or may be stored remotely from the smart expense application  105 . The service ratings may be used by the smart expense application  105  in providing a recommendation to the user  110  based upon a “best value” approach by factoring in both cost and quality. For example, the lowest cost provider may not offer the best value purchase because of poor quality, which may necessitate further costs to be incurred in order to realize the expected value of the purchase.  
         [0041]     The smart expense application  105  may also present additional specific service offerings to the user  110  that are derived from accessing service data  130 . Service providers, suppliers, or manufacturers  150 , among others, may input the service data  130 . The service data  130  may include, for example, offers, specials, information, advertisements, or standard costs associated with the goods or services.  
         [0042]     Specific context data also may be retrieved (step  335 ). The smart expense application  105  may also access and present additional context data derived from context data  135 . The context data  135  may include, for example specific weather, special event, seasonal data, specific expense limits, or local data that may affect the pricing of goods and services at the travel destination in the targeted time.  
         [0043]     The smart expense application sorts options using the pricing, rating, and/or context data (step  340 ) and presents the data to the user (step  345 ).  
         [0044]     The smart expense application  105  will then allow the user  110  to pre-select desired options, if applicable (step  350 ). User preferences entered may also be saved (step  355 ).  
         [0045]     Upon entering the required data, the user  110  may start with the standard reservation process based on the pre-selected data (step  360 ). For example, the user  110  may proceed with making the reservation using a travel agent  145  or a self-service travel reservation application  140 .  
         [0046]     After the travel is completed, the user  110  submits a travel expense report to the travel expense application  115 . Upon submitting the travel expense report to the travel expense application  115 , the smart expense application  105  will compute the new average expense data  250  and will calculate the number of points that the user  110  gained by purchasing goods and services that were cheaper than the specific average expenses, if applicable. In another implementation, the smart expense application  105  may compute the new average expense data  250  when the user  110  completes the reservation process and new expense data is available based upon that transaction.  
         [0047]     For example, if the user  110  submits a travel expense report for a one day trip to New York, N.Y., USA in November of 2002 paying $163 for a hotel room, this data would be stored with the travel expense data  200  and may be associated with the New York Hotel expenses  255 . The new average price  257  would be computed based upon the new expense of $163 and the pre-existing data  255   a ,  255   b , and  255   c . Thus, after the data is entered, the new average price  257  would be $178. The user  110  would gain  20  points (former average price of $183 minus the actual expense of $163), assuming that the points are computed as one point for each dollar saved from the average applicable hotel expense  257 . For the next user traveling to New York, the new average hotel expense  257  would be computed as $178. Thus, the system  100  is self-adjusting and context aware. The system  100  dynamically updates the averages costs and encourages cost saving behavior by users. A variety of point and award rules may be implemented.  
         [0048]     If prices were to rise due to, for example, a general increase in the cost of obtaining the goods or services, this trend would be captured by the system  100 . Thus, the numbers used by the system  100  reflect reality, and users are incentivized, not penalized for cost saving behavior in an inflationary market.  
         [0049]     The smart expense application  105  is able to maintain and present a statement of the point account of the user  110  upon request. For example, the point account balance may be presented to the user  110  using the reporting  155  feature of the system  100 . The reporting  155  feature may also be used for other reporting, forecasting and planning functions. For example, the reporting  155  feature may be used for in-depth reporting across user groups, destinations, and expense types and may be used to generate reports for upper management. Also, the reporting  155  feature may be used for real-time exception reporting when costs change dramatically in a specific segment, for example to report an inflationary market in certain goods and services in a certain geographic location.  
         [0050]     The smart expense application  105  also may be configured to interfaces to other applications  160 . The other applications  160  may include other expense applications, data mining applications, forecasting applications, real-time exception messaging applications, and/or software agent-based applications such as fraud detection agent applications. For example, based on data derived from the smart expense application  105  using data mining, the location or time for an annual business conference may be changed due to a better-forecasted Return On Investment (ROI) at a newly identified location or time.  
         [0051]     A number of implementations have been described. Nevertheless, it will be understood that various modifications may be made. Accordingly, other implementations are within the scope of the following claims.