A COMPUTING DEVICE AND COMPUTER READABLE STORAGE MEDIUM FOR CALCULATING SALES ACTIVITY TARGET DATA IN ACCORDANCE WITH HISTORICAL SALES STATISTIC PARAMETER DATA

Field of the Invention

The present invention relates to data processing and in particular to a computing device and computer readable storage medium for calculating sales activity target data in accordance with historical sales statistic parameter data.

_ The invention has been developed primarily for use in/with sales planning and will be described hereinafter with reference to this application. However, it will be appreciated that the invention is not limited to this particular field of use.

Background

Sales corporations employ forecasting and sales training tools in an attempt to increase sales and associated profit.

However, existing forecasting and sales training tools suffer from administrative burden, especially when implementing new sales methodology or initiatives. Such administrative burden is usually met with resistance from sales professionals.

Furthermore, existing forecasting and sales training tools typically employ the "Just Sell more to Earn More" sales approach and are specifically incapable of allowing the sales individual to forecast their own sales activity targets in accordance with individual parameters. While certain forecasting and sales training tools do allow customization to an extent, such forecasting and sales training tools are usually overly complex, resulting in low accuracy on account of tedious forecast reporting and data entering. As a result, sales individuals sometimes resort to inflating forecast figures to align their performance with company targets.

As such, a need therefore exists for a forecasting and sales training tool focused on the benefit for the sales individual and not on the sales corporation.

The present invention seeks to provide a computing device and computer readable storage medium for calculating sales activity target data in accordance with historical sales statistic parameter data, which will overcome or substantially ameliorate at least some of the deficiencies of the prior art, or to at least provide an alternative. It is to be understood that, if any prior art information is referred to herein, such reference does not constitute an admission that the information forms part of the common general knowledge in the art, in Australia or any other country.

Summary

According to one aspect there is provided a computing device for calculating sales activity target data in accordance with historical sales statistic parameter data, the computing device comprising a processor for processing digital data; a memory device for storing digital data including computer program code and being coupled to the processor via a bus; a data interface for sending and receiving digital data and being coupled to the processor via the bus; and a database connection for retrieving digital data including periodically retrieving historical sales statistic parameter data, the database being coupled to the processor via the bus, wherein the processor is further controlled by the computer program code to receive, via the data interface, remuneration target parameter data; load, using the database connection, historical sales statistic parameter data; calculate sales activity target data in accordance with the remuneration target parameter data and the historical sales statistic parameter data; and send, via the data interface, the sales activity target data.

Preferably, the database connection is adapted to load data from a content resource management system.

Advantageously, sales activity target data generated by the computing device may be employed in the sales planning process in allowing one or more targets to be set for a sales individual. Furthermore, the historical sales statistic parameter data may be updated in accordance with real time sales data, ensuring the currency of the sales activity target data.

Preferably, the remuneration target data comprises remuneration target parameter data selected from the set of remuneration target parameter data comprising base salary parameter data; variable income parameter data; and desired income parameter data.

Advantageously, the computing device is adapted to calculate sales activity target data in accordance with a variety of remuneration target parameters set by the sales individual .

Preferably, the historical statistic sales data comprises historical sales statistic parameter data selected from the set of historical sales statistic parameter data comprising historical average deal size parameter data; historical deals to opportunities percentage parameter data; historical opportunities to meetings percentage parameter data; and historical meetings to calls percentage parameter data.. Advantageously, the computing device is adapted to employ historical sales data for the purposes of calculating the sales activity target data. In this manner, the sales activity target data is accurate and tailored to the particular sales organization.

Preferably, the sales activity target data comprises sales activity target data selected from the set of sales activity target data comprising required number of deals per time period data; required number of opportunities per time period data; required number of meetings per time period data; and required number of calls per time period data.

Advantageously, the computing device is adapted to generate a variety of sales activity target data depending on the sales person's needs.

Preferably, the required number of deals per time period data is calculated as the quotient of the sales activity target data parameter data and the historical average deal size parameter data.

Preferably, the required number of meetings per time period data is calculated as the quotient of the required number of opportunities per time period data and the historical opportunities to meetings percentage parameter data.

Preferably, the required number of opportunities per time period data is calculated as the quotient of the required number of deals per time period data and the historical deals to opportunities percentage parameter data.

Preferably, the required number of calls per time period data is calculated as the quotient of the required number of deals per time period data and the historical meetings to calls percentage parameter data.

Preferably, the processor is controlled by the computer program code to calculate progress tracking data as a quotient of the sales booked data and the sales activity target data.

Advantageously, the computing device is adapted to calculate progress tracking data for the purposes of keeping the sales individual on target.

Preferably, the processor is controlled by the computer program code to calculate key performance indicator data in accordance with the with the sales activity target data.

Advantageously, the computing device is adapted for generating key performance indicator data in accordance with the with the sales activity target data allowing for the performance of the sales person to be monitored in real time.

Preferably, the processor is furtlier controlled by the computer program code to load, using the database connection, account data representing at least one account, and categorise the at least one account in accordance with the current vs potential spend amount of the at least one account. Current spend is defined as the current revenue received from an account. Potential spend is defined as the maximum possible revenue from an account. Account is defined as a prospect or customer entity.

According to another aspect, there is provided a client computing device comprising a network interface for sending and receiving digital data and being coupled, across a data network, to a computing device as described herein, wherein the network interface is adapted for sending and receiving data as referred to herein.

According to another aspect, there is provided a computer readable storage medium for calculating sales activity target data in accordance with historical sales statistic parameter data, the computer readable storage medium having computer program code instructions recorded thereon, the computer program code instructions being executable by a computer and comprising instructions for receiving, via a data interface, remuneration target parameter data; instructions for loading, using a database connection, historical sales statistic parameter data; instructions for calculating sales activity target data in accordance with the remuneration target parameter data and the historical sales statistic parameter data; and instructions for sending, via the data interface, the sales activity target data.

Preferably, the database connection is adapted to load data from a content resource management system.

Preferably, the remuneration target data comprises remuneration target parameter data selected from the set of remuneration target parameter data comprising base salary parameter data variable income parameter data; and desired income parameter data.

Preferably, the historical statistic sales data comprises historical sales statistic parameter data selected from the set of historical sales statistic parameter data comprising historical average deal size parameter data; historical deals to opportunities percentage parameter data; historical opportunities to meetings percentage parameter data and historical meetings to calls percentage parameter data.

Preferably, the sales activity target data comprises sales activity target data selected from the set of sales activity target data comprising required number of deals per time period data; required number of meetings per time period data; and required number of calls per time period data. Preferably, the sales activity target data comprises sales activity target data selected from the set of sales activity target data comprising required number of deals per time period data; required number of opportunities per time period data; required number of meetings per time period data; and required number of calls per time period data. Preferably, the required number of deals per time period data is calculated as the quotient of the sales target data and the historical average deal size parameter data.

Preferably, the required number of opportunities per time period data is calculated as the quotient of the required number of deals per time period data and the historical deals to opportunities percentage parameter data.

Preferably, the required number of meetings per time period data is calculated as the quotient of the required number of opportunities per time period data and the historical opportunities to meetings percentage parameter data.

Preferably, the required number of calls per time period data is calculated as the quotient of the required number of meetings per time period data and the historical meetings to calls percentage parameter data.

Preferably, the computer readable storage medium further comprises instructions for calculating progress tracking data as a quotient of the sales booked data and the sales activity target data.

Preferably, the computer readable storage medium further comprises instructions for calculate key performance indicator data in accordance with the with the sales activity target data.

Preferably, the computer readable storage medium further comprises instructions for loading, using the database connection, account data representing at least one account, and categorising the at least one account in accordance with a potential spend amount of the at least one account.

Other aspects of the invention are also disclosed.

Brief Description of the Drawings

Notwithstanding any other forms which may fall within the scope of the present invention, preferred embodiments of the invention will now be described, by way of example only, with reference to the accompanying drawings in which:

Fig. 1 shows a computing device on which the various embodiments described herein may be implemented in accordance with a preferred embodiment of the present invention;

Fig. 2 shows a network of computing devices on which the various embodiments described herein may be implemented in accordance with an embodiment of the present invention;

Fig. 3 shows a computer implemented method for calculating sales activity target data in accordance with historical sales statistic parameter data in accordance with an embodiment of the present invention; Fig. 4 shows an exemplary graphical user interface (GUI) for receiving remuneration target parameter data in accordance with an embodiment of the present invention;

Fig. 5 shows a GUI for displaying revenue targets in accordance with an embodiment of the present invention;

Fig. 6 shows a GUI for displaying key performance data in accordance with an embodiment of the present invention;

Fig. 7 shows a current quarter plan GUI in accordance with an embodiment of the present invention;

Fig. 8 shows a next quarter plan GUI in accordance with an embodiment of the present invention, and

Figs 10 to 16 show exemplary graphical user interfaces of a commercial embodiment for calculating sales activity target data in accordance with historical sales statistic parameter data.

Description of Embodiments

It should be noted in the following description that like or the same reference numerals in different embodiments denote the same or similar features.

Computing device

Fig. 1 shows a computing device 100 on which the various embodiments described herein may be implemented. In particular the steps of the method 300 for calculating sales activity target data in accordance with historical sales statistic parameter data described below may be implemented as computer program code instructions executable by the computing device 100. The computing device 100 may take on different embodiments depending on the application, such as, and as will be described in further detail below with reference to figure 2, a web server 210, client computing device 220 or the like.

The computer program code instructions may be divided into one or more computer program code instruction libraries, such as dynamic link libraries (DLL), wherein each of the libraries performs a one or more steps of the method. Additionally, a subset of the one or more of the libraries may perform graphical user interface tasks relating to the steps of the method.

The device 100 comprises semiconductor memory 110 comprising volatile memory such as random access memory (RAM) or read only memory (ROM). The memory 100 may comprise cither RAM or ROM or a combination of RAM and ROM.

The device 100 comprises a computer program code storage medium reader 130 for reading the computer program code instructions from computer program code storage media 120. The storage media 120 may be optical media such as CD-ROM disks, magnetic media such as floppy disks and tape cassettes or flash media such as USB memory sticks.

The device further comprises I/O interface 140 for communicating with one or more peripheral devices. The I/O interface 140 may offer both serial and parallel interface connectivity. For example, the I/O interface 140 may comprise a Small Computer System Interface (SCSI), Universal Serial Bus (USB) or similar I/O interface for interfacing with the storage medium reader 130. The I/O interface 140 may also communicate with one or more human input devices (HID) 160 such as keyboards, pointing devices, joysticks and the like. The I/O interface 140 may also comprise a computer to computer interface, such as a Recommended Standard 232 (RS-232) interface, for interfacing the device 100 with one or more personal computer (PC) devices 190. The I/O interface 140 may also comprise an audio interface for communicate audio signals to one or more audio devices 1050, such as a speaker or a buzzer.

The device 100 also comprises a network interface 170 for communicating with one or more computer networks 180. The network 180 may be a wired network, such as a wired Ethernet™ network or a wireless network, such as a Bluetooth™ network or IEEE 802.1 1 network. The network 180 may be a local area network (LAN), such as a home or office computer network, or a wide area network (WAN), such as the Internet or private WAN.

The device 100 comprises an arithmetic logic unit or processor 1000 for performing the computer program code instructions. The processor 1000 may be a reduced instruction set computer (RISC) or complex instruction set computer (CISC) processor or the like. The device 100 further comprises a storage device 1030, such as a magnetic disk hard drive or a solid state disk drive.

Computer program code instructions may be loaded into the storage device 1030 from the storage media 120 using the storage medium reader 130 or from the network 180 using network interface 170. During the bootstrap phase, an operating system and one or more software applications arc loaded from the storage device 1030 into the memory 1 10. During the fetch- decode-execute cycle, the processor 1000 fetches computer program code instructions from memory 110, decodes the instructions into machine code, executes the instructions and stores one or more intermediate results in memory 100.

In this manner, the instructions stored in the memory 1 10, when retrieved and executed by the processor 1000, may configure the computing device 100 as a special-purpose machine that may perform the functions described herein. The device 100 also comprises a video interface 1010 for conveying video signals to a display device 1020, such as a liquid crystal display (LCD), cathode-ray tube (CRT) or similar display device.

The device 100 also comprises a communication bus subsystem 150 for interconnecting the various devices described above. The bus subsystem 150 may offer parallel connectivity such as Industry Standard Architecture (ISA), conventional Peripheral Component Interconnect (PCI) and the like or serial connectivity such as PCI Express (PCIe), Serial Advanced Technology Attachment (Serial ATA) and the like.

In various embodiments, the processes described herein maybe implemented using a stand-alone computing device 100. However, in alternative embodiments, the processes described herein may be implemented using a web-based client-server architecture.

System for calculating sales activity target data in accordance with historical sales statistic parameter data

As such, fig. 2 shows a system 200 of computing devices 100 on which the various embodiments described herein may be implemented. The system 200 comprises a web server 210 for serving web pages to one or more client computing devices 220 over the Internet 230.

The web server 210 is provided with a web server application 240 for receiving requests, such as Hypertext Transfer Protocol (HTTP) and File Transfer Protocol (FTP) requests, and serving hypertext web pages or files in response. The web server application 240 may be, for example the Apache™ or the Microsoft TM IIS HTTP server.

The web server 210 is also provided with a hypertext preprocessor 250 for processing one or more web page templates 260 and data from one or more databases 270 to generate hypertext web pages. The hypertext preprocessor may, for example, be the PHP: Hypertext Preprocessor (PHP) or Microsoft AspTM hypertext preprocessor. The web server 210 is also provided with web page templates 260, such as one or more PHP or ASP files.

Upon receiving a request from the web server application 240, the hypertext preprocessor 250 is operable to retrieve a web page template, from the web page templates 260, execute any dynamic content therein, including updating or loading information from the one or more databases 270, to compose a hypertext web page. The composed hypertext web page may comprise client side code, such as Javascript, for Document Object Model (DOM) manipulating, asynchronous HTTP requests and the like.

The database 270 may be adapted for storing historical sales statistic parameter data for use in the manner described below. In this regard, the database 270 may be populated periodically with historical sales statistic parameter data. However, in a preferred embodiment, the web server 210 is adapted to integrate with existing content resource management system 280 (such as the Salesforce™ or similar content management system) for the purposes of obtaining the historical sales statistic parameter data. In this regard, the web server 210 may comprise a database connection for obtaining sales data such that the web server 210 is able to calculate their historical sales statistic parameter data. Alternatively, the content resource management system 280 may already comprise the historical sales statistic parameter data. In this manner, the web server 210 may simply retrieve the historical sales statistic parameter data from the content resource management system 280 using the database connection. It should be noted that the term "database connection" as used herein should not be construed as being limited to a database connection in the. technical sense and is broad enough to cover other means for retrieving data from other data sources including application program interface (API) calls and the like.

It should also be noted that in one less preferred embodiment, the web server 210 need not necessarily retrieve the historical sales statistic parameter data using the database connection wherein the historical sales statistic parameter data may rather be input into the Web server using the I/O interface 140.

Client computing devices 220 are provided with a browser application 280, such as the Mozilla Firefox™ or Microsoft Internet Explorer™ browser applications. The browser application 280 requests hypertext web pages from the web server 210 and renders the hypertext web pages on a display device 1020.

It should be noted that a web server architecture need not necessarily be employed by system 200. For example, the method 300 described herein may be implemented by a network comprising a data network other than a packet switched data network, such as by a data network implementing a propriety transmission protocol. Furthermore, the method 300 may be implemented by a stand-alone computing device.

Computer implemented method for calculating sales activity target data in accordance with historical sales statistic parameter data

Fig. 3 shows a computer implemented method 300 for calculating sales activity target data in accordance with historical sales statistic parameter data. The method 300 is executed by one or more computing devices 100 and in one embodiment by one or more computing devices 100 connected across the Internet 230 as substantially shown in Fig. 2.

Specifically, such a computing device 100 comprises a processor 1000 for processing digital data; a memory device 1 10 for storing digital data including computer program code and being coupled to the processor via a bus 150, a data interface (180, 140) for sending and receiving digital data and being coupled to the processor 1000 via the bus 150 and a database 1030 for storing digital data including historical sales statistic parameter data and being coupled to the processor 1000 via the bus 150. A computing device further comprises a database connection for retrieving digital data including periodically retrieving historical sales statistic parameter data, preferably from a content resource management system.

As will be described herein, the method 300 provides the basis of the desired outcome for the individual, sales team or sales organization as a whole allowing for customization by individual sales professionals to monitor their own sales performance, department or team to determine the desired targets and to monitor the progress of individuals within the team or organization to track, manage and gain visibility over the entire sales force.

Sales plan

The method 300 starts at step 305 where the computing device 100 is adapted to receive, via the data interface (180, 140), remuneration target parameter data. Turning now to Fig. 4, there is shown an exemplary graphical user interface (GUI) 400 for receiving remuneration target parameter data.

The GUI 400 comprises input fields 405 for inputting the remuneration target parameter data. Specifically, the GUI 400 comprises input fields as follows:

Base Salary input field 405a

The Annual Variable or Commission input field 405b component (usually most sales or quota carrying employees have a 50/50 or 60/40 split)

Desired Income for the year input field 405c

Having input the remuneration target parameter data using fields 405, the computing device 100 is adapted to calculate the quota achievement 415 as the quotient of the required attainment and the bookings quota in order for the sales individual to satisfy their desired income.

The required attainment 420 may be input by the sales person or their manager. However, in a preferred embodiment, the computing device 100 is adapted to calculate the required attainment 420 using a commission plan formula (which may vary from company to company) which is calculated in accordance with the desired income.

At step 310, having calculated the required commission 410, quota achievement 415 and required sales attainment 420, at step 310 the processor 1000 is controlled by the computer program code to load, using the database connection 1030 historical sales statistic parameter data. In this manner, the database 1030 may be periodically populated with historical sales statistics such that at the time required, the historical sales statistic parameter data 435 may be loaded from the database 1030.

In an alternative embodiment, the historical sales statistic parameter data 435 may be received from the data interface (180, 140). Specifically, the processor 1000 is controlled by the computer program code to receive, via the data interface (180, 140), historical sales statistic parameter data 435. The historical sales statistic parameter data 435 is typically input by a manager working in conjunction with the sales individual.

In one embodiment, the historical sales statistic parameter data 435 comprises:

Average deal size 425a;

deal to opportunity ratio (or closer rate%);

opportunity to meeting ratio (or closer rate %) 425b; and

meeting to call rates (percentage of meetings achieved to number of calls) 425c.

It should be noted that in other embodiments, the historical sales statistic parameter data 435 may comprise other inputs other than those shown above, depending on the application.

Having received the historical sales statistic parameter data 435, at step 315 of method 300, the processor 1000 is controlled by the computer program code to calculate sales activity target data 430 in accordance with the remuneration target parameter data 405 and the historical sales statistic parameter data 425.

Specifically, referring to Fig. 4, the sales activity target data 430 comprises:

The required number of deals needed based on the average deal size to achieve the desired income 430a;

The required number of opportunities needed to achieve the desired income based on the percentage of closure rates.

The required number of meetings 430b needed to achieve the desired income based on the percentage of closure rates.

The required number of client calls 430c needed to achieve the desired income.

The sales activity target data 430 can be modified to reflect daily, weekly, monthly, quarterly or annual targets. At step 320 of method 300, the processor 1000 is controlled by the computer program code to send, via the data interface (180, 140), the sales activity target data, such as for display in the GUI 400.

In one embodiment, the computing device 100 is programmed to calculate the sales activity target data 430 as follows:

The required number of deals needed based on the average deal size to achieve the desired income 430a is calculated as the quotient of the base 405a and the average deal size 425a;

The required number of opportunities needed to achieve the desired income based on the percentage of closure rates is calculated as the quotient of the required number of deals needed based on the average deal size to achieve the desired income 430a and the deal to opportunity ratio (or close rate %); and

The required number of meetings 430b needed to achieve the desired income is calculated as the quotient of the required number of opportunities and the opportunity to meeting ratio (or close rate %); and

The required number of client calls 430c needed to achieve the desired income is calculated as the quotient of the required number of meetings 430b and the meeting to call rates (percentage of meetings achieved to number of calls) 425 c.

As such, the sales individual may employ the sales activity target data 430 to gain insight into the following;

How ambitious the sales individual is based on the desired income goal;

How driven the sales individual is in regards to whether he or she is actually exceeding their number of calls and meetings needed based on the tools recommendations. This will in turn also reflect the sales persons ambitions in regards to overachieving the desired outcome goals

Determine the profile of the desired clients he she would like to pursue i.e. the type of client that will achieve the Average Deal Size 425a and enable the most optimum return on time investment. In addition, this will provide clarity to the sales individual on what sales activities can be delegated and also how his or her sales territory can be segmented to achieve a higher Average Deal Size 425a so that his meeting and call rates can be lowered;

Enabling the sales individual and their manager to determine what training and personal development needs need to be invested in to achieve the desired results. Enables the sales individual to determine their ow Key Performance Indicators "KPI's" instead of having them dictated by their manager. This will increase the morale and motivation of the individual as the individual can truly be in control of their destiny and self-actualization.

The processor 1000 may be controlled by the computer program code to perform the following calculations as shown in the pseudo code below:

A B C D

4 Inputs

5 New Bookings Quota From 'Revenue + Projection'(See below)

6 Base 100000

7 Total Annual Variable 100000

8 OTE =SUM(C6:C7)

9 Desired Income 400000

10 Required Variable =C9-C6

11 Commission Achievement =C10/C7

12 Quota Achievement =C20/C5

13

14 Settings

15 Average Deal Size 30000

16 Dea Meetings 0.3

17 Meetings.Calls 0.1

18

19 Plan to Meet Target

20 Required Attainment =G6

21

22 Per Year Per Week

23 Required Deals =G6/C15 =C23 48

24 Required Meetings -C23/C16 =C24/48 25 Required Calls =C24/C17 =C25/48

The computing device 100 is adapted to employ a commission calculation formula (which may differ from company to company) to determine required attainments and hence the activity required.

Revenue & Projection

In a preferred embodiment, the computing device is adapted to align the company and individuals goals with the key organizational objectives and requirements.

Turning now to Fig. 5, there is shown GUI 500 for displaying revenue targets. In this manner, whether sales quotas are based on daily, weekly, monthly, quarterly or yearly timeframes the computing device 100 is adapted to populate GUI 500 with sales quotas or targets.

The GUI 500 is configured such that the sales individual and manager can populate the tool with revenue taTget input data 505, including:

target data;

forecast or sales projections data; and

current or period to date sales booked.

In an alternative embodiment, the revenue target input data 505 can be updated automatically from an enterprise resource management system or the like.

Having received the revenue target input data 505, the computing device is adapted to calculate progress tracking data indicating how the salesperson is tracking from a sales booked perspective in relation to their sales activity target.

As is shown in Fig. 5, once a sales period has been completed the computing device 100 is adapted to close off the period and calculate how the sales individual is tracking for the year or period end. For example only the first two Quarters have been included as part of the annual target as shown in Fig. 5. As is show, the sales individual has booked 14% of meetings required to achieve the sales activity target.

Furthermore, having received the revenue target input data 505 the computing device 100 is adapted to calculate revenue quota tracking and projection data 510, which includes quota tracking and current, gap between sales achieved and OTE (On Target Earnings or current sales and commission plan). Furthermore, the revenue quota tracking and projection data 510 specifies for the sales individual what is needed to achieve their OTE from a Required Meetings and Call rate for the current and future periods.

Now that the sales individual has clarity on what is needed to achieve the revenue target that is expected from the organization the sales individual can now focus on what is required to achieve their desired income as per the sales individual's personal goals previously set.

As such, the computing device 100 is adapted to calculate GAP (gap to desired income) and activity needed data 515 representing the calculate GAP and activity needed by the sales individual to achieve the sales individual's personal and desired income goals.

Specifically, based on the sales individual's forecasted opportunities and average deal size the level of activity needed will be affected. For example, the higher the average deal size, the lower the level of activity required, making the desired income goal more achievable. The computing device 100 is adapted to make similar calculations for the conversion ratios.

This is turn will increase the sales individuals morale and motivation as the direction to achieve their personal objectives are made clear.

Key Performance Indicators (KPI's)

In a yet further embodiment, the computing device 100 is adapted to calculate a key performance data, as is shown in in Fig. 6.

As will be described herein, the computing device 100 addresses the problem of aligning a companies' goals and key performance measurements with achievable goals. In this regard it is not unusual to hear a sales individual complain that they feel they have been set up to fail. Furthermore, existing doctrine is that the cost of hiring, training and "ramp up" period of a new team member depending on the industry may attract a 2.5 x Y investment where "Y" represents the remuneration package of the new team member. As attracting and retaining good talent is a major challenge in an ever increasing competitive world the computing device 100 is adapted to provide a planning tool empowering the sales individual and their manager to form a collaborative approach to the success of the sales individual and furthermore develop a level of trust that will result in a motivated and loyal team member.

As such, GUI 600 is adapted for calculating KPI's based on the salesperson's remuneration target parameters 405. As shown in the figure, the GUI comprises agreed KPI data 605 that the manager and sales individual have agreed on as part of the performance appraisal process. The computing device 100 is adapted to update the agreed KPI data 605 with the sales activity target data 430 described above with reference to GUI 400. Specifically, as shown, the agreed KPI data 605 comprises the required telephone calls and meetings by the sales individuals. GUI 400 further comprises progress data 610 categorizing the sales individual's progress and weight data 15 indicating the relative weights of each KPI.

In this manner, the GUI 600 now enables the manager to work closely with the sales individual in identifying whether the activities needed are actually achievable based on their experience and what performance weightings are required based on the activities needed.

The processor 1000 is controlled by the computer program code to perform the following calculations:

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Current and next quarter planning

In one embodiment, and turning now to Fig. 7, there is shown a current quarter plan GUI 700. Similarly, Fig. 8 shows the next quarter plan GUI 800. GUI 700 and 800 enable the sales individual and manager to have visibility on the health of the current sales periods and following period. GUI 700 and 800 not only shows what the individual can or will achieve for the company sales activity targets, but GUI 700 and 800 gives visibility into how the sales individuals are tracking for their own desired income goals.

Using the information provided from GUI 700 and 800, the manager now can take a two-step approach into assisting their team members achieve company and personal goals. Furthermore, GUI 700 and 800 additionally indicates the average deal size and will clarify whether the desired and company income objectives are achievable or modifications to activity, training or development arc needed.

In a further embodiment, the computing device 100 is adapted to calculate marketing plan return on investment data. The marketing plan return on investment data will be developed based on individual company marketing and lead generations activities. The marketing plan return on investment data will furthermore be based on marketing activities and leads generated for the individual. This information can be either inputted directly or extracted from external sources or similar existing company tools, as an example.

Attainment Mapping

Turning now to Fig. 10, there is shown attainment mapping GUI 900. GUI 900 is adapted to allow a sales individual to map or calculate their income in real time reducing or eliminating payment disputes within a company.

GUI 900 comprises a map of attainment vs commission 905 and key sales accelerator data 910 indicating the percentage paid by a company based on sales performance.

The key sales accelerator data 910 may be customised or configured to each individual company needs and commission calculations.

The GUI 900 furthermore comprises a chart 910 of the individual, department or organization performance based on the individual commission or attainment calculations.

Preferred embodiment

Reference will now be made to the exemplary graphical user interfaces 1001 to 1007 as substantially shown in figure is 10 to 16 indicative of a commercial embodiment of the method 300. As is apparent from the interfaces, the interfaces are rendered within a browser application 280. However, as alluded to above, the interfaces need not necessarily be provided in this way by the system 200 and may be provided on a stand-alone computing device. Yet further, the interfaces may be provided by way of downloadable software application (such as a software application downloadable from an application store such as the Apple ^rM iTunes™ store or the Google™ Marketplace™) for execution by a mobile computing device such as a tablet computing device (such as an Apple™ iPad™) or a mobile telecommunication device (such as an Apple™ iPhone™) and the like.

Referring now to the exemplary graphical user interface 1001 as substantially shown in figure 10, the interface 1001 comprises the sales plan for a salesperson, given as John Smith in this instance. The sales plan interface 1001 is adapted to inform the salesperson the number of activities that are required in order to achieve their desired income. Specifically, the interface comprises the total remuneration 1005 representing the salesperson's current remuneration. However, the salesperson may desire a higher remuneration as indicated by the desired total remuneration 1010. In the example given, the current remuneration of the salesperson is $200,000 whereas the salesperson wishes to achieve a remuneration of $300,000.

As such, the web server 210 is adapted to utilize the historical sales statistic parameter data in the manner described above to calculate the required activity 1015 required by the sales person in order to meet their desired remuneration of $300,000. Specifically, the required activity 1015 indicates to the salesperson the number of calls, meetings, opportunities and bookings that should be made in order to achieve the desired remuneration 1010. As is apparent, the activities 1015 are divided into per quarter, per month and per week categories. In this manner, the salesperson is given immediate targets to meet in order to achieve their desired annual remuneration 1010.

As is apparent from the interface 1001, the activities further comprises a "rev counter" control adapted to provide a visually intuitive metric as to halve the sales person is performing for a particular activity. For example, the rev counter control indicates that the salesperson currently has made 9 meetings for the week which is in line with the salesperson is calculated activity level for meetings as completed by the web server 210. As such, the rev counter indicates that the salesperson "is in the green".

Also provided by the interface 1001 is a graphical representation 1020 of the salesperson is total remuneration indicative of the salesperson's desired total remuneration 1010 ($300,000 in this case) and the on-target remuneration of the salesperson ($200,000 in this case) which is the on target remuneration calculated by the web server 210 based on the user's current activities and the historical sales statistic parameter data.

Referring now to the exemplary graphical user interface 1002 as substantially shown in figure 11 , there is shown the interface 1002 displaying a "scoreboard" providing feedback to the salesperson as to whether there is any aspect of their sales performance that requires attention. The interface 1002 is adapted to provide a snapshot to the salesperson as holder salesperson is performing against their sales metrics. The metrics displayed in the interface 1002 are completed by the web server 210 in accordance with the salesperson's past current and projected future performance.

The scoreboard comprises a number of indica 1110 for different aspects of the salesperson sales performance which are represented by the web server 210 in different colours as to whether each aspect requires attention. For example, the first indica 1110 represents whether the salesperson is on target to meet their year-to-date target. Specifically, the web server 210 represents to the salesperson that based on the number of commits by the salesperson, at the end of the period the salesperson would have booked 94% of their year-to-date target. As such, were the salesperson to have booked less than 80% of their year-to-date target, for example, the web server 210 may represent the indica in red representing that attention is required. The subsequent indica represents to the salesperson how many meetings are required to achieve their annual target, how many meetings are required per week in order to achieve their second-quarter target and how many meetings per week are required to achieve their third-quarter target.

The next indicia relates to the forecast accuracy of the salesperson. For example, the web server 210 has calculated that the salesperson's commitment to the actual number of bookings is 86% accurate. Furthermore, the web server 210 has calculated that the commitment figures provided by the salesperson has varied by 47%.

The final indica representing to the salesperson how many meetings the salesperson is attending per week and how many meetings the salesperson should be attending per week in order to achieve their target.

As such, using the interface 1002, the salesperson is able to quickly identify aspects of their sales metrics that require attention, such as whether the salesperson is not achieving the required number of meetings per week and the like.

The interface 1002 further comprises an activity section 1115 showing the gap in remuneration in accordance with the salesperson's current activity. For example, if the salesperson is required to attend 10 meetings per week in order to achieve the desired remuneration of $300,000, the web server 210 is adapted to calculate the gap in remuneration (given as $128,278 in this example) should be salesperson only attend three meetings per week (which is in accordance with the salesperson's current activity) and the gap (given as $95,278 in this example) were the salesperson only attend five meetings per week (which is in accordance with the salesperson is second-quarter average).

Referring now to the interface 1003 as substantially shown in figure 12, there is shown the interface 1003 showing the year-to-date progress of the salesperson. The interface 1003 is adapted to provide up-to-date progress tracking to provide the salesperson (or the salesperson's manager) an insight as to whether the salesperson's sales metrics are on target.

Specifically, the interface 1003 comprises a graph 1205 indicating the salesperson's booked bookings as opposed to target. For example, the graph 1205 represents that the salesperson has currently booked $270,000 whereas the salesperson's target is $1 million, and furthermore that the salesperson's desired target is $1.8 million. The table beneath the graph 1025 breaks the bookings and target starting to further detail per quarter and additionally shows the salesperson's commitments, commitment gap and booked sales. For example, in the second quarter the salesperson has a sales target of $225,000, a desired target of $405,000 in order to achieve their desired remuneration of $300,000, a commit of $200,000, a commit gap of $25,000, bookings of $120,000 and a bookings gap of $105,000.

Referring now to the exemplary graphical user interface 1004 as substantially shown in figure

13, there is shown the interface 1004 displaying the weekly sales activity of the salesperson. The web server 210 is adapted to retrieve forecast and meeting data from the content resource management system 280 in order to track activity execution as displayed in the interface 1004. Specifically, the interface 1004 comprises a graph 1305 displaying activity for the second quarter. Specifically, the graph 1305 indicates the salesperson's target 1310, the salesperson's desired target 1315, the salesperson's commitments 1320 and the salesperson's bookings 1325. In this manner, the salesperson's manager is able to identify variations in the salesperson's sales metrics especially the salesperson's commits 1320.

Referring now to the exemplary graphical user interface 1006 as substantially shown in figure

14, there is shown the interface 1006 displaying a territory analysis for the salesperson used for market segmentation and analysis. The interface 1006 is adapted to calculate whether a salesperson's territory is able to support the salesperson's sales plan. For example, the interface 1006 can be used to determine whether the salesperson's sales plan is realistic such that remedial action may be taken such as by assigning the salesperson a greater territory for example.

In a preferred embodiment, the web server 210 is adapted to retrieve account information data from the content resource management system 280 in order to provide the information displayed in the interface 1006.

Specifically, the interface 1006 comprises a matrix 1405 segmenting the accounts of the salesperson's territory in accordance with account type (represented in columns as new, expanding and retention) and it account size (represented in rows as small medium and large). For example, the first sale of the matrix 1405 represents that the salesperson has six accounts that have fewer than 1500 units (which could be any suitable metric representative of size such as number of employers, number of computers or the like) and the sales offering saturation. For example, the new account type represents that the salesperson could potentially offer new sales to the account whereas the retention account type represents that the account has received sufficient sales such that further new sales are unlikely. In other words, accounts falling within *

the large size category and new account type (bottom left hand corner of the matrix 1405) offer the greatest potential sale amount (given as $3.16 million in this case) as opposed to accounts falling within the small size category and retention account type (given as $473,000 in this case)

The matrix 1405 is bounded by total rows and columns wherein the bottom right hand corner cell represents that the potential sales volumes for all 63 accounts of the salesperson's territory could support sales of $34.34 million, whereas the current sales of the- salesperson within the salesperson territory is $ 12.86 million. In this manner, the salesperson and the salesperson's manager would be able to ascertain whether the salesperson's sales plan is achievable or not. In ^■ this example, the salesperson could potentially realise an additional $21.84 million of sales within the salesperson's territory and thus it could be expected that the persons sales plan in order to achieve the salesperson's desired remuneration is achievable.

The interface 1006 further comprises pie charts 1410 dividing up the accounts by potential revenue on the left hand side (wherein in this example it is apparent that accounts falling within cell E3 provided the greatest potential revenue) and by a number of accounts oh the right hand side. As such, the easiest targets would be those having the highest potential revenue and the least number of accounts.

Referring now to the exemplary graphical user interface 1007 as substantially shown in figure

15, there is shown the interface 1007 showing a forecast of the number of commitment opportunities for the salesperson. In the example provided, it is apparent that the web server 210 has extracted commitment opportunities from the SalesForce content resource management system 280. However, as alluded to above, any content resource management system may be used depending on the application. As is apparent from the interface 1007, the interface 1007 indicates to the salesperson the expected revenue that could be achieved from each of the salesperson's accounts. For example, for the Grand Hotels generator installation account, the salesperson could expect a 90% probability of generating generate $350,000 from the account so as to generate expected revenue of $315,000.

Referring now to the exemplary graphical user interface 1008 as substantially shown in figure

16, there is shown the interface 1008 displaying a "manager scoreboard" for use by a salesperson's manager in displaying various indica 1 1 10 for different salespersons of a sales team so as to identify any potential problems. In a similar manner as described above, each indica 1 1 10 may be represented by the web server 210 in a different colour in accordance with the particular salespersons performance. For example, for the sales employee Jack Smith, the manager would be able to view whether Jack Smith was on track to meet his year to date target, where there has annual target was achievable, whether his second and third quarters were achievable, whether his forecast is accurate or not and his meeting execution. Furthermore, the interface 1008 comprises a representation 1605 displaying the remuneration, desired remuneration for the salesperson and also the forecast target remuneration, and forecast desired target.

It should be noted that other interfaces may be provided by the web server 210 as the case may be. For example, the application server 210 may provide an interface providing the ability to compare two or more sales professional's performance to identify areas for improvement. This performance includes current and past sales metrics relating to forecast, commitments, bookings as well as activity metrics such as meeting execution.

Yet further, the application server.210 may provide an interface providing the ability to use sales cycles (length of sale) to predict future forecast. Typically, activity such as meeting execution has a potential revenue impact several months down the track (for example where purchase orders issued at the end of the sales cycle).

Yet further; the application server 210 may provide the ability to perform detailed territory analysis by defining required sales activity based on each market segment. For example, for small, new customers the average sale amount is x and the conversion rates are y therefore z many meetings are required in this segment.

Yet further, the application server 210 may be adapted to provide the ability to separate "run rate" revenue from "new business" revenue. Run rate is expected revenue that will come in without sales activity, vs new business which requires sales activity (i.e. meetings).

Yet further, the application server 210 may be adapted to provide different activity plans for different roles. A acquisition sales professional will have a different plan to a renewal or retention sales professional.

Also, the application server 210 may be adapted to provide the ability to pull activity execution data from different sources in addition or alternative to the content resource management system 280 described above. Examples include number of calls made from the phone system, number of meetings attended from an email or calendar program and the like.

Interpretation

Database connection

It should be noted that the term "database connection" as used herein should not be construed as being limited to a database comiection in the technical sense and is broad enough to cover other means for retrieving data from other data sources including application program interface (API) calls and the like. In a preferred embodiments described herein, the database connection is adapted for retrieving data from a content resource management system so as to load historical sales statistic parameter data.

Bus

In the context of this document, the term "bus" and its derivatives, while being described in a preferred embodiment as being a communication bus subsystem for interconnecting various devices including by way of parallel connectivity such as Industry Standard Architecture (ISA), conventional Peripheral Component Interconnect (PCI) and the like or serial connectivity such as PCI Express (PCIe), Serial Advanced Technology Attachment (Serial ATA) and the like, should be construed broadly herein as any system for communicating data.

In accordance with:

As described herein, 'in accordance with' may also mean 'as a function of and is not necessarily limited to the integers specified in relation thereto.

Composite items

As described herein, 'a computer implemented method' should not necessarily be inferred as being performed by a single computing device such that the steps of the method may be performed by more than one cooperating computing devices.

Similarly objects as used herein such as 'web server', 'server', 'client computing device', 'computer readable medium' and the like should not necessarily be construed as being a single object, and may be implemented as a two or more objects in cooperation, such as, for example, a web server being construed as two or more web servers in a server farm cooperating to achieve a desired goal or a computer readable medium being distributed in a composite manner, such as program code being provided on a compact disk activatable by a license key downloadable from a computer network.

Database:

In the context of this document, the term "database" and its derivatives may be used to describe a single database, a set of databases, a system of databases or the like. The system of databases may comprise a set of databases wherein the set of databases may be stored- on a single implementation or span across multiple implementations. The term "database" is also not limited to refer to a certain database format rather may refer to any database format. For example, database formats may include MySQL, MySQLi , XML or the like.

Wireless: The invention may be embodied using devices conforming to other network standards and for other applications, including, for example other WLAN standards and other wireless standards. Applications that can be accommodated include IEEE 802.11 wireless LANs and links, and wireless Ethernet.

In the context of this document, the term "wireless" and its derivatives may be used to describe circuits, devices, systems, methods, techniques, communications channels, etc., that may communicate data through the use of modulated electromagnetic radiation through a non-solid medium. The term does not imply that the associated devices do not contain any wires, although in some embodiments they might not. In the context of this document, the term "wired" and its derivatives may be used to describe circuits, devices, systems, methods, techniques, communications channels, etc., that may communicate data through the use of modulated electromagnetic radiation through a solid medium. The term does not imply that the associated devices are coupled by electrically conductive wires.

Processes:

Unless specifically stated otherwise, as apparent from the following discussions, it is appreciated that throughout the specification discussions utilizing terms such as "processing", "computing", "calculating", "determining", "analysing" or the like, refer to the action and/or processes of a computer or computing system, or similar electronic computing device, that manipulate and/or transform data represented as physical, such as electronic, quantities into other data similarly represented as physical quantities.

Processor:

In a similar manner, the term "processor" may refer to any device or portion of a device that processes electronic data, e.g from registers and/or memory to transform that electronic data into other electronic data that, e.g., may be stored in registers and/or memory. A "computer" or a "computing device" or a "computing machine" or a "computing platform" may include one or more processors.

The methodologies described herein are, in one embodiment, performable by one or more processors that accept computer-readable (also called machine-readable) code containing a set of instructions that when executed by one or more of the processors carry out at least one of the methods described herein. Any processor capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken are included. Thus, one example is a typical processing system that includes one or more processors. The processing system further may include a memory subsystem including main RAM and/or a static RAM, and/or ROM. Computer-Readable Medium:

Furthermore, a computer-readable carrier medium may form, or be included in a computer program product. A computer program product can be stored on a computer usable carrier medium, the computer program product comprising a computer readable program means for causing a processor to perform a method as described herein.

Networked or Multiple Processors:

In alternative embodiments, the one or more processors operate as a standalone device or may be connected, e.g., networked to other processor(s), in a networked deployment, the one or more processors may operate in the capacity of a server or a client machine in server-client network environment, or as a peer machine in a peer-to-peer or distributed network environment. The one or more processors may form a web appliance, a network router, switch or bridge, or any machine capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that machine.

Note that while some diagram(s) only show(s) a single processor and a single memory that carries the computer-readable code, those in the art will understand that many of the components described above are included, but not explicitly shown or described in order not to obscure the inventive aspect. For example, while only a single machine is illustrated, the term "machine" shall also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein.

Additional Embodiments:

Thus, one embodiment of each of the methods described herein is in the form of a computer- readable carrier medium carrying a set of instructions, e.g., a computer program that are for execution on one or more processors. Thus, as will be appreciated by those skilled in the art, embodiments of the present invention may be embodied as a method, an apparatus such as a special purpose apparatus, an apparatus such as a data processing system, or a computer-readable carrier medium. The computer-readable carrier medium carries computer readable code including a set of instructions that when executed on one or more processors cause a processor or processors to implement a method. Accordingly, aspects of the present invention may take the form of a method, an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of carrier medium (e.g., a computer program product on a computer-readable storage medium) carrying computer-readable program code embodied in the medium. Carrier Medium:

The software may further be transmitted or received over a network via a network interface device. While the carrier medium is shown in an example embodiment to be a single medium, the term "carrier medium" should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more sets of instructions. The term "carrier medium" shall also be taken to include any medium that is capable of storing, encoding or carrying a set of instructions for execution by one or more of the processors and that cause the one or more processors to perform any one or more of the methodologies of the present invention. A carrier medium may take many forms, including but not limited to, non-volatile media, volatile media, and transmission media.

Implementation:

It will be understood that the steps of methods discussed are performed in one embodiment by an appropriate processor (or processors) of a processing (i.e., computer) system executing instructions (computer-readable code) stored in storage. It will also be understood that the invention is not limited to any particular implementation or programming technique and that the invention may be implemented using any appropriate techniques for implementing the functionality described herein. The invention is not limited to any particular programming language or operating system.

Means For Carrying out a Method or Function

Furthermore, some of the embodiments are described herein as a method or combination of elements of a method that can be implemented by a processor of a processor device, eomputer system, or by other means of carrying out the function. Thus, a processor with the necessary instructions for carrying out such a method or element of a method forms a means for carrying out the method or element of a method. Furthermore, an element described herein of an apparatus embodiment is an example of a means for carrying out the function performed by the element for the purpose of carrying out the invention.

Connected

Similarly, it is to be noticed that the term connected, when used in the claims, should not be interpreted as being limitative to direct connections only. Thus, the scope of the expression a device A connected to a device B should not be limited to devices or systems wherein an output of device A is directly connected to an input of device B. It means that there exists a path between an output of A and an input of B which may be a path including other devices or means. "Connected" may mean that two or more elements are either in direct physical or electrical contact, or that two or more elements are not in direct contact with each other but yet still cooperate or interact with each other.

Embodiments:

Reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment, but may. Furthermore, the particular features, structures or characteristics may be combined in any suitable manner, as would be apparent to one of ordinary skill in the art from this disclosure, in one or more embodiments.

Similarly it should be appreciated that in the above description of example embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. This method of disclosure, however, is not to be interpreted as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the Detailed Description of Specific Embodiments are hereby expressly incorporated into this Detailed Description of Specific Embodiments, with each claim standing on its own as a separate embodiment of this invention.

Furthermore, while some embodiments described herein include some but not other features included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the invention, and form different embodiments, as would be understood by those in the art. For example, in the following claims, any of the claimed embodiments can be used in any combination.

Different Instances of Objects

As used herein, unless otherwise specified the use of the ordinal adjectives "first", "second", "third", etc., to describe a common object, merely indicate that different instances of like objects are being referred to, and are not intended to imply that the objects so described must be in a given sequence, either temporally, spatially, in ranking, or in any other manner.

Specific Details

In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the invention may be practiced without these specific details. In other instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.

Terminology

In describing the preferred embodiment of the invention illustrated in the drawings, specific terminology will be resorted to for the sake of clarity. However, the invention is not intended to be limited to the specific terms so selected, and it is to be understood that each specific term includes all technical equivalents which operate in a similar manner to accomplish a similar technical purpose. Terms such as "forward", "rearward", "radially", "peripherally", "upwardly", "downwardly", and the like are used as words of convenience to provide reference points and are not to be construed as limiting terms.

Comprising and Including

In the claims which follow and in the preceding description of the invention, except where the context requires otherwise due to express language or necessary implication, the word "comprise" or variations such as "comprises" or "comprising" are used in an inclusive sense, i.e. to specify the presence of the stated features but not to preclude the presence or addition of further features in various embodiments of the invention.

Any one of the terms: including or which includes of that includes as used herein is also an open term that also means including at least the elements/features that follow the term, but not excluding others. Thus, including is synonymous with and means comprising.

Scope of Invention

Thus, while there has been described what are believed to be the preferred embodiments of the invention, those skilled in the art will recognize that other and further modifications may be made thereto without departing from the spirit of the invention, and it is intended to claim all such changes and modifications as fall within the scope of the invention. For example; any formulas given above are merely representative Of procedures that may be used. Functionality may be added or deleted from the block diagrams and operations may be interchanged among functional blocks. Steps may be added or deleted to methods described within the scope of the present invention. .

Although the invention has been described with reference to specific examples, it will be appreciated by those skilled in the art that the invention may be embodied in many other forms.

Industrial Applicability It is apparent from the above, that the arrangements described are applicable to the data processing industry.