COMPUTERIZED-METHOD AND COMPUTERIZED-SYSTEM FOR IDENTIFYING HIGH IMPACTED SCHEDULES, IN A CONTACT CENTER

1 . A computerized-method for identifying high impacted schedules, in a contact center, said computerized-method comprising:

retrieving schedules of agents during a preconfigured period from a Workforce Management (WFM) system, for each schedule:

(i) operating a schedule quotient module to derive schedule-quotient score;

(ii) operating an agent quotient module to derive agent-quotient score;

(iii) operating a Schedule Impact Score (SIS) module to derive a schedule-impact score based on the derived schedule-quotient score and the derived agent-quotient score; and

(iv) operating a recommendation module for auto-corrective measures in one or more systems based on the derived schedule-impact score.

2 . The computerized-method of claim 1 , wherein the retrieved schedules are at least one of: (i) active schedules and the schedule-impact score is derived in real-time; and (ii) future schedules.

3 . The computerized-method of claim 1 , wherein the auto-corrective measures include at least one of: (i) displaying the derived schedule-impact score of each schedule on schedule management dashboard which is associated to a schedule management module in the WFM system; (ii) generating a report including key statistics representing an impact of the schedule on schedule working days; (iii) performing realignment of routing of an Automatic Call Distribution (ACD) system; (iv) optimizing schedules in the WFM system in an order that is based on each schedule schedule-impact score.

4 . The computerized-method of claim 1 , wherein the schedule quotient module derives the schedule-quotient score based on retrieved schedule metrics from a schedule metrics database.

5 . The computerized-method of claim 1 , wherein the agent-quotient score is derived based on retrieved agent metrics from an agent metrics database.

6 . The computerized-method of claim 1 , wherein the schedule quotient module derives the schedule-quotient score based on at least one parameter of:

(i) schedule staffing variance;

(ii) Schedule average Service Level Agreement (SLA) variance in a preconfigured period;

(iii) Average Handle Time (AHT) for this schedule in the preconfigured period;

(iv) Average Speed of Answer (ASA) for the schedule in the preconfigured period;

(v) number of time-off requests raised for the schedule in status of approved, pending and denied;

(vi) number of shift trade-off requests raised for the schedule in status of approved, pending and denied;

(vii) forecast results of whether the schedule could be impacted due to natural calamities or pandemic situations;

(viii) forecast results for trend change in call or interactions volume for this schedule;

(ix) average customer sentiment for interactions handled in the schedule in the preconfigured period;

(x) number of schedule changes in status of approved, pending and denied; and

(xi) percentage of agents having a user-defined activity code which prevents them from contributing to participate in activities of the schedule.

7 . The computerized-method of claim 1 , wherein the agent quotient module derives the agent-quotient score based on at least one parameter of:

(i) average schedule adherence;

(ii) average agent performance;

(iii) average agent proficiency;

(iv) average agent sentiments for interactions handled in the schedule in a preconfigured period;

(v) average agent occupancy rate in the schedule in the preconfigured period;

(vi) agent absenteeism trend in the preconfigured period;

(vii) agent performing overtime;

(viii) agent tenure;

(ix) agent with more than a preconfigured number of skills;

(x) percentage of agents with assigned skills in less than preconfigured number of days;

(xi) percentage of agents handling concurrent interactions in a preconfigured number of skills;

(xii) percentage of agents working shifts more than a preconfigured number of hours;

(xiii) percentage of agents whose last day off was a preconfigured number of days prior to the schedule;

(xiv) agents schedule preferences;

(xv) agent handling more than a preconfigured number of concurrent interactions;

(xvi) percentage of agents not associated to a preconfigured business unit; and

(xvii) total time planned for a user-defined activity code where the agent would not contribute to the schedule with the agent's skills.

8 . The computerized-method of claim 3 , wherein the optimizing of schedules in a Workforce Management (WFM) system in an order that is based on each schedule schedule-impact score comprising optimizing schedules for resource overstaffing and optimizing for schedules for resource understaffing.

9 . The computerized-method of claim 1 , wherein the derived schedule-impact score is further used for performance rewards and recognition of highly performant agents in schedules having a schedule-impact score above a preconfigured threshold.

10 . The computerized-method of claim 1 , wherein the schedule-impact score is further used by a Quality Management (QM) system by: (i) checking a schedule-impact score above a preconfigured threshold for an increased sampling rate of interactions during the schedule-impact score related schedule; (ii) upon evaluation, assigning agents in interactions lacking quality metrics in the related schedule to training.

11 . The computerized-method of claim 1 , wherein the SIS module derives the schedule-impact score base on formula I:

Schedule Impact Score=Σ(schedule-quotient score× W 1 +agent-quotient score× W 2 )  (II)

whereby:

schedule-quotient score is the derived schedule-quotient score,

agent-quotient score is the derived agent-quotient score,

W 1 is a first preconfigured weightage,

W 2 is a second preconfigured weightage,

wherein a value of W 1 and a value of W 2 ranges between ‘0’ and ‘1’.

12 . A Computerized-system for identifying high impacted schedules, in a contact center, said computerized-system comprising:

one or more processors;

database of agent metrics;

database of schedule metrics;

a memory to store the database of agents metrics and the database of schedule metrics,

said one or more processors are configured to retrieve schedules during a preconfigured period from a WFM system, for each schedule:

(i) operating a schedule quotient module to derive schedule-quotient score based on schedule metrics retrieved from the database of schedule metrics;

(ii) operating an agent quotient module to derive agent-quotient score based on agent metrics retrieved from the database of agent metrics;

(iii) operating a Schedule Impact Score (SIS) module to derive a schedule-impact score based on the derived schedule-quotient score and the derived agent-quotient score; and

(iv) operating a recommendation module for auto-corrective measures in one or more systems based on the derived schedule-impact score.