Patent Application
20120191494
This invention relates generally to calculating the total cost of an incident that occurs within a business, and more particularly, embodiments of the invention relate to apparatuses and methods for calculating the remediation costs, failed customer interaction (“FCI”) channel costs, and reputational costs associated with incidents occurring within a business.
When a business experiences an incident, the incident often affects the day to day operations of the business and results in potential monetary losses for the business. An incident can include, but is not limited to, system bugs, partial system failures, complete system outages, etc. on one or more systems, which prevents customers from using the goods or services (“products”) provided by the business. Incidents within a business can result in failed customer interactions (“FCIs”) because for every incident one or more customers may be affected by the business's failure to provide at least a part of a product to the one or more customers. The tangible losses a business experiences with respect to the incident are generally related to investigating the incident, determining a fix for the incident, and implementing the fix for the incident. The process of investigating an incident, determining a fix, and implementing the fix is often monitored within each business in order to allow the business to track the incident and how the business remediated the incident. However, the costs associated with investigating an incident, determining a fix, and implementing the fix are often not tracked or tracked accurately within businesses. Therefore, businesses may not have a good idea of the total costs that can be associated with an incident. For example, costs associated with incidents are not only due to investigating and fixing the incident, but there are often unrelated costs that are hard to track, measure, and quantify.
There are complicated issues in determining how an incident affects a business and measuring the total costs to the business when an incident occurs. Therefore, there is a need for apparatuses and methods for effectively determining how an incident affects a business and measuring the total costs of the incident throughout the business.
Embodiments of the present invention address the above needs and/or achieve other advantages by providing apparatuses (e.g., a system, computer program product, and/or other device) and methods for determining how an incident can affect a business and how the business can calculate the total costs associated with the incident.
Embodiments of the present invention provide apparatuses and methods for determining the cost of poor quality of an incident within a business. One way to measure costs associated with an incident is by measuring failed customer interactions (“FCIs”). FCIs are defined as incidents that occur within the business that either directly or indirectly affect a customer's ability to use a product or service offered by the business. In most situations an FCI relates to a failed interaction between the business and the customer through a channel that affected the customer's use of a product or service through the channel. The cost of poor quality application calculates the total cost of an incident through a multifaceted valuation that factors in hard metrics, such as but not limited to actual costs, duration, channel costs, FCI severity, etc. in order to calculate a remediation cost, a channel FCI cost, and a reputation cost.
Embodiments of the invention comprise a method, system and computer program product for determining a remediation cost of an incident, determining a channel failed customer interaction cost of the incident, and determining a cost of poor quality of the incident based in part on the remediation cost and the channel failed customer interaction cost using a processing device.
In further accord with an embodiment of the invention, the invention comprises determining a reputational cost of the incident, and determining the cost of poor quality based in part on the reputational cost of the incident.
In another embodiment of the invention, determining the remediation cost comprises determining a restoral cost, determining an executive cost, determining a capital rework cost, and/or determining a communication cost.
In yet another embodiment of the invention, determining the reputational cost of the incident comprises determining a media coverage cost, wherein determining the media coverage cost comprises determining a traditional media cost and/or determining a social media cost.
In still another embodiment of the invention, determining the channel failed customer interaction cost of the incident comprises determining a rate of attrition cost, determining a less likely to deepen cost, determining an increased cost to serve cost, determining a direct loss of revenue or fees cost, and/or determining a reputation cost.
The features, functions, and advantages that have been discussed may be achieved independently in various embodiments of the present invention or may be combined in yet other embodiments, further details of which can be seen with reference to the following description and drawings.
Having thus described embodiments of the invention in general terms, reference will now be made to the accompanying drawings, which are not necessarily drawn to scale, and wherein:
Embodiments of the present invention now will be described more fully hereinafter with reference to the accompanying drawings, in which some, but not all, embodiments of the invention are shown. Indeed, the invention may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will satisfy applicable legal requirements. Like numbers refer to like elements throughout.
As explained in further detail throughout this application, one way to measure costs associated with an incident in a business is by measuring failed customer interactions (“FCIs”) associated with the incident. FCIs are defined as incidents that occur within the business that either directly or indirectly affect a customer's ability to use a product or service offered by the business. In most situations an FCI deals with some type of interaction between the business and the customer through a channel (i.e. telephone call, website, point of sale (“POS”) machine, face-to-face transaction, etc.) in which the customer had an experience that affected the customer's use of a product or service through the channel. When a business experiences an incident resulting in a large number of FCIs it is unclear as to what is the actual cost to the business. The cost of poor quality application is a framework for an incident based approach that calculates the total cost of an incident through a multifaceted valuation application that factors in hard metrics, such as but not limited to actual costs, duration, channel costs, and FCI severity to assess the costs associated with the incident.
Also, the cost of poor quality may include the channel FCI costs, as illustrated in block 200 of
As illustrated in block 300 of
As illustrated in
The processing device 14 is operatively coupled to the communication device 12, and the memory device 16. The processing device 14 uses the communication device 12 to communicate with the network 2, and other devices on the network 2, such as, but not limited to, the incident system 6 and other business systems 8. Furthermore, the user computer systems 4 can be located at various sites throughout the business and can communicate with each other, as well as other systems and devices over the network 2. As such, the communication device 12 generally comprises a modem, server, or other device for communicating with other devices on the network 2, and a display, camera, keypad, mouse, keyboard, microphone, and/or speakers for communicating with one or more users 3.
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It will be understood that systems, devices, servers, processors, computers, networks, and other devices described herein may be made up of one system, device, server, processor, computer, network, etc., or numerous systems, devices, servers, processors, computers, networks, etc. working in conjunction with each other. Also, it is to be understood that use of the term computer system includes, but is not limited, desktop, laptop, smart phone, personal display device (PDA), televisions with network access, or any other electronic system that has a communication device, processing device, and memory device.
In other embodiments of the invention, the business could be a bank or other financial institution that has a failure in the bank that affects the customers' ability to use the bank's automated transaction machines (“ATMs”) or e-commerce website through which customers can log into their accounts at the bank. However, it is to be understood that the framework for determining the cost of poor quality described herein, as well as the cost of poor quality application 10 illustrated throughout, can be used with any type of business. Furthermore in any embodiments that are generally described as involving a “bank,” one of ordinary skill in the art will appreciate that other embodiments of the invention may involve other financial institutions, or businesses outside of financial institutions that take the place of or work in connection with a bank.
In order to use the cost of poor quality application 10 illustrated and described throughout this application the user 3 may first enter some general information into the cost of poor quality application 10.
In other embodiments of the invention for other types of business, such as a bank, the channels that could be affected include, but are not limited to, ATMs, banking centers, e-commerce website, call center, card services, Global Wealth & Investment Management (“GWIM”), Home Loans and Insurance Technology (“HLIT”), etc.
After the user 3 fills out the general information, the user 3 can input other information related to the incident in the cost of poor quality application 10. Again, in some embodiments of the invention, and elsewhere throughout this application, the information in the cost of poor quality application 10 can be filled out automatically so the user 3 does not need to manually fill out the information.
In other embodiments of the invention, the restoral cost value 1034 can be calculated by estimating the amount of associate resource time spent on average on an incident from each of the associates at the business, such as the manager on duty, the Subject Matter Expert (“SME”), senior managers, incident management, domain executive, domain generalist, as well as other associates and associate time spent in the support and follow-up meetings for the incident. The total time spent by the associates of the business can be multiplied by an average cost per associate time in order to determine the total restoral value cost 1034 per incident. One example of the estimation of the restoral value cost 1034 is illustrated in
The remediation costs, as illustrated by block 104 in
The remediation costs, as illustrated in block 106 of
As illustrated in block 108 of
As illustrated in block 110, the cost of poor quality application 10 sums all of the costs in the remediation cost interface 1030 to determine the total remediation costs 1040. The total remediation costs 1040 are illustrated in the remediation cost interface 1030, as illustrated in
As illustrated in block 200 of
As illustrated in the FCI Types section 1060, the user 3 can select the type of FCIs for each channel selected in the FCIs by Channel section 1052. The FCI types include the types of failures that the customer experienced because of the incident. For example, in the case of a retail business, the FCIs failures could be related to account logins, purchase payment, reward enrollments, card account detail views, product image, home page failures, product offer failures, POS availability, malfunctions on the POS, POS connectivity issues, store inventory system failures, ordering failures, shipping failures, etc.
In other embodiments of the invention, when the business is a bank the FCI types may include e-commerce failures related to account logins, fund transfers, bill payment, enrollment, card details, account details, e-bill delivery, image errors, e-statement failures, account opening errors, home page failures, product offers failures, small business account failures, payroll movement errors, mortgager origination failures, mortgage fulfillment errors, mortgage account details errors, insurance access failures, or other e-commerce issues. The ATM failures could be related to machine availability issues, frozen transactions, captured cards, cash rejects, check rejects, image deposit errors, image deposit holds, deposit claims, dispense claims, etc. Banking center teller failures could be related to teller equipment or platform issues. The call center failures could be related to systems that do not work, resource tools that the call center associate cannot use, dropped calls, etc. The severity for each of the FCIs listed in the FCI Types section 1060 can be automatically populated in some embodiments for standardization, or can be assigned by a user 3 for flexibility in rating the severity of the FCIs related to the incident.
In some embodiments of the invention, every possible FCI at the business is rated based on severity level by one or more groups at the business. Therefore, when the FCI is selected for an incident the FCI severity rating is automatically populated by the cost of poor quality application 10. One way to calculate FCI severity is to measure how the business views how customers are affected when each particular FCI occurs. In some embodiments, the severity is ranked as 1, 2, and 3, with one being most severe and 3 being the least severe. In other embodiments of the invention, the severity can be ranked on other scales or using other data collected from customer feedback. In still other embodiments of the invention, the user 3 or the groups within the business can rank the severity of each of the FCIs affected by the incident using the cost of poor quality application 10 as the FCIs are selected.
As illustrated by block 304 in
While the severity level is a measure of how the business feels that a FCI affects a customer, alternatively, the PI ratio is a measure or prediction of how the actual customers feel on average that a FCI affects them. In other embodiments, other types of data analysis or customer feedback information can be used to determine metrics associated with how customers feel that FCIs affect them. The business may feel that an FCI affects a customer one way, but the customer might not actually realize that there was an FCI. However, in other cases the customer may feel that an FCI impacts them more than the business may feel that the FCI impacts the customer. The FCI severity level and PI ratio can be used alone or in combination throughout the cost of poor quality application 10 in order to determine various costs associated with the FCIs that occur as a result of an incident. Thus, the PI ratio provides a way to statistically discover which FCI types are more impactful to customers of the business.
As illustrated by block 306 the change in attrition rate for the problem incidents may be determined.
The value 1214 for each FCI type may be determined by multiplying the new attrition rate 1222 by the average profitability of a customer that experienced the FCI (e.g., number of FCIs multiplied by the PI ratio and the profit per customer, which is the average profit of the business on a per customer basis), as illustrated by block 308 in
In some embodiments of the invention, the total attrition cost 1250 can be further broken down into customer segments (either at the beginning or end of the process). For example, customer segments may be broken down to male and female, age groups (i.e. 18-30, 31-50, 51 and above, or the like), regions of the country (i.e. state, Northeast, etc.), or any other type of customer segment. In this way, the total attrition cost can be used to identify what customer segments had the most attrition costs related to the incident.
The cost of poor quality application 10 calculates the FCI value 1314, the FCI severity 1316, and the PI ratio 1318 for each FCI in the FCI valuation section 1312. The percent likely to deepen before 1320 is the average deepen rate for all of the products before an incident, while the percent likely to deepen after 1322 is the average deepen rate after an incident. As illustrated by block 406, in one embodiment of the invention the rates are determined based on customer feedback information from surveys, customer inquires, social media, etc. In other embodiments, these rates are determined based on historical data from before and after incidents that occurred in the past. In still other embodiments these rates are based on assumptions.
The FCI value 1314 may be calculated by multiplying the percent likely to deepen after 1322 by the average profitability of a new product (e.g., number of FCIs multiplied by the PI ratio and the profit per new product, which is the average profit of a new product on weighted average basis), as illustrated by block 408 in
The total less likely to deepen cost 1350 is determined based on the information entered into the general input section 1010. For example, if the incident affected multiple channels the total less likely to deepen cost 1350 equals the affected multiple channel cost 1340, if the incident occurred on the weekend the weekend only cost 1338 is used, and if the incident affected multiple channels and occurred on the weekend the combined cost 1342 equals the total less likely to deepen cost 1350. The total less likely to deepen cost percentage 1352 is the percentage of the total incident cost that can be associated to the likelihood of a customer not purchasing additional products. As previously described with the attrition costs 1250, the total less likely to deepen cost 1350 can be broken down into customer segments.
As illustrated by block 504, the other channel options available to customers are determined depending on channel type and transaction type that were affected by the incident. In order to do this the cost of poor quality application 10 determines the other available channels if a single channel experiences an outage. For example, if the e-commerce channel experiences an outage, customers can utilize other channels such as, the call center, store, POS machine, etc. and visa versa for any other channel that experiences an outage. In some embodiments if one channel is experiencing an outage the customer cannot or may likely not use another channel, therefore, the other channel may not be included in the calculations.
As illustrated by block 506, the percentage of customers expected to use other channels due to the incident is calculated. For example, as illustrated in the e-commerce down section 1414, if the e-commerce channel is down then the cost of poor quality application 10 lists the percentage of customers that will become call center customers 1416, store customers 1418, and POS customers 1420. These values are the percentages of customers that would use the other channels in lieu of the e-commerce channel. Furthermore, the POS down section 1422 lists the percentage customers that will become call center customers 1424 and store customers 1426, if the POS machines experienced an outage. In some embodiments, the percentages are based on historical data from customer surveys, customer contact e-mails, social media, etc. In some embodiments of the invention, the user 3 can determine the customer percentages based on the incident, FCIs, and the user's knowledge of the channels that customers would typically utilize during outages of other channels.
As illustrated by block 508 the increased cost to serve for a channel is calculated by subtracting the variable cost of the channel related to the incident from the variable cost of the channel forced to be used because of the incident. Thereafter, as illustrated by block 510 the increased cost to serve for a channel is calculated by multiplying the difference in variable costs by the total number FCIs and the percentage of FCIs that will use the alternate channels. For example, as illustrated in the e-commerce increased cost to serve section 1428, the e-commerce only cost 1430 is found by taking the difference in the variable cost of the call center and the e-commerce channel multiplied by the total FCIs and the percentage of customers who will use the call center. This is added to the difference in the variable cost of the store and the e-commerce channel multiplied by the total FCIs and the percentage of customers who will use the store. This is added to the difference in the variable cost of the POS and the e-commerce channel multiplied by the total FCIs and the percentage of customers who will use the POS. The sum of the three values results in the e-commerce only increased cost to serve 1430. Similar calculations are done for the combination of channels as illustrated in the e-commerce increased cost to serve section 1420 and the POS increased cost to serve section 1450.
As illustrated by block 512 in
As illustrated by block 604, the cost of poor quality application 10 may also calculate the lost purchases expected 1524. In order to determine the lost purchases expected 1524 the average number of purchases per hour 1524 may be determined based on historical data. In some embodiments of the invention, the customer may also take out credit cards from the business which also results in a loss of revenue. Therefore, in some embodiments the card application loss expected 1526 is also determined. The percentage of customers who won't repurchase or reapply 1528 for the card is determined, and may be estimated based on historical data or assumptions made by the business. The SVA of the products 1532 is determined, which is the average profit made from each purchase for the business. The SVA of the average card products 1534 is also determined, which may be higher in some cases because of the added discount customers get when purchasing products with a card issued by the business. The total lost product revenue 1538 is determined by multiplying the duration of the incident 1522 by the purchases expected 1524 per unit time and by the SVA average products 1532, as well as in some embodiments by an acceptance rate or percentage of returns rate. In some embodiments this number is reduced by the percentage of customers that won't repurchase or reapply 1528. The lost revenue from card applications can be calculated in the same or similar way.
As illustrated by block 606 the lost fees may also be calculated in some embodiments of the invention. For example, the business may receive a fee every time a POS machine is used. This may be the case for a vending company, bank, or other business that uses POS machines. For example, a business may know that they receive on average $0.02 per transaction on a POS machine based on historical data or other assumptions. Therefore, the number of FCIs 1502 is multiplied by the fee per transaction 1518 to get the total POS lost fee revenue 1540.
As illustrated by block 608 the total lost ad revenue 1536, is added to the total lost product revenue 1538, and the total POS lost fee revenue 1540 to get the total lost direct revenue 1542.
As illustrated by block 700 of
As illustrated by block 704, the number of FCIs may be multiplied by the number of people a customer is likely to tell about the incident. For example, severity 1 FCIs are more severe than severity 2 FCIs, therefore customers will most likely tell more people about severity 1 FCIs than severity 2 FCIs. Severity 2 FCIs are more severe than severity 3 FCIs, therefore customers will most likely tell more people about the severity 2 FCIs than the severity 3 FCIs. Since the customers may not even recognize severity 3 FCIs, they may not tell any other people about the severity 3 FCIs. The reputation cost output interface displays the number of individuals who heard the news 1604, which represents the sum of the severity 1, 2, and 3 FCIs multiplied by the number of people a customer is likely to tell for each severity level.
As illustrated by block 706, the number of people who heard the news 1604 may be multiplied by the percentage of people impacted by the news 1606. Only a certain percentage of the people that are told about the incident will actually make a purchasing decision based on the negative impression. As illustrated in
In some embodiments of the invention, the percentage of people who are impacted by the news 1606 may be higher for severity 1 FCIs as opposed to severity 2 FCIs, as well as severity 2 FCIs as opposed to severity 3 FCIs, thus, different percentages may be used for different levels of FCIs in some embodiments of the invention. Therefore, in some embodiments of the invention, the number of individuals who receive a secondary negative impression is based on different percentages for severity 1, severity 2, and severity 3 FCIs.
As illustrated in block 710, attrition and less likely to deepen calculations are made for the number of people who receive a secondary negative impression. A percentage of the number of people who receive a secondary negative impression are already bank customers and a percentage of them are not bank customers, which can be assumed based on population numbers, geographic customer location numbers, etc. In some embodiments of the invention the cost is a function of the attrition of current customer, less likely to deepen of current customers, and less likely of non-customers to become customers. The cost due to the attrition of current customers is measured by the number of people who receive a secondary negative impression multiplied by the percentage of people that are customers, multiplied by the profitability of an average customer, multiplied by an attrition rate. The attrition rate can be determined by historical data or assumptions. The less likely to deepen cost of the current customers is measured by the number of people who receive a secondary negative impression multiplied by the percentage who are customers, multiplied by the average profit of additional products purchased, multiplied by a percentage of the likelihood of purchasing additional products. The percentage of likelihood of purchasing additional products can be determined by historical data or assumptions. The less likely to deepen cost of non-customers becoming customers is measured by the number of people who receive a secondary negative impression multiplied by the percentage who are not customers, multiplied by the average profitability of an average customer, multiplied by percentage of the likelihood that a non-customer would become a customer. The percentage of the likelihood of a non-customer becoming a customer can be determined by historical data or assumptions. These costs are summed, depending on the situation, and result in the reputation cost for the FCI channel cost. The reputation cost can be broken down into reputation cost impact by severity 1 FCIs 1610, severity 2 FCIs, severity 3 FCIs, as illustrated in the reputation output interface 1600. The cost for each level of severity is summed, and as illustrated by block 712, results in the total reputation cost 1620, which is displayed in the reputation cost output interface 1600. The total reputation cost by percent 1622, is also illustrated in the reputation cost output interface 1600, and indicates the percentage of the reputation cost as a function of the total FCI channel cost.
As illustrated by block 210 of
In some embodiments of the invention, a component of the total incident cost of poor quality can also be based in part on additional reputational costs as illustrated by block 800 in
As illustrated by block 804 in
As illustrated by block 900 in
The cost of poor quality application 10 can be used as tool to calculate end-to-end cost information related to how particular incidents affect various channels and lines of business within a business. All of the different costs associated with an incident can be brought into a single application allowing the business to determine to determine the most important incidents to investigate and fix. The user 2 of the cost of poor quality application 10 can add, remove, or change assumptions within the cost of poor quality application 10 on an incident by incident basis in order to provide more accurate evaluations of the actual costs within a business related to an incident. The ability to provide a general framework that can be customized for particular incidents helps a business to place values on identifying and fixing the systems, processes, and software within a business that lead to the various incidents.
In some embodiments the cost of poor quality application 10 can be utilized to identify the costs associated with specific FCIs, as opposed to an incident or group of incidents. For example, the incident may be only based on a single FCI, and thus the cost of poor quality calculated is based solely on a single FCI. Furthermore, the cost of poor quality application 10 may be customized to specific independent business groups or the whole business since the costs are calculated based on individual FCIs that can be measured as to how each individual FCI impacts the independent business groups differently.
In some embodiments the cost of poor quality application 10 can be linked to different types of customer information that is captured throughout the business, such as the information on the incident system 6 or other business systems 8. In this way, the cost of poor quality application 10 provides the ability to leverage the real-time, hourly, daily, etc. customer data captured by the business to provide up to date tracking and cost analysis of the FCIs within the business.
As will be appreciated by one of ordinary skill in the art in view of this disclosure, the present invention may be embodied as an apparatus (including, for example, a system, machine, device, computer program product, and/or the like), as a method (including, for example, a business process, computer-implemented process, and/or the like), or as any combination of the foregoing. Accordingly, embodiments of the present invention may take the form of an entirely software embodiment (including firmware, resident software, micro-code, etc.), an entirely hardware embodiment, or an embodiment combining software and hardware aspects that may generally be referred to herein as a “system.” Furthermore, embodiments of the present invention may take the form of a computer program product that includes a computer-readable storage medium having computer-executable program code portions stored therein. As used herein, a processor may be “configured to” perform a certain function in a variety of ways, including, for example, by having one or more general-purpose circuits perform the function by executing one or more computer-executable program code portions embodied in a computer-readable medium, and/or by having one or more application-specific circuits perform the function.
It will be understood that any suitable computer-readable medium may be utilized. The computer-readable medium may include, but is not limited to, a non-transitory computer-readable medium, such as a tangible electronic, magnetic, optical, electromagnetic, infrared, and/or semiconductor system, apparatus, and/or device. For example, in some embodiments, the non-transitory computer-readable medium includes a tangible medium such as a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a compact disc read-only memory (CD-ROM), and/or some other tangible optical and/or magnetic storage device. In other embodiments of the present invention, however, the computer-readable medium may be transitory, such as a propagation signal including computer-executable program code portions embodied therein.
It will also be understood that one or more computer-executable program code portions for carrying out operations of the present invention may include object-oriented, scripted, and/or unscripted programming languages, such as, for example, Java, Perl, Smalltalk, C++, SAS, SQL, Python, Objective C, and/or the like. In some embodiments, the one or more computer-executable program code portions for carrying out operations of embodiments of the present invention are written in conventional procedural programming languages, such as the “C” programming languages and/or similar programming languages. The computer program code may alternatively or additionally be written in one or more multi-paradigm programming languages, such as, for example, F#.
It will further be understood that some embodiments of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of systems, methods, and/or computer program products. It will be understood that each block included in the flowchart illustrations and/or block diagrams, and combinations of blocks included in the flowchart illustrations and/or block diagrams, may be implemented by one or more computer-executable program code portions. These one or more computer-executable program code portions may be provided to a processor of a general purpose computer, special purpose computer, and/or some other programmable data processing apparatus in order to produce a particular machine, such that the one or more computer-executable program code portions, which execute via the processor of the computer and/or other programmable data processing apparatus, create mechanisms for implementing the steps and/or functions represented by the flowchart(s) and/or block diagram block(s).
It will also be understood that the one or more computer-executable program code portions may be stored in a transitory or non-transitory computer-readable medium (e.g., a memory, etc.) that can direct a computer and/or other programmable data processing apparatus to function in a particular manner, such that the computer-executable program code portions stored in the computer-readable medium produce an article of manufacture including instruction mechanisms which implement the steps and/or functions specified in the flowchart(s) and/or block diagram block(s).
The one or more computer-executable program code portions may also be loaded onto a computer and/or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer and/or other programmable apparatus. In some embodiments, this produces a computer-implemented process such that the one or more computer-executable program code portions which execute on the computer and/or other programmable apparatus provide operational steps to implement the steps specified in the flowchart(s) and/or the functions specified in the block diagram block(s). Alternatively, computer-implemented steps may be combined with operator- and/or human-implemented steps in order to carry out an embodiment of the present invention.
Specific embodiments of the invention are described herein. Many modifications and other embodiments of the invention set forth herein will come to mind to one skilled in the art to which the invention pertains, having the benefit of the teachings presented in the foregoing descriptions and the associated drawings. Therefore, it is to be understood that the invention is not to be limited to the specific embodiments disclosed and that modifications and other embodiments and combinations of embodiments are intended to be included within the scope of the appended claims. Although specific terms are employed herein, they are used in a generic and descriptive sense only and not for purposes of limitation.
U.S. patent application Ser. No. ______ to Heiman et al. and entitled “Incident Cost Model” is filed concurrently with the present application and is hereby incorporated by reference.
