Abstract:
A method for improving performance in a business organisation by facilitating competition between two or more different participants within the business, the method comprising; (a) one or more servers, and (b) one or more remote terminals accessible by the participants, wherein the method includes the steps of; (1) choosing a measure of participant performance, (2) inputting the measure of participant performance to a remote terminal, (3) calculating a score based on the measure of performance, the calculation being performed at the server, or performed at the remote terminal for communication to the server; (4) collating and ranking the scores, and (5) displaying the relative scores of the participants.

Description:
TECHNICAL FIELD OF THE INVENTION  
       [0001]     This invention relates to business management systems and, more specifically, to a system and method for evaluating disparate measures of performance so as to allow participants engaged in different business activities to compete against one another.  
       BACKGROUND OF THE INVENTION  
       [0002]     In this specification where a document, act or item of knowledge is referred to or discussed, this reference or discussion is not an admission that the document, act or item of knowledge or any combination thereof was at the priority date publicly available, known to the public, part of the common general knowledge or known to be relevant to an attempt to solve any problem with which this specification is concerned.  
         [0003]     Competition has long been recognised as an effective way to improve performance within a group, and any competition requires a means by which the relative position of participants may be determined. This is generally a simple undertaking when the participants are engaged in the same activity, and are therefore subject to the same measures of performance. The appropriate measures of performance will depend on the nature of the activity. For example, in a business environment such measures could include profitability, sales volume, production output, or the number of hours lost due to accidents. For large businesses with numerous functional divisions that perform a range of activities, assessment of the relative performance of units within a particular division is relatively simple, as their performance can be directly compared using the same criteria. However, for managers charged with improving performance across an entire organisation it is desirable to foster some degree of competition between different functional divisions. This is made difficult by the disparate measures used to gauge the performance of divisions engaged in different activities. For example, competition between different sales teams could be based on a shared measure of performance such as sales volume, and would be relatively simple to establish, but competition between a sales team and a maintenance crew becomes more difficult.  
         [0004]     The present invention provides a new and improved method for evaluating disparate measures of performance so as to allow participants engaged in different business activities to compete against one another. In addition to providing an incentive to improve performance, this fosters teamwork within individual units while reminding them that they are part of a larger organisation working towards a common goal.  
       SUMMARY OF THE INVENTION  
       [0005]     In accordance with one embodiment of the invention, a system and method are disclosed for improving performance in a business organisation by facilitating competition between participants within the business, such as different business groups, irrespective of the disparate measures by which the performance of those groups may be measured.  
         [0006]     Typically the present invention provides a method for improving performance in a business organisation by facilitating competition between two or more different participants within the business, the method comprising;  
         [0007]     (a) one or more servers, and  
         [0008]     (b) one or more remote terminals accessible by the participants, wherein the method includes the steps of;  
         [0009]     (1) choosing a measure of participant performance,  
         [0010]     (2) inputting the measure of participant performance to a remote terminal,  
         [0011]     (3) calculating a score based on the measure of performance, the calculation being performed at the server, or performed at the remote terminal for communication to the server;  
         [0012]     (4) collating and ranking the scores, and  
         [0013]     (5) displaying the relative scores of the participants.  
         [0014]     Steps 2 to 5 may be carried out once, or repeated multiple times until the competition is terminated until a terminating event occurs, such as for example, by one or more participants reaching a predetermined score.  
         [0015]     Typically the present invention provides a system for improving performance in a business organisation by facilitating competition between two or more different participants within the business, the system comprising;  
         [0016]     (a) one or more servers, and  
         [0017]     (b) one or more remote terminals accessible by the participants, wherein the system includes;  
         [0018]     (1) communicating a measure of participant performance to a remote terminal,  
         [0019]     (2a) communicating the measure of participant performance to the server for calculation of a score, or  
         [0020]     (2b) communication to the server a score calculated at the remote terminal,  
         [0021]     (3) communication of collated and ranked scores to the remote terminal, and  
         [0022]     (4) display of the collated and ranked scores to show their relative values.  
         [0023]     Participants in the competition each elect, or have selected for them, one or more measures of performance that are capable of regular determination and are applicable to their day-to-day business activities. Ideally, the measures chosen should be those for which a target or benchmark (for example, a budget) is set on a periodic basis.  
         [0024]     The chosen measures may be characterised by type. Depending on what is being measured, a smaller or a larger value may be preferable. Similarly, some measures may fall on a finite scale, such as those expressed as percentage values (0-100%), whereas others may be open-ended; some may be positive, others may be negative.  
         [0025]     Typically data for each of the chosen measures is entered into the system on a regular basis, and certain calculations are performed on that data to determine a score for each participant. The precise calculations performed will depend on the type of measure, but each case involves comparing each participant&#39;s performance to its past performance and to its predetermined targets or benchmarks for each measure.  
         [0026]     In effect, typically the scores produced are a measure of each participant&#39;s performance against itself, which provide a common measure shared by all participants irrespective of differences in the underlying measures used to generate those scores. Direct competition between participants based on this shared measure then becomes possible.  
         [0027]     In a system according to one embodiment of the invention, a server is configured to receive and store the data entered in respect of each participant, to perform the relevant calculations, and to generate a representation showing the relative position of the participants in the competition based on their calculated scores. Participants may access that server either directly or via a network for the purpose of entering data and viewing the results of the competition. Those results may be represented in a number of forms, either numerically or graphically.  
         [0028]     Typically, the participants are individuals, teams or business units within a company, or a company itself within a broader corporate group. Participants may compete individually and/or as part of larger teams. For example, if a number of business units from two different companies within a corporate group participated as separate entities, then competition could occur between individual participants, and between the broader ‘teams’ to which those participants belong, such as the two companies for which they work.  
         [0029]     At least one measure of performance may then be selected for each participant to serve as the basis on which their performance in the competition will be assessed. The selected measure(s) should be capable of regular determination and should be relevant to the business activities of the participant. The measures chosen are typically those for which a target or benchmark (for example, a budget) is set, or can be set, on a periodic basis. Budgeted performance targets for each fiscal year, and the measures for which these targets are set could be suitable performance measures for use in the present invention. The selection of appropriate measures may be left to the discretion of the participants, or be subject to selection or review by a third party such as a manager or an administrator of the competition  
         [0030]     The chosen measures are typically characterised by type. Depending on what is being measured, a smaller or a larger value may be preferable. Similarly, some measures may fall on a finite scale, such as those expressed as percentage values (0-100%), whereas others may be open-ended.  
         [0031]     Data for each of the chosen measures can be entered into the system on a regular basis. That data may be entered by the participants, by a third party, or even fed automatically into the system by another computer system. The data may be entered, stored and processed on the client computer, or entered on the client computers then transmitted to the server for storage and processing.  
         [0032]     Calculations can be performed on the data entered to determine a score for each participant for each performance measure, and a combined overall score for each participant if they have selected more than one performance measure. These calculations may be performed either by the client computers or by the server. If the calculations are performed on the client computers, then the results are transmitted to the server for storage, further processing and display as outlined below. If the calculations are performed on the server, then the results can be stored on the server for further processing. The precise calculations performed on the data will depend on the type of performance measure in question.  
         [0033]     The calculations to be performed on the data to determine the participant&#39;s score depend on the nature of the measure to which that data relates. For example, some measures may be expressed as units, and others may be expressed as percentages, some may fall on a finite scale, whereas others may be open-ended. For example, the measure of participant performance may be based on a value chosen from the group comprising sales values, budget values, production values, wastage values or occupational health and safety values. In some cases (such as production or sales), a higher value may be better, while in others (such as wastage or accidents) a lower value may be preferable. The first step in the calculation process is typically a determination of the type of measure involved, which allows the appropriate calculations to be used.  
         [0034]     In one embodiment of the present invention, the various types of measures are grouped into four categories—unit positive (measured in units, where higher values represent better results), unit negative (measured in units, where lower values represent better results), percentage positive (measured as a percentage, where higher values represent better results), and percentage negative (measured as a percentage, where lower values represent better results).  
         [0035]     In each case, a series of general calculations are performed on the data entered for each measure. The broad purpose of these calculations is to assess and assign a numerical score to each participant&#39;s change in performance and/or their performance against predetermined targets.  
         [0036]     In one embodiment the participant&#39;s change in performance may be calculated by comparing, for each measure:  
         [0037]     the average for the current calculation period (eg. the past week) to the average for the previous calculation period (eg. the previous week);  
         [0038]     the average for the current calculation period to the average for the year to date; and  
         [0039]     the variance in values for the current calculation period to the variance for the previous calculation period.  
         [0040]     The participant&#39;s performance against a predetermined target may be calculated by comparing, for each measure:  
         [0041]     the average for the year to date to the target for that year; and  
         [0042]     the average for the current calculation period to the target for that year.  
         [0043]     Each of these factors may be weighted according to their relative importance when determining the overall score for the measure in question.  
         [0044]     The overall scores for each participant can then be collated and ranked by the server and the individual scores and relative positions of the participants displayed. Consistent with the present invention, these results may be displayed in numerous ways. For example, the results may simply be displayed in numerical form, as a list or table, or may be represented graphically by depicting each participant as a separate car in a race and using the numerical scores to determine the relative position of those cars on a race track.  
         [0045]     The competition described by the present invention may comprise one round or a number of rounds. Data may be entered and scores determined and displayed at discrete intervals, or continuously, with data entry, score calculation and display occurring constantly on a ‘real time’ basis while the competition continues. When the competition comes to an end the final scores and relative positions of the participants are determined. In one embodiment, when the competition comprises a number of discrete rounds, then the participants may be allocated a certain number of points for their relative position at the end of each round. Those points may be collated at the end of the competition to determine the overall winners. Points may be earned by individual participants, and by any larger teams into which those participants may be aggregated.  
         [0046]     The present invention is typically fully automated. The server used for carrying out the method of the present invention may be configured to:  
         [0047]     (i) receive and store the measure of participant performance from a remote terminal,  
         [0048]     (ii) calculate a score based on the measure of participant performance or receive and store a score calculated at a remote terminal,  
         [0049]     (iii) collate and rank the calculated score, and  
         [0050]     (iv) display the relative scores of the participants.  
         [0051]     The operation of the server and remote terminal is typically controlled by a code including:  
         [0052]     (1) programming code for receiving input of a measure of participant performance to a remote terminal,  
         [0053]     (2a) programming code for calculating a score based on the measure of performance at the server, or  
         [0054]     (2b) programming code for calculating a score based on the measure of performance performed and programming code for communicating the score to the server,  
         [0055]     (3) programming code for collating and ranking the scores, and  
         [0056]     (4) programming code for displaying the relative scores of the participants.  
         [0057]     The invention may further include code for calculating a participant&#39;s change in performance. Specifically the invention may include;  
         [0058]     programming code for calculating a first average score for a first calculation period and comparing the first average score with a second average score for a second calculation period,  
         [0059]     programming code for calculating a first average score for a first calculation period and comparing the first average score with a second average score for a calculation period comprising the year to date,  
         [0060]     programming code for calculating a first variance in scores for a first calculation period and comparing the first variance in scores with a second variance in scores for a second calculation period. 
     
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0061]     The present invention will now be further described with reference to the drawings in which:  
         [0062]      FIG. 1  illustrates a computer system that may be used to implement the present invention.  
         [0063]      FIG. 2  is a flow diagram illustrating the basic sequence of steps in a competition consistent with one embodiment of the present invention.  
         [0064]      FIG. 3  is a flow diagram illustrating the calculations performed on data entered by each participant in one embodiment of the present invention.  
         [0065]      FIG. 4  is a table containing an exemplary set of data and calculation results stored by one embodiment of the present invention for a participant using one measure of performance.  
         [0066]      FIG. 5  is a table containing an exemplary set of data and calculation results stored by one embodiment of the present invention for a participant using two different measures of performance.  
         [0067]      FIG. 6  is a table containing an exemplary set of data and calculation results stored by one embodiment of the present invention for a participant using three different measures of performance.  
         [0068]      FIG. 7  illustrates one embodiment of a method for displaying the results from the calculation examples illustrated in FIGS.  4  to  6 . 
     
    
     DETAILED DESCRIPTION OF THE INVENTION  
       [0069]      FIG. 1  is a diagram illustrating one embodiment of a system  100  according to the current invention. System  100  includes, but is not limited to, one or more client computers  110  connected to one or more servers  120  by a network  130 . Clients  110  participate in a competition hosted by a server  120 , and may submit data to and receive results from that server  120  via a network  130 . Clients  110  and server  120  may be located anywhere in the world. For example, clients  110  may all be located in the same building as server  120 , and network  130  may be a local area network, or clients  111  and  115  may be located at remote mine sites on different continents and connected to server  120  via the internet, to which access may be facilitated by satellite, whereas clients  112  and  113  may be located in the same building and connected via a local area network  114  to the internet, and thereby to server  120 .  
         [0070]     Clients  110  are generally operated by different elements of the one business organisation, for example, by different companies within a corporate group, or by different operating divisions within one of those companies. Server  120  may be operated by the same business organisation, or by an external service provider. To continue the previous example, client  111  may be operated by the department responsible for production at a mine in Australia, client  115  may be operated by the department responsible for maintenance at a mine in South America, client  112  may be operated by the IT department of the company&#39;s head office in the USA, and client  113  may be operated by the sales and marketing department, also in the USA head office.  
         [0071]     Server  120  includes, among other things, a suitable device for storing data, and a processor for manipulating that data. In one embodiment of the present invention, clients  110  transmit data to server  120  via the network  130 , and that data is stored on the server  120 . Also stored on the server  120  are certain instructions regarding the processing of the stored data in accordance with the present invention. In another embodiment of the present invention, the data may be processed on the client computers  110 , and the results transmitted to the server  120  for collation and storage.  
         [0072]     The processing of the stored data in accordance with the instructions may occur either as it is received, on a scheduled basis, or upon receipt of a request for results.  
         [0073]     Upon receipt of a request for results, the server  120  may either perform the necessary calculations on the stored data in accordance with the instructions or retrieve the results of previously performed calculations, and transmit those results to the requesting client  110 . The results will generally be embodied in an internet page, which may be either a pre-generated static page or a page that is dynamically generated by the server in response to the client&#39;s request, and are transmitted to the relevant client via a network  130  using hypertext transfer protocol (HTTP) or a similar data transfer protocol. In one embodiment of the present invention, the network  130  is a secure network such as a company intranet, and access to the results from the server  120  is restricted to those clients  110  with access to that secure network.  
         [0074]      FIG. 2  is a flow diagram illustrating the basic sequence of steps in a competition consistent with one embodiment of the present invention.  
         [0075]     In step  200 , the competition begins with the selection of the participants. In one embodiment, the participants may be individuals, teams or business units within a company, or a company itself within a broader corporate group. Participants may compete individually and/or as part of larger teams. For example, if a number of business units from two different companies within a corporate group participated as separate entities, then competition could occur between individual participants, and between the broader ‘teams’ to which those participants belong, such as the two companies for which they work.  
         [0076]     In step  210 , at least one measure of performance is selected for each participant to serve as the basis on which their performance in the competition will be assessed. The selected measure(s) should be capable of regular determination and should be relevant to the business activities of the participant. In one embodiment, the measures chosen should also be those for which a target or benchmark (for example, a budget) is set, or can be set, on a periodic basis. In many businesses, budgeted performance targets are set for each fiscal year, and the measures for which these targets are set would be suitable performance measures for use in the present invention. The selection of appropriate measures may be left to the discretion of the participants, or be subject to selection or review by a third party such as a manager or an administrator of the competition.  
         [0077]     The chosen measures are characterised by type. Depending on what is being measured, a smaller or a larger value may be preferable. Similarly, some measures may fall on a finite scale, such as those expressed as percentage values (0-100%), whereas others may be open-ended.  
         [0078]     In step  220 , data for each of the chosen measures is entered into the system described in  FIG. 1  on a regular basis. That data may be entered by the participants, by a third party, or even fed automatically into the system by another computer system. As described with regard to  FIG. 1 , the data may be entered, stored and processed on the client computers  110 , or entered on the client computers  110  then transmitted to the server  120  for storage and processing.  
         [0079]     In step  230 , calculations are performed on the data entered in step  220  to determine a score for each participant for each performance measure, and a combined overall score for each participant if they have selected more than one performance measure. These calculations may be performed either by the client computers  110  or by the server  120 . If the calculations are performed on the client computers  110 , then the results are transmitted to the server  120  for storage, further processing and display as outlined below. If the calculations are performed on the server  120 , then the results are stored on the server for further processing and display as outlined below. The precise calculations performed on the data will depend on the type of performance measure in question, and are described in more detail in connection with  FIG. 4  below.  
         [0080]     In step  240 , the overall scores for each participant are collated and ranked by the server  120  and, in step  250 , the individual scores and relative positions of the participants are displayed. Consistent with the present invention, these results may be displayed in numerous ways. For example, the results may simply be displayed in numerical form, as a list or table, or may be represented graphically by depicting each participant as a separate car in a race and using the numerical scores to determine the relative position of those cars on a race track.  
         [0081]     The competition described by the present invention may comprise a number of rounds, with data being entered and scores being determined and displayed in accordance with steps  220 ,  230 ,  240  and  250  at discrete intervals, or may be a continuous process with data entry, score calculation and display occurring constantly on a ‘real time’ basis. While the competition continues, then following each display of results  250  the process will loop back  260  to the entry of further data in accordance with step  220 . That loop  260  is broken when the competition comes to an end  270 , at which point the final scores and relative positions of the participants are determined. In one embodiment, when the competition comprises a number of discrete rounds, then the participants may be allocated a certain number of points for their relative position at the end of each round. Those points may be collated at the end of the competition to determine the overall winners. Points may be earned by individual participants, and by any larger teams into which those participants may be aggregated.  
         [0082]      FIG. 3  is a flow diagram illustrating the general calculations performed on the data entered by each participant in one embodiment of the present invention.  
         [0083]     As described in relation to step  210  above, each participant in the competition in the competition elects the measures against which their performance is to be judged. Any number of measures may be used, with each participant&#39;s overall score being the average of their scores for each measure.  
         [0084]     Once the measures are selected, data in respect of each measure is entered  300  into the system by or on behalf of the participants.  
         [0085]     The calculations to be performed on the data to determine the participant&#39;s score depend on the nature of the measure to which that data relates. For example, some measures may be expressed as units, and others may be expressed as percentages, some may fall on a finite scale, whereas others may be open-ended. In some cases (such as production or sales), a higher value may be better, while in others (such as wastage or accidents) a lower value may be preferable. The first step  310  in the calculation process is therefore to determine the type of measure involved, which allows the appropriate calculations to be used.  
         [0086]     In one embodiment of the present invention, the various types of measures are grouped into four categories—unit positive  312  (measured in units, where higher values represent better results), unit negative  314  (measured in units, where lower values represent better results), percentage positive  316  (measured as a percentage, where higher values represent better results), and percentage negative  318  (measured as a percentage, where lower values represent better results).  
         [0087]     In each case, a series of general calculations are performed on the data entered for each measure. The broad purpose of these calculations is to assess and assign a numerical score to each participant&#39;s change in performance and their performance against predetermined targets.  
         [0088]     In one embodiment the participant&#39;s change in performance may be calculated by comparing, for each measure:  
         [0089]     the average for the current calculation period (eg. the past week) to the average for the previous calculation period (eg. the previous week);  
         [0090]     the average for the current calculation period to the average for the year to date; and  
         [0091]     the variance in values for the current calculation period to the variance for the previous calculation period.  
         [0092]     The participant&#39;s performance against a predetermined target may be calculated by comparing, for each measure:  
         [0093]     the average for the year to date to the target for that year; and  
         [0094]     the average for the current calculation period to the target for that year.  
         [0095]     Each of these factors may be weighted according to their relative importance when determining the overall score for the measure in question. In the example illustrated in  FIG. 3 , the short term trend for each measure is calculated  320  by comparing the average value for the current calculation period to the average value for the previous calculation period, and is given a weighting of 35% of the overall score. The long term trend is calculated  322  by comparing the average for the current calculation period to the average for the year to date, and is weighted at 10%. Changes in the consistency of each participant&#39;s performance are assessed  324  by comparing the standard deviation of the values for the current calculation period to the standard deviation of the values for the previous calculation period and, in this example, is weighted at 5%. Performance against predetermined targets is calculated by comparing  326  the year-to-date average to the target average for that year, and by comparing  328  the average for the current calculation period to the target average for that year, with the results each being weighted at 25% of the overall score for that measure. In the example illustrated in  FIG. 3 , half of each participant&#39;s score is therefore based on performance trends (ie. whether it is improving, stable, or deteriorating) and half is based on performance against their target for that year. However, this is but one example, and the weightings may be altered to reflect the different priorities of different enterprises.  
         [0096]     The above calculations are repeated  350  for each measure selected, and the results are added together  340  to produce an aggregate score for each participant. The aggregate score for each participant is then divided  360  by the number of measures used by that participant, to produce an average. That average then constitutes the participant&#39;s final score  370  for that round of calculations.  
         [0097]     FIGS.  4  to  6  illustrate three teams participating in one embodiment of the invention, using a variety of performance measures. In the particular embodiment illustrated in these examples, data is entered by participants and calculations are made on a fortnightly basis. For the purpose of these examples, data has therefore been provided for 28 days, or two consecutive calculation periods.  
         [0098]      FIG. 4  is a table containing an exemplary set of data and calculation results stored by one embodiment of the present invention for a participant using a single measure of performance. In this example, the participant is a sales team, and the selected measure of performance is sales volume in tonnes. This is regarded as a ‘unit positive’ measure, as it is expressed in units, and the higher the unit value the better the result. Data  400  for the selected measure has been entered for two consecutive fortnights. In this embodiment, five calculations are performed on the data  400  to produce the participant&#39;s weighted score  440 . The relative contribution made by each of the five calculations towards the final score  440  will vary according to the priorities of the organisation implementing the invention, but in this case the weights attached to each calculation are set out in column  420  as percentage values. In this case, short term improvement is the most important factor, contributing 35% towards the final score. For ease of calculation, these percentage values are converted into a numerical ‘factor’  421 , although the invention may be worked effectively without this step, as long as the figures used have the same relative value that corresponds with the desired weighting, and are applied consistently to each participant.  
         [0099]     When comparing value X to value Y for unit positive measures, the general formula used is:  
       Δ   =       (       X   Y     ×   Z     )     -   Z         
 
 where Z is the relevant weighted factor and A is the weighted difference between X and Y. 
 
         [0100]     In the first calculation  430 , the short-term performance trend is determined by dividing the average for the most recent calculation period (in this case, the past 14 days) by the average for the preceding calculation period, multiplying the result by the relevant weighted factor  421 , then subtracting the weighted factor from that result. In this case, the average for the most recent 14 days&#39; performance data  412  is 2464 tonnes, and the average for the preceding 14 days&#39; performance data  411  was 2511 tonnes. The result of the calculation is −1.3, with the negative value representing the fact that the average performance for this measure has deteriorated.  
         [0101]     In the second calculation  431 , the longer term performance trend is determined by dividing the average for the most recent calculation period by the average for the year to date, multiplying the result by the relevant weighted factor, then subtracting the weighted factor from that result. In this case, the average for the most recent 14 days&#39; performance data  412  is 2464 tonnes, and the average for the year to date is 2326 tonnes. The result of the calculation is 1.2, with the positive value representing the fact that the average performance for this measure has improved.  
         [0102]     In the third calculation  432 , the short-term trend in variability of the performance results is determined by dividing the standard deviation of the performance figures the most recent calculation period by the standard deviation of the performance figures for the preceding calculation period multiplying the result by the relevant weighted factor, then subtracting the weighted factor from that result. In this case, the standard deviation for the most recent 14 days&#39; performance data  412  is 2014, and the standard deviation for the preceding period&#39;s data was 3896. The result of the calculation is 9.3, with the positive value representing the fact that the variability in results has decreased, implying greater consistency of performance. Standard deviation is a well-known statistical algorithm, and is effectively a measurement of the average deviation from the mean within which the majority of results lie. A higher value indicates a greater ‘spread’ of results, and therefore greater variability.  
         [0103]     In the fourth and fifth calculations,  433  and  434  respectively, the participant&#39;s performance against predetermined targets is assessed for each measure.  
         [0104]     In calculation  433 , the average for the year to date is divided by the target value for that year. The result of this is then multiplied by the relevant weighted factor, and the weighted factor is then subtracted from the result. In this case, the average for the year to date is 2326 tonnes, and the target value for the year is 2500 tonnes. The result of the calculation is −3.5, with the negative value reflecting the fact that the current average is below the target value.  
         [0105]     In calculation  434 , the average for the most recent calculation period is divided by the target value for that year. The result of this is then multiplied by the relevant weighted factor, and the weighted factor is then subtracted from the result. In this case, the average for the most recent calculation period is 2464 tonnes, and the target value for the year is 2500 tonnes. The result of the calculation is −0.7, with the negative value reflecting the fact that the current average is below the target value by a small amount.  
         [0106]     The sum of the five weighted calculation results described above is 5.0, which gives the overall score for that measure. As there is only one measure in this case, this value is the participant&#39;s overall score  440  for this calculation round.  
         [0107]      FIG. 5  is a table containing an exemplary set of data and calculation results stored by one embodiment of the present invention for a participant using two different measures of performance. In this example the participant is an information technology department, and the selected measures of performance are system availability (expressed as a percentage) and average response time to requests for assistance (expressed in minutes). In this case, system availability is a percentage positive measure (ie. a higher percentage is better), and response time is a unit negative measure (ie. a lower unit value is better).  
         [0108]     The calculations for unit negative measures are the same as those for unit positive measures, although the results are multiplied by minus one (−1) to reflect the fact that the preferred trend is in the opposite direction. The exception to this is for the variance calculations, as a smaller variance is preferable irrespective of the preferred trend in the underlying measure.  
         [0109]     When comparing value X to value Y for unit negative measures, the general formula used is therefore:  
       Δ   =     -     [       (       X   Y     ×   Z     )     -   Z     ]           
 
 where Z is the relevant weighted factor and A is the weighted difference between X and Y. 
 
         [0110]     In the first calculation  530  for the unit negative measure (response time), the short-term performance trend is determined by dividing the average for the most recent calculation period (in this case, the past 14 days) by the average for the preceding calculation period, multiplying the result by the relevant weighted factor  531 , then subtracting the weighted factor from that result. The end result is then multiplied by minus one. In this case, the average for the most recent 14 days&#39; performance data is 21.7 minutes, and the average for the preceding 14 days&#39; performance data was 7.4 tonnes. The result of the calculation is −136.0, with the strongly negative value representing the marked deterioration in performance on this measure.  
         [0111]     In the second calculation  531  for the unit negative measure (response time), the longer term performance trend is determined by dividing the average for the most recent calculation period by the average for the year to date, multiplying the result by the relevant weighted factor, then subtracting the weighted factor from that result. The end result is then multiplied by minus one. In this case, the average for the most recent 14 days&#39; performance data is 21.7 minutes, and the average for the year to date is 12.4 minutes. The result of the calculation is −15.0, with the negative value representing the fact that the average performance for this measure has deteriorated.  
         [0112]     In the third calculation  532  for the unit negative measure (response time), the short-term trend in variability of the performance results is determined by dividing the standard deviation of the performance figures the most recent calculation period by the standard deviation of the performance figures for the preceding calculation period. multiplying the result by the relevant weighted factor, then subtracting the weighted factor from that result. In this case, the standard deviation for the most recent 14 days&#39; performance data is 25.1, and the standard deviation for the preceding period&#39;s data was 3.7. The result of the calculation is −8.5, with the negative value representing the fact that the variability in results has increased, implying less consistency of performance.  
         [0113]     In the fourth and fifth calculations,  533  and  534  respectively, the participant&#39;s performance against predetermined targets is assessed for each measure.  
         [0114]     In calculation  533  for the unit negative measure (response time), the average for the year to date is divided by the target value for that year. The result of this is then multiplied by the relevant weighted factor, and the weighted factor is then subtracted from the result. The end result is then multiplied by minus one. In this case, the average for the year to date is 12.4 minutes, and the target value for the year is 10.0 minutes. The result of the calculation is −12.0, with the negative value reflecting the fact that the current average is higher than the target value.  
         [0115]     In calculation  534  for the unit negative measure (response time), the average for the most recent calculation period is divided by the target value for that year. The result of this is then multiplied by the relevant weighted factor, and the weighted factor is then subtracted from the result. The end result is then multiplied by minus one. In this case, the average for the most recent calculation period is 21.7 minutes, and the target value for the year is 10.0 minutes. The result of the calculation is −58.5, with the strongly negative value reflecting the fact that the current average is more than double the target value.  
         [0116]     In the case of values measured as a percentage, each value is processed by the system as a value between 0 and 1, ie. 50% would be 0.5, and 100% would be 1.0. This gives rise to a risk of division by zero, which generates a calculation error. As such, in this embodiment, each percentage value is first subtracted from 1.1, so a percentage of 0 would become 1.1, and 100% would become 0.1. When comparing value X to value Y for percentage positive measures, the general formula used is therefore:  
       Δ   =       (         1.1   ⁢           -           ⁢   X               ⁢     1.1   ⁢           -           ⁢   Y         ×   Z     )     -   Z         
 
 where Z is the relevant weighted factor and Δ is the weighted % difference between X and Y. Values other than 1.1 may be used in other embodiments provided that the chosen value is used consistently across all participants—the key element is the ratio between values X and Y and the avoidance of division by zero. 
 
         [0117]     In the first calculation  540  for the percentage positive measure (availability), the short-term performance trend is determined using the above formula, where X is the average for the most recent calculation period (in this case, the past 14 days), and Y is the average for the preceding calculation period. In this case, the average for the most recent 14 days&#39; performance data is 84.6%, and the average for the preceding 14 days&#39; performance data was 96.3%. The result of the calculation is −59.2, with the negative value representing the fact that the average performance for this measure has deteriorated.  
         [0118]     In the second calculation  541  for the percentage positive measure (availability), the longer term performance trend is determined using the above formula, where X is the average for the most recent calculation period and Y is the average for the year to date. In this case, the average for the most recent 14 days&#39; performance data is 84.6%, and the average for the year to date is 92.6%. The result of the calculation is −9.2, with the negative value representing the fact that the average performance for this measure has deteriorated.  
         [0119]     In the third calculation  542  for the percentage positive measure (availability), the short-term trend in variability of the performance results is determined by dividing the standard deviation of the performance figures for the most recent calculation period by the standard deviation of the performance figures for the preceding calculation period, multiplying the result by the relevant weighted factor, then subtracting the weighted factor from that result. In this case, the standard deviation for the most recent 14 days&#39; performance data is 31.7%, and the standard deviation for the preceding period&#39;s data was 4.3%. The result of the calculation is −8.7, with the negative value representing the fact that the variability in results has increased, implying less consistency of performance. Despite the large deterioration in consistency, a relatively low negative score is produced due to the low weighting (5%) for this calculation.  
         [0120]     In the fourth and fifth calculations,  543  and  544  respectively, the participant&#39;s performance against predetermined targets is assessed for each measure.  
         [0121]     In calculation  543  for the percentage positive measure (availability), the above formula is used, where X is the average for the year to date and Y is the target value for that year. In this case, the average for the year to date is 92.6%, and the target value for the year is 98.5%. The result of the calculation is −25.7, with the negative value reflecting the fact that the current average is below the target value.  
         [0122]     In calculation  544  for the for the percentage positive measure (availability), the above formula is used, where X is the average for the most recent calculation period and Y is the target value for that year. In this case, the average for the most recent calculation period is 84.6%, and the target value for the year is 98.5%. The result of the calculation is −60.3, with the negative value reflecting the fact that the current average is well below the target value.  
         [0123]     The scores for each of the participant&#39;s measures,  535  and  545 , are then added together to produce the participant&#39;s aggregate score  550  for that calculation round. This is then divided by the number of measures used to produce that aggregate score (in this case, two) to produce an average, which is the participant&#39;s overall score  560  for that calculation round. In this case, the participant&#39;s overall score is −196.5, the strongly negative value of which reflects generally unsatisfactory performance.  
         [0124]      FIG. 6  is a table containing an exemplary set of data and calculation results stored by one embodiment of the present invention for a participant using three different measures of performance. In this example the participant is the production unit at a mine, and the selected performance measures are production (expressed in tonnes per day), plant availability (expressed as a percentage of scheduled operating time) and waste (expressed as a percentage of product recovered). In this case, production is a unit positive measure, availability is a percentage positive measure (ie. a higher percentage is better), and waste is a percentage negative measure (ie. a lower percentage is better).  
         [0125]     Calculations  630  through to  634  are for a unit positive measure (production), and therefore proceed in the same manner as described for calculations  430  through to  434  in relation to  FIG. 4  above. The resulting overall score for this measure is 7.6.  
         [0126]     Calculations  640  through to  644  are in respect of the waste data, which is a percentage negative measure (ie. it is expressed as a percentage, and the lower the value the better).  
         [0127]     When comparing value X to value Y for percentage negative measures, the general formula used is the same as that for percentage positive measures, albeit multiplied by minus one:  
       Δ   =     -     [       (         1.1   ⁢           -           ⁢   X               ⁢     1.1   ⁢           -           ⁢   Y         ×   Z     )     -   Z     ]           
 
 where Z is the relevant weighted factor and A is the weighted % difference between X and Y. Values other than 1.1 may be used in other embodiments, provided that the chosen value is used consistently across all participants—the key element is the ratio between values X and Y and the avoidance of division by zero. 
 
         [0128]     In the first calculation  640  for the percentage negative measure (waste), the short-term performance trend is determined using the above formula, where X is the average for the most recent calculation period (in this case, the past 14 days), and Y is the average for the preceding calculation period. In this case, the average for the most recent 14 days&#39; performance data is 1.9%, and the average for the preceding 14 days&#39; performance data was 2.5%. The result of the calculation is 17.1, with the positive value representing the fact that the average performance for this measure has improved.  
         [0129]     In the second calculation  641  for the percentage negative measure (waste), the longer term performance trend is determined using the above formula, where X is the average for the most recent calculation period and Y is the average for the year to date. In this case, the average for the most recent 14 days&#39; performance data is 1.9%, and the average for the year to date is 2.1%. The result of the calculation is 2.4, with the positive value representing the fact that the average performance for this measure has improved.  
         [0130]     In the third calculation  642  for the percentage negative measure (waste), the short-term trend in variability of the performance results is determined by dividing the standard deviation of the performance figures for the most recent calculation period by the standard deviation of the performance figures for the preceding calculation period, multiplying the result by the relevant weighted factor, then subtracting the weighted factor from that result. In this case, the standard deviation for the most recent 14 days&#39; performance data is 0.8%, and the standard deviation for the preceding period&#39;s data was 1.4%. The result of the calculation is 8.0, with the positive value representing the fact that the variability in results has decreased, implying greater consistency of performance.  
         [0131]     In the fourth and fifth calculations,  643  and  644  respectively, the participant&#39;s performance against predetermined targets is assessed for each measure.  
         [0132]     In calculation  643  for the percentage negative measure (waste), the above formula is used, where X is the average for the year to date and Y is the target value for that year. In this case, the average for the year to date is 2.1%, and the target value for the year is 1.8%. The result of the calculation is −8.3, with the negative value reflecting the fact that the current average is above the target value.  
         [0133]     In calculation  644  for the for the percentage negative measure (waste), the above formula is used, where X is the average for the most recent calculation period and Y is the target value for that year. In this case, the average for the most recent calculation period is 1.9%, and the target value for the year is 1.8%. The result of the calculation is −1.4, with the negative value reflecting the fact that the current average remains slightly above the target value.  
         [0134]     Calculations  650  through to  654  are for a percentage positive measure (plant availability), and therefore proceed in the same manner as described for calculations  540  through to  544  in relation to  FIG. 5  above. The resulting overall score for this measure is 3.6.  
         [0135]     The scores for each of the participant&#39;s measures,  635 ,  645  and  655  are then added together to produce the participant&#39;s aggregate score  660  for that calculation round. This is then divided by the number of measures used to produce that aggregate score (in this case, three) to produce an average, which is the participant&#39;s overall score  670  for that calculation round. In this case, the participant&#39;s overall score is 9.67.  
         [0136]     In one embodiment of the invention, the scores returned for each participant may be used to generate a graphical representation of the relative position of the participants. For example, each participant may be represented as a car on a race track, with their scores being used to determine how far along the track they have advanced.  
         [0137]      FIG. 7  illustrates one embodiment of a method for displaying the results from the calculation examples illustrated in FIGS.  4  to  6 . In this example, car  710  represents the participant whose performance figures and score were described in  FIG. 4 , car  720  represents the participant from  FIG. 5 , and car  710  represents the participant from  FIG. 6  relative to a finish line  740 . The scores for cars  710 ,  720  and  730  were 5.0, −196.5 and 9.7 respectively, and their relative positions on the track  700  reflect these scores, ie. car  730  is placed first, car  710  is placed second, and car  720  is placed third by a considerable margin. More specifically, the spread between the highest value (9.7) and the lowest value (−196.5) is 206.2. The highest and lowest values define the front and back of the field, and the other participants are placed on the track  700  according to their relative position within these bounds. In this case, car  710  is 201.5 ‘points’ ahead of the back-marker, placing it 97.6% of the way around the track  700 , given that the length of the track is effectively defined by the score of the winner.  
         [0138]     In addition to there being a winner of the overall competition, the competition itself can be broken down into a number of discrete events towards which participants can aim at regular intervals. For embodiments of the present invention in which calculations are performed at discrete intervals, the results from each round of calculations may constitute one round of the competition. For example, the results of each round of calculations may constitute the results of one ‘race’ within a broader competition. Participants may be awarded points based on their relative positions in each race, with those points being collated to determine the winner of the overall competition.  
         [0139]     The competition may be ongoing, or for a fixed period of time. In one embodiment, the calculation dates may correspond to actual events, such as car races, and the duration of the competition may correspond to the duration of the relevant sporting season or championship.  
         [0140]     The invention has been explained above with reference to specific embodiments. Other embodiments will be apparent to those skilled in the art in light of this disclosure. The invention may readily be implemented using configurations other than those described in the preferred embodiments above. Additionally, the invention may effectively be used in conjunction with systems other than the one described above. Therefore, these and other variations upon the described embodiments are intended to be covered by the invention, which is limited only by the appended claims.  
         [0141]     The word ‘comprising’ and forms of the word ‘comprising’ as used in this description and in the claims does not limit the invention claimed to exclude any variants or additions.