System and Method to Measure, Aggregate and Analyze Exact Effort and Time Productivity

• US 20170116552A1
• Filed: 01/05/2017
• Published: 04/27/2017
• Est. Priority Date: 06/04/2010
• Status: Abandoned Application

• Current Assignee: Sapience Analytics Private Limited
• Original Assignee: Sapience Analytics Private Limited
• Inventors: Deodhar, Shirish Prabhakar, Deodhar, Swati Shirish, Bhatia, Madhukar Sharan
• Application Number:
  US15/398,960
• Publication Number:
  US 20170116552A1
• Time in Patent Office: Days
• CPC Class Codes: G06Q 10/063114 Status monitoring or status determination for a person or group
• CPC Class Codes: G06Q 10/06316 Sequencing of tasks or work
• CPC Class Codes: G06Q 10/0639 Performance analysis of employees; Performance analysis of enterprise or organisation operations
• CPC Class Codes: G06Q 10/06398 Performance of employee with respect to a job function
• CPC Class Codes: G06Q 10/105 Human resources

Abstract

A system and method for automatically measuring, aggregating, analysing, predicting exact effort and time productivity, of white collar employees, within an organization and thereafter providing instructions for improving productivity and workload allocation, and optimizing workforce and operational efficiency, without requiring manual intervention or configuration, is described. The system captures all the work effort put on by the users. The system tracks the daily time spent by employees. This is mapped to activities and objectives that are automatically inferred based on the applications and artifacts being used, the source of offline time usage, and the employee'"'"'s position in the organization and role therein. The captured individual work effort is mapped to the organization'"'"'s hierarchy and business attributes. As a result, Work Patterns and trends within each sub-unit/operational dimension of the business are identified.

Claims

1. A computer implemented system for automatically measuring, aggregating, analysing and predicting exact effort and time productivity, of at least one user having access to at least one Computing System (CS) agent, within an organization and thereafter providing instructions for improving productivity and workload allocation, and optimizing workforce and operational efficiency, the system comprising:

at least one server;

said at least one CS agent associated with said at least one user accessing the server, said CS agent adapted to automatically measure and generate consolidated and exact online and offline effort data throughout the day (24 hours), for all days, wherein said CS agent is selected from the group consisting of a computer desktop, laptop, electronic notebook, personal digital assistant, tablet, and smartphone, and wherein the CS agent has access to;

a master list for the user containing his or her Purposes and Activities, role and business attributes, and an optional assignment of work units for one or more Purposes, the master list automatically preconfigured at an organization level server based on the user'"'"'s role and other work related attributes, and

a rules and pattern mapping engine containing organization mapping rules and current user specific mapping rules for mapping online applications and offline slots to a default Purpose and Activity;

a user identifier adapted to identify the user by his or her unique login ID available with the CS agent, said user identifier further configured to prompt the user for an ID in case a neutral login ID is being used by more than one user;

a time tracker having access to said CS agent and adapted to track the user'"'"'s online time on a currently active user application and associated artifact from a multiplicity of open applications on said CS agent, and record the name of the active application and artifact name(s) and duration of usage, said time tracker further adapted to mark the user'"'"'s offline time slots by determining each period of inactivity time during which no movement of physical input device(s) of said CS agent is detected for more than a predetermined period of time, wherein;

said associated artifact is selected from the group consisting of a file, a folder, and a website, and

said physical input device(s) are selected from the group consisting of keyboards, keypads, touchpads, and mouse;

a comparator adapted to compare scheduled engagements, meetings, calls, lab work, travel time and remote visits of the user as obtained from the user'"'"'s calendar on said CS agent and from local Presence Devices (PDs), with the duration of said offline time slots for determining the user'"'"'s offline time utilization, wherein the local Presence Devices include smartphones with GPS that are connectable to or part of the CS agent;

a logger adapted to maintain a consolidated and sequential log of the user'"'"'s online and offline time slots;

a time analyser adapted to map said log of the slots to an appropriate Activity, Purpose, and optionally a work unit based on the mapping rules, and further adapted to generate and upload an effort map of the user on the server, wherein;

said Purpose is selected from the group consisting of assigned projects and functions,

said appropriate Activity, for the selected Purpose, is selected from the group consisting of design, programming, testing, documentation, communication, browsing, meetings, calls, lab work, travel, and visits, and

said work unit, for the selected Purpose, is selected from the group consisting of assigned transactions, tasks and deliverables;

a CS agent interface, resident in said server, configured to collect effort data from every CS agent for the user, wherein the effort data is in the form of an CS effort map, said CS effort map configured to list in a chronological order, the online and offline time for the user;

a PD interface, resident in said server, configured to determine the offline PD effort map for the user by obtaining information about user'"'"'s time on business calls, meetings, visits to labs and other intra-office locations, business travels, and time spent at customer/vendor locations, by interfacing with all remote Presence Devices and PD servers;

a server effort map unit, resident in said server, configured to merge said CS effort map and said offline PD effort map for every user, and generate a chronologically accurate and complete final user effort map, said final user effort map uploaded back to every user'"'"'s CS agent;

a user Work Pattern analyser adapted to periodically receive said final user effort map, said user Work Pattern analyser further adapted to;

compute a plurality of Work Pattern items, using said final user effort map, wherein said plurality of Work Pattern items are selected from the group consisting of a work time, an online work time, an offline work time, time spent on each Purpose, Activity, application and work unit for the user, a core activity time, a collaboration work time, work habits, a total travel time, a fitness time, a CS usage time, a smart-phone addiction, a physical time in a workplace, a private time in a workplace, a work time at home, a work effectiveness index, and a work life balance index,

generate wellness instruction prompts for the user,

automatically tag each day, in said final user effort map, as a workday, a weekend day, a public holiday or a vacation,

automatically detect the user'"'"'s location as home, office and other, and

automatically tag each day, in the final user effort map, as a work from office day, a work from home day or a work from other location day;

a user predictor and instructor module adapted to periodically receive the plurality of Work Pattern items, the user predictor and instructor module further adapted to;

select appropriate Work Pattern items, from said plurality of Work Pattern items, for tracking the user'"'"'s performance based on the user'"'"'s role in an organization hierarchy,

provide a feedback to the user on highlights related to work effort, work output and the work life balance index,

suggest areas of improvements for the user,

set goals for the user based on said plurality of Work Pattern items,

provide encouragement for the user with points and badges,

generate a progress report based on the goals, the points and the badges won, and

predict the improvements in the work effort, the work output, the work effectiveness index and the work life balance index for the user;

a local user interface adapted to receive inputs from said user Work Pattern analyser and said user predictor and instructor module, said local user interface further adapted to;

display privately and exclusively to the user, the Work Pattern trends for a predetermined period, and the wellness instruction prompts,

indicate the areas of improvements and the goals,

display the progress report based on the goals, the points and the badges won, and

review and edit Activity, Purpose, and work unit mappings;

a user private time selector adapted to disable a user'"'"'s time tracker for specified time ranges, wherein said time ranges includes the time slots, said time slots in the time ranges are marked as unaccounted and private time;

a privacy filter, resident in said CS agent, said privacy filter cooperating with the rules and pattern mapping engine and adapted to;

mark all effort that is not identified as being on work related activities by the server and the user'"'"'s mapping rules as personal time,

enable the user to explicitly change any time that was marked as personal to work,

enable the user to explicitly change any time that was marked as work by the server or the user'"'"'s mapping rules to personal,

enable the user to select, or enable the CS agent to set directly, from one or more of the following privacy filter settings, when the CS agent is enabled to upload the user'"'"'s effort data;

deactivate uploading of user'"'"'s personal time details to said server,

deactivate uploading of some aspects of the user'"'"'s work related information including applications and associated artifacts, to said server, and

reduce the granularity of the user'"'"'s work related information that is uploaded to the server to a daily, weekly, or monthly average of the Work Patterns, and

deactivate uploading of all the user'"'"'s information to the server, when said CS agent is not enabled to upload the user'"'"'s effort, both work and personal, to the server, thereby enabling the CS agent to function in a self-improvement mode for the user and further enable the CS agent to select from one of the following data sharing options;

allow the user to voluntarily disclose identity and some or all aspects of the user'"'"'s Work Patterns to the server in return for being able to collaborate with peers or the entire organization for benchmarking and cross-learning from each other, and

allow the user to voluntarily disclose some or all aspects of the user'"'"'s Work Patterns to the server, wherein said CS agent is adapted to obfuscate the user'"'"'s identity, in return for being able to benchmark user'"'"'s own performance with that of the peers or the entire organization as provided by the server;

and

said at least one server comprises;

an organization sync agent configured to collect and maintain the list of current valid users and the organization hierarchy that maps each user to one or more organization sub-units, the organization sync agent further configured to collect and maintain the business attributes qualifying each user and organization sub-unit from organization application data stores, wherein;

said business attributes for the user are selected from the group consisting of role, skills, salary, position, and location, and

said business attributes for the organization sub-unit are selected from the group consisting of domain, vertical, cost and profit center, and priority;

an organization settings and rules engine adapted to configure a master list of Purposes and Activities, derived from the organization hierarchy, wherein said organization hierarchy represents projects and functions, and said master list may be multi-level and adapted for each organization sub-unit and user, said organization settings and rules engine further adapted to configure default rules for mapping online and offline time slots to Purposes and Activities, said organization settings and rules engine further configured to adapt the mapping rules for organization sub-units based on their business attributes and further adapted for each user based on his or her position in the sub-unit hierarchy and the user'"'"'s business attributes,

an organization effort aggregation and analytics engine configured to consolidate and roll up individual online and offline effort data as per the organization hierarchy, said organization effort aggregation and analytics engine further configured to compute a per-employee Daily Average Work Pattern for each sub-unit, said organization effort aggregation and analytics engine still further configured to generate an n-dimensional effort data cube mapping individual and collective efforts of respective users as per the organization hierarchy,

an organization Work Pattern analyser configured to periodically receive the per-employee Daily Average Work Pattern for each sub-unit, said organization Work Pattern analyser further configured to;

compute a plurality of sub-unit Work Pattern items for each sub-unit, wherein said plurality of sub-unit Work Pattern items are selected from the group consisting of a sub-unit effort, sub-unit habits, a sub-unit effort distribution across Purposes, Activities, applications and work units, a sub-unit work life balance index, a sub-unit capacity utilization, and a sub-unit work effectiveness index,

an organization predictor and instructor module configured to receive said plurality of sub-unit Work Pattern items, the organization predictor and instructor module further configured to;

select appropriate sub-unit Work Pattern items, from said plurality of sub-unit Work Pattern items, for tracking each sub-unit'"'"'s performance based on the nature of each of the sub-unit,

provide a feedback to a manager on highlights related to a sub-unit work effort, a sub-unit work output, a sub-unit workload assignment and a sub-unit staff allocation for each of the sub-unit,

suggest areas of improvements for each of the sub-unit;

track progress of each of the sub-unit,

set goals for improving the sub-unit work effectiveness index and sub-unit productivity for each of the sub-unit;

suggest recommendations about the best practices for each of the sub-unit,

predict the improvements in said sub-unit work effort, said sub-unit work output, said sub-unit work effectiveness index and said sub-unit work life balance index for each of the sub-unit,

predict delays in project timelines, effort and cost overruns, inability to meet an output target, and an impact possible with improvements, and

generate intelligent reports for improving operational effectiveness and workforce optimization in each of the sub-unit;

a recognition and rewards module configured to assign performance points to users and sub-units based on individual and aggregate effort and completed work units, and

a web user interface configured to facilitate views at each level of the organization hierarchy across Work pattern items, said web user interface further configured to selectively filter and drill down to generate and compare discrete effort data for any Work Pattern item across any business attribute, wherein;

said Work Pattern items are selected from the group consisting of effort, habits, effort distribution across Purposes, Activities, applications and work units, work life balance index, capacity utilization, and work effectiveness index, and

said business attributes are selected from the group consisting of role, skills, salary, position, and location for the user, and from the group consisting of domain, vertical, cost and profit center, and priority for the organization sub-unit;

and

a blocker, resident in said server, said blocker cooperating with said CS agent and adapted to;

control third party access to individual level data by restricting access to said individual level data based on the organization hierarchy and as per assigned access rights,

block individual data visibility of certain users based on their role or seniority in the organization,

block individual data visibility entirely, and

block organization sub-unit visibility if a user count computed for the organization sub-unit is below a predetermined user count.

2. The system as claimed in claim 1, wherein the web user interface is configured to:

communicate with an internet browser and display through said internet browser the organization trends, reports, alerts, goals and administrative functions depending upon the user'"'"'s position and role in the organization hierarchy; and

provide access to the organization effort aggregation and analytics engine for generation of user defined custom reports from the n-dimensional effort data cube.

3. The system as claimed in claim 1, wherein said organization effort aggregation and analytics engine is further configured to deduce a best working pattern and top performers at individual and organization sub-unit level, said organization effort aggregation and analytics engine further configured to determine unusual Work Patterns and the recent positive and negative deviations in Work Patterns for an organization sub-unit, said organization effort aggregation and analytics engine still further configured to generate a report including specific actions that can be undertaken to improve the efforts of the users.

4. The system as claimed in claim 1, wherein the rules and pattern mapping engine is adapted to generate the default mapping rules for mapping the online and offline time slots to Purposes and Activities, including pattern matching to deduce best fit rules, the rules and pattern mapping engine further configured to adapt the rules for users in organization sub-units based on the business attributes and further adapted based on each user'"'"'s position in the sub-unit hierarchy and the user'"'"'s role therein.

5. The system as claimed in claim 1, wherein said CS agent includes a user interface local to the Computing System agent, and configured to provide the respective users with private access to their corresponding entire work related and personal online and offline effort data.

6. The system as claimed in claim 1, wherein said blocker is further configured to actuate an ‘

anonymous mode’

wherein the visibility of individual effort data is completely blocked for the entire organization or for sub-units in certain geographies, and trends and reports are available only up to team level provided a team has a certain minimum number of employees.

7. The system as claimed in claim 1, wherein said privacy filter is further configured to actuate a ‘

self-improvement mode’

wherein;

no effort data is uploaded by default to the server;

productivity improvements are achieved through employee self-awareness by tracking user'"'"'s own Work Patterns as provided on the local Computing System agent and by comparing against the goals set by the managers and the organization;

Work Patterns are uploaded anonymously to the server, in return for being able to view the comparative trends across the users who voluntarily shared their respective effort data, and thereby rate one'"'"'s own relative performance; and

user'"'"'s profile is defined and comparisons are made with peers having a similar profile and who voluntarily but anonymously shared their respective effort data, wherein the user'"'"'s profile is selected from the group consisting of role, seniority, location and skills.

8. The system as claimed in claim 1, wherein the system further includes:

a global pattern knowledge platform configured to enable the participating organizations to share their high-level Work Pattern analytics and trends based on employee and sub-organization categories;

a profile definition module configured to enable the participating organizations to define profiles corresponding to at least their respective sizes, industry and vertical; and

a report generation module configured to prepare reports rating the organization'"'"'s performance and standing relative to peer organizations in accordance with the selected profile criteria.

9. The system as claimed in claim 1, wherein said time tracker is further configured to ignore any simulated input device or spurious movement through robotic control of the physical devices.

10. The system as claimed in claim 1, wherein said user Work Pattern analyser employs an automated and adaptive learning for:

deciding improvement goals for the user, and

determining the user'"'"'s work effectiveness index and work life balance index;

11. The system as claimed in claim 1, wherein the user Work Pattern analyser employs a fuzzy logic to determine user vacations, weekends and holidays, shift timings, work from home and office and other locations, and unaccounted time in office.

12. The system as claimed in claim 1, wherein said user predictor and instructor module uses correlation between the Work Pattern items and the work output to:

provide feedback to the user about the Work Pattern items that impact work output; and

make recommendations to improve performance.

13. The system as claimed in claim 1, wherein said organization predictor and instructor module employs an automated and adaptive learning for:

deciding improvement goals for each sub-unit; and

determining said sub-unit'"'"'s work effectiveness index and said sub-unit'"'"'s work life balance index.

14. The system as claimed in claim 1, wherein said organization predictor and instructor module employs correlation between said sub-unit Work Pattern items and said sub-unit work output to:

provide feedback to managers about the sub-unit Work Pattern items that impact sub-unit work output; and

make recommendations to improve the sub-units performance.

15. A computer-implemented method for automatically measuring, aggregating, analysing and predicting exact effort and time productivity of at least one user associated with at least one Computing System (CS) agent accessing at least one server, within an organization and thereafter providing instructions for improving productivity and workload allocation, and optimizing workforce and operational efficiency, the method comprising the following steps:

creating a master list for every user, wherein said master list includes the user'"'"'s Purposes and Activities and configuring the master list to reflect the user'"'"'s role and other work related attributes;

storing organization settings and mapping rules, said mapping rules being configured as per the position of the user in the organization hierarchy and role;

mapping online applications and offline slots in accordance with the stored organization settings and rules;

identifying the user by his or her unique login ID;

tracking the user'"'"'s online time on a currently active user application and associated artifact from a multiplicity of applications opened by the user, and recording the name of the active application and artifact name(s) and duration of usage, wherein the associated artifact is selected from the group consisting of a file, a folder and a web site;

marking the user'"'"'s offline time slots by determining each period of inactivity time during which no movement of physical input devices is detected for more than a predetermined period of time, wherein the physical input devices are selected from the group consisting of keyboards, keypads, touchpads and mouse;

comparing scheduled engagements, meetings, calls, lab work, travel time and remote visits of the user as obtained from a calendar of the user on the CS agent and from local Presence Devices (PDs), wherein the local Presence Devices includes smartphone with GPS, that are connectable to or a part of the Computing System agent, with the duration of the offline time slots for determining the user'"'"'s offline time utilization;

maintaining, using a logger, a consolidated and sequential log of user'"'"'s online and offline time slots;

applying the mapping rules to the online application and offline slots and deducing best fit rules to map all slots to an appropriate Activity, Purpose and optionally a work unit automatically based on the mapping rules, wherein;

said Purpose is selected from the group consisting of assigned projects and functions,

said appropriate Activity, for the selected Purpose, is selected from the group consisting of design, programming, testing, documentation, communication, browsing, meetings, calls, lab work, travel and visits, and

said work unit, for the selected Purpose, is selected from the group of assigned transactions, tasks and deliverables;

generating the user'"'"'s online and offline time utilization log mapped to the Activities, Purposes and work units constituting the user'"'"'s effort map for the CS agent;

collecting effort data, at said server, from every Computing System agent of every user, wherein the effort data is in the form of a CS effort map, the CS effort map listing in a chronological order, the online and offline time for each user;

obtaining, at the server, offline PD effort maps for each user having information about the user'"'"'s time on business calls, meetings, visits to labs and other intra-office locations, business travels and time spent at customer/vendor locations, by interfacing all remote Presence Devices (PDs) and PD servers;

merging, at said server, the CS effort map and the offline PD effort map and generating a chronologically accurate and complete final user effort map, and uploading the final user effort map to every user'"'"'s CS agent;

downloading the final user effort map back onto each of the CS agents of the user;

periodically receiving said final user effort map at a user Work Pattern analyser of the CS agent and performing the analysis of the Work Patterns of the user, wherein the step of performing the analysis of the Work Patterns of the user includes following sub-steps;

computing a plurality of Work Pattern items, using the final user effort map, wherein the plurality of Work Pattern items are selected from the group consisting of a work time, an online work time, an offline work time, a time spent on each Purpose, Activity, application and work unit for the user, a core activity time, a collaboration work time, work habits, a total travel time, a fitness time, a PD usage time, a smartphone addiction, a physical time in a workplace, a private time in a workplace, a work time at home, a work effectiveness index and a work life balance index,

generating wellness instruction prompts for the user,

tagging each day, in the final user effort map, as a workday, a weekend day, a public holiday or a vacation,

automatically detecting the user'"'"'s location as home, office and other, and

tagging each day, in the final user effort map, as a work from office day, a work from home day or a work from other location day;

periodically receiving said plurality of Work Pattern items at a user predictor and instructor module of the CS agent and performing predictions and instructions for the user, wherein step of performing predictions and instructions for the user includes following sub steps;

selecting appropriate Work Pattern items, from said plurality of Work Pattern items, for tracking the user'"'"'s performance based on the user'"'"'s role in an organization hierarchy,

providing a feedback to the user on highlights related to work effort, work output, and the work life balance index,

suggesting areas of improvements,

setting goals for the user based on said plurality of Work Pattern items;

providing encouragement for the user with points and badges,

generating a progress report based on the goals, the points and badges won, and

predicting the improvements in said work effort, said work output, said work effectiveness index and said work life balance index;

receiving, at a local user interface, the Work Patterns, the wellness instruction prompts, the suggested areas of improvement, goals, and the progress report based on the goals, the points and the badges won;

displaying privately and exclusively to the user the Work Pattern trends, instructions and the progress report for a predetermined period;

disabling the user'"'"'s time tracker for specified time ranges, wherein the time ranges includes the time slots, said time slots in the time ranges are marked as unaccounted and private time;

marking all effort that is not identified as being on work related activities by the server and the user'"'"'s mapping rules as personal time;

enabling the user to explicitly change any time that was marked as personal to work;

enabling the user to explicitly change any time that was marked as work by the server or the user'"'"'s mapping rules to personal;

enabling the user to select, or enabling the CS agent to set directly, from one or more of the following privacy filter settings, when said CS agent is enabled to upload the user'"'"'s effort data;

i. deactivating uploading of user'"'"'s personal time details to the server,

ii. deactivating uploading of some aspects of the user'"'"'s work related information including applications and associated artifacts to the server, and

iii. reducing the granularity of the user'"'"'s work related information that is uploaded to the server to a daily, weekly, or monthly average of the Work Patterns;

deactivating upload of all the user'"'"'s information to the server, when said CS agent is not enabled to upload the user'"'"'s effort, both work and personal, to the server, thereby enabling the CS agent to function in self-improvement mode for the user and further enable the CS agent to select from one of the following data sharing options;

i. allowing the user to voluntarily disclose identity and some or all aspects of the user'"'"'s Work Patterns to the server in return for being able to collaborate with peers or the entire organization for benchmarking and cross-learning from each other, and

ii. allowing the user to voluntarily disclose some or all aspects of the user'"'"'s Work Patterns to the server, wherein said CS agent is adapted to obfuscate the user'"'"'s identity, in return for being able to benchmark user'"'"'s own performance with that of the peers or the entire organization as provided by the server;

collecting and maintaining, at the server, a list of current valid users and the organization hierarchy that maps every user to one or more organization sub-units, and collecting and maintaining the business attributes qualifying each user and organization sub-unit, wherein;

said business attributes for the user are selected from the group consisting of employee levels, roles, skills, locations, verticals, technologies and cost centers, and

said business attributes for the organization sub-unit are selected from the group consisting of domain, vertical, cost, profit center, and priority;

consolidating and rolling up, at said server, individual online and offline effort data as per the organization hierarchy, and computing a per-employee Daily Average Work Pattern for every sub-unit;

generating, at said server, an n-dimensional effort data cube mapping individual and collective efforts of respective users as per the organization hierarchy;

periodically receiving said per-employee Daily Average Work Pattern for each sub-unit at an organization Work Pattern analyser of the server and performing the analysis of said per-employee Daily Average Work Pattern for each sub-unit, wherein the step of performing the analysis of said per-employee Daily Average Work Pattern for each sub-unit includes following sub-step;

i. computing a plurality of sub-unit Work Pattern items for each sub-unit, wherein said plurality of sub-unit Work Pattern items are selected from the group consisting of a sub-unit effort, sub-unit habits, a sub-unit effort distribution across Purposes, Activities, applications and work units, a sub-unit work life balance index, a sub-unit work effectiveness index, and a sub-unit capacity utilization;

periodically receiving said plurality of sub-unit Work Pattern items at an organization predictor and instructor module of the server and performing predictions and instructions for each sub-unit, wherein step of performing predictions and instructions for each sub-unit includes following sub steps;

i. selecting appropriate sub-unit Work Pattern items, from said plurality of sub-unit Work Pattern items, for tracking each sub-unit'"'"'s performance based on the nature of each sub-unit,

ii. providing a feedback to a manager on highlights related to a sub-unit work effort, a sub-unit work output, a sub-unit workload assignment and a sub-unit staff allocation for each sub-unit,

iii. suggesting areas of improvements,

iv. tracking progress,

v. setting goals for improving said sub-unit work effectiveness index and sub-unit productivity for each of the sub-unit,

vi. suggesting recommendations about the best practices,

vii. predicting the improvements in said sub-unit work effort, said sub-unit work output, said sub-unit work effectiveness index and said sub-unit work life balance index,

viii. predicting delays in project timelines, effort and cost overruns, inability to meet an output target, and the impact possible with improvements, and

ix. generating intelligent reports for improving operational effectiveness and a talent management;

assigning, at said server, performance points to users and sub-units based on the individual and aggregate effort, and completed work units;

facilitating, over a web user interface, the display of trends related to work effort, Work Patterns, predictions and instructions relating to sub-units at each level of the organization hierarchy subject to the view access rights of the user and a blocker;

enabling the user, over the web user interface, to selectively filter and drill down, at the server, for generating and comparing discrete effort data for any Work Pattern item across any business attribute, wherein;

said Work Pattern items are selected from the group consisting of effort, habits, effort distribution across Purposes, Activities, applications and work units, work life balance index, capacity utilization, and work effectiveness index, and

i. said business attributes are selected from the group consisting of role, skills, salary, position, and location for the user, and from the group consisting of domain, vertical, cost and profit center, and priority for the organization sub-unit;

and

displaying the entire work related and personal online and offline effort data on a user interface local to the Computing System agent of the user.

16. The method as claimed in claim 15, wherein the method further includes the following steps:

displaying the organization trends, reports, alerts, goals and administrative functions depending upon user'"'"'s position and role in the organization hierarchy; and

generating user-defined custom reports from the n-dimensional effort data cube.

18. The method as claimed in claim 15, wherein the method further includes the step of actuating an ‘

anonymous mode’

wherein the visibility of individual effort data is completely blocked for the entire organization or for sub-units in certain geographies, and trends and reports are available only up to team level, provided the team has a certain minimum number of employees.

19. The method as claimed in claim 15, wherein the method further includes the step of actuating a ‘

self-improvement mode’

wherein no user effort data is uploaded to the server.

20. The method as claimed in claim 15, wherein the method further includes the following steps:

providing a global knowledge platform and enabling participating organizations to share their high-level Work Pattern analytics and trends based on employee and sub-organization categories;

enabling the participating organizations to define profiles corresponding to their respective sizes, industry and vertical; and

preparing reports rating the organization'"'"'s performance and standing, relative to peer organizations in accordance with the selected profile criteria.

17. The method as claimed in 15, wherein the step of consolidating and rolling up individual online and offline effort data further includes the following steps:

deducing a best working pattern, top performers at individual and organization sub-unit level;

determining unusual Work Patterns and the recent positive and negative deviations in Work Patterns for an organization sub-unit; and

generating a report including specific actions that can be undertaken to improve the efforts of the users.