Abstract:
A method, an apparatus, and a computer program are provided to better analyze business activities. Metrics are utilized to mine information gathered on a businesses operations. At times of user labeled events, snap shots of the state of the business can be taken. Statistical analyses are performed on the data corresponding to the state of the business to determine if correlations between user labeled events and business activities. Therefore, a business can become more competitive by determining the behaviors that both help and hurt business operations.

Description:
FIELD OF THE INVENTION  
       [0001]     The present invention relates generally to business dashboards and, more particularly, to the improve performance of a business dashboard.  
       DESCRIPTION OF THE RELATED ART  
       [0002]     Over recent years, business dashboards have become more commonplace. Business dashboards are essentially visual representations of business events. Through the use of middleware, such as computer networks, dashboards are able to collect and harvest data about a business. For example, tracking sales for a particular business sector, like energy, are commonly measured. The varying measurements are then refined using a variety of statistical analyses, like regression analysis.  
         [0003]     The varying analyses, though, are of little use unless the information is provided to the correct persons. Hence, graphical and other user interfaces have been employed to provide information to employees. These employees, then, can use the information to make predictions and business judgments, which can lead to successes or failures, such as increase or decrease sales.  
         [0004]     However, it is not entirely clear as to how successes or failures are predicted or what may cause the successes or failures. Currently, such measurements or correlation techniques to determine the characteristics of both predictions and successes do not exist.  
         [0005]     Therefore, a need exists for a method and/or apparatus for determining the characteristics of predictions in a business dashboard environment that addresses at least some of the problems associated with conventional business dashboards.  
       SUMMARY OF THE INVENTION  
       [0006]     The present invention provides an apparatus, method, and computer program for debugging business activities. A plurality of metrics and a plurality of source databases are provided. Each metric is configured to choose and process data from the source databases according to predefined criteria to produce refined data. Also, the metrics are coupled to a user interface. Included in the middleware is a processor, wherein the processor utilizes statistically analysis with the refined data at or after a user labeled event. The statistical analysis determines if there is an association between the user defined event and the refined data.  
     
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0007]     For a more complete understanding of the present invention and the advantages thereof, reference is now made to the following descriptions taken in conjunction with the accompanying drawings, in which:  
         [0008]      FIG. 1  is a block diagram depicting a business dashboard system; and  
         [0009]      FIG. 2  is a flow chart depicting the operation of a business dashboard that measures states of companies. 
     
    
     DETAILED DESCRIPTION  
       [0010]     In the following discussion, numerous specific details are set forth to provide a thorough understanding of the present invention. However, those skilled in the art will appreciate that the present invention may be practiced without such specific details. In other instances, well-known elements have been illustrated in schematic or block diagram form in order not to obscure the present invention in unnecessary detail. Additionally, for the most part, details concerning network communications, electro-magnetic signaling techniques, and the like, have been omitted inasmuch as such details are not considered necessary to obtain a complete understanding of the present invention, and are considered to be within the understanding of persons of ordinary skill in the relevant art.  
         [0011]     It is further noted that, unless indicated otherwise, all functions described herein may be performed in either hardware or software, or some combination thereof. In a preferred embodiment, however, the functions are performed by a processor such as a computer or an electronic data processor in accordance with code such as computer program code, software, and/or integrated circuits that are coded to perform such functions, unless indicated otherwise.  
         [0012]     Referring to  FIG. 1  of the drawings, the reference numeral  100  generally designates a business dashboard system. The business dashboard  100  comprises middleware  102 , employee input  106 , other input  104 , and output  118 .  
         [0013]     In order for the business dashboard to operate and effectively measure the performance of a company, middleware  102  is utilized. The middleware  102  comprises a processor with an incorporated predictive algorithm  112 , a plurality of metrics  108 , and storage  114 . The plurality of metrics  108  is essentially the receiver portion of the middleware  102 . Each of the plurality of metrics  108  defines a manner in which a measurement can be taken. Typically, metrics  108  are subroutines that collect and mine data, wherein the data is derived from a specific source or type of source, such as financial databases. Metrics, too, can be tired to a user interface. By coupling a metric to a user interface, a user can easily manipulate the measurements for the middleware  102  and user labeled events. For example, if a metric is utilized to determine the state of a business that operates in multiple sectors, such as the energy industry, a metric can collect financial data, sales data, and so forth of a company concerning the energy industry. The metrics can collect data from employee input  106 , such as hourly time invested by an employee or employees, and can collect from other input  104 , such as from financial databases. Each of the employee inputs  106  and the other inputs  104  are coupled to the middleware  102  through a first communication channel  120  and a second communication channel  118  to provide the means of communication between the middleware  102  and the inputs  104  and  106 .  
         [0014]     Once the data has been collected, the data is then processed. A processor  112  is utilized to process the input data from the employee inputs  106  and the other inputs  104  that has been refined by the metrics  108 . Typically, the processor  112  employs a predictive or pattern recognition algorithm to determine possible patterns of behaviors that may have caused a particular event, be it a relatively good or bad event. The data from the plurality of metrics  108  is provided to the processor  112  through a third communication channel  126 . Once the predictive algorithm utilized by the processor  112  has processed the data refined by a metric  108 , a resultant, recognized pattern, if any, is communicated. The processor  112  can then store the resultant, recognized pattern, or lack thereof, in storage  114 . The processor  112  communicates the resultant, recognized pattern, or lack thereof, to storage through a fourth communication channel  130 .  
         [0015]     Once the data has been processed and stored, the recognized pattern can be displayed to a user. The recognized pattern is output from the middleware  102  to an output device  116  through a fifth communication channel  124 . The business dashboard  100 , though, does not appear to be different from conventional dashboards, except that the pattern recognition used by the processor  112  is substantially different.  
         [0016]     The predictive algorithm used by the processor  112  operates by effectively taking snap shot of the state of a company or division of a company. The processor  112  determines when a user labeled event, such as a good event or a bad event, has occurred. The good or bad event can be the improved sales or some recognized trend. For example, a recognized trend could be specific growth of a portion of an industrial sector. The processor  112  could be then prompted to take such a snap shot of the state of a company or division of a company. Once the snap shot of the state of the company or division of a company has been taken, then the predictive algorithm used by the processor  112  employs statistical analysis, such as regression analysis, to determine why the a user labeled event, such as a good event or a bad event, occurred. The event or prediction could be as a result of the type of information gathered by a specific employee, or the event could be as a result of chance when there appears to be no statistical significance.  
         [0017]     Referring to  FIG. 2  of the drawings, the reference numeral  200  generally designates a flow chart depicting the operation of a business dashboard that measures states of companies.  
         [0018]     The entire process of measuring the state of a company begins with data entry. In step  202 , data is entered into the business dashboard of  FIG. 1 . The data can be from multiple types of sources, such as employees or financial databases.  
         [0019]     The data that is entered, though, is meaningless unless the data is organized. Organization of data is accomplished through data mining. Data mining is the sorting and the selecting of data based on specified criteria, which is accomplished through the use of metrics. In step  204 , metric measurements are taken. Metrics are the specific manner in which data is measured. For example, return on investments, churn rates, revenues, and so forth are all metrics. The metrics are usually deployed in algorithms that mine the input data.  
         [0020]     Once the data has been mined, a determination of whether a user labeled event, such as a good or bad event, has occurred in step  206 . The user labeled event, such as good or bad events, can be characterized in many ways. For example, exceeding expected earnings for a particular sector and an employee prediction of a small market depression could be characterized as a good and bad event respectively. The characterization of user labeled events can be preprogrammed into the business dashboard  100  of  FIG. 1 , manually requested, or both. Additionally, the good or bad event can be selecting arbitrarily with no predefined criteria. In any event, if there has not been a good or bad event, then there is a determination of whether a periodic measurement of the state of the system should be taken in step  208 . If not, then the business dashboard  100  of  FIG. 1  simply continues to receive input in step  202 .  
         [0021]     However, if a user labeled event, such as a good event or a bad event, occurs or a request for a periodic measurement occurs, then the data is properly processed. For a user labeled event, such as a good event or a bad event, a snap shot of all of the input data is taken. Effectively, the state of the company or division of the company is captured. The data gathered by the specific metric is stored in step  210 . Then, an algorithm begins to analyze the data gathered by the metric in step  214 . Many types of statistical analyses, such as linear regression analysis, multiple regression analysis, nonlinear least square fitting, and so forth, can be employed to determine trends in step  216 . Once the business dashboard  100  of  FIG. 1  has completed the statistical analysis, an output pattern can be yielded in step  218 . The patterns can be as a result of the receipt of information to the correct employees or some other statistically significant phenomenon, or there may be no pattern at all.  
         [0022]     The benefit of utilizing such a dashboard system, such as the business dashboard  100  of  FIG. 1 , is to improve performance. By allowing a business to effectively take a snap shot of the company or division of the company at a user labeled events, such as good events or bad events, a company can determine what has been done correctly and incorrectly. Utilization of varying metrics in combination with the snap shots allows for a nearly infinite number of analyses that can be performed to determine the behavior or behaviors that caused an event. Therefore, a clear advantage of the business dashboard  100  of  FIG. 1  is the ability to determine correct and incorrect behavioral patterns by employees, markets, and others to better tailor business models and business behaviors to improve overall performance.  
         [0023]     It is understood that the present invention can take many forms and embodiments. Accordingly, several variations may be made in the foregoing without departing from the spirit or the scope of the invention. The capabilities outlined herein allow for the possibility of a variety of programming models. This disclosure should not be read as preferring any particular programming model, but is instead directed to the underlying mechanisms on which these programming models can be built.  
         [0024]     Having thus described the present invention by reference to certain of its preferred embodiments, it is noted that the embodiments disclosed are illustrative rather than limiting in nature and that a wide range of variations, modifications, changes, and substitutions are contemplated in the foregoing disclosure and, in some instances, some features of the present invention may be employed without a corresponding use of the other features. Many such variations and modifications may be considered desirable by those skilled in the art based upon a review of the foregoing description of preferred embodiments. Accordingly, it is appropriate that the appended claims be construed broadly and in a manner consistent with the scope of the invention.