9. - Workforce Management WFM OVerview & Setup Genesys Workforce Management (WFM) Overview & Setup Documentation Study Notes Topic Description WFM Purpose Manage forecasting, scheduling, intraday management, adherence, and capacity planning Core Capabilities AI-powered forecasting, multi-media scheduling, real-time monitoring, adherence tracking Organization Business Units contain Management Units contain Sites contain Teams Key Features Multi-channel support (voice, email, chat, callback, messaging, workitems) Integration Tightly integrated with Genesys Administrator for skills and real-time data Architecture Hierarchical org structure with permissions at BU and MU levels Navigation Admin → Workforce Management OR Home → Workforce Management → [Module Name] WFM Overview Genesys Workforce Management provides comprehensive tools to manage contact center workforce through forecasting, scheduling, intraday management, real-time adherence monitoring, and capacity planning. WFM enables organizations to create accurate staffing plans accounting for projected volumes, average handle times, agent skills, and business constraints. Workforce Management is designed for multi-media, multi-site environments, providing optimal schedules for multi-skilled agents handling different interaction types. Agent preferences, skills, proficiency levels, customer segmentation, historical trends, email response times, and outbound call lengths are all considered within forecast, schedule, and adherence components. Core Modules Forecasting - AI-powered volume and AHT predictions Scheduling - Agent schedule creation and optimization Intraday Management - Real-time monitoring and adjustments Real-Time Adherence - Live agent status tracking Capacity Planning - Hiring and long-range planning Time-Off & Trades - Agent self-service and request management Key Capabilities Multi-media support (voice, email, chat, callback, messaging, workitems) AI-powered forecasting with Automatic Best Method Optimized scheduling across multiple management units Real-time performance monitoring Integration with Genesys Universal Routing Agent self-service portal (desktop and mobile) Comprehensive reporting and analytics Edition & Module Requirements Requirement Details Minimum Edition Genesys Cloud CX 2-4, Digital, or WEM Add-ons Licensing Dedicated WFM licensing per organization Setup Requires WFM configuration and integration with Genesys Administrator Multicloud Available for Genesys Multicloud CX and Genesys Engage Mobile Agent self-service available on iOS and Android WFM Architecture Genesys Workforce Management Structure Business Unit (BU) ├─ Max: 5,000 agents ├─ Forecasts created at BU level ├─ Schedules created at BU level ├─ One master schedule per BU active at a time │ ├─ Management Unit 1 (MU) │ ├─ Max: 1,500 agents │ ├─ Represents department, site, or location │ ├─ Access control at MU level │ └─ Time-off requests managed at MU level │ ├─ Management Unit 2 (MU) │ ├─ Site A │ │ ├─ Team 1 │ │ │ └─ Agents (10-50) │ │ └─ Team 2 │ │ └─ Agents (10-50) │ │ │ └─ Site B │ └─ Agents │ └─ Management Unit 3 (MU) └─ Virtual agents (remote workers) WFM Workflow Overview WFM Management Lifecycle: PLANNING PHASE: ├─ Define business units and management units ├─ Set up service goals and planning groups ├─ Configure staffing groups and contracts └─ Establish permissions and access controls FORECASTING PHASE: ├─ Gather historical interaction data ├─ Create forecast scenarios ├─ Use AI (Automatic Best Method) for accuracy ├─ Validate and publish Master Forecast └─ Forecast available for scheduling SCHEDULING PHASE: ├─ Receive published Master Forecast ├─ Create schedule scenarios (up to 6 weeks) ├─ Balance forecasted demand with constraints ├─ Optimize for service levels and contracts ├─ Publish to Master Schedule └─ Schedule available to agents OPERATIONS PHASE: ├─ Real-time intraday monitoring ├─ Adherence tracking vs schedule ├─ Real-time adjustments as needed ├─ Capacity management └─ Performance metrics tracking FEEDBACK PHASE: ├─ Capture actual vs forecast variance ├─ Gather interaction data ├─ Analyze adherence patterns └─ Refine future forecasts and schedules Edition Comparison Feature CX 2 CX 3 CX 4 WEM Add-on Basic WFM ✓ ✓ ✓ ✓ Forecasting ✓ ✓ ✓ ✓ Scheduling ✓ ✓ ✓ ✓ Intraday Mgmt ✓ ✓ ✓ ✓ Real-Time Adherence ✓ ✓ ✓ ✓ Advanced Analytics Limited ✓ ✓ ✓ Capacity Planning Limited ✓ ✓ ✓ Agent Self-Service ✓ ✓ ✓ ✓ Initial Setup Steps Step 1: Organizational Structure Design Define Business Units Group by operational objectives Each BU forecasts/schedules together Max 5,000 agents per BU Define Management Units (within each BU) Represent departments/sites/locations Max 1,500 agents per MU Enable permission boundaries Define Sites (within each MU) Physical locations or virtual groups Agents assigned to sites Step 2: Configure WFM Settings Navigate to Admin → Workforce Management Set default time zones Configure week start day Set up planning period (typically 26 weeks) Enable required modules Step 3: Create Planning Groups Define by media type and queue/route Configure service goals Set staffing requirements Establish activity/skill mappings Step 4: Configure Agents Assign skills and proficiency levels Assign to teams and sites Set contracts and work rules Configure preferences Step 5: Set Permissions Assign WFM roles: Administrator (full access) Supervisor (forecasting/scheduling) Analyst (reporting/analytics) Agent (self-service) Grant at Business Unit level: Forecasting permissions Schedule creation/editing Grant at Management Unit level: Time-off approvals Team-specific schedules Step 6: Integration Connect to Genesys Administrator Enable real-time statistics via Stat Server Configure Data Aggregator Set up Universal Routing integration Enable agent portal (web and mobile) Key Terminology Term Definition Business Unit (BU) Group of Management Units sharing common operational objectives Management Unit (MU) Group of agents within a BU (max 1,500) Site Physical location or virtual grouping within an MU Team Collection of agents within a site Activity Type of work (inbound calls, emails, chats, etc.) Planning Group Workload organized by media type and route Service Goal Target metrics (SL, ASA, abandon rate) Master Forecast Published forecast scenario used for scheduling Master Schedule Published schedule scenario used by agents Work Plan Definition of shifts, breaks, meals, contracts Staffing Group Cluster of agents with similar skills Adherence Agent's actual activity vs scheduled activity Multi-Channel Support WFM manages workloads across: Voice - Traditional phone interactions Email - Asynchronous email support Chat - Real-time chat conversations Callback - Scheduled return calls Messaging - SMS, web messaging, social messaging Workitems - Tasks routed to agents Each media type: Has distinct forecasting requirements Supports different interaction patterns Requires appropriate planning groups Contributes to overall agent workload Real-World Example Mid-Market Financial Services Contact Center Organization Structure: Financial Services Company │ ├─ Business Unit: North America Operations │ │ │ ├─ Management Unit: Support (500 agents) │ │ ├─ Site: New York (200 agents) │ │ │ ├─ Team: Tier 1 Support (100) │ │ │ └─ Team: Tier 2 Support (100) │ │ │ │ │ └─ Site: Dallas (300 agents) │ │ ├─ Team: Tier 1 Support (150) │ │ └─ Team: Tier 2 Support (150) │ │ │ └─ Management Unit: Sales (300 agents) │ ├─ Site: New York (150) │ └─ Site: Dallas (150) │ └─ Business Unit: International Operations ├─ Management Unit: Europe (400 agents) └─ Management Unit: APAC (350 agents) Media Types: ├─ Voice (70% of volume) ├─ Email (15% of volume) ├─ Chat (10% of volume) └─ Callback (5% of volume) Planning Groups: ├─ Support - Inbound Voice ├─ Support - Email (3-4 hour response) ├─ Support - Chat ├─ Sales - Outbound Calls └─ Sales - Sales Chat Service Goals: ├─ Support: 80% SL, 20 sec ASA, 5% abandon └─ Sales: 75% SL, 30 sec ASA, 10% abandon Staffing Model: ├─ Full-time agents (40 hrs/week, 5 days) ├─ Part-time agents (20 hrs/week, 3 days) ├─ Flex agents (variable hours) └─ Remote agents (work-from-home) Best Practices Organization Design Align BUs with business operations Keep MUs at manageable size (<1,500 agents) Use sites for geographic separation Use teams for skill-based grouping Access Control Grant minimal necessary permissions Use BU-level for forecasting/scheduling control Use MU-level for time-off and local scheduling Audit permissions quarterly Data Quality Ensure accurate agent configurations Keep skills current and proficiency honest Validate historical interaction data Regular imports of new data Configuration Document organizational structure Establish naming conventions Create backup configurations Test changes in non-prod first Common Setup Issues Issue Cause Resolution Can't create forecasts Missing BU-level permissions Grant Forecast > Create permission at BU Agents not in scheduling Not assigned to sites/teams Configure agent site/team assignments Inaccurate forecasts Poor historical data Clean data, ensure 90+ days available Schedule conflicts Contract violations Review contract rules, adjust availability Adherence issues Unclear activity codes Simplify, train agents on correct codes Permission problems Incorrect scope (MU vs BU) Verify permission level and scope Interview Cheat Sheet Question Answer What is WFM? Software for forecasting, scheduling, intraday monitoring, and adherence What's a Business Unit? Group of MUs sharing operational objectives, forecasts/schedules at BU level What's a Management Unit? Group of agents within BU (max 1,500), enables permission boundaries How many agents per BU? Max 5,000 agents per business unit How many agents per MU? Max 1,500 agents per management unit Where are forecasts created? At Business Unit level Where are schedules created? At Business Unit level How many schedules per BU? One master schedule per BU at a time What channels does WFM support? Voice, email, chat, callback, messaging, workitems What's a planning group? Workload organized by media type and route What's the forecasting basis? Volume (Offered) and Average Handle Time (AHT) What's Service Goal? Target metrics (Service Level, ASA, abandon rate) Where are permissions granted? At BU level for forecasting, at MU level for time-off How long is scheduling window? 26 weeks prior and 26 weeks future from current What's a work plan? Definition of shifts, breaks, meals, contracts Key Takeaways Hierarchical Structure - Business Units contain Management Units which contain Sites and Teams Agent Limits - 5,000 per BU, 1,500 per MU Multi-Channel - Supports 6 media types (voice, email, chat, callback, messaging, workitems) AI-Powered - Uses Automatic Best Method for optimal forecasting Real-Time - Live monitoring and adherence tracking Integrated - Tight integration with Genesys Administrator and routing Self-Service - Agent portal on desktop and mobile devices Scalable - Supports large, multi-site contact centers Flexible - Multiple scheduling methods and contract types Data-Driven - Continuous improvement through metrics and analytics Additional Resources Official Documentation WFM Overview: all.docs.genesys.com/PEC-WFM Genesys Cloud WFM: help.genesys.cloud/articles/about-workforce-management/ Business Units: help.genesys.cloud/articles/business-units-overview/ Scheduling: help.genesys.cloud/articles/work-with-workforce-management-schedules/ Support & Training Genesys University: genesys.com/training Community Forums: https://community.genesys.com Technical Support: https://support.genesys.com Document Version Info Last Updated: March 2026 Source: Genesys WFM Official Documentation Validated: Current with January-March 2026 releases Version: 1.0 Business & Management Units Genesys WFM Business & Management Units Documentation Study Notes Topic Description Business Unit Organizational unit grouping management units sharing objectives Management Unit Sub-unit containing agents (max 1,500 per MU) Agent Capacity 5,000 max per BU, 1,500 max per MU Hierarchy BU → MU → Site → Team → Agent Permissions Granted at BU level for forecasting, MU level for local control Multi-MU Scheduling Forecasts/schedules run across all MUs in a BU simultaneously Navigation Admin → Workforce Management → Business Units OR Admin → Workforce Management → Management Units Business Units Overview In workforce management, business units enable customers to organize their agents and leverage permissions to meet business needs. Business units allow customers to configure agents who share queues into more than one management unit. The agent capacity for management unit is 1,500 agents; however, business units help alleviate this limitation by providing support for up to 5,000 agents per business unit. Business units enable cross-management unit scheduling and forecasting within the same business unit. Forecasts and schedules run at the business unit level, and administrators can create the most efficient schedules by factoring in coverage from all agents in more than one management unit within the business unit. Business Unit Characteristics Agent Capacity : Max 5,000 agents per business unit Forecast Scope : Entire BU (all MUs included) Schedule Scope : Entire BU (all MUs included) One Master Schedule : Only one active master schedule per BU at a time Time Zone : Default time zone set at BU level (applies to all MUs) Week Start Day : Set at BU level (applies to all sites) Common Objective : Group MUs that share operational objectives Business Unit Use Cases Geographically dispersed sites - Multiple locations serving same function Skill-based organization - Different teams with complementary skills Multi-shift operations - 24/7 coverage across multiple time zones Blended internal/outsourced - Internal staff + third-party partners Virtual operations - Remote work + office-based agents Growth planning - Prepare for future headcount expansion Management Units Overview Management Units are groups of agents within a business unit. They can represent a department, site, or geographic location within the same business unit. Management units provide organizational flexibility and permission boundaries. Management Unit Characteristics Agent Capacity : Max 1,500 agents per management unit Purpose : Represent dept/site/location within BU Permissions : Local control of time-off, team management Organization : Agents grouped for local management Flexibility : Multiple MUs per BU enable large-scale operations Cross-MU Work : Agents in different MUs can share queues/skills Management Unit Use Cases Site-based organization - Each office location = 1 MU Department organization - Support/Sales/Billing each = 1 MU Shift-based organization - Morning/Evening/Night shift = 1 MU Skill-based teams - Technical/Billing/Sales each = 1 MU Outsourced partners - Third-party vendor = 1 MU Virtual agent groups - Remote workers = 1 MU Hierarchy Structure Organizational Hierarchy Example: Business Unit: North America (4,800 agents) │ ├─ Management Unit: New York Operations (1,200 agents) │ ├─ Site: Manhattan (600 agents) │ │ ├─ Team: Support Tier 1 (150 agents) │ │ ├─ Team: Support Tier 2 (150 agents) │ │ ├─ Team: Sales (150 agents) │ │ └─ Team: Billing (150 agents) │ │ │ └─ Site: Brooklyn (600 agents) │ └─ 4 teams (150 each) │ ├─ Management Unit: Dallas Operations (1,200 agents) │ ├─ Site: Downtown (600 agents) │ └─ Site: Suburb (600 agents) │ ├─ Management Unit: Remote Operations (1,200 agents) │ └─ Virtual site (1,200 remote agents) │ └─ Management Unit: Outsourced Partners (1,200 agents) └─ Partner site (1,200 vendor agents) Agent Distribution: ├─ MU1: 1,200 agents (25%) ├─ MU2: 1,200 agents (25%) ├─ MU3: 1,200 agents (25%) ├─ MU4: 1,200 agents (25%) └─ Total BU: 4,800 agents (80% of 5,000 capacity) Permission Model Business Unit Level Permissions Permissions granted at BU level apply to entire business unit: Forecasting - Create, edit, publish forecasts for all MUs Schedule Generation - Create schedules across all MUs Service Goals - Define service goals for BU Planning Groups - Create planning groups for BU Reporting - Cross-MU reports and analytics Configuration - BU-wide settings and policies Management Unit Level Permissions Permissions granted at MU level apply only to that MU: Time-Off Approvals - Approve time-off requests Schedule Details - View/edit MU-specific schedules Team Management - Manage teams within MU Activity Configuration - MU-specific activities Reporting - MU-only reports Agent Management - Add/remove agents from MU Permission Matrix Feature BU Level MU Level ──────────────────────────────────────────── Forecasting ✓ Full ✗ No Schedule Generation ✓ Full ✗ No Intraday Management ✓ Full ✓ View Real-Time Adherence ✓ Full ✓ View Time-Off Approvals ✗ No ✓ Full Team Management ✗ Limited ✓ Full Agent Assignment ✓ Full ✓ Limited Reporting ✓ Full ✓ Limited Configuration ✓ Full ✓ Limited Capacity Planning Agent Capacity Calculations Example 1: Single MU Organization Business Unit: Small Contact Center ├─ Management Unit: Support (800 agents) │ └─ Capacity Used: 800/1,500 (53%) └─ Business Unit Total: 800/5,000 (16%) Growth Plan: ├─ Year 1: Add 200 agents → 1,000 total ├─ Year 2: Add 300 agents → 1,300 total └─ Year 3: Need to split → Create 2nd MU Example 2: Multi-MU Organization Business Unit: Enterprise Contact Center ├─ Management Unit 1: NYC (1,400 agents) - 93% ├─ Management Unit 2: Dallas (1,350 agents) - 90% ├─ Management Unit 3: Remote (1,200 agents) - 80% ├─ Management Unit 4: Outsourced (950 agents) - 63% └─ Business Unit Total: 4,900/5,000 (98%) Challenge: Almost at BU capacity Solution: ├─ Option 1: Create new BU for new location ├─ Option 2: Split existing MU to another BU └─ Option 3: Reduce headcount in lowest-performing MU Exceeding Capacity If MU exceeds 1,500 agents: Cannot add more agents to that MU Must create new MU or split agents Requires reorganization of teams If BU exceeds 5,000 agents: Cannot add more agents to that BU Must create new business unit Existing MUs remain operational but frozen Configuration Creating a Business Unit Navigate to Admin → Workforce Management → Business Units Click Create Business Unit Configure: Name - Unique within WFM environment Time Zone - Default for all sites Week Start Day - Monday-Sunday default Data Aggregator - Specify DA instance Stat Server - Auto-populated from DA Tenant - Genesys environment name Tenant Password - Required for connection Add Sites Associate multiple sites if needed Each site belongs to one MU Sites can have multiple teams Finalize and Save Creating a Management Unit Navigate to Admin → Workforce Management → Management Units Click Create Management Unit Configure: Name - Unique within WFM Business Unit - Select parent BU Description - Optional (recommended) Team Structure - Define teams if needed Add Sites Assign existing sites Or create new sites Max 1,500 agents per MU Assign Agents Add individual agents Or bulk import from CSV Set agent properties Finalize and Save Real-World Scenarios Scenario 1: Scaling Beyond 1,500 Agents Current State: Business Unit: Support Operations └─ Management Unit: Support Team └─ 1,500 agents (at capacity) New Hire Requirements: +200 agents needed Solution: Split into Two MUs Business Unit: Support Operations ├─ Management Unit: Support - Group A (1,350 agents) │ └─ Location: NYC + Boston ├─ Management Unit: Support - Group B (1,200 agents) │ └─ Location: Dallas + Remote └─ Business Unit Total: 2,550/5,000 (51%) Benefits: ├─ Accommodates growth ├─ Local team management at MU level ├─ Still shared forecasting/scheduling └─ Room for future expansion Scenario 2: Multi-Location Organization Company Structure: Financial Services - 3,600 employees in support Business Unit: Global Support ├─ Management Unit: North America (1,500) │ ├─ Site: New York (750) │ └─ Site: Dallas (750) ├─ Management Unit: Europe (1,200) │ ├─ Site: London (600) │ └─ Site: Dublin (600) └─ Management Unit: Outsourced (900) └─ Site: Philippines (900) Forecasting: ├─ Single global forecast across all 3 MUs ├─ Factors in time zone differences ├─ Optimizes scheduling for 24/7 coverage └─ Published to master schedule covering all locations Agent Movement: ├─ Can't move agents between MUs automatically ├─ Must manually reassign for temporary overflow ├─ Permanent transfers require admin action Scenario 3: Outsourced Partner Integration Setup: Business Unit: Multi-Channel Support (2,500 agents) ├─ Management Unit: Internal Team (1,500) │ └─ Full control over scheduling/policies ├─ Management Unit: Outsourced Partner (1,000) │ └─ Integrated into unified forecasting └─ Benefits: ├─ Single forecast across internal + outsourced ├─ Unified scheduling window ├─ Coordinated service goals └─ Partner agents included in adherence Challenges: ├─ Different contracts/rules per MU ├─ Partner availability limitations ├─ Communication across organizations Best Practices Organization Design Right-size MUs - Keep at 1,000-1,300 agents for growth room Clear separation - Align with business structure Future-proof - Plan for 2-3 years of growth Skill groups - Use for agent assignment, not org structure Geographic logic - Use locations/sites for MU boundaries Permission Management Principle of least privilege - Grant only needed permissions Role-based access - Create roles for common scenarios Audit regularly - Review who has what access Documentation - Maintain permission matrix Approval workflow - Require BU-level for major changes Agent Assignment Consistent naming - Use standard naming conventions Skill accuracy - Ensure skills match actual capabilities MU assignment logic - Clear criteria for placement Cross-MU skills - Agents can have skills across queues Regular audits - Verify assignment accuracy Growth Planning Capacity monitoring - Track MU usage quarterly Headcount forecasts - Plan additions in advance Reorganization planning - Prepare for splits/merges Communication - Inform stakeholders of changes Test in non-prod - Always validate changes first Common Issues & Solutions Issue Cause Solution Can't add agent to MU MU at 1,500 limit Create new MU or split existing Schedule won't generate Agents in multiple MUs missing Ensure all agents properly assigned Permission denied for forecast Not BU-level permission Grant Forecast permission at BU level Agents can't trade across MUs Not configured Enable cross-MU trading in settings Time-off approval pending Wrong approval level Ensure MU-level approver assigned Wrong time zone Inherited from parent Change at BU level or override at Site Interview Cheat Sheet Question Answer What's a Business Unit? Group of MUs sharing operational objectives, max 5,000 agents What's a Management Unit? Sub-unit within BU representing dept/site/location, max 1,500 agents How does hierarchy work? BU → MU → Site → Team → Agent Where are forecasts created? Business Unit level (includes all MUs) Where are schedules created? Business Unit level (includes all MUs) What permissions at BU level? Forecasting, scheduling, service goals, reporting What permissions at MU level? Time-off approvals, team management, local scheduling Can agents work across MUs? Yes, if they have required skills for queues Can one agent be in two MUs? No, each agent assigned to one MU only Max agents per BU? 5,000 agents Max agents per MU? 1,500 agents How many master schedules per BU? One active master schedule per BU How to handle growth over 1,500? Create additional MU within same BU How to exceed 5,000 agents? Create new business unit Can MUs share queues? Yes, agents across MUs can handle same queues Key Takeaways Hierarchical Organization - BU organizes multiple MUs for shared forecasting Capacity Planning - 5,000 agents per BU, 1,500 per MU Unified Forecasting - Single forecast across all MUs in BU Unified Scheduling - One master schedule for entire BU Permission Boundaries - BU level for strategic, MU level for operational Scalability - Split MUs when exceeding 1,500 agents Flexibility - Agents can work across MUs if skilled Management Clarity - Clear org structure for delegation Growth-Ready - Design with future expansion in mind Cross-MU Optimization - Forecasting balances coverage across locations Additional Resources Official Documentation Business Units: help.genesys.cloud/articles/business-units-overview/ Management Units: help.genesys.cloud/articles/management-units-overview/ WFM Configuration: help.genesys.cloud/articles/workforce-management-and-divisions-overview/ Permissions: help.genesys.cloud/articles/workforce-management-permissions/ Support & Training Genesys University: genesys.com/training Community Forums: https://community.genesys.com Technical Support: https://support.genesys.com Document Version Info Last Updated: March 2026 Source: Genesys WFM Official Documentation Validated: Current with January-March 2026 releases Version: 1.0 Forecasting Genesys WFM Forecasting Documentation Study Notes Topic Description Master Forecast Published forecast scenario used for scheduling Automatic Best Method AI analyzes 10+ algorithms to select best forecast Forecasting Methods ABM, WHI, HDI, Import Forecast Main Forecast Continuous daily calculation from latest data Accuracy ABM: 85-92% vs Traditional: 70-80% Planning Groups Organize workload by media type and route Service Goals Define SL, ASA, abandon rate targets Recalculation Main forecast recalculates nightly with new data Navigation Admin → Workforce Management → Forecasting OR Menu → Workforce Management → Forecasting → Forecasts Forecasting Overview Forecasting is the process of predicting future contact volume and average handle time to determine required staffing levels. WFM uses forecasts to create optimal schedules that balance service level goals with operational efficiency. Forecasts form the foundation of workforce planning. Accurate forecasts drive better schedules, which drive better adherence, which drives better service levels. The forecasting process involves analyzing historical data, selecting appropriate forecasting methods, validating scenarios, and publishing the best scenario to become the Master Forecast. Forecasting Objectives Volume Prediction - Predict number of interactions (offered) AHT Prediction - Predict average handle time per interaction Staffing Calculation - Determine agents needed to meet service goals Scenario Planning - Evaluate multiple forecasting approaches Continuous Improvement - Refine based on actual vs forecast variance Capacity Planning - Support long-range hiring decisions Forecasting Scope Business Unit Level - Forecasts created for entire BU (all MUs) Time Granularity - Hourly and daily forecasts Planning Period - 26 weeks forward (can search up to 104 weeks) Historical Data - Requires 90+ days of data for accuracy Multiple Scenarios - Create and compare multiple approaches Master Forecast - One published forecast per BU at a time Forecasting Methods 1. Automatic Best Method (ABM) Automatic Best Method is the AI-powered forecasting approach that analyzes historical interaction data and automatically selects the most accurate forecasting algorithm from 10+ methods. How ABM Works: Historical Data Input ↓ Analyze 10+ Forecasting Algorithms: ├─ Moving Average ├─ Exponential Smoothing ├─ Trend Analysis ├─ Seasonal Decomposition ├─ Regression Models ├─ Time Series Analysis └─ ... 4+ additional models ↓ Evaluate Each Against Historical Data ├─ Calculate accuracy metrics ├─ Test fit quality ├─ Assess seasonal patterns └─ Validate trend capture ↓ Select Best Performing Model ├─ Lowest error rate ├─ Best seasonal fit ├─ Most stable predictions └─ Confidence validation ↓ Generate Forecast ├─ Volumes (Offered) ├─ AHT (Average Handle Time) └─ Staffing Requirements ABM Characteristics: Requires minimum 90 days historical data Automatically evaluates 10+ algorithms Selects best fit without manual intervention Accuracy: 85-92% (vs traditional 70-80%) Recalculates nightly with new data Supports all media types Cloud-based processing When to Use ABM: ✓ Mature contact center (90+ days data) ✓ Accurate historical data available ✓ Want AI-driven optimization ✓ Looking for best accuracy ✓ Limited forecasting expertise ABM Limitations: ✗ Requires 90+ days data minimum ✗ Cannot account for business events manually ✗ May not work with highly volatile data ✗ Limited control over algorithm selection 2. Weighted Historical Index (WHI) Weighted Historical Index allows forecasters to assign importance to specific historical periods, enabling forecasts that reflect anticipated trends or business changes. How WHI Works: Select Historical Periods ↓ Assign Weights to Periods: ├─ Recent period: 40% weight (higher importance) ├─ Same season last year: 35% weight ├─ 2 years ago: 15% weight └─ Older data: 10% weight ↓ Calculate Weighted Average ├─ Multiply volumes by weights ├─ Multiply AHT by weights └─ Generate forecast ↓ Manual Adjustments ├─ Add/subtract for known events ├─ Adjust for staffing changes └─ Account for market changes ↓ Forecast Output WHI Characteristics: Manual weight assignment Incorporates business judgment Good for known changes Moderate accuracy (75-85%) Requires forecasting expertise Supports business events When to Use WHI: ✓ Known business changes upcoming ✓ New product launch planned ✓ Merger/acquisition integration ✓ Staffing changes anticipated ✓ Want forecaster control WHI Limitations: ✗ Requires manual configuration ✗ Subject to forecaster bias ✗ More time-consuming setup ✗ Less accurate than ABM typically 3. Historical Data Import (HDI) Historical Data Import enables importing external historical data via CSV files, useful for organizations lacking internal historical data or integrating data from legacy systems. How HDI Works: Prepare Historical Data CSV: ├─ Date, Time, Interactions Offered ├─ Date, Time, Average Handle Time └─ Format per Genesys specifications Upload CSV File ↓ Data Validation ├─ Check date formats ├─ Validate interaction counts ├─ Verify AHT values └─ Check for gaps Map to Planning Groups ├─ Assign data to queues/routes ├─ Set media types └─ Configure mapping rules Import and Store ├─ Historical data added to system ├─ Available for forecasting └─ Retained for 90+ days Create Forecast ├─ ABM or WHI using imported data ├─ Generate volumes and AHT └─ Publish to master forecast HDI Characteristics: CSV-based import Supports external data sources Integrates legacy system data Enables quick setup for new centers Maintains data history Works with ABM/WHI methods When to Use HDI: ✓ New contact center (no history) ✓ Migrating from legacy system ✓ Acquiring another company ✓ Need to supplement internal data ✓ Have external forecasting data HDI Limitations: ✗ Requires proper CSV formatting ✗ Data validation needed ✗ Manual upload process ✗ Can't import future predictions 4. Import Forecast Import Forecast supports uploading externally generated forecasts into Genesys Cloud, integrating with existing forecasting systems or third-party tools. How Import Forecast Works: External Forecast Generation: ├─ Create in Excel/third-party tool ├─ Calculate volumes and AHT ├─ Format per specifications └─ Validate accuracy Export as CSV/XML ↓ Upload to Genesys WFM ├─ Select planning group ├─ Map forecast period └─ Validate format System Processing: ├─ Parse forecast data ├─ Validate ranges ├─ Check for completeness └─ Store in system Publish to Master Forecast ├─ Available for scheduling ├─ Used for staffing calculations └─ Drives schedule generation Import Forecast Characteristics: Forecast generated externally Upload pre-calculated volumes/AHT Bypasses ABM/WHI Useful for specialized models One-time or periodic imports No recalculation When to Use Import Forecast: ✓ Have specialized forecasting tool ✓ Third-party forecast provider ✓ Complex custom models ✓ Forecasting done elsewhere ✓ Minimal WFM forecasting expertise Import Forecast Limitations: ✗ No automatic updates ✗ Must re-import when data changes ✗ No integration with real-time data ✗ Less adaptive to changes Main Forecast The Main Forecast is a special forecast calculated continuously (typically nightly) based on all available historical data. It provides the baseline forecast that can be used immediately or modified through scenarios. Main Forecast Characteristics: Continuous Calculation - Recalculates every night All Historical Data - Uses complete data history Automatic - No manual intervention required Read-Only - Cannot be directly edited Baseline Reference - Starting point for scenarios Always Available - Immediately accessible Best Current Data - Uses latest interactions Main Forecast Flow: Day 1: Historical Data (30 days) ↓ Nightly Calculation ↓ Main Forecast Published ↓ Day 2: Historical Data (30 days) + Day 1 New Data ↓ Nightly Calculation ↓ Main Forecast Updated ↓ Ongoing: Continuous refinement with new daily data Planning Groups Planning Groups organize workloads by specific media types and route paths, enabling targeted forecasting and scheduling. Planning Group Components: Planning Group: Support - Inbound Voice ├─ Media Type: Voice (inbound) ├─ Queue/Route: Support_Queue_001 ├─ Skill Required: Support_Skill_Level_2+ ├─ Service Goal: 80% SL, 20 sec ASA, 5% abandon ├─ Staffing Group: Support_Agents └─ Forecast Data: Volume + AHT Planning Group: Sales - Outbound Calls ├─ Media Type: Voice (outbound) ├─ Campaign: Q1_Spring_Campaign ├─ Skill Required: Sales_Skill_Level_1+ ├─ Service Goal: Contact 50% of list, 5 min calls ├─ Staffing Group: Sales_Agents └─ Forecast Data: Dialing ratio + AHT Planning Group: Support - Email ├─ Media Type: Email ├─ Queue: Support_Email_Queue ├─ Response Time Goal: 4 hours ├─ Staffing Group: Support_Agents └─ Forecast Data: Volume + AHT Planning Group: Chat Support ├─ Media Type: Chat ├─ Route: Support_Chat_Route ├─ Concurrency: 4-5 chats per agent ├─ Response Time: Immediate └─ Forecast Data: Offered + AHT Planning Group Creation: Navigate to Admin → Workforce Management → Planning Groups Click Create Planning Group Configure: Name - Unique identifier Business Unit - Parent BU Media Type - Voice, Email, Chat, Callback, Messaging, Workitems Queue/Route - Associated queue or route Service Goal - Target metrics Staffing Model - Agents to use Save and activate Planning Group Best Practices: Clarity - Clear names reflecting function Consolidation - Group similar work together Skill Alignment - Agents have required skills Service Goals - Match business objectives Regular Review - Update as operations change Documentation - Maintain planning group mapping Service Goals Service Goals define the performance targets for a planning group: Service Level, Average Speed to Answer, and Abandonment Rate. Service Goal Components: Service Goal Template: Premium Support ├─ Service Level Goal: 80% │ └─ Definition: 80% of calls answered within 20 seconds ├─ Average Speed to Answer: 20 seconds │ └─ Definition: Average answer time across all calls ├─ Abandon Rate: 5% │ └─ Definition: Max 5% of offered calls abandoned ├─ Media Type: Voice ├─ Time Intervals: Hourly └─ Period: Weekly Service Goal Template: Standard Support ├─ Service Level Goal: 75% ├─ Average Speed to Answer: 30 seconds ├─ Abandon Rate: 8% └─ More lenient targets for lower-volume periods Service Goal Template: Email Support ├─ Service Level Goal: 95% within 4 hours ├─ Average Speed to Answer: 2 hours (median response) ├─ Abandon Rate: 0% (not applicable) └─ Media Type: Email Service Goal Best Practices: Realistic Targets - Achieve 80-85% of time Business Aligned - Match customer expectations Media-Specific - Different for voice vs email Documented - Communicate to teams Regular Review - Adjust based on performance Incremental Improvement - Tighten gradually Forecasting Process Step 1: Data Preparation Ensure 90+ days of historical data available Validate data accuracy Check for gaps or anomalies Clean outliers if necessary Confirm queue/route mappings Step 2: Create Scenario Navigate to Forecasts → Scenarios Click New Scenario Configure: Name - e.g., "Q2_2026_Base_Forecast" Period Start - Beginning of forecast Period End - 26 weeks forward Planning Groups - Select which to include Create scenario Step 3: Build Volumes Open scenario Click Build Volumes Select forecasting method: ABM - Recommended for accuracy WHI - For known business changes Template - Copy from similar period Configure method-specific settings Generate volumes Step 4: Build AHT Open scenario volumes Click Build AHT Select method (typically same as volumes) Configure AHT-specific settings Generate AHT Step 5: Review & Validate Open Scenario Volumes view Review volume trends: ✓ Match business expectations ✓ Seasonal patterns visible ✓ Growth/decline appropriate ✓ No obvious anomalies Open Scenario Staffing view Review staffing requirements: ✓ Realistic agent counts ✓ Service level achievable ✓ Aligned with budget ✓ Growth manageable Step 6: Compare Scenarios Create multiple scenarios if desired Compare side-by-side: Volume projections Staffing requirements Cost implications Service level achievement Select best scenario Step 7: Publish to Master Forecast Open best scenario Click Publish to Master Forecast Confirm publication Master Forecast now available for scheduling Step 8: Monitor & Adjust Track actual vs forecast weekly Calculate variance: Volume Variance = (Actual - Forecast) / Forecast AHT Variance = (Actual - Forecast) / Forecast Adjust future forecasts based on variance Recalculate Main Forecast Forecasting Accuracy Measuring Accuracy Volume Accuracy: Forecast Accuracy = 1 - |Actual - Forecast| / Actual Example: Forecasted Offered: 1,000 calls Actual Offered: 980 calls Variance: |980 - 1,000| / 1,000 = 2% Accuracy: 98% AHT Accuracy: Forecasted AHT: 420 seconds Actual AHT: 410 seconds Variance: |410 - 420| / 420 = 2.4% Accuracy: 97.6% Overall Forecast Accuracy: Excellent - 95%+ accuracy Good - 90-95% accuracy Acceptable - 85-90% accuracy Poor - <85% accuracy Factors Affecting Accuracy Positive Factors: ✓ Abundant historical data (90+ days) ✓ Consistent seasonal patterns ✓ Stable agent population ✓ No major business changes ✓ Accurate data collection ✓ Use of ABM method Negative Factors: ✗ Insufficient historical data (<30 days) ✗ Volatile contact volumes ✗ Seasonal anomalies ✗ Major staffing changes ✗ Business discontinuities ✗ Data quality issues Improving Forecast Accuracy Data Quality Validate interaction data Remove duplicate entries Correct time stamps Clean outliers appropriately Time Frame Selection Use 90+ days of data Include full seasonal cycle Exclude anomalous periods Weight recent data higher Method Selection Use ABM for stable patterns Use WHI for known changes Test multiple methods Compare results Ongoing Monitoring Track actual vs forecast weekly Identify variance sources Adjust future forecasts Document lessons learned Business Communication Inform of known changes Get campaign dates in advance Understand staffing constraints Align on service goals Real-World Examples Example 1: New Contact Center (Using HDI) Scenario: New financial services contact center Problem: No historical data in Genesys Solution: Historical Data Import Process: 1. Obtain 6 months of data from legacy system 2. Format as CSV (Date, Time, Volume, AHT) 3. Upload to WFM via Historical Data Import 4. Validate imported data (1,000+ calls/day confirmed) 5. Create ABM forecast using imported data 6. Generate 26-week forecast with 85% confidence 7. Publish to Master Forecast 8. Create schedules based on forecast 9. Begin tracking actual vs forecast 10. Refine with real Genesys data over time Result: Forecast accuracy 82% week 1, improving to 90% by week 12 Example 2: Seasonal Business (Using WHI) Scenario: Retail customer service (high holiday season) Problem: Regular ABM doesn't account for expected surge Solution: Weighted Historical Index Process: 1. Run ABM to get baseline forecast 2. Weight recent 4 weeks: 50% 3. Weight same season last year: 30% 4. Weight 2 years ago: 20% 5. Manual adjustment: +25% for new catalog 6. Manual adjustment: +10% for holiday promotions 7. Result: 15,000 calls/day (vs ABM baseline 12,000) 8. Schedule accordingly with additional flex agents 9. Publish to Master Forecast 10. Monitor first week for variance Result: Forecast accuracy 88% during peak season Alternative: Would have been 65% with unmodified ABM Example 3: Business Event (Using Import Forecast) Scenario: Product launch with external forecast Problem: Marketing has already forecasted demand impact Solution: Import Forecast from external source Process: 1. Marketing provides forecast: - Week 1: +30% volume increase - Week 2: +50% volume increase - Week 3: +40% volume increase - Week 4-8: Declining to normal 2. Obtain volumes from marketing 3. Format as CSV per Genesys spec 4. Upload via Import Forecast 5. Map to Support planning group 6. Validate import completeness 7. Publish to Master Forecast 8. Create high-staffing schedule for weeks 1-3 9. Monitor actual vs marketing forecast 10. Adjust staffing based on real results Result: Forecast accuracy 92% (marketing expertise applied) Cost: Hired 50 temporary agents, all utilized during surge Best Practices Forecasting Process Establish Baseline - Start with ABM for consistency Regular Reviews - Monthly variance analysis Scenario Planning - Test multiple approaches Documentation - Record assumptions and decisions Communication - Share forecasts with operations Validation - Compare to business expectations Data Management Data Quality - Daily validation and cleanup Retention - Keep 90+ days for pattern recognition Integrity - Prevent manual edits without documentation Backup - Maintain forecast history Audit Trail - Track who changed what when Continuous Improvement Weekly Tracking - Actual vs forecast variance Root Cause Analysis - Understand variances Method Adjustment - Change weights/methods as needed Feedback Loop - Share insights with business Seasonal Adjustment - Update for known patterns Interview Cheat Sheet Question Answer What's ABM? Automatic Best Method - AI selects best algorithm from 10+ ABM accuracy? 85-92% (vs traditional 70-80%) ABM data requirement? Minimum 90 days historical data When use ABM? Mature center, good data, want best accuracy When use WHI? Known business changes, want forecaster control When use HDI? New center, migrating systems, external data When use Import? External forecast available, specialized models What's Main Forecast? Automatically calculated nightly using all data What's planning group? Organizes work by media type and route What's service goal? Targets for SL, ASA, abandon rate Where forecasts created? Business Unit level How far forward? 26 weeks (can search up to 104) How often recalculate? Main forecast nightly, scenarios on demand Forecast impacts? Drives scheduling, staffing, service level How measure accuracy? Compare actual vs forecast volume and AHT Key Takeaways AI-Powered - ABM automatically selects best method from 10+ algorithms Accuracy - ABM achieves 85-92% vs traditional 70-80% Flexibility - Four methods (ABM, WHI, HDI, Import) for different scenarios Continuous - Main Forecast recalculates nightly with new data Planning Groups - Organize by media type and route for precise forecasting Service Goals - Define targets for SL, ASA, abandon rate Data-Driven - Requires 90+ days of data for accuracy Validation - Regular monitoring of actual vs forecast variance Business Events - WHI and Import methods support known changes Foundation - Forecast quality directly impacts schedule quality Additional Resources Official Documentation Forecasting Overview: help.genesys.cloud/articles/forecasting-overview/ Automatic Best Method: help.genesys.cloud/articles/automatic-best-method/ Planning Groups: help.genesys.cloud/articles/planning-groups-overview/ Service Goals: help.genesys.cloud/articles/service-goals-overview/ Support & Training Genesys University: genesys.com/training Community Forums: https://community.genesys.com Technical Support: https://support.genesys.com Document Version Info Last Updated: March 2026 Source: Genesys WFM Official Documentation Validated: Current with January-March 2026 releases Version: 1.0 Scheduling & Work Plans Genesys WFM Scheduling & Work Plans Documentation Study Notes Topic Description Scheduling Methods 3 approaches: Load-based (forecast), Shift pattern, Blank schedule Schedule Window 26-week visibility (±26 weeks from current), one master per BU Generation Period Maximum 6 weeks at a time Work Plan Defines shifts, breaks, meals, contracts, weekly constraints Shift Items Breaks and meals with time windows and configuration Schedule Bidding Agents bid on pre-created schedules Master Schedule Published schedule available to all agents Navigation Admin → Workforce Management → Scheduling OR Menu → Workforce Management → Scheduling → Schedules Scheduling Overview Scheduling is the process of assigning agents to work times that balance forecasted demand, service level goals, agent preferences, contract obligations, and business constraints. WFM scheduling creates optimal schedules for multi-skilled agents handling different interaction types across multiple sites. The scheduler considers each agent's individual skills, contracted working rules, and calendar items to identify when each agent can work and what work they will perform. Once finalized, schedules are published to the Master Schedule where agents view and potentially trade them. Scheduling Objectives Demand Coverage - Match staffing to forecasted volume and AHT Service Level Achievement - Achieve SL, ASA, abandon rate targets Contract Compliance - Respect working rules and labor laws Agent Preferences - Accommodate scheduling preferences where possible Flexibility - Enable shift trades and time-off requests Optimization - Minimize over/under staffing Scheduling Scope Business Unit Level - Schedules created for entire BU Time Granularity - Hourly detail, weekly structure Planning Period - 26 weeks forward (can search 104 weeks) Generation Window - 6 weeks maximum per schedule One Master - One published master schedule per BU at a time Future Schedules - Multiple scenarios before publishing Three Scheduling Methods WFM provides three primary scheduling methods, each suited to different scenarios: Method 1: Load-Based Scheduling with Forecasts Load-based scheduling uses the published Master Forecast to determine required staffing at each hour, then creates agent schedules to meet those requirements. How Load-Based Scheduling Works: Master Forecast Published ├─ Volume forecast (Offered) ├─ AHT forecast └─ By planning group and hour WFM Scheduler Receives Forecast ├─ Calculates required agents by hour ├─ Factors in service level goals ├─ Applies shrinkage rules └─ Determines agent needs (staffing target) Apply Constraints ├─ Agent skills and proficiency ├─ Contract working rules ├─ Availability and preferences ├─ Existing calendar items ├─ Team assignments Generate Schedule ├─ Assign agents to shifts ├─ Balance workload across agents ├─ Optimize shift times └─ Minimize over/under staffing Optimize for Efficiency ├─ Minimize overtime ├─ Maximize full utilization ├─ Consider split shifts ├─ Adjust for specific requests Output: Optimized schedule tied to demand Load-Based Characteristics: Data-Driven - Based on forecasted demand Demand-Responsive - Adjusts to volume changes Constraint-Aware - Respects contracts and preferences Accurate Staffing - Right people, right time Dependent on Forecast - Only as good as forecast When to Use Load-Based: ✓ Have accurate Master Forecast ✓ Want demand-driven scheduling ✓ Need to achieve service levels ✓ Have multiple media types ✓ Want cost optimization Load-Based Limitations: ✗ Dependent on forecast quality ✗ Requires forecast to be published ✗ Cannot create without forecast ✗ Changes to forecast require reschedule Load-Based Example: Master Forecast for Support Planning Group: Monday: 08:00-09:00: 50 calls, AHT 300s → Need 5 agents 09:00-10:00: 75 calls, AHT 300s → Need 7 agents 10:00-11:00: 100 calls, AHT 300s → Need 10 agents 11:00-12:00: 95 calls, AHT 300s → Need 9 agents ... (continue for full day) Schedule Generated: - Agent1: 08:00-16:30 (8.5 hours, with 1 hour lunch) - Agent2: 08:30-17:00 (8.5 hours, with 1 hour lunch) - Agent3: 09:00-17:30 (8.5 hours, with 1 hour lunch) - Agent4: 10:00-18:30 (8.5 hours, with 1 hour lunch) - ...and so on Result: 10 agents scheduled for peak period (10:00-11:00) Efficiency: Minimal over/under staffing Method 2: Shift Pattern-Based Scheduling (Without Forecasts) Shift pattern-based scheduling creates schedules based on predefined shift patterns without using forecast data. Useful when forecasts are unavailable or when standard shifts are preferred. How Shift Pattern Scheduling Works: Define Shift Patterns (Work Plans) ├─ Pattern A: 09:00-17:30 (Monday-Friday) ├─ Pattern B: 10:00-18:30 (Tuesday-Saturday) ├─ Pattern C: Flex (varies by week) └─ Pattern D: Part-time (13:00-17:00, Mon-Wed) Determine Agent Allocation ├─ How many agents per pattern? ├─ How many full-time vs part-time? ├─ How many per location/team? └─ How many per skill group? Assign Agents to Patterns ├─ Match agent skills to patterns ├─ Consider preferences ├─ Balance across teams └─ Respect availability Generate Schedule ├─ Agents follow assigned patterns ├─ All agents same shift per week ├─ No forecast-based adjustments └─ Predictable recurring schedule Output: Consistent repeating schedule (no forecast needed) Shift Pattern Characteristics: No Forecast Required - Works without demand data Predictable - Same pattern each week Simple - Easy for agents to understand Cost-Predictable - Fixed staffing levels Limited Flexibility - Cannot adjust to volume changes When to Use Shift Pattern: ✓ No accurate forecast available ✓ Want simple repeating schedules ✓ Prefer staffing stability ✓ New contact center (building history) ✓ Fixed cost model required Shift Pattern Limitations: ✗ Not demand-responsive ✗ May over/under staff ✗ Cannot meet varying service levels ✗ Inefficient for volatile volume Shift Pattern Example: Staffing Plan: 30 agents Shift Pattern Distribution: ├─ Pattern A: 09:00-17:30, Mon-Fri (12 agents) ├─ Pattern B: 10:00-18:30, Tue-Sat (10 agents) ├─ Pattern C: 12:00-20:00, Wed-Sun (8 agents) └─ Total: 30 agents, consistent coverage all day Schedule Result: ├─ Agents A1-A12: Always 09:00-17:30 ├─ Agents B1-B10: Always 10:00-18:30 ├─ Agents C1-C8: Always 12:00-20:00 └─ Same schedule every week (no variation) Method 3: Blank Schedule Creation Blank schedules create agent slots with no agent names assigned, useful for: Evaluating new shift patterns before agent assignment Planning for future hiring Testing schedule scenarios Creating templates for agent bidding Blank Schedule Methods: 3A. Profile-Based Scheduling: Create Profiles (Agent Templates): ├─ Profile: Full-Time Support (40 hrs/week) │ └─ Skills: Support_Level_2, Account_Mgmt ├─ Profile: Part-Time Support (20 hrs/week) │ └─ Skills: Support_Level_1 ├─ Profile: New Hire Flex (Variable) │ └─ Skills: None yet (training) └─ Profile: Sales Support (32 hrs/week) └─ Skills: Sales, Support_Level_1 Generate Blank Schedule Using Profiles: ├─ 20 Full-Time profiles (800 hours) ├─ 15 Part-Time profiles (300 hours) ├─ 5 New Hire profiles (160 hours) └─ 10 Sales Support profiles (320 hours) Result: 50 blank shifts, ready for agent assignment Use: Plan hiring, test new patterns, create bidding pools 3B. Schedule Bidding: Create Blank Schedule ├─ 30 distinct shifts (no agent names) ├─ All with required skills └─ Covering all time periods Open for Agent Bidding ├─ Agents view 30 available shifts ├─ Rank preferences: 1 (most wanted) to 30 ├─ Submit bids by deadline └─ Supervisors review bids WFM Automated Assignment ├─ Algorithm considers: │ ├─ Agent preferences (bid ranking) │ ├─ Seniority (longer tenure weighted higher) │ ├─ Skill match │ └─ Coverage requirements └─ Output: Assigned schedule Result: Fair assignment matching agent preferences Benefit: High satisfaction, voluntary participation Blank Schedule Characteristics: No Agents Yet - Empty slots Template Use - Test patterns before deployment Hiring Planning - Determine future hiring needs Flexibility - Can assign agents later Bidding Ready - Prepare for agent selection When to Use Blank Schedule: ✓ Planning new locations/teams ✓ Testing shift pattern changes ✓ Preparing for schedule bidding ✓ Evaluating staffing models ✓ Future hiring scenarios Work Plans Work Plans define how agents work: shifts, breaks, meals, contracts, weekly constraints, and labor compliance rules. Work Plan Components: Work Plan: Standard Full-Time Support 1. Shift Definition ├─ Start Time: 08:00 ├─ End Time: 16:30 ├─ Duration: 8 hours 30 minutes ├─ Paid Hours: 8 hours (lunch unpaid) └─ Days Available: Monday-Friday 2. Breaks ├─ Break 1: │ ├─ Name: Morning Break │ ├─ Duration: 15 minutes │ ├─ Timing: 10:00-12:00 window │ └─ Paid: Yes ├─ Break 2: │ ├─ Name: Afternoon Break │ ├─ Duration: 15 minutes │ ├─ Timing: 14:00-15:30 window │ └─ Paid: Yes └─ Total Break: 30 minutes paid 3. Meals ├─ Meal: Lunch │ ├─ Duration: 1 hour │ ├─ Timing: 12:00-13:00 window │ ├─ Paid: No │ └─ Required: Yes 4. Work Rules (Contract) ├─ Min Hours/Week: 40 ├─ Max Hours/Week: 40 ├─ Max Consecutive Days: 5 ├─ Min Hours/Day: 8 ├─ Max Hours/Day: 9 (includes breaks/meal) ├─ Days Off Required: 2 consecutive └─ Overtime Rules: After 40 hrs/week 5. Weekly Constraints ├─ Min Full Days/Week: 5 ├─ Max Split Days/Week: 1 ├─ Min Days Off/Week: 2 └─ Weekend Rule: Flexible 6. Planning Periods ├─ Planning Period: 1 week ├─ Minimum Periods: 4 weeks └─ Maximum Periods: 26 weeks 7. Additional Rules ├─ Lunch Hour Timing: 11:00-13:30 window ├─ Break Timing: 09:00-16:00 available ├─ Shift Flexibility: ±30 min start/end └─ Blending Allowed: Multiple activities/day Work Plan Best Practices: Clear Definition - Unambiguous rules Legal Compliance - Labor law adherence Flexibility - Account for agent needs Simplicity - Easy for agents to understand Documentation - Maintain copies Testing - Validate before deployment Creating a Work Plan: Navigate to Admin → Workforce Management → Work Plans Click Create Work Plan Define: Shift patterns (start, end, duration) Break configuration (when, how long, paid/unpaid) Meal configuration (when, how long, paid/unpaid) Work rules (min/max hours, consecutive days) Weekly constraints (full days, split days, days off) Planning period structure Save and activate Work Plan Scenarios: Example 1: Full-Time Permanent ├─ 08:00-16:30, Mon-Fri ├─ 30 min paid breaks ├─ 1 hour unpaid lunch ├─ 40 hours/week guaranteed └─ Use: Core permanent staff Example 2: Part-Time Flexible ├─ Variable 4-8 hours/day ├─ 15 min break per 4 hours ├─ 30 min lunch if >6 hours ├─ 20 hours/week average └─ Use: Supplemental staff Example 3: Shift Work (24/7 Coverage) ├─ Shift A: 07:00-15:00 (8 hours) ├─ Shift B: 15:00-23:00 (8 hours) ├─ Shift C: 23:00-07:00 (8 hours) ├─ Rotation: 3-day on, 4-day off └─ Use: 24/7 contact centers Example 4: Flex Hours ├─ Core hours: 10:00-15:00 (required) ├─ Flex hours: 08:00-10:00 or 15:00-18:00 ├─ Total: 40 hours/week ├─ Breaktime: Flexible └─ Use: Modern flexible work Schedule Management Creating a Schedule Step 1: Schedule Setup Navigate to Admin → Workforce Management → Schedules Click Create Schedule Configure: Name - Descriptive identifier (e.g., "Q2_2026_Week1-6") Period Start - First day to schedule Period End - Last day to schedule Duration - Maximum 6 weeks Business Unit - Select parent BU Planning Groups - Include relevant groups Click Next Step 2: Forecast Selection (Load-Based Only) Select Master Forecast or scenario Click Next Step 3: Scheduling Method Select method: Load-Based (with forecast) Shift Pattern (without forecast) Blank Schedule Configure method-specific options Click Next Step 4: Constraints Verify agent assignments Confirm work plans Set parameters: Allow overtime? Yes/No Allow split shifts? Yes/No Allow part-time? Yes/No Click Next Step 5: Generate Click Generate Schedule WFM processes agents and shifts Creates optimized schedule Displays results Step 6: Review & Adjust Review coverage by hour Check staffing levels: ✓ Service level achievable ✓ No excessive overtime ✓ Agent preferences honored ✓ No contract violations Make manual adjustments if needed Compare coverage to forecast Step 7: Publish Click Publish to Master Schedule Confirm publication Schedule immediately available to agents Becomes official working schedule Publishing Process Schedule Generated ↓ Status: Draft (not yet published) ├─ Visible only to admins/supervisors ├─ Can be edited ├─ Can be deleted └─ Agents cannot see Manual Review Period ├─ Check coverage ├─ Verify service level ├─ Review agent satisfaction └─ Make final adjustments Click: Publish to Master Schedule ↓ Status: Published (now official) ├─ Visible to all agents ├─ Agents can request time-off ├─ Agents can trade shifts ├─ Enforced for adherence Benefits: ├─ Only one master schedule per BU ├─ All agents see same official schedule ├─ Clear baseline for adherence ├─ Foundation for real-time monitoring One Master Schedule Per Business Unit Important Constraint: Only ONE master schedule can be active per business unit at a time Publishing a new schedule replaces the previous one Previous schedule versions retained in history Agents see only current master schedule Implication: Scenario: Multi-week scheduling Option A: Publish all at once ├─ Create 26-week schedule (6 weeks per period) ├─ Generate schedule periods 1-6 (weeks 1-6) ├─ Publish to master ├─ Weeks 1-6 active immediately ├─ During week 1: Generate periods 2-7 (weeks 7-12) ├─ At end of week 6: Publish next 26 weeks └─ Result: Continuous 26-week visibility Option B: Publish as needed ├─ Create schedule for weeks 1-6 only ├─ Publish to master ├─ During week 3: Create schedule for weeks 7-12 ├─ At end of week 6: Publish weeks 7-12 ├─ Result: Constant re-planning cycle Schedule Window & Visibility 26-Week Window The Schedules list displays a maximum of: 26 weeks PRIOR from earlier of current week or last schedule week 26 weeks FORWARD from earlier of current week or last schedule week 26-Week Window Example: Today: March 10, 2026 (Week 11 of year) Visible Window: ├─ Start: September 1, 2025 (Week 36-11 = Week 25 back) │ └─ Actually visible: ~26 weeks back from now ├─ Current: March 10, 2026 (Week 11) └─ End: September 1, 2026 (Week 36) └─ 26 weeks forward from now Outside Visible Window: ├─ Before: August 2025 and earlier │ └─ Available via search feature ├─ After: September 2026 and later └─ Available via search feature Search Capability The search feature extends beyond the 26-week window: Search Range - Up to 104 weeks (2 years) Use Search - Find old schedules or far-future plans Filters - By date range, status, name Download - Export search results Scheduling Constraints WFM applies multiple constraints during scheduling: Agent-Level Constraints: Individual skills and proficiency Current work schedule Time-off requests Calendar items (training, meetings) Availability windows Maximum hours/week limit Minimum hours/day Contract-Level Constraints: Employment type (full-time, part-time, flex) Minimum/maximum hours per week Maximum consecutive work days Minimum consecutive days off Lunch and break requirements Overtime rules Split shift limitations Team/Site-Level Constraints: Required staffing levels Coverage requirements Minimum agents per activity Team balance Cross-training requirements Backup coverage needs Business-Level Constraints: Service level goals Cost budget Overtime authorization Skill mix requirements New hire integration Manager approval requirements Schedule Metrics Coverage Analysis Staffing Report: Hour Forecast Scheduled Variance Coverage ──────────────────────────────────────────────────────── 08:00-09:00 6 agents 6 agents 0 (0%) ✓ 100% 09:00-10:00 8 agents 8 agents 0 (0%) ✓ 100% 10:00-11:00 12 agents 11 agents -1 (-8%) ⚠ 92% 11:00-12:00 11 agents 11 agents 0 (0%) ✓ 100% 12:00-13:00 9 agents 9 agents 0 (0%) ✓ 100% 13:00-14:00 10 agents 10 agents 0 (0%) ✓ 100% 14:00-15:00 10 agents 11 agents +1 (+10%) ✓ 110% 15:00-16:00 8 agents 8 agents 0 (0%) ✓ 100% 16:00-17:00 6 agents 6 agents 0 (0%) ✓ 100% ──────────────────────────────────────────────────────── Daily Total 80 agents 80 agents 0 (0%) ✓ 100% Analysis: ✓ Good overall coverage (100%) ⚠ Slight under-staffing at peak (10:00-11:00) ✓ Minimal over-staffing (hour 14:00) ✓ Efficient balance achieved Efficiency Metrics Schedule Efficiency Report: Metric Value Target Status ──────────────────────────────────────────────────────── Total Scheduled Hours 4,000 4,020 96% Required Staffing Hours 3,800 3,800 100% Over-Staffing Hours 200 200 On-target Overtime Hours (>40/week) 120 100 ⚠ High Average Hours/Agent 40.0 40.0 ✓ On-target Agents with Overtime 3/50 0 ⚠ 6% Average Shift Length 8.5h 8.5h ✓ On-target Part-Time Usage 12/50 12/50 ✓ On-target Multi-Activity Assignments 35/50 30/50 ✓ Good blend Cost per Hour $45.50 $45.00 ⚠ 1% over Overall Efficiency: 94% (Good) Real-World Examples Example 1: 100-Agent Contact Center Scenario: Mid-size support center, 100 agents Master Forecast Published: ├─ Weekly volume: 15,000 calls ├─ Average AHT: 300 seconds ├─ Service level goal: 80% in 20 seconds ├─ Staffing required: ~95 agents Work Plans: ├─ Full-time: 40 hrs/week (70 agents) ├─ Part-time: 20 hrs/week (20 agents) ├─ Flex: 10-30 hrs/week (10 agents) └─ Total: 100 agents Schedule Generated: ├─ Create 6-week schedule (weeks 1-6) ├─ Use load-based method with Master Forecast ├─ Generate optimized shifts ├─ Coverage verified: │ ├─ Monday-Friday peak: 12-13 agents/hour │ ├─ Monday-Friday valley: 5-6 agents/hour │ ├─ Weekend: 3-4 agents (limited hours) │ └─ Night: Minimal coverage (auto-handled) ├─ Overtime: 5% of agents (acceptable) └─ Agent satisfaction: High (preferences honored) Publish to Master Schedule ├─ Week 1 effective immediately ├─ Agents view on portal ├─ Time-off requests begin └─ Adherence tracking starts Management: ├─ Monitor actual vs forecast ├─ Handle shift trades ├─ Approve time-off requests └─ Real-time adjustments as needed Example 2: Growing Business (Scaling Up) Scenario: Adding new team (20 agents) for new product Situation: ├─ Current: 100 agents fully scheduled ├─ Adding: 20 new agents (onboarding week 3) ├─ Challenge: How to integrate new team? Solution: Phase 1 (Weeks 1-2): Current schedule ├─ Use existing 100-agent schedule ├─ All forecasts/schedules unchanged └─ New team not yet integrated Phase 2 (Week 3+): Reschedule with new team ├─ Week 2: Create new Master Forecast │ ├─ Include new product volume │ ├─ Adjust planning groups │ └─ Recalculate staffing needs (now 115 agents) ├─ Week 2: Generate new schedule (weeks 3-8) │ ├─ Include all 120 agents (100 existing + 20 new) │ ├─ Use load-based method │ ├─ Distribute new volume across team │ └─ Assign new agents training hours ├─ Week 3: Publish new Master Schedule │ ├─ Replaces previous master │ ├─ All 120 agents see new schedule │ ├─ Service level improved (more agents) │ └─ Coverage now matches expanded demand Result: ├─ Smooth integration of new team ├─ Service level maintained/improved ├─ Existing agents' schedules adjusted fairly └─ New agents fully utilized from start Example 3: Holiday Season Planning Scenario: Retail support (holiday surge) Situation: ├─ Normal staffing: 80 agents ├─ Holiday season: Expected 150% volume ├─ Duration: November 20 - January 5 ├─ Challenge: Massive temporary spike Solution: 1. Forecast Planning (October) ├─ Marketing provides volume projections ├─ Create ABM forecast with holiday data ├─ Result: 15,000→22,500 daily calls (50% increase) ├─ Staffing needed: 80 agents → 120 agents 2. Hiring & Training (October) ├─ Hire 40 temporary agents ├─ 2-week training period ├─ Ramp to full productivity by week 3 └─ Flexible contracts (seasonal) 3. Work Plan Updates (October) ├─ Expand existing work plans ├─ Create temporary shift patterns ├─ 10:00-18:00 shifts (high volume hours) ├─ Weekend staffing added └─ Overtime authorized for existing staff 4. Schedule Generation (October, weekly) ├─ Week 1 (Oct 30): 80 agents + 20 new trained ├─ Week 2 (Nov 6): 80 agents + 40 new trained ├─ Weeks 3-10 (Nov 13-Jan 5): Full 120 agents └─ Week 11 (Jan 12): Ramp down to 80 agents 5. Real-Time Adjustments ├─ Week 1: Volume 15,200 calls (↓5% vs forecast) ├─ Week 2: Volume 23,100 calls (↑3% vs forecast) ├─ Week 3: Add 10 more agents (unplanned) ├─ Weeks 4-10: Adjust as actual trends emerge └─ Week 11: Begin releasing temporary agents 6. Results ├─ Service level: 82% (goal 80%) ✓ ├─ ASA: 18 seconds (goal 20s) ✓ ├─ Abandon: 4% (goal 5%) ✓ ├─ Temp agent cost: $180,000 ├─ Revenue increase: $500,000 └─ ROI: 278% (strong business case) Best Practices Schedule Creation Regular Cycle - Create 6-week schedules weekly Advance Planning - 4-6 weeks notice to agents Quality Review - Verify coverage before publishing Communication - Announce new schedule to team Version History - Keep archive of old schedules Flexibility - Allow trades and time-off requests Optimization Monitor Variance - Track actual vs scheduled Adjust Timing - Shift times to match real demand Reduce Overtime - Trim excessive OT through timing Balance Load - Equalize workload across agents Agent Preferences - Honor where possible Cost Focus - Minimize labor costs Communication Transparency - Share with agents early Rationale - Explain scheduling decisions Feedback - Listen to agent concerns Accessibility - Portal available 24/7 Updates - Notify of changes promptly Support - Help agents understand schedule Interview Cheat Sheet Question Answer 3 scheduling methods? Load-based (forecast), Shift pattern, Blank schedule Load-based when? Have accurate forecast, want demand-driven Shift pattern when? No forecast, want simple repeating schedule Blank schedule when? Planning hiring, testing patterns, bidding How long schedule? Max 6 weeks per generation Schedule window? 26 weeks prior, 26 weeks forward Master schedules per BU? One active at a time What's work plan? Defines shifts, breaks, meals, contracts Shift items? Breaks and meals with time windows Scheduling constraints? Skills, contracts, availability, service level How verify coverage? Compare scheduled agents to forecast When publish? After review, when ready for agents Agent trades? Allowed if approved, don't violate schedule Schedule bidding? Agents rank preference, auto-assigned Reschedule how often? Weekly or as needed for changes Key Takeaways Three Methods - Load-based (forecast), Shift pattern, Blank schedule 6-Week Maximum - Single generation limited to 6 weeks 26-Week Window - Visibility and planning horizon One Master - Only one published schedule per BU active Work Plans - Define hours, breaks, meals, contracts Constraints - Skills, contracts, preferences all considered Demand-Driven - Load-based matches forecast to staffing Optimization - Minimize cost while achieving service level Flexibility - Agents can trade and request time-off Continuous - Weekly reschedule cycle for optimization Additional Resources Official Documentation Scheduling: help.genesys.cloud/articles/work-with-workforce-management-schedules/ Work Plans: help.genesys.cloud/articles/work-plans-overview/ Shift Patterns: help.genesys.cloud/articles/shift-patterns-overview/ Schedule Constraints: help.genesys.cloud/articles/workforce-management-supported-configuration/ Support & Training Genesys University: genesys.com/training Community Forums: https://community.genesys.com Technical Support: https://support.genesys.com Document Version Info Last Updated: March 2026 Source: Genesys WFM Official Documentation Validated: Current with January-March 2026 releases Version: 1.0 Intraday Management Genesys WFM Intraday Management Documentation Study Notes Topic Description Intraday Management Real-time monitoring of contact center performance Performance Views Summarized and detailed grid displays of metrics Metrics Volume offered, AHT, service level, staffing, adherence Activity Codes Map agent states to schedule states Thresholds 15, 30, or 60-minute monitoring intervals Real-Time Adjustments Add/remove agents, modify activities on-the-fly What-If Analysis Project impact of staffing changes Navigation Menu → Workforce Management → Performance → Intra-Day OR Supervisor → Performance → Intraday Monitoring Intraday Management Overview Intraday Management is the real-time monitoring and adjustment of contact center operations throughout the day. It compares actual performance against forecasted expectations, enabling supervisors to make data-driven decisions about agent staffing, activity assignments, and schedule adjustments in response to fluctuating demand. Intraday Management allows supervisors to: Monitor real-time performance metrics Compare actual vs forecasted volumes and AHT Identify service level risks Add or remove agents from activities Make schedule adjustments for unexpected demand Project impact of staffing changes Maintain service level targets Intraday Management Objectives Performance Tracking - Monitor actual vs forecast Risk Detection - Identify service level at risk Quick Response - Make rapid staffing adjustments Data-Driven Decisions - Use metrics to guide choices Service Level Maintenance - Protect SL targets Cost Optimization - Minimize unnecessary overtime Workload Balancing - Redistribute work as needed Key Metrics Monitored Real-Time Intraday Metrics: Current (Actual): ├─ Interaction Volume (Offered) ├─ Average Handle Time (AHT) ├─ Service Level % (achieved) ├─ Average Speed to Answer (ASA) ├─ Abandon Rate % ├─ Agents on Queue ├─ Occupancy % └─ Interactions Handled Forecasted (Predicted): ├─ Expected Volume (remainder of day) ├─ Projected AHT ├─ Predicted Service Level ├─ Staffing Requirements ├─ Expected ASA └─ Coverage Gap Analysis Variance Analysis: ├─ Volume Variance (Actual vs Forecast) ├─ AHT Variance ├─ Service Level Status (On Track/At Risk/Critical) ├─ Staffing Gap (Over/Under) └─ Trend Direction (↑ improving / ↓ declining) Performance Intraday View The Intraday View displays real-time and forecasted performance metrics in a detailed grid format, updated continuously throughout the day. Intraday View Structure: Performance Intraday View Grid: Time Step | Offered | AHT | SL % | ASA | Agents | Status ──────────────|---------|------|-------|------|--------|──────────── 08:00-09:00 | 45 | 280s | 82% | 18s | 6 | ✓ On Track 09:00-10:00 | 68 | 290s | 79% | 22s | 8 | ✓ On Track 10:00-11:00 | 95 | 310s | 75% | 28s | 11 | ⚠ At Risk 11:00-12:00 | 88 | 305s | 77% | 26s | 10 | ⚠ At Risk 12:00-13:00 | 52 | 270s | 85% | 16s | 6 | ✓ On Track 13:00-14:00 | 65 | 285s | 81% | 20s | 8 | ✓ On Track 14:00-15:00 | 72 | 300s | 78% | 24s | 9 | ⚠ At Risk 15:00-16:00 | 58 | 295s | 80% | 21s | 7 | ✓ On Track Legend: ✓ On Track = SL within 2-3% of goal (goal 80%) ⚠ At Risk = SL within goal but trending down, or 1-2% below goal 🔴 Critical = SL >2% below goal, immediate action needed Current Status (as of 13:15): ├─ Offered Today: 543 calls ├─ Average AHT: 292 seconds ├─ Current SL: 79.5% ├─ Service Goal: 80% ├─ Status: On Track (within acceptable range) View Refresh Intervals: 15-minute intervals - Most frequent, impacts system performance 30-minute intervals - Balanced (recommended) 60-minute intervals - Less frequent, lower system impact Data Display Options: Summarized View - High-level overview by hour Detailed View - Granular metrics with all statistics Graphical View - Charts showing trends over time Real-Time Metrics Interaction Volume (Offered) Definition: Total number of interactions offered to the contact center How Calculated: ├─ Sum of all inbound interactions (calls, emails, chats, etc.) ├─ Per time interval ├─ Across selected planning group(s) └─ Real-time count + forecast for remainder of day Example: ├─ 10:00-10:15: 25 calls offered ├─ 10:15-10:30: 28 calls offered ├─ 10:30-10:45: 22 calls offered ├─ 10:45-11:00: 20 calls offered └─ Hour Total: 95 calls offered Variance from Forecast: ├─ Forecasted: 92 calls ├─ Actual: 95 calls ├─ Variance: +3 (3.3% higher than forecast) Average Handle Time (AHT) Definition: Average duration of each interaction (call, email, chat) Components: ├─ Talk Time (conversation) ├─ Hold Time (customer on hold) ├─ After Call Work (processing after call) └─ Wrap-up Time (notes, documentation) Example (Voice Interactions): ├─ Call 1: 5 min 30 sec ├─ Call 2: 4 min 45 sec ├─ Call 3: 6 min 15 sec ├─ Call 4: 5 min 00 sec └─ Average: 5 min 22 sec (322 seconds) Variance Tracking: ├─ Forecasted AHT: 300 seconds (5 min) ├─ Actual AHT: 322 seconds (5:22) ├─ Variance: +22 seconds (+7.3% higher) └─ Impact: Requires more agents for same volume Service Level (SL) Definition: % of interactions answered within target time Calculation: ├─ Target: 80% of calls answered in 20 seconds ├─ Actual: 82% of calls answered in 20 seconds ├─ Status: ✓ Exceeding target Examples: ├─ 1,000 calls offered ├─ 800 calls answered ≤20 seconds ├─ 200 calls answered >20 seconds ├─ SL = (800/1000) × 100 = 80% ✓ Target met Real-Time Example: ├─ Hour 10:00-11:00 ├─ Offered: 95 calls ├─ Answered ≤20s: 71 calls ├─ Answered >20s: 24 calls ├─ SL: (71/95) × 100 = 74.7% ├─ Goal: 80% ├─ Status: ⚠ Below target (5.3% gap) Average Speed to Answer (ASA) Definition: Average time from call offered to agent answer Calculation: ├─ Sum of all answer wait times ├─ Divided by number of answered calls ├─ Result in seconds Example: ├─ Call 1: 12 seconds wait ├─ Call 2: 18 seconds wait ├─ Call 3: 25 seconds wait ├─ Call 4: 22 seconds wait ├─ Average: (12+18+25+22) / 4 = 19.25 seconds ≈ 19s Relationship to Service Level: ├─ SL: 80% in 20 seconds = at least 80% ≤20s ├─ ASA: 19 seconds = average across all calls ├─ Both track speed, different perspectives └─ SL is goal-focused, ASA is performance-focused Real-Time Adjustments Adding Agents to Activity Scenario: Service level dropping (75% vs 80% goal), trend declining Step 1: Identify Risk ├─ Monitoring shows SL at 75% (below 80% goal) ├─ Trend shows -2% per 15 minutes ├─ Current staffing: 8 agents on support queue └─ Remaining shift: 3 hours Step 2: Analyze Options ├─ Option A: Pull 2 agents from lower-priority activity ├─ Option B: Authorize overtime for available agents ├─ Option C: Use on-call backup agents └─ Decision: Option A (least cost impact) Step 3: Make Adjustment ├─ Modify schedule manually ├─ Assign 2 agents from "Idle" activity to "Support" ├─ Update system in real-time └─ Effect: Immediate Step 4: Monitor Impact ├─ Next 15 minutes: SL improves to 78% (trend reversed) ├─ Next 30 minutes: SL reaches 81% (goal achieved) ├─ After 1 hour: Decision made to keep additional agents Step 5: Cleanup ├─ Removed agents: Return to original activity ├─ Overtime: Document and approve as needed └─ Analysis: Record what worked for future reference Modifying Activity Assignments Scenario: Email queue backing up, response times extending Current State: ├─ Email queue: 250 emails waiting ├─ Average response time: 2.5 hours ├─ Goal: 1.5 hours response └─ Staffing: 4 agents on email Decision: Temporarily assign chat agents to email Action: ├─ Identify 2 available chat agents ├─ Reassign to email activity ├─ Update their work assignment in real-time ├─ System recalculates workload Result: ├─ Email staffing: 4 → 6 agents ├─ Queue starts processing faster ├─ Response time improves to 1.8 hours ├─ Chat queue slightly longer but acceptable Reversal: ├─ When email clears, chat agents reassigned ├─ Return to normal staffing model Schedule Intraday Rebuild WFM can regenerate schedules for specific days based on updated demand: Use Case: Unexpected surge in volume Morning (09:00): ├─ Forecast: 2,000 calls for day ├─ Actual by 09:30: 500 calls already (ahead of pace) ├─ New projection: 3,000 calls (50% surge) ├─ Current schedule: Insufficient Action: Intraday Schedule Rebuild ├─ Select days: Today (rest of day) ├─ Recalculate staffing: Based on new forecast ├─ Generate new schedule: For current time forward ├─ Adjust Agent assignments: For remainder of shift ├─ Publish changes: To affected agents Result: ├─ Schedule optimized for actual demand ├─ Additional agents added to peak periods ├─ Prevents service level failure ├─ Agents notified of schedule changes What-If Analysis The What-If calculator allows supervisors to project impact of staffing changes before implementing them. What-If Process: Current State: ├─ Volume offered: 95 calls/hour ├─ AHT: 300 seconds ├─ Staffing: 10 agents ├─ Projected SL: 81% Question: What if we add 2 more agents? What-If Calculation: ├─ Input: Staffing = 12 agents (instead of 10) ├─ Calculate new SL: 87% ├─ Calculate new ASA: 15 seconds (instead of 18) ├─ Calculate new occupancy: 72% (instead of 80%) Question: What if volume increases 20%? What-If Calculation: ├─ Input: Volume = 114 calls/hour (95 × 1.2) ├─ Calculate new SL: 76% (with 10 agents) ├─ Calculate new ASA: 23 seconds ├─ Calculate new occupancy: 95% Conclusion: ├─ Need to add 3-4 agents to maintain SL └─ 20% volume increase requires ~30% staffing increase What-If Variables: Staffing levels (agents on activity) Interaction volume (offers per hour) Average handle time (seconds per interaction) Service level goal (% in seconds) Occupancy target Shrinkage rate Activity Code Management Activity codes map agent states to schedule states for adherence and reporting. They represent what agents are doing at any given time. Common Activity Codes: On-Queue Activities (Customer-Facing): ├─ Inbound Call - handling incoming calls ├─ Inbound Email - responding to emails ├─ Inbound Chat - managing chat conversations ├─ Outbound Call - making outbound calls ├─ Callback - handling scheduled callbacks ├─ Workitem - handling task-based work └─ Multi-Activity - performing multiple types Off-Queue Activities (Non-Customer): ├─ Break - scheduled break time ├─ Meal - lunch or meal period ├─ Training - formal training session ├─ Meeting - team or coaching meeting ├─ Administrative - paperwork, documentation ├─ Idle - waiting for next interaction ├─ After Call Work - call follow-up work └─ Time Off - approved absence Special Activities: ├─ Exception - unscheduled activity ├─ Overtime - additional hours ├─ Shift Trade - schedule swap ├─ Unavailable - temporarily not available ├─ Coaching - one-on-one coaching session └─ Quality - call monitoring Activity Code Mapping: Schedule State Group: On-Queue Voice Maps to Real-Time States: ├─ WaitingForNextCall → Idle/Available ├─ Connected → Connected/Call ├─ Held → Held/Call ├─ AfterCallWork → ACW/Post-Call └─ Reason Codes: ├─ "C100": Connected call ├─ "BRK": Break (if mapped) └─ "TRN": Training (if mapped) For Adherence: ├─ Agent scheduled: On-Queue Voice 10:00-15:00 ├─ Agent actual: Connected (Connected call) ├─ Mapping: Connected maps to On-Queue ✓ Adherent │ ├─ Agent actual: Break (taking break) ├─ Mapping: Break mapped to On-Queue? If yes ✓ Adherent │ If no ✗ Non-adherent Monitoring Views Summary View (By Time Interval) Hourly Summary View - Support Planning Group Hour | Offered | AHT | SL % | Staffing | Occupancy | Status ──────────|---------|------|-------|----------|-----------|────────── 08:00-09 | 42 | 280s | 84% | 5 | 68% | ✓ Good 09:00-10 | 68 | 290s | 81% | 8 | 79% | ✓ Good 10:00-11 | 95 | 310s | 75% | 11 | 87% | ⚠ Risk 11:00-12 | 88 | 305s | 77% | 10 | 85% | ⚠ Risk 12:00-13 | 52 | 270s | 86% | 6 | 62% | ✓ Good Daily Avg | 349 | 293s | 80.6% | 8 | 76% | ✓ On Target Detailed View (By Agent) Agent-Level Intraday View - Current Time 14:30 Agent Name | Activity | Duration | SL Target | Status | Notes ────────────|-----------|----------|-----------|-----------|───────────── Agent_001 | Connected | 4:23 | Speaking | ✓ OK | Handling call Agent_002 | ACW | 1:05 | After CW | ✓ OK | Wrapping up Agent_003 | Available | 0:00 | Available | ✓ OK | Ready for next Agent_004 | Break | 8:30 | On Break | ✓ OK | Scheduled break Agent_005 | Connected | 5:47 | Speaking | ⚠ Long | Extended call Agent_006 | Training | 1:15:00 | Training | ✓ OK | Product training Agent_007 | Off | OFF | Time Off | ✓ OK | Approved absence Agent_008 | Idle | 2:15 | Available | ✓ OK | In queue Summary: ├─ Agents Available: 3 ├─ Agents Connected: 2 ├─ Agents Off-Queue: 3 ├─ Total Team: 8 agents Performance Scenarios Scenario 1: Volume Spike Tuesday 11:00 AM - Unexpected Surge Timeline: 10:00: ├─ Forecasted: 85 calls this hour ├─ Actual: 82 calls (on track) ├─ SL: 81% └─ Staffing: 10 agents 10:30: Alert! Volume Spike Detected ├─ Trend: +35% above forecast ├─ Current: 60 calls in 30 min (120/hour pace) ├─ Projected: 115 calls for 11:00 hour ├─ Impact: SL likely to drop to 72% (below 80% goal) 11:00: Supervisor Takes Action ├─ Analysis: Need +3 agents to maintain SL ├─ Action: Pull 2 agents from email queue + 1 from callback ├─ New Staffing: 13 agents on support ├─ Notify agents: Immediate activity change ├─ Update schedule: Reflect change 11:30: Monitor Impact ├─ Actual: 118 calls for hour (matched projection) ├─ SL achieved: 79.5% (close to goal) ├─ Occupancy: 91% (high but acceptable) ├─ Status: ✓ Crisis averted 11:45: Plan Staffing Reversal ├─ Volume trend: Normalizing ├─ Project: Peak ending at 13:00 ├─ Plan: Return agents to original activities at 13:15 ├─ Communication: Notify agents of planned change Result: ├─ Service level maintained through spike ├─ Agents reassigned with notice ├─ Customer experience protected ├─ Learning: Update forecast model for this day type Scenario 2: Service Level Failure Thursday 15:00 - Service Level Deteriorating 14:00: ├─ SL: 82% ├─ Trend: Stable └─ Action: Monitor 14:15: ├─ SL: 81% ├─ Trend: -1% ├─ Action: Watch closely 14:30: ├─ SL: 80% ├─ Trend: -1% ├─ Action: Prepare contingency 14:45: ├─ SL: 78% ├─ Trend: Worsening ├─ Action: IMMEDIATE RESPONSE NEEDED Analysis: ├─ Root Cause: 2 agents called in sick ├─ Current: 9 agents (down from scheduled 11) ├─ Current SL: 78% ├─ Needed SL: 80% └─ Solution: Add 2-3 agents within 30 min Options: ├─ A) Callback on-call agents (20 min lag) ├─ B) Offer voluntary overtime (immediate) ├─ C) Pull from other activities (immediate) └─ Selected: A + C (both) Action Taken: ├─ Authorize voluntary overtime (3 agents offered) ├─ Pull 1 agent from lower-priority activity ├─ Call on-call agent (ETA 20 min) ├─ Temporary staffing: 10 agents Result by 15:30: ├─ Additional agent arrives ├─ Staffing: 12 agents ├─ SL recovers to 81% ├─ Goal achieved Closeout: ├─ Paid overtime to 3 volunteers ├─ Approved additional staffing for rest of week ├─ Reviewed scheduling process for gaps └─ Cost impact: ~$400 additional labor Best Practices Real-Time Monitoring Constant Vigilance - Watch trends, not just snapshots Threshold Management - Set alerts for SL drop (e.g., -2%) Trend Awareness - Declining trends warrant early action Granular Intervals - 15-30 min intervals catch problems early Regular Review - Check every 15-30 minutes during peak Decision Making Data-Driven - Use what-if calculator before acting Proportional Response - Match staffing change to demand Communication - Notify agents of changes promptly Documentation - Record actions and reasons Learning - Review decisions post-shift for improvement Staffing Adjustments Minimize Disruption - Use lowest-impact sources first Early Action - Add agents before crisis, not during Reversal Planning - Plan removal of extra agents early Cost Awareness - Balance service vs overtime cost Agent Care - Provide notice of changes when possible Interview Cheat Sheet Question Answer What is intraday management? Real-time monitoring and adjustment of operations Key metrics monitored? Volume, AHT, SL, ASA, abandon rate, occupancy What's intra-day view? Grid display of real-time and forecasted metrics Monitor intervals? 15, 30, or 60-minute intervals What's AHT? Average handle time - duration per interaction What's SL? Service level - % answered within target time What's ASA? Average speed to answer - wait time average What's occupancy? % of time agents spend handling interactions What-if calculator? Projects impact of staffing/volume changes Activity codes? Map agent states (on-queue, break, etc.) When add agents? SL dropping, trend negative, volume spike Intraday rebuild? Regenerate schedule based on new demand Real-time adjustment? Reassign agents between activities immediately Yellow/red status? Yellow = non-adherent, Red = severely non-adherent How respond to spike? Monitor, calculate need, reassign agents Key Takeaways Real-Time Visibility - Constant monitoring of actual vs forecast Data-Driven Decisions - Use metrics to guide staffing changes Quick Response - Make adjustments within minutes of risk detection Service Protection - Prevent SL failures before they occur What-If Planning - Project impact before implementing changes Activity Flexibility - Dynamically assign agents to needs Trend Awareness - Declining trends warrant proactive action Communication - Notify agents of changes promptly Cost Balance - Optimize service level vs labor cost Continuous Learning - Review and improve daily decisions Additional Resources Official Documentation Intraday Monitoring: help.genesys.cloud/articles/intraday-monitoring-overview/ Performance Views: all.docs.genesys.com/PEC-WFM/Current/Supervisor/PrfmIntrDyVw Activity Codes: help.genesys.cloud/articles/activity-codes-overview/ Support & Training Genesys University: genesys.com/training Community Forums: https://community.genesys.com Technical Support: https://support.genesys.com Document Version Info Last Updated: March 2026 Source: Genesys WFM Official Documentation Validated: Current with January-March 2026 releases Version: 1.0 Time-off & Shift Trades Genesys WFM Time-Off & Shift Trades Documentation Study Notes Topic Description Time-Off Management Automated request evaluation, approvals Auto-Approval Qualifying requests approved automatically Time-Off Plans Define activity codes linked to limits Daily Limits Max hours per day per management unit Shift Trades Agent-to-agent schedule swaps Trade Rules Configuration of swap eligibility Approval Workflow Auto-approve or manual review Self-Service Portal Agents request via desktop/mobile Navigation Menu → Workforce Management → Time Off OR Agent Portal → Schedule → Time Off / Shift Trades Time-Off Management Overview Time-Off Management enables agents to request absences while maintaining workforce balance and service levels. Supervisors can define automated approval rules, allowing qualifying requests to be approved instantly while flagging exceptions for manual review. Time-Off functions: Automate approval of routine requests Maintain visibility across absences Track time-off limits and balances Enforce policy rules Support work-life balance Reduce administrative burden Key Components Time-Off System: 1. Time-Off Types ├─ Vacation ├─ Sick Leave ├─ Personal Time ├─ Unpaid Time Off ├─ Bereavement ├─ Jury Duty └─ Other (customizable) 2. Request Submission (Agent) ├─ Select dates ├─ Choose type ├─ Submit request └─ Receive approval/notification 3. Approval Rules (Supervisor) ├─ Auto-approve if meets criteria ├─ Flag exceptions for review ├─ Document decision └─ Notify agent 4. Scheduling Impact ├─ Reduce available staffing ├─ Trigger schedule adjustments ├─ Maintain service levels └─ Update master schedule 5. Reporting ├─ Track utilization ├─ Monitor patterns ├─ Identify trends └─ Manage balances Time-Off Plans Time-Off Plans link activity codes to time-off limits, defining how much of each type agents can use. Time-Off Plan Example: Standard Benefits Plan Name: Standard Employee Vacation: ├─ Activity Code: VAC ├─ Annual Limit: 20 days ├─ Monthly Accrual: 1.67 days ├─ Carryover: 5 days max to next year ├─ Blackout Dates: Dec 24-25 (no vacation) └─ Min. Notice: 2 weeks advance Sick Leave: ├─ Activity Code: SICK ├─ Annual Limit: 10 days ├─ Monthly Accrual: 0.83 days ├─ Carryover: None (use it or lose it) ├─ Blackout Dates: None ├─ Min. Notice: None (emergency allowed) └─ Requires: Medical note if >3 consecutive Personal Time: ├─ Activity Code: PERSONAL ├─ Annual Limit: 5 days ├─ Monthly Accrual: 0.42 days ├─ Carryover: 1 day to next year ├─ Blackout Dates: Dec 24-25 ├─ Min. Notice: 3 days advance └─ Approval: Supervisor discretion Unpaid Time: ├─ Activity Code: UNPAID ├─ Annual Limit: Unlimited ├─ Accrual: N/A ├─ Carryover: N/A ├─ Blackout Dates: None ├─ Min. Notice: 1 week advance └─ Approval: Requires supervisory approval Automated Approval Rules Supervisors configure rules for automatic approval of time-off requests. Auto-Approval Rule Example: Rule: Vacation Request Auto-Approval Conditions (ALL must be true): ├─ Time-Off Type: Vacation ├─ Balance Available: > 8 hours (full day) ├─ Notice Period: ≥ 2 weeks advance ├─ Minimum Staffing: ≥ 3 agents remaining ├─ Blackout Dates: Not during Dec 24-25 ├─ Previous Pending: None pending for agent └─ Manager Approval: Not required if rules met Result: ├─ Request arrives Sunday ├─ System checks all conditions ├─ If all met: ✓ APPROVED instantly ├─ If any fail: ⚠ PENDING for supervisor review └─ Agent notification: Immediate Example Scenarios: Request 1: 2 weeks advance, 4 agents remain ├─ Conditions: All met ✓ ├─ Result: AUTO-APPROVED ✓ └─ Agent: Sees approval immediately Request 2: 1 week advance (less than 2 weeks) ├─ Condition: Notice period failed ✗ ├─ Result: PENDING manual review └─ Agent: Waits for supervisor decision Request 3: 2 weeks advance, only 2 agents remain (below 3) ├─ Condition: Minimum staffing failed ✗ ├─ Result: PENDING manual review └─ Agent: Can be denied or rescheduled Daily Time-Off Limits Supervisors can set maximum hours per day per management unit to prevent over-staffing on any day. Daily Limits Configuration: Management Unit: Support - Dallas Monday: ├─ Total Agents: 50 ├─ Max Allowed Off: 8 agents (16%) └─ Configuration: 8 hours max (full day) Tuesday: ├─ Total Agents: 50 ├─ Max Allowed Off: 8 agents (16%) └─ Configuration: 8 hours max ... (same for all days) Holiday Period (Dec 20-26): ├─ Total Agents: 50 ├─ Max Allowed Off: 5 agents (10%) ← More restrictive └─ Configuration: 5 agents max Application: Request 1: Vacation Dec 22 (within holiday period) ├─ Currently Approved: 4 agents off ├─ Requesting Agent: 1 more ├─ Total if Approved: 5 agents (at limit) ├─ Result: ✓ APPROVED (meets limit) Request 2: Vacation Dec 22 (within holiday period) ├─ Currently Approved: 5 agents off ├─ Requesting Agent: 1 more ├─ Total if Approved: 6 agents (exceeds limit of 5) ├─ Result: ✗ DENIED (over limit) Shift Trades Shift Trades allow agents to swap work schedules with other agents, subject to supervisor-configured rules. Trade Configuration Shift Trade Rules Setup: Rule 1: Basic Trade Eligibility ├─ Agents in same team: Must trade with same team ├─ Agents in different teams: Can trade (if enabled) ├─ Same skill requirements: Both must be qualified ├─ Hours equivalence: Trades must be similar duration └─ Master schedule: Can't trade published master schedule Rule 2: Trade Window ├─ Minimum notice: 2 weeks before shift ├─ Maximum advance: Up to 26 weeks forward ├─ Trade-back window: Must reverse within X days └─ Freeze period: No trades during blackout dates Rule 3: Agent Eligibility ├─ Minimum tenure: 3 months to trade ├─ Performance: No active disciplinary actions ├─ Adherence: >85% adherence to qualify ├─ Pending trades: Only 1 trade pending at a time └─ Trade history: Limit to X trades per period Rule 4: Approval Workflow ├─ Agent 1: Initiates trade ├─ Agent 2: Reviews and accepts/declines ├─ Supervisor: Auto-approves if eligible ├─ Supervisor: Denies if rule violations └─ Notification: Both agents notified of decision Rule 5: Service Level Protection ├─ Staffing impact: Must not drop below minimum ├─ Skill requirements: Both agents must be skilled ├─ Activity match: Can trade between activities? (config) └─ Override: Supervisor can force approve Trade Process Shift Trade Workflow: Agent A Initiates Trade: ├─ 1. Select shift to trade (Mine: Tuesday 09:00-17:00) ├─ 2. Search for potential trades │ └─ Can filter by: Agent, Team, Date, Activity ├─ 3. Identify Agent B with matching shift │ └─ Wednesday 09:00-17:00 ├─ 4. Send trade request │ └─ Propose: My Tuesday for Your Wednesday │ Agent B Reviews: ├─ 1. Receives trade notification ├─ 2. Reviews details: │ ├─ My shift: Wednesday 09:00-17:00 │ ├─ Agent A's shift: Tuesday 09:00-17:00 │ ├─ Hours: Both 8 hours ✓ │ ├─ Skills: Both trained ✓ │ └─ Duration: Both same activity ✓ ├─ 3. Accept or decline │ ├─ Accept: Proceeds to supervisor │ └─ Decline: Agent A notified │ Supervisor Auto-Approval: ├─ 1. System checks approval rules: │ ├─ Both agents eligible ✓ │ ├─ Skill match ✓ │ ├─ Staffing impact acceptable ✓ │ ├─ No rule violations ✓ │ └─ Service level maintained ✓ ├─ 2. Result: ✓ AUTO-APPROVED ├─ 3. Schedules updated: │ ├─ Agent A: Now Tuesday off, Wednesday working │ ├─ Agent B: Now Tuesday working, Wednesday off │ └─ Master Schedule: Updated ├─ 4. Both agents notified │ └─ Approved, effective immediately │ Result: ├─ Trade completed ├─ Master schedule updated ├─ Both agents working new dates └─ Can be reversed if both agree Trade Exceptions Scenario 1: Skills Don't Match Agent A: Support Tier 2 (advanced skills) Agent B: Support Tier 1 (basic skills) Trade Request: A's Tuesday for B's Wednesday ├─ A has: Advanced skills for Tier 2 work ├─ B has: Only basic skills ├─ Tuesday activity: Tier 2 required ├─ B not qualified for Tuesday ├─ Result: ✗ DENIED (skill mismatch) Solution: ├─ Agent B must complete training first ├─ OR Agent A finds Tier 2 agent to trade with └─ OR Supervisor overrides (if business allows) Scenario 2: Staffing Impact Team: Support (5 agents) Tuesday staffing: All 5 present Trade Request: Agent A & B both want to trade out Impact: ├─ Both agents trading simultaneously ├─ Tuesday minimum: 3 agents required ├─ Remaining: 3 agents (meets minimum) ├─ Service Level: Might be at risk ├─ Result: ⚠ PENDING supervisor review Supervisor Options: ├─ Approve (accept slight service risk) ├─ Deny one trade, approve other ├─ Offer alternative dates └─ Request one agent to post-pone Self-Service Portal Agents manage time-off and trades through desktop or mobile portal. Agent Self-Service Features: Time-Off Request: ├─ 1. Select "Time Off" module ├─ 2. Click "Request Time Off" ├─ 3. Choose: │ ├─ Type (Vacation, Sick, etc.) │ ├─ Dates (calendar picker) │ ├─ Notes (optional) │ └─ Submit ├─ 4. See: │ ├─ Time-off balance │ ├─ Blackout dates highlighted │ ├─ Minimum notice requirements │ └─ Approval status └─ 5. Receive notification └─ Auto-approved or pending review Shift Trade Request: ├─ 1. Select "Schedule" module ├─ 2. Click "Find Trades" ├─ 3. View: │ ├─ Own scheduled shifts │ ├─ Available agents to trade with │ ├─ Their shift availability │ └─ Compatibility check (skills, hours) ├─ 4. Select trade │ └─ Propose: "My Tuesday for Your Wednesday" ├─ 5. Request sent │ └─ Other agent notified └─ 6. Await response ├─ Accepted: Goes to supervisor ├─ Denied: Request closed └─ Auto-approved: Notification of approval View Schedules: ├─ Calendar view of all shifts ├─ Color-coded by activity ├─ Mobile-friendly display ├─ Search and filter options └─ Print or export option Mobile Features: ├─ Responsive design ├─ Touch-friendly interface ├─ Push notifications for approvals ├─ Photo ID verification (optional) └─ Works offline (syncs when online) Real-World Examples Example 1: Vacation Request (Auto-Approved) Agent: AGENT_045 Vacation Request: ├─ Type: Vacation ├─ Dates: June 15-22, 2026 (8 days) ├─ Submitted: May 1, 2026 ├─ Notice: 45 days advance ✓ └─ Date: Monday request for Monday-Monday week System Checks: ├─ Vacation balance: 18 days available ✓ ├─ Notice period: 45 days (requirement: 14 days) ✓ ├─ Minimum staffing check: │ ├─ Support team: 8 agents total │ ├─ Currently approved off: 2 agents │ ├─ Daily limit: 4 agents max │ ├─ If approved: 3 agents off (within limit) ✓ │ └─ Minimum on hand: 5 agents ✓ ├─ Blackout dates: No (June 15-22 not blackout) ✓ └─ All conditions: MET ✓ Result: ✓ AUTO-APPROVED Notification: ├─ Agent receives email: "Vacation approved" ├─ Schedule updated: June 15-22 marked as VAC ├─ Balance: 18 - 8 = 10 days remaining └─ Can cancel up to 2 weeks before with notice Example 2: Trade (Manual Approval Due to Staffing) Agents: AGENT_033, AGENT_128 Trade Request: ├─ Agent 033 offers: Friday 09:00-17:00 ├─ Agent 128 offers: Wednesday 09:00-17:00 ├─ Submitted: Thursday (2 days notice) └─ Proposed dates: Next week Rule Checks: ├─ Notice period: 2 days (requirement: 2 weeks) ✗ ├─ Result: DOES NOT MEET AUTO-APPROVAL │ Supervisor Review: ├─ 1. Check request details: │ ├─ Both agents qualified ✓ │ ├─ Same activity (Support) ✓ │ ├─ Same hours (8 hours each) ✓ │ └─ No pending trades ✓ │ ├─ 2. Staffing impact: │ ├─ Support team: 6 agents │ ├─ Friday staffing: Currently 5 agents │ ├─ If trade: Still 5 agents (no change) ✓ │ └─ Service level: Not impacted ✓ │ ├─ 3. Business decision: │ ├─ Short notice: Usually denied │ ├─ But: Staffing impact minimal │ ├─ Decision: APPROVE with exception │ └─ Note: "Last-minute trade due to emergency" │ Result: ✓ MANUALLY APPROVED Outcome: ├─ Both agents notified ├─ Schedule updated ├─ Trade effective next week └─ Documented for future reference Best Practices Time-Off Clear Rules - Simple, documented policies Fair Application - Consistent across team Balance - Support work-life balance while maintaining service Planning - Encourage advance notice Limits - Realistic balance between coverage and flexibility Communication - Transparent approval/denial reasons Shift Trades Flexibility - Enable trades to improve agent satisfaction Safeguards - Protect service level and skill requirements Training - Ensure agents know how to trade Monitoring - Watch for abuse of trade system Documentation - Keep record of all trades Supervisor Review - Spot-check for compliance Interview Cheat Sheet Question Answer What's time-off management? Automated approval of absence requests Auto-approval criteria? Balance, notice, staffing, blackout dates Daily limits function? Prevent over-staffing by limiting absences per day Time-off types? Vacation, sick, personal, unpaid, bereavement, jury duty What's shift trade? Agent-to-agent schedule swap Trade requirements? Skill match, hours match, staffing maintained Trade approval? Auto-approve if eligible, else supervisor review Notice requirement? Varies by type (vacation 2 weeks, sick immediate) Can trades be reversed? Yes, if both agents agree within timeframe Mobile access? Agents can request via mobile app Approval notification? Email/in-system notification immediately What blocks approval? Insufficient balance, short notice, staffing risk Key Takeaways Automation - Approve routine requests automatically Self-Service - Agents manage own time-off/trades Balance - Support flexibility while protecting service Rules - Clear criteria for approval/denial Visibility - Supervisors see impact before approval Fairness - Consistent application of policies Convenience - Mobile and desktop access Work-Life - Enable better work-life balance Efficiency - Reduce administrative burden Service Level - Never compromise customer service Additional Resources Time-Off Management: help.genesys.cloud/articles/time-off-management/ Shift Trades: help.genesys.cloud/articles/shift-trades-overview/ Support: https://support.genesys.com Document Version Info Last Updated: March 2026 Validated: Current with March 2026 release Version: 1.0 Real-Time Adherence Genesys WFM Real-Time Adherence Documentation Study Notes Topic Description Real-Time Adherence Compares actual agent state vs scheduled state Adherence States On-queue, breaks, meetings, training, time-off, etc. Schedule State Groups Maps Genesys states to scheduled activities Compliance Tracking 15, 30, or 60-minute interval checking Reason Codes Aux codes for secondary classifications Thresholds Start Before/After flexibility (minutes) Multi-Channel Track adherence per media type separately Ignore Codes Activities excluded from adherence calculation Navigation Menu → Workforce Management → Adherence OR Supervisor → Adherence → Adherence Monitoring Real-Time Adherence Overview Real-Time Adherence measures how well agents follow their assigned schedules. It compares each agent's actual real-time state with their scheduled state during each monitoring interval, tracking compliance in real-time throughout the day. Adherence monitoring enables supervisors to: Track agent schedule compliance continuously Identify agents not following schedules Investigate reasons for non-compliance Manage exceptions and unplanned activities Generate adherence reports for performance management Calculate adherence metrics for coaching and evaluation Adherence Objectives Schedule Compliance - Ensure agents work as scheduled Service Level Support - Proper staffing for demand Performance Accountability - Track and measure adherence Issue Identification - Find patterns and problems Coaching Opportunity - Address non-compliance with agents Compliance Reporting - Document adherence for audits Key Adherence Concepts Scheduled State vs Actual State: Scheduled (from Master Schedule): ├─ 09:00-12:00: On-Queue Support ├─ 12:00-13:00: Lunch (Meal) ├─ 13:00-16:00: On-Queue Support ├─ 16:00-16:15: Break └─ 16:15-16:30: After Call Work Actual (Real-Time State): ├─ 09:00-09:45: On-Queue ✓ Adherent ├─ 09:45-10:15: Training ✗ Non-adherent (unscheduled) ├─ 10:15-12:30: On-Queue ⚠ Late from training (+45 min) ├─ 12:30-12:50: Lunch ✓ Adherent (within threshold) ├─ 13:00-15:45: On-Queue ✓ Adherent ├─ 15:45-16:10: Meeting ✗ Non-adherent (missing break) └─ 16:10-16:30: After Call Work ✓ Adherent Overall Adherence for Day: ├─ Compliant Time: 6 hours 15 min ├─ Non-Compliant Time: 1 hour 15 min ├─ Total Shift Time: 7.5 hours ├─ Adherence %: (6:15 / 7:30) = 83.3% ⚠ Below goal (90%) Adherence States On-Queue States Agents are available to handle customer interactions: On-Queue Activities: Available/Ready (WaitingForNextCall): ├─ Status: Available for interactions ├─ Duration: Variable (until call arrives) ├─ Adherence: Compliant if scheduled on-queue └─ Example: Agent in queue waiting for next call Connected (Connected): ├─ Status: Currently handling interaction ├─ Duration: Call/chat/email duration ├─ Adherence: Compliant if on-queue scheduled └─ Example: Agent on call with customer On-Hold (Held): ├─ Status: Customer on hold (agent still active) ├─ Duration: Hold time while processing ├─ Adherence: Compliant if on-queue scheduled └─ Example: Agent researching issue, customer on hold Occupied (various): ├─ Status: Agent occupied with interaction ├─ Duration: From connection to end ├─ Adherence: Compliant if on-queue scheduled └─ Example: Agent handling multiple interactions Off-Queue States Agents not available for customer interactions: Off-Queue Activities: After Call Work (ACW/AfterCallWork): ├─ Status: Processing after interaction ends ├─ Duration: Wrap-up work time ├─ Adherence: Depends on scheduling ├─ Scheduled: Yes (included in shift) ├─ Example: Agent logging notes after call Break (Break): ├─ Status: Scheduled break time ├─ Duration: 15-30 minutes typically ├─ Adherence: Compliant if scheduled break ├─ When: Scheduled time window (10-12am) └─ Example: Agent on 15-minute break Meal/Lunch (Meal): ├─ Status: Lunch or meal period ├─ Duration: 30-60 minutes typically ├─ Adherence: Compliant if scheduled lunch ├─ When: Scheduled lunch window (12-1pm) └─ Example: Agent on lunch break Meeting (Meeting): ├─ Status: Team, coaching, or training meeting ├─ Duration: 30-120 minutes ├─ Adherence: Depends on scheduling (can be exception) ├─ Planned: Usually scheduled in advance └─ Example: 1-on-1 coaching session Training (Training): ├─ Status: Formal training or development ├─ Duration: Hours or days ├─ Adherence: Depends on scheduling ├─ Planned: Scheduled in advance └─ Example: Product training course Time Off (TimeOff): ├─ Status: Approved absence ├─ Duration: Full shift or partial ├─ Adherence: Compliant if approved time-off ├─ Types: Vacation, sick, personal, unpaid └─ Example: Approved vacation day Administrative (Administrative): ├─ Status: Admin work, documentation, reports ├─ Duration: 30-60 minutes typically ├─ Adherence: Depends on scheduling ├─ When: Off-peak hours or scheduled └─ Example: Agent doing filing, reports Exception States Unplanned or special situations: Exception Activities: Unavailable (Unavailable): ├─ Status: Temporarily unavailable ├─ Reason: Unplanned absence, technical issue, etc. ├─ Duration: Minutes to hours ├─ Adherence: Non-adherent (unplanned) └─ Example: Agent system down, logged out Coaching/Monitoring (Coaching): ├─ Status: Under supervision or QA review ├─ Duration: Call duration + review ├─ Adherence: Can be scheduled or exception ├─ Purpose: Quality assessment └─ Example: Supervisor listening to call Idle/Not Ready (Idle): ├─ Status: Logged in but not accepting work ├─ Duration: Variable ├─ Adherence: Non-adherent if not scheduled └─ Example: Agent between calls, extended idle Marked Time (Marked): ├─ Status: Special marked period ├─ Duration: 15 minutes to hours ├─ Adherence: Depends on configuration └─ Example: Quality review, special activity Schedule State Groups Schedule State Groups map Genesys real-time states to WFM scheduled states, defining which states are considered compliant with each scheduled activity. Schedule State Group Configuration: Example: Support On-Queue Voice SSG Name: Support_OnQueue_Voice ├─ Media Channel: Voice (or Unspecified) ├─ Associated Real-Time States: │ ├─ WaitingForNextCall │ ├─ Connected │ ├─ Held │ └─ Occupied ├─ Reason Codes (if applicable): │ ├─ No code required │ └─ Maps all calls regardless of type ├─ Adherence Rules: │ ├─ Start Before Threshold: 5 minutes │ ├─ Start After Threshold: 5 minutes │ ├─ End Before Threshold: 5 minutes │ └─ End After Threshold: 5 minutes └─ Result: Agent compliant if on any of these states within thresholds Threshold Configuration Thresholds define flexibility in start/end times: Threshold Scenario 1: Strict (0 minutes) ├─ Scheduled: On-Queue 09:00-13:00 ├─ Start Before: 0 min (must start exactly at 09:00) ├─ Start After: 0 min (cannot be late) ├─ Actual: 09:03 (3 minutes late) └─ Result: ✗ Non-adherent (outside 0-min threshold) Threshold Scenario 2: Flexible (5 minutes) ├─ Scheduled: On-Queue 09:00-13:00 ├─ Start Before: 5 min (can start 08:55) ├─ Start After: 5 min (can start up to 09:05) ├─ Actual: 09:03 (3 minutes late) └─ Result: ✓ Adherent (within 5-min threshold) Threshold Scenario 3: Very Flexible (15 minutes) ├─ Scheduled: On-Queue 09:00-13:00 ├─ Start Before: 15 min (can start 08:45) ├─ Start After: 15 min (can start up to 09:15) ├─ Actual: 09:12 (12 minutes late) └─ Result: ✓ Adherent (within 15-min threshold) Best Practice: ├─ On-Queue activities: 5-10 minutes (reasonable) ├─ Break/Meal: 10-15 minutes (more lenient) ├─ Training: 0-5 minutes (strict) Reason Codes (Auxiliary Codes) Reason codes provide secondary classification for states, tracking why agents are in particular states. Common Reason Codes: Break Reasons: ├─ BRK: Regular break ├─ BRKAT: Break at-will ├─ UNPAID: Unpaid break └─ PAID: Paid break Absence Reasons: ├─ SICK: Sick leave ├─ VACATION: Vacation ├─ PERSONAL: Personal time ├─ UNPAID: Unpaid time off ├─ JURY: Jury duty └─ BEREAVEMENT: Bereavement Activity Reasons: ├─ TRAIN: Training ├─ MEET: Meeting ├─ COACH: Coaching ├─ ADMIN: Administrative work ├─ QA: Quality assurance └─ MGT: Management activity Connection Reasons (Calls): ├─ IN: Inbound call ├─ OUT: Outbound call ├─ TRANSFER: Call transfer ├─ CONFERENCE: Conference call └─ CALLBACK: Scheduled callback Usage: ├─ Mapped to schedule state groups ├─ Provide detail in adherence reports ├─ Track reasons for non-compliance └─ Improve accuracy of adherence calculations Single vs Multi-Channel Adherence Single-Channel Adherence Tracking adherence for agents handling one media type: Single-Channel Configuration: Agent: Support_Agent_001 ├─ Media Type: Voice only ├─ Scheduled: On-Queue Voice 09:00-17:00 ├─ At 10:30: │ ├─ Real-time State: Connected (handling call) │ ├─ Scheduled State: On-Queue Voice │ ├─ Mapping: Connected maps to On-Queue ✓ │ └─ Result: Adherent │ ├─ At 14:00: │ ├─ Real-time State: ACW (after call work) │ ├─ Scheduled State: On-Queue Voice │ ├─ Mapping: ACW maps to On-Queue ✓ │ └─ Result: Adherent │ └─ At 14:45: ├─ Real-time State: Meeting (unscheduled) ├─ Scheduled State: On-Queue Voice ├─ Mapping: Meeting does NOT map to On-Queue ✗ └─ Result: Non-adherent Daily Adherence: 92% (good) Multi-Channel Adherence Tracking adherence when agents handle multiple media types: Multi-Channel Configuration: Agent: Support_Agent_002 ├─ Media Types: Voice + Email (blended) ├─ Schedule: │ ├─ 09:00-13:00: On-Queue (Voice or Email) │ ├─ 13:00-14:00: Lunch │ ├─ 14:00-17:00: On-Queue (Voice or Email) │ └─ 17:00-17:30: After Call Work │ ├─ At 10:30 (Voice call): │ ├─ Voice Channel State: Connected │ ├─ Email Channel State: Idle │ ├─ Voice SSG Check: Connected maps to On-Queue ✓ │ ├─ Email SSG Check: Idle maps to On-Queue? (No) │ └─ Overall: Adherent (on Voice, allowed) │ ├─ At 11:00 (Email work): │ ├─ Voice Channel State: Available │ ├─ Email Channel State: Occupied │ ├─ Voice SSG Check: Available maps to On-Queue ✓ │ ├─ Email SSG Check: Occupied maps to On-Queue ✓ │ └─ Overall: Adherent (both channels compliant) │ └─ At 14:45 (Unscheduled training): ├─ Voice Channel State: Training ├─ Email Channel State: Training ├─ Voice SSG Check: Training ✗ (no mapping) ├─ Email SSG Check: Training ✗ (no mapping) └─ Overall: Non-adherent (both channels fail) Adherence Details: ├─ Voice Adherence: 95% ├─ Email Adherence: 94% └─ Overall Adherence: 92% (both channels must be compliant) Key Difference: Single-Channel: One adherence percentage (simple) Multi-Channel: Separate adherence per channel + overall (complex) Adherence Calculation WFM calculates adherence through a multi-step process: Adherence Calculation Steps: Step 1: Map Agent State + Reason Code ├─ Get agent's real-time state ├─ Get reason code (if any) ├─ Example: WaitingForNextCall + no code └─ Create state mapping for comparison Step 2: Find Compliant Schedule State Groups ├─ Look up all SSGs configured for site ├─ Check which SSGs map to agent's state ├─ Consider media channel if configured ├─ Example: "Support_OnQueue" maps to WaitingForNextCall └─ Create list of matching SSGs Step 3: Get Scheduled States for Agent ├─ Retrieve agent's current schedule for time interval ├─ Example: Scheduled for "On-Queue Voice" 10:00-12:00 ├─ If multiple activities: Pick primary └─ Compare to matched SSGs from Step 2 Step 4: Check Thresholds ├─ Did agent start on time? (Start Before/After) ├─ Did agent end on time? (End Before/After) ├─ Are they within configured thresholds? ├─ Example: Within 5-min threshold = compliant └─ Result: Adherent or Non-adherent Step 5: Calculate Result ├─ If intersection not empty: ✓ Adherent ├─ If intersection empty: ✗ Non-adherent ├─ If multiple channels: All must pass └─ Track non-adherence time in minutes Example Execution: Time: 10:15 ├─ Agent: AGENT_001 ├─ Real-time State: Connected ├─ Reason Code: None ├─ Scheduled: On-Queue Voice (10:00-12:00) ├─ SSG Lookup: Connected maps to "On-Queue" ✓ ├─ Threshold Check: 10:15 is within start threshold ✓ ├─ Result: ✓ ADHERENT ├─ Non-adherence Time: 0 minutes └─ Added to adherence report as compliant minute Adherence Visualization Real-Time Adherence View Example: Agent Name | Status | Activity | Duration | Adherence ────────────────|-----------|-------------|----------|──────────────── AGENT_001 | ✓ Green | Connected | 4:32 | ✓ Adherent AGENT_002 | ✓ Green | Available | 0:15 | ✓ Adherent AGENT_003 | ⚠ Yellow | Break | 18:30 | ⚠ Non-adherent AGENT_004 | ✓ Green | Connected | 3:12 | ✓ Adherent AGENT_005 | 🔴 Red | Meeting | 45:00 | 🔴 Severely non-adherent AGENT_006 | ✓ Green | ACW | 2:05 | ✓ Adherent AGENT_007 | ✓ Green | On-Queue | 1:30 | ✓ Adherent AGENT_008 | ⚠ Yellow | Idle | 12:30 | ⚠ Non-adherent Legend: ✓ Green = Adherent (within schedule) ⚠ Yellow = Non-adherent (off schedule <15 min or 1st alert) 🔴 Red = Severely non-adherent (off schedule >15 min or 2+ alerts) Ignore Codes Certain activities can be marked "Ignore for Adherence," excluding them from adherence calculations. Why Use Ignore Codes: Scenario: Quality Assurance Monitoring Standard: ├─ Agent scheduled: On-Queue 09:00-17:00 ├─ At 10:00: Supervisor monitors agent call (QA) ├─ Agent state: Quality (being monitored) ├─ Non-adherent: Yes (QA not on schedule) ├─ Problem: Impacts adherence score unfairly Solution: Mark QA as "Ignore for Adherence" ├─ Agent scheduled: On-Queue 09:00-17:00 ├─ At 10:00: Supervisor monitors agent call (QA) ├─ Agent state: Quality (being monitored) ├─ Non-adherent: No (QA ignored) ├─ Result: QA time doesn't count against adherence ✓ Example Activities to Ignore: ├─ Quality assurance monitoring ├─ Coaching/training observations ├─ System maintenance time ├─ Emergency situations ├─ Technical outages affecting all agents └─ Special projects or initiatives Configuration: Ignore Codes Setup: Activity Code: QUALITY_MONITOR ├─ Name: Quality Assurance Monitoring ├─ Category: QA ├─ Mark as: Ignore for Adherence ✓ ├─ Schedule State Group: (optional) └─ Result: Doesn't impact adherence % Activity Code: SYSTEM_ISSUE ├─ Name: System Outage ├─ Category: Technical ├─ Mark as: Ignore for Adherence ✓ ├─ Schedule State Group: (optional) └─ Result: Doesn't impact adherence % Usage: ├─ Only for legitimate non-schedule activities ├─ Must be approved by management ├─ Document in policy ├─ Review quarterly for accuracy Real-World Scenarios Scenario 1: Break Threshold Agent: AGENT_033 Schedule: On-Queue 09:00-17:00 Break: Scheduled 10:30-10:45 (15-minute break) Break Threshold: ±10 minutes Actual: ├─ 10:40: Agent takes break (10 min late) ├─ 10:55: Agent returns (back on-queue) ├─ Duration: 15 minutes (correct) ├─ Start: 10:40 (scheduled 10:30, 10 min late) Analysis: ├─ Start Threshold: ±10 minutes ├─ Actual Start: 10:40 (10 min late) ├─ Within Threshold: Yes ✓ └─ Result: Adherent ✓ If Start Threshold was ±5 minutes: ├─ Actual Start: 10:40 (10 min late) ├─ Within Threshold: No ✗ └─ Result: Non-adherent ✗ Lesson: Threshold configuration is critical Scenario 2: Unscheduled Training Agent: AGENT_115 Schedule: On-Queue Support 09:00-13:00 Actual: ├─ 10:00-10:45: On-Queue (compliant) ├─ 10:45-11:30: Training (emergency product training) ├─ 11:30-13:00: On-Queue (compliant) Adherence Impact: ├─ Compliant Time: 2:15 (09:00-10:45 + 11:30-13:00) ├─ Non-Compliant Time: 0:45 (training) ├─ Total Time: 4:00 ├─ Adherence: (2:15 / 4:00) = 56% Non-adherent ✗ Solution Option 1: Schedule Exception ├─ Update master schedule for 10:45-11:30 ├─ Mark as "Training - Exception" ├─ Configure SSG to include Training ├─ Result: Would be adherent ✓ Solution Option 2: Ignore Code ├─ Mark "Emergency Training" as Ignore ├─ When agent in training: Doesn't count ├─ Result: Adherence = 100% (training ignored) ✓ Solution Option 3: Coaching ├─ Supervisor counsels agent on schedule ├─ Reinforce adherence importance ├─ Coach on better timing for breaks └─ Plan to avoid future non-adherence Best Practice: Combination ├─ Use Solution 1 (schedule exception) immediately ├─ Use Solution 3 (coaching) to prevent future └─ Use Solution 2 (ignore) only for legitimate reasons Best Practices Adherence Configuration Clear Rules - Unambiguous state mappings Realistic Thresholds - Balance flexibility with accountability Simple Codes - Easy for agents to understand Documentation - Maintain mapping diagrams Testing - Validate configuration in test environment Training - Teach agents adherence expectations Monitoring Regular Review - Check adherence daily Trend Analysis - Look for patterns Investigation - Ask "why?" for outliers Communication - Share results with team Positive Coaching - Praise improvements Accountability - Address chronic issues Coaching Empathy - Understand barriers to adherence Clarity - Explain why adherence matters Support - Help with scheduling challenges Consequences - Clear performance expectations Recognition - Celebrate good adherence Follow-up - Track improvements over time Interview Cheat Sheet Question Answer What's real-time adherence? Compares actual agent state to scheduled state How often monitored? 15, 30, or 60-minute intervals (configurable) Yellow status meaning? Non-adherent or approaching non-adherence Red status meaning? Severely non-adherent (significantly off schedule) What's threshold? Flexibility in start/end time (e.g., ±5 min) Adherence calculation? Map real-time state to schedule state, check threshold Reason codes? Aux codes for secondary classification Schedule state group? Maps Genesys states to scheduled activities Multi-channel adherence? Track adherence per media type separately What's ignore code? Activity excluded from adherence calculation Common non-adherence? Unscheduled breaks, late returns, unplanned training How improve adherence? Clear rules, thresholds, coaching, support Impacts of poor adherence? Service level failure, staffing gaps, customer impact Exception handling? Can be scheduled or handled with ignore codes Reporting adherence? Daily/weekly reports by agent/team/site Key Takeaways Continuous Tracking - Real-time monitoring throughout day State Mapping - Clear mapping of actual to scheduled states Threshold Flexibility - Balance accountability with realism Multi-Channel - Support for blended agent work Reason Codes - Detailed tracking of why agents are off-schedule Ignore Codes - Exclude legitimate exceptions Visualization - Color-coding for quick status assessment Coaching Opportunity - Address issues with support and empathy Service Impact - Poor adherence damages service levels Policy Enforcement - Consistent application of rules Additional Resources Official Documentation Adherence: all.docs.genesys.com/PEC-WFM/Current/Supervisor/AdherenceMdl Schedule State Groups: all.docs.genesys.com/PEC-WFM/Current/Administrator/CfgAdhRls Adherence Calculation: docs.genesys.com/Documentation/WM/latest/SHelp/AdhrCalcs Support & Training Genesys University: genesys.com/training Community Forums: https://community.genesys.com Technical Support: https://support.genesys.com Document Version Info Last Updated: March 2026 Source: Genesys WFM Official Documentation Validated: Current with January-March 2026 releases Version: 1.0 Service Goals & Planning Groups Genesys WFM Service Goals & Planning Groups Documentation Study Notes Topic Description Service Goals Define SL, ASA, abandon rate targets Service Level % of interactions answered within target time ASA Average Speed to Answer in seconds Abandon Rate % of offered interactions not answered Planning Groups Organize workload by media type and route Media Types Voice, email, chat, callback, messaging, workitems Goal Templates Reusable at business unit level Staffing Impact Goals drive forecasting and scheduling Navigation Admin → Workforce Management → Service Goals OR Admin → Workforce Management → Planning Groups Service Goals Overview Service Goals define target performance metrics for contact center operations. They specify acceptable levels for Service Level, Average Speed to Answer, and Abandon Rate, providing the basis for staffing forecasts and schedule creation. Goal Components Service Goal: Premium Support Voice Performance Targets: ├─ Service Level: 80% in 20 seconds │ └─ 80% of calls answered within 20 seconds ├─ Average Speed to Answer: 18 seconds average │ └─ All calls average 18 second wait ├─ Abandon Rate: 5% maximum │ └─ Maximum 5% of calls not answered Definition: ├─ Media Type: Voice (inbound) ├─ Planning Group: Support Queue 001 ├─ Time Period: Monday-Friday, 08:00-18:00 ├─ Applies To: All support agents └─ Level: Business Unit level Key Metrics Service Level (SL) Definition: Percentage of calls answered within target time Calculation: ├─ Offered: 1,000 calls ├─ Answered ≤20 seconds: 800 calls ├─ Answered >20 seconds: 200 calls ├─ SL = (800/1,000) × 100 = 80% Benchmark: ├─ Excellent: 90%+ ├─ Good: 80-90% ├─ Acceptable: 75-80% ├─ Poor: <75% Average Speed to Answer (ASA) Definition: Average wait time before agent answer Calculation: ├─ Call 1 wait: 12 seconds ├─ Call 2 wait: 25 seconds ├─ Call 3 wait: 18 seconds ├─ Average: (12+25+18)/3 = 18.3 seconds Benchmark: ├─ Excellent: <10 seconds ├─ Good: 10-20 seconds ├─ Acceptable: 20-30 seconds ├─ Poor: >30 seconds Abandon Rate Definition: Percentage of calls not answered Calculation: ├─ Offered: 1,000 calls ├─ Answered: 950 calls ├─ Abandoned: 50 calls ├─ Abandon Rate = (50/1,000) × 100 = 5% Benchmark: ├─ Excellent: <3% ├─ Good: 3-5% ├─ Acceptable: 5-8% ├─ Poor: >8% Goal Templates Service Goal Templates are reusable at the Business Unit level, providing standard goals for different work types. Template Library: Template 1: Premium Support (Voice) ├─ Service Level: 80% in 20 seconds ├─ ASA: 18 seconds ├─ Abandon Rate: 5% ├─ Use Case: VIP customers, escalations └─ Staffing Impact: High (expensive) Template 2: Standard Support (Voice) ├─ Service Level: 75% in 30 seconds ├─ ASA: 25 seconds ├─ Abandon Rate: 8% ├─ Use Case: Typical support queue └─ Staffing Impact: Medium Template 3: Basic Support (Voice) ├─ Service Level: 70% in 60 seconds ├─ ASA: 45 seconds ├─ Abandon Rate: 10% ├─ Use Case: IVR escalations, callbacks └─ Staffing Impact: Low (cost efficient) Template 4: Email Support ├─ Service Level: 95% in 4 hours ├─ ASA: 2 hours (median) ├─ Abandon Rate: N/A ├─ Use Case: Email queue └─ Staffing Impact: Different (async work) Template 5: Chat Support ├─ Service Level: 85% in 30 seconds ├─ ASA: 20 seconds ├─ Abandon Rate: 7% ├─ Use Case: Real-time chat └─ Staffing Impact: Medium-High Template 6: Callback ├─ Service Level: 90% within 1 hour ├─ ASA: N/A (scheduled) ├─ Abandon Rate: <2% ├─ Use Case: Scheduled callbacks └─ Staffing Impact: Planned Planning Groups Overview Planning Groups organize workloads by media type and route path, enabling precise forecasting and scheduling for different work types. Planning Group Structure Planning Group: Support - Voice Queue 001 Organization: ├─ Name: Support - Voice Queue 001 ├─ Business Unit: Support Operations ├─ Media Type: Voice (Inbound) ├─ Queue/Route: Support_Queue_001 ├─ Service Goal: Premium Support ├─ Staffing Group: Support_Agents_Tier_2 Configuration: ├─ Agent Skills Required: Support Level 2+ ├─ Agents Available: 50 ├─ Agent Availability: Scheduled ├─ Activity Code: SUPPORT_VOICE └─ Multi-Activity: Can blend with other activities Scheduling: ├─ Work Plans: Standard Full-Time, Part-Time Flex ├─ Hours Available: 09:00-17:00 Mon-Fri ├─ Staffing Model: Load-based (forecast-driven) └─ Peak Coverage: 10:00-14:00 (highest demand) Multi-Media Planning Groups Planning Group 1: Blended Support (Voice + Email) Media Types: ├─ Voice (Inbound) - 60% of time ├─ Email (Responses) - 40% of time ├─ Single planning group spans both Service Goals: ├─ Voice: 80% SL, 20s ASA ├─ Email: 95% 4-hour response └─ Blended staffing meets both Agent Assignment: ├─ Agents skilled in both voice and email ├─ Can switch between during shift ├─ Occupancy: Total work load └─ Adherence: Tracks combined Benefits: ├─ Flexibility (switch between work types) ├─ Efficiency (right sizing) ├─ Cost effective (fewer agents needed) └─ Better work variety Example: ├─ Agent on call: 5 minutes (voice) ├─ Agent responds to emails: 2 minutes each (email) ├─ Total work + availability = occupancy Planning Group Creation Checklist Step 1: Define Fundamentals ☐ Planning Group Name ☐ Business Unit ☐ Media Type(s) ☐ Queue/Route Assignment ☐ Description & Purpose Step 2: Associate Service Goals ☐ Service Level % ☐ ASA Target ☐ Abandon Rate ☐ Performance Interval Step 3: Assign Resources ☐ Select Staffing Group ☐ Define Skill Requirements ☐ Specify Agent Availability ☐ Configure Blending (if multi-media) Step 4: Configure Scheduling ☐ Work Plans ☐ Available Hours ☐ Days Operational ☐ Staffing Flexibility Step 5: Test & Activate ☐ Validate skill assignments ☐ Test with sample forecast ☐ Confirm staffing calculations ☐ Activate for use Goal Setting Best Practices SL Target Selection: Considersations: ├─ Industry Standard: 80% for voice typical ├─ Customer Expectations: What do customers expect? ├─ Staffing Cost: Higher SL = more agents ├─ Competition: What competitors offer ├─ Current Performance: Realistic improvement path └─ Business Objectives: Strategic alignment Decision Matrix: Volume Level | Industry SL | Typical SL | Cost Impact ─────────────|──────────── |────────── |──────────── Low (<500/day)| 80% | 85-90% | - Medium (500-2k)| 80% | 80-85% | Baseline High (2k+) | 75-80% | 75-80% | High (many agents) Recommendation: ├─ Start with 80% in 20 seconds (industry standard) ├─ Adjust based on customer feedback ├─ Increase gradually as team improves ├─ Only decrease if cost absolutely prohibitive └─ Communicate goals to team Real-World Examples Example 1: Single Planning Group (Voice Only) Organization: Small Contact Center Team: Support Only Volume: 5,000 calls/day Planning Group Setup: ├─ Name: Support - Voice Queue ├─ Media Type: Voice Inbound ├─ Queue: Support_Main ├─ Service Goal: Standard Support │ ├─ SL: 75% in 30 seconds │ ├─ ASA: 25 seconds │ └─ Abandon: 8% ├─ Staffing Group: Support Agents (40 total) └─ Scheduling: Load-based with forecast Impact: ├─ Single forecast for all support calls ├─ All agents cross-trained in support ├─ Flexible scheduling across team ├─ Straightforward staffing calculations └─ 5,000 calls ÷ 40 agents = 125 calls/agent/day Example 2: Multi-Planning Group (Segmented) Organization: Enterprise Contact Center Team: Support (Tiered) + Sales Volume: 50,000 calls/day Planning Group 1: Support Tier 1 (Inbound Voice) ├─ SL: 70% in 60 seconds (lower priority) ├─ Agents: 100 ├─ Volume: 20,000 calls/day └─ Complex calls escalated to Tier 2 Planning Group 2: Support Tier 2 (Inbound Voice) ├─ SL: 85% in 20 seconds (VIP/escalations) ├─ Agents: 40 ├─ Volume: 10,000 calls/day (escalated + complex) └─ Expert agents with higher skill Planning Group 3: Support - Email ├─ SL: 95% in 4 hours ├─ Agents: 25 ├─ Volume: 8,000 emails/day └─ Async work, different staffing model Planning Group 4: Sales - Outbound ├─ Outbound calls ├─ Agents: 30 ├─ Volume: 3,000 calls/day (dialing ratio) └─ Non-traditional SL (contact rate goals) Planning Group 5: Blended - Email + Chat ├─ Email + Chat handling ├─ Agents: 20 ├─ Volume: 9,000 interactions/day └─ Flexible blended staffing Total: ├─ Planning Groups: 5 ├─ Agents: 215 total ├─ Calls/Emails/Chats: 50,000 total daily └─ Complexity: High (requires separate forecasts for each) Benefits: ├─ Skill segmentation (Tier 1 vs 2) ├─ Appropriate goals per tier (70% vs 85%) ├─ Specialized handling (email vs voice) ├─ Cost optimization (right agents for right work) └─ Performance clarity (each group tracked separately) Example 3: Multi-Channel Blended Organization: Financial Services Team: Support (Multi-Channel) Channels: Voice, Email, Chat Planning Group: Support - Omnichannel ├─ Media Types: Voice + Email + Chat ├─ Volume Mix: │ ├─ Voice: 50% (5,000 calls/day) │ ├─ Email: 35% (3,500 emails/day) │ └─ Chat: 15% (1,500 chats/day) │ ├─ Service Goals: │ ├─ Voice: 80% SL, 20s ASA, 5% abandon │ ├─ Email: 95% in 4 hours response │ └─ Chat: 85% SL, 25s response │ ├─ Staffing: 50 agents │ ├─ All trained in voice │ ├─ Most trained in email │ └─ Some trained in chat │ ├─ Scheduling: │ ├─ Agents switch between channels during day │ ├─ Chat staffing peak 10-14:00 │ ├─ Email staffing even throughout day │ └─ Voice staffing follows volume curve │ └─ Benefits: ├─ Flexibility (agents move where needed) ├─ Efficiency (prevent over-staffing one channel) ├─ Agent variety (less repetitive) └─ Cost effective (fewer total agents needed) Staffing Calculation: ├─ Voice 5,000 calls: Need ~12-15 agents ├─ Email 3,500/day: Need ~8-10 agents ├─ Chat 1,500: Need ~4-6 agents ├─ If separate: ~25-30 agents total needed ├─ If blended: ~18-20 agents sufficient └─ Savings: ~25% headcount reduction through blending Service Goal Alignment Cascading Goals: Business Strategy ├─ Customer experience excellence ├─ 95% customer satisfaction target └─ Competitive advantage Operations Goals ├─ Support SL: 80% ├─ Sales SL: 75% ├─ Email Response: 4 hours └─ Chat Response: 25 seconds Team Goals ├─ Agent individual targets ├─ Team performance tracking ├─ Coaching opportunities └─ Recognition for achievement Individual Goals ├─ Adherence to schedule ├─ Quality metrics ├─ Compliance └─ Development Measurement & Feedback ├─ Daily intraday metrics ├─ Weekly/monthly reports ├─ Coaching sessions ├─ Performance reviews └─ Adjustments to goals Best Practices Goal Setting Realistic - Achievable with reasonable staffing Challenging - Push for improvement Industry Aligned - Competitive with peers Communicated - Clear to all agents Measured - Tracked consistently Flexible - Adjust based on business changes Planning Group Design Clarity - Clear purpose and scope Skill Alignment - Match agents to requirements Balance - Not too granular, not too broad Scalability - Grows with business Maintenance - Regular updates Documentation - Maintain mappings Interview Cheat Sheet Question Answer What's service goal? Target metrics for SL, ASA, abandon rate What's SL? % of calls answered within target time What's ASA? Average wait time before answer Typical SL? 80% in 20 seconds (industry standard) What's planning group? Workload organized by media type and route Planning group purpose? Separate forecasting and scheduling How many planning groups? 1-5 typical (depends on complexity) Media types? Voice, email, chat, callback, messaging, workitems Goal templates? Reusable at business unit level Why segment? Cost optimization, skill alignment, clear metrics Multi-channel? Agents handle multiple media types Benefits blending? Flexibility, efficiency, cost savings SL formula? (Answered within target) / Total offered × 100 Key Takeaways Goals Drive Staffing - SL goals determine forecast and schedules Segment Wisely - Use planning groups for precision Templates - Reusable at BU level for consistency Realistic - Achievable goals drive motivation Communicate - Clear goals to all staff Track - Measure and report regularly Adjust - Modify as business changes Multi-Channel - Blend for efficiency Industry Standard - 80% SL in 20 seconds typical Measurement - Daily tracking drives improvement Document Version Info Last Updated: March 2026 Validated: Current with March 2026 release Version: 1.0 Capacity Planning Genesys WFM Capacity Planning Documentation Study Notes Topic Description Capacity Planning Long-range 2-year staffing forecasts and hiring needs Hiring Plans Project required agents based on volume growth Shrinkage Modeling Account for breaks, absences, training, meetings Attrition Planning Factor in turnover rates (typical 10-15% annual) FTE Calculation Full-time equivalent staffing requirements What-If Scenarios Model multiple growth/demand scenarios Multi-Skill Planning Plan for multiple planning groups and skill sets Business Unit Level Create capacity plans per business unit Navigation Admin → Workforce Management → Capacity Planning OR Menu → Workforce Management → Planning → Capacity Plans Capacity Planning Overview Capacity Planning enables organizations to forecast long-range (up to 2 years) staffing needs based on projected demand, anticipated shrinkage, and expected attrition. It answers the strategic question: "How many agents do we need to hire in the next 6-12-24 months?" Capacity Planning functions: Project future staffing requirements Model growth scenarios Account for turnover and attrition Plan hiring timelines Determine training needs Support budget planning Enable proactive recruitment Capacity Planning Process Capacity Planning Workflow: Input Phase: ├─ Volume Forecast (2 years forward) ├─ Service Level Goals ├─ Average Handle Time (AHT) ├─ Shrinkage Rate (% unavailable) ├─ Attrition Rate (% turnover) └─ FTE Targets (if applicable) Processing: ├─ Calculate staffing needed by period ├─ Apply shrinkage adjustments ├─ Apply attrition (turnover) adjustments ├─ Factor in training ramp-up time └─ Model multiple scenarios Output Phase: ├─ Hiring requirements by month ├─ Training schedule ├─ Budget projections ├─ Risk identification ├─ Recommendation scenarios └─ Long-term staffing plan Usage: ├─ HR coordinates recruitment ├─ Budget allocates hiring resources ├─ Training schedules onboarding ├─ Leadership makes staffing decisions └─ Ongoing refinement based on actuals Key Concepts Staffing Calculation Formula Basic Staffing Calculation: Staffing Required = (Volume × AHT) / Available Hours Example: ├─ Volume: 5,000 calls/day ├─ AHT: 300 seconds (5 minutes) ├─ Target SL: 80% in 20 seconds │ └─ Staffing calculation: (5,000 × 300) / 3,600 = 416.67 agent-hours needed │ ├─ Workday: 8 hours (28,800 seconds available per agent) ├─ Agents needed: 416.67 ÷ 8 = 52.08 agents └─ Rounded: 52-53 agents minimum for stated conditions Advanced Calculation (with shrinkage): Staffing Required = ((Volume × AHT) / Available Hours) × (1 / (1 - Shrinkage Rate)) With 30% Shrinkage: ├─ Base staffing: 52 agents ├─ Shrinkage factor: 1 / (1 - 0.30) = 1.43 ├─ Total staffing needed: 52 × 1.43 = 74.36 agents └─ Actual: 75 agents (accounting for shrinkage) Shrinkage Shrinkage represents the percentage of time agents are unavailable for customer work. Shrinkage Components (Typical 25-35%): Paid Time Off: ├─ Vacation: 2.5% (20 days ÷ 260 work days) ├─ Sick Leave: 1.5% (12 days ÷ 260) ├─ Personal Time: 1% (8 days ÷ 260) └─ Subtotal: ~5% Scheduled Non-Work: ├─ Breaks: 8% (2 × 15 min breaks per 8-hr shift) ├─ Lunch: 12% (1 hour per 8-hr shift) └─ Subtotal: ~20% Other Non-Productive: ├─ Meetings: 2% ├─ Training: 2% ├─ Administrative: 1% ├─ Unplanned absences: 2% └─ Subtotal: ~7% Total Shrinkage: ~32% (typical) This means: ├─ 8-hour shift = 5.44 hours available for customer work ├─ OR you need 1.47 agents for every 1 customer-facing agent needed Attrition (Turnover) Attrition is the rate at which employees leave the organization. Typical Contact Center Attrition: 10-20% annually Attrition Impacts: Monthly Impact Example (100 agents, 15% annual): ├─ 15% ÷ 12 = 1.25 agents/month turnover ├─ Planning for 12 months: 15 agents departing ├─ To maintain 100 agents: Must hire 15 new agents With Growth (5% growth + 15% turnover): ├─ Current: 100 agents ├─ Target: 105 agents (5% growth) ├─ Turnover expected: 15 agents ├─ Total to hire: 105 - 100 + 15 = 20 agents ├─ Hiring rate: 1.67 agents/month └─ Timeline: 12 months to recruit and train Factors Affecting Attrition: ├─ Compensation levels ├─ Work environment quality ├─ Career development opportunities ├─ Schedule flexibility ├─ Work-life balance ├─ Management quality ├─ Job satisfaction └─ Industry benchmarks Capacity Plan Creation Creating a Capacity Plan Step 1: Define Planning Parameters Period Definition: ├─ Start Date: January 1, 2026 ├─ End Date: December 31, 2027 (24 months) ├─ Intervals: Monthly └─ Business Unit: Select target BU Step 2: Input Volume Forecast Volume Projections: ├─ Month 1: 5,000 calls/day (baseline) ├─ Month 2: 5,100 calls/day (+2%) ├─ Month 3: 5,200 calls/day (+4% YoY) ├─ ... (continue for 24 months) └─ Can import from existing forecasts or enter manually Step 3: Configure Service Levels Service Goals: ├─ Service Level: 80% in 20 seconds ├─ ASA: 18 seconds ├─ Abandon Rate: 5% ├─ AHT: 300 seconds (5 minutes) └─ Apply to all planning groups or specific ones Step 4: Set Staffing Parameters Shrinkage & Attrition: ├─ Shrinkage Rate: 30% ├─ Attrition Rate: 15% annually (1.25% monthly) ├─ Training Ramp-Up: 60% productivity week 1, 80% week 2, 100% week 3 ├─ Training Duration: 2 weeks └─ Seasonal Adjustments: Higher in Q4, lower in Q1 Step 5: Configure Planning Groups Multi-Skill Planning: ├─ Planning Group 1: Voice Support (60% of volume) ├─ Planning Group 2: Email Support (40% of volume) ├─ Planning Group 3: Chat (optional blended group) └─ Staffing Groups: Can map multiple skills to handle Step 6: Review Calculations System Calculates: ├─ Monthly staffing requirements ├─ Hiring needs accounting for attrition ├─ Training schedule and capacity ├─ Budget impact ├─ FTE projections ├─ Multi-skill distribution └─ Over/under-staffing risks Step 7: Scenario Analysis Create What-If Scenarios: ├─ Copy existing plan ├─ Adjust variables: │ ├─ Modify volume forecast (+/- %) │ ├─ Adjust SL targets │ ├─ Change attrition assumptions │ └─ Update shrinkage rates ├─ Compare scenarios └─ Select recommended plan Real-World Examples Example 1: Growth Planning (30% Growth Over 12 Months) Current State (Jan 2026): ├─ Headcount: 100 agents ├─ Daily Volume: 5,000 calls ├─ SL: 80% ├─ Annual Attrition: 15% Growth Forecast: ├─ Q1: +5% volume (5,250 calls) ├─ Q2: +10% volume (5,500 calls) ├─ Q3: +20% volume (6,000 calls) ├─ Q4: +30% volume (6,500 calls) Capacity Plan Calculation: Month 1 (Jan): ├─ Volume: 5,000 calls/day ├─ Staffing needed: 75 (including 30% shrinkage) ├─ Current staff: 100 ├─ Status: Over-staffed (+25) Month 3 (Mar): ├─ Volume: 5,250 calls/day (+5%) ├─ Staffing needed: 79 ├─ Attrition: 1.25 agents/month = 3.75 to date ├─ Current staff: 96 ├─ Status: Over-staffed, but shrinking Month 6 (Jun): ├─ Volume: 5,500 calls/day (+10%) ├─ Staffing needed: 83 ├─ Attrition YTD: 7.5 agents ├─ Current staff: 92 ├─ Status: At capacity Month 12 (Dec): ├─ Volume: 6,500 calls/day (+30%) ├─ Staffing needed: 98 ├─ Attrition YTD: 15 agents ├─ Total to hire: (98 - 100) + 15 = +13 agents ├─ Current staff with hires: 113 └─ Status: Meeting demand Hiring Plan: ├─ Month 1-2: No hiring (use excess) ├─ Month 3-4: Begin recruiting (start with 2-3/month) ├─ Month 5-8: Accelerate hiring (5/month) ├─ Month 9-12: Intensive hiring (4/month) ├─ Total new hires: 28 agents ├─ Training cohorts: 4 groups of 7 agents ├─ Training timeline: 2-week program per cohort Budget Impact: ├─ Current salary cost: $4.8M/year (100 × $48k) ├─ Additional 13 agents: +$624K/year ├─ Training cost: 28 × $2,000 = $56K ├─ Equipment/setup: 28 × $500 = $14K └─ Total additional cost: ~$694K over 12 months Example 2: Scenario Planning (High vs Low Growth) Base Scenario: 15% Growth ├─ Jan: 5,000 calls/day ├─ Dec: 5,750 calls/day ├─ Staffing Jan: 75 agents ├─ Staffing Dec: 87 agents ├─ Hiring needed: 15 agents (net of attrition) └─ Annual cost increase: $720K Aggressive Scenario: 25% Growth ├─ Jan: 5,000 calls/day ├─ Dec: 6,250 calls/day ├─ Staffing Jan: 75 agents ├─ Staffing Dec: 94 agents ├─ Hiring needed: 22 agents (net of attrition) └─ Annual cost increase: $1,056K Conservative Scenario: 5% Growth ├─ Jan: 5,000 calls/day ├─ Dec: 5,250 calls/day ├─ Staffing Jan: 75 agents ├─ Staffing Dec: 79 agents ├─ Hiring needed: 8 agents (net of attrition) └─ Annual cost increase: $384K Comparison: ├─ Cost Range: $384K to $1,056K ├─ Headcount Range: 8 to 22 new hires ├─ Timing Impact: Early hires for high growth, delayed for conservative └─ Recommendation: Plan for base case, stay flexible for scenarios Example 3: Multi-Skill Planning Scenario: Voice + Email Blended Team Planning Group Distribution: ├─ Voice Support: 60% of workload ├─ Email Support: 40% of workload └─ Single agent team handling both Staffing Calculation: Voice Staffing: ├─ Volume: 3,000 calls/day ├─ AHT: 300 seconds ├─ Base: 45 agents (with shrinkage) Email Staffing: ├─ Volume: 2,000 emails/day ├─ AHT: 600 seconds ├─ Base: 30 agents (with shrinkage) Blended Approach (Single Planning Group): ├─ Combined workload: 45 + 30 = 75 agent-hours ├─ Blended team: 60 agents (20% efficiency gain) ├─ Staffing needed: 60 agents (vs 75 separate) ├─ Savings: 15 agents / $720K annually Requirements: ├─ All 60 agents trained in voice ├─ All 60 agents trained in email ├─ Ability to switch between during shift ├─ Proper activity coding for tracking ├─ Balanced workload distribution └─ Adequate systems for both channels Benefits: ├─ Cost savings: 20% staffing reduction ├─ Flexibility: Can shift agents to high-demand channel ├─ Agent satisfaction: Work variety ├─ Efficiency: Prevents over-staffing one channel └─ Resilience: Handle channel imbalances Best Practices Forecasting Accuracy Use Historical Data - ABM requires 90+ days minimum Account for Seasonality - Q4 peaks, Q1 valleys typical Plan for Growth - Include business growth plans Conservative Approach - Better to over-hire than under-staff Ongoing Refinement - Adjust monthly based on actuals Scenario Planning - Model multiple growth scenarios Hiring & Training Lead Time - Start recruiting 3-6 months before need Batch Training - Group new hires into cohorts Ramp-Up Plan - Account for 2-4 week productivity ramp Retention Focus - Lower attrition through engagement Budget Planning - Include hiring and training costs Skill Planning - Ensure multi-skill coverage Staffing Decisions Monitor Actuals - Track actual vs planned monthly Adjust Early - Don't wait for crisis to hire Communicate - Keep HR and leadership informed Flexibility - Plan for contingencies Cost Control - Balance service level with cost Continuous Improvement - Review and refine quarterly Interview Cheat Sheet Question Answer What's capacity planning? Long-range (2-year) workforce staffing forecasts Why capacity planning? Project hiring needs months in advance Key inputs? Volume forecast, SL goals, AHT, shrinkage, attrition What's shrinkage? % unavailable time (breaks, meetings, training ~30%) What's attrition? Employee turnover rate (typical 10-20% annually) How calculate staffing? (Volume × AHT) / Available Hrs × (1 / (1 - Shrinkage)) Planning horizon? Up to 2 years forward FTE? Full-time equivalent (one agent = 1 FTE) Multi-skill planning? Plan for agents handling multiple channels What-if scenarios? Model high/low growth alternatives Training ramp-up? New agents reach 100% productivity over 2-4 weeks Hiring timeline? Start recruiting 3-6 months before need Cost calculation? Salary + benefits + training + equipment Over-staffing issue? Wasted labor cost, low occupancy Under-staffing issue? Service level failure, agent burnout Key Takeaways Strategic Planning - Look ahead 2 years for staffing Growth Alignment - Match hiring to business growth Turnover Factor - Account for normal attrition rates Shrinkage Modeling - Realistic availability calculations FTE Tracking - Monitor full-time equivalent staffing Scenario Flexibility - Plan for multiple growth paths Lead Time - Start recruiting before you need agents Cost Planning - Budget hiring and training expenses Multi-Skill - Plan for blended team capabilities Continuous Refinement - Adjust monthly based on actuals Additional Resources Official Documentation Capacity Plans: help.mypurecloud.com/articles/capacity-plans-overview/ Planning: help.genesys.cloud/articles/plan-workforce-management/ Staffing: help.genesys.cloud/articles/about-workforce-management/ Support & Training Genesys University: genesys.com/training Community Forums: https://community.genesys.com Technical Support: https://support.genesys.com Document Version Info Last Updated: March 2026 Validated: Current with March 2026 release Version: 1.0 Agent Self-Service Genesys WFM Agent Self-Service Documentation Study Notes Topic Description Agent Portal Web-based access to schedules, time-off, trades Mobile App iOS/Android for on-the-go schedule management Desktop Features View schedules, request time-off, trade shifts Mobile Features Push notifications, offline access, touch-friendly Schedule View Calendar and detailed views of shifts Preferences Availability, shift preferences, communication settings Reporting Personal adherence, performance history Flexibility Agent control over schedules within policy Navigation Agent Portal: Agent Self-Service URL (desktop) Mobile App: Genesys Tempo (iOS/Android) Agent Self-Service Overview Agent Self-Service empowers employees to manage their work schedules and make work-life balance decisions within company policies. Available on desktop web portal and mobile apps (iOS/Android), self-service reduces administrative burden on supervisors while giving agents more control over their schedules. Agent Self-Service functions: View current and future schedules Request time-off with automatic approvals Propose and accept shift trades Set work preferences and availability Submit adherence explanations Track personal performance metrics Manage personal settings and contact info Receive schedule notifications Self-Service Benefits For Agents: ├─ Anytime access (24/7 from home/mobile) ├─ Flexibility to trade shifts easily ├─ Control over scheduling preferences ├─ Transparency in time-off balances ├─ Fast approvals (often automatic) ├─ Mobile convenience ├─ Peace of mind with visibility └─ Reduced interactions with supervisor For Supervisors: ├─ Reduced administrative work ├─ Faster request processing ├─ Better visibility of changes ├─ Fewer phone inquiries ├─ More time for coaching ├─ Accurate preference tracking ├─ Better agent satisfaction └─ Improved team morale For Organization: ├─ Improved agent satisfaction ├─ Better work-life balance perception ├─ Lower turnover risk ├─ Operational efficiency ├─ Cost savings (less admin time) ├─ Data accuracy ├─ Competitive advantage in hiring └─ Agility in staffing changes Desktop Web Portal The desktop Agent Self-Service Portal is accessed through a web browser, providing full functionality on any computer with internet access. Home Dashboard Agent Portal Home: Welcome Header: ├─ Agent Name: John Smith ├─ Site: New York - Support Team ├─ Next Shift: Tuesday 09:00-17:00 (2 days away) └─ Status: On Schedule Quick Actions (Buttons): ├─ View Full Schedule ├─ Request Time Off ├─ Find Shift Trades ├─ See My Performance ├─ Manage Preferences └─ Contact Manager Next Shift Details: ├─ Start Time: 09:00 ├─ End Time: 17:00 ├─ Activity: Support Voice ├─ Location: Manhattan Office ├─ Duration: 8 hours └─ Status: Confirmed Recent Notifications: ├─ "Schedule updated for next week" ├─ "Time-off request approved" ├─ "John accepted your trade request" └─ "Team meeting rescheduled" Schedule View Features My Schedule - Calendar View: Calendar Display: ├─ 4-week view (customizable) ├─ Color-coded by activity: │ ├─ Blue: Voice Support │ ├─ Green: Email Support │ ├─ Yellow: Training │ ├─ Gray: Time Off │ ├─ Red: Holiday │ └─ White: Day Off ├─ Click date for details ├─ Drag to copy/move └─ Export to calendar app Shift Details (Click Any Shift): ├─ Date: Tuesday, March 18, 2026 ├─ Start: 09:00 | End: 17:00 ├─ Duration: 8 hours 0 minutes ├─ Activity: Support Voice ├─ Queue: Support_Queue_001 ├─ Break 1: 10:30-10:45 (15 min) ├─ Lunch: 12:00-13:00 (1 hour) ├─ Break 2: 14:30-14:45 (15 min) ├─ Location: Office ├─ Manager: Jane Doe └─ Notes: Regular schedule Historical Schedule: ├─ View past weeks (up to 12 months) ├─ Review actual vs scheduled ├─ Track adherence history └─ Understand patterns Future Schedule: ├─ View up to 26 weeks forward ├─ Plan ahead for preferences ├─ Identify conflicts early ├─ See blackout dates └─ Plan time-off accordingly Time-Off Management Request Time Off: Simple Workflow: 1. Click "Request Time Off" 2. Select Type: ├─ Vacation ├─ Sick Leave ├─ Personal Time ├─ Unpaid └─ Other 3. Select Dates (Calendar Picker): ├─ Click start date ├─ Click end date ├─ See selected dates highlighted └─ Show conflicting requests 4. Add Notes (Optional): └─ "Family visit" or "Medical appointment" 5. Review & Submit: ├─ Confirm dates ├─ See balance impact ├─ Check approval likelihood └─ Submit request View Status: ├─ Pending Requests: │ ├─ March 20-21 (Vacation) - PENDING │ ├─ Submitted: 3 days ago │ ├─ Required days notice: Met (14 days) │ └─ Status: Awaiting manager review │ ├─ Approved: │ ├─ April 5-10 (Vacation) - APPROVED │ ├─ June 15 (Personal) - APPROVED │ └─ July 4 (Holiday) - AUTOMATIC │ └─ Rejected: ├─ None recorded └─ No rejections in history View Balances: ├─ Vacation: │ ├─ Total Available: 20 days │ ├─ Used YTD: 5 days │ ├─ Pending Requests: 2 days │ └─ Remaining: 13 days │ ├─ Sick Leave: │ ├─ Total Available: 10 days │ ├─ Used YTD: 2 days │ ├─ Pending Requests: 0 days │ └─ Remaining: 8 days │ └─ Personal Time: ├─ Total Available: 5 days ├─ Used YTD: 1 day ├─ Pending Requests: 0 days └─ Remaining: 4 days Shift Trading Find Shift Trades: Search Interface: ├─ Start Date Picker ├─ End Date Picker ├─ Activity Filter (Optional): │ ├─ All Activities │ ├─ Voice Support Only │ └─ Email Support Only ├─ Time Filter (Optional): │ ├─ Morning (before 12:00) │ ├─ Afternoon (12:00-17:00) │ └─ Evening (after 17:00) └─ Search Button Results Display: ├─ Agent 1: Thomas │ ├─ Shift: Thursday 10:00-18:00 (Support Voice) │ ├─ Skills Match: Yes ✓ │ ├─ Propose Trade: Button │ └─ View Profile: Link │ ├─ Agent 2: Maria │ ├─ Shift: Friday 09:00-17:00 (Support Voice) │ ├─ Skills Match: Yes ✓ │ ├─ Propose Trade: Button │ └─ View Profile: Link │ └─ Agent 3: David ├─ Shift: Wednesday 14:00-22:00 (Email Support) ├─ Skills Match: Partial ⚠ ├─ Propose Trade: Button (with note) └─ View Profile: Link Propose Trade: 1. Select agent from results 2. Confirm Details: ├─ My Shift: Friday 09:00-17:00 ├─ Their Shift: Thursday 10:00-18:00 ├─ Skills Compatibility: Verified ✓ └─ Activity Match: Voice to Voice ✓ 3. Add Message (Optional): └─ "Really appreciate if you can help!" 4. Send Trade Request Track Pending Trades: ├─ Request Sent: │ ├─ To: Thomas (Friday trade) │ ├─ Sent: 2 hours ago │ ├─ Status: AWAITING RESPONSE │ └─ Cancel Request: Option │ ├─ Requests Received: │ ├─ From: Sarah (Tuesday trade) │ ├─ Received: 1 hour ago │ ├─ Shift Details: Mon 09-17 for Wed 14-22 │ ├─ Accept: Button │ └─ Decline: Button │ └─ Completed Trades: ├─ Traded with Jason (March 10) ├─ Traded with Lisa (February 28) └─ View History: Link Personal Preferences Manage Preferences: Basic Information: ├─ Name: John Smith (Read-only) ├─ Email: john.smith@company.com (Editable) ├─ Phone: 212-555-0123 (Editable) ├─ Site: New York Support (Read-only) ├─ Team: Support Tier 1 (Read-only) ├─ Manager: Jane Doe (Read-only) └─ Start Date: January 15, 2023 (Read-only) Availability Windows: ├─ Preferred Start Time: 09:00 ├─ Preferred End Time: 17:00 ├─ Can Start Earlier: 08:00 (Willing) ├─ Can End Later: 18:00 (Willing) ├─ Days Preferred: Mon-Fri ├─ Weekends: Not preferred └─ Save Preferences: Button Scheduling Preferences: ├─ Split Shifts: Not preferred ├─ Consecutive Days Worked: Max 5 (preferred) ├─ Days Off Preference: Mondays (if possible) ├─ Break Timing: Before 11:00 preferred ├─ Lunch Timing: 12:00-13:00 preferred ├─ Flexibility: Moderate (willing to adjust) └─ Save Preferences: Button Work Preferences: ├─ Preferred Activity: Voice Support ├─ Willing to Blend: Yes (40% email) ├─ Open to New Activities: Yes ├─ Overtime Interest: Some (up to 5 hrs/week) ├─ Schedule Variation: Prefer consistency └─ Save Preferences: Button Communication Preferences: ├─ Schedule Updates: Email ✓ SMS ☐ App ☐ ├─ Emergency Notices: Email ✓ SMS ✓ Phone ✓ ├─ Shift Changes: Email ✓ SMS ✓ ├─ Manager Messages: Email ✓ App ✓ ├─ Preferred Language: English └─ Save Preferences: Button Performance & Reporting My Performance: Adherence: ├─ Current Week Adherence: 94% │ └─ Status: ✓ Excellent (>90%) ├─ Last Week Adherence: 91% │ └─ Status: ✓ Good ├─ Monthly Average: 92% │ └─ Trend: Improving ↑ ├─ YTD Average: 91% │ └─ Status: On Target └─ View Detailed Report: Link Quality Metrics: ├─ Customer Satisfaction: 4.2/5.0 (if tracked) ├─ Call Quality Score: 87/100 (if tracked) ├─ First Contact Resolution: 92% (if tracked) ├─ Email Response Quality: Good (if tracked) └─ View Detailed Report: Link Historical Data: ├─ Adherence by Week (chart) ├─ Adherence by Day (breakdown) ├─ Attendance Record (details) ├─ Coaching Feedback (recent) └─ Export to Excel: Option Submit Adherence Explanation: ├─ If below threshold (e.g., <85%): │ ├─ Day: Monday │ ├─ Reason: Training session (unplanned) │ ├─ Duration: 1 hour 30 min │ ├─ Explanation: "Emergency product training" │ └─ Submit: Button └─ Manager notified of explanation Mobile App (iOS/Android) The mobile Genesys Tempo app provides schedule management on-the-go with push notifications and offline access. Mobile Features Mobile Home Screen: Next Shift Widget: ├─ Date & Day: Tuesday, March 18 ├─ Time: 09:00 - 17:00 ├─ Countdown: "In 2 days" ├─ Activity: Support Voice └─ Tap to Expand Quick Action Buttons: ├─ 📅 View Schedule (Calendar) ├─ ⏰ Request Time Off ├─ 🔄 Find Trades ├─ 📊 My Performance ├─ ⚙️ Preferences └─ 💬 Message Manager Recent Notifications: ├─ 🟢 Schedule Updated (2 hrs ago) ├─ ✅ Time-off Approved (5 hrs ago) ├─ 🔄 Trade Request from Sarah (1 hr ago) └─ 📅 Meeting Scheduled (1 day ago) Swipe Navigation: ├─ ← Left: Previous week/section └─ Right →: Next week/section Schedule View (Mobile) Mobile Schedule - Week View: Compact Calendar: ├─ MON | TUE | WED | THU | FRI | SAT | SUN ├─ [Off] [9-5] [9-5] [9-5] [9-5] [Off] [Off] │ 💙 💙 💙 💙 │ (Color indicates activity) │ ├─ Tap date for full shift details └─ Swipe to change week Shift Detail View (Tap Shift): ├─ Tuesday, March 18 ├─ 09:00 - 17:00 (8 hours) ├─ Support Voice ├─ Break: 10:30-10:45 ├─ Lunch: 12:00-13:00 ├─ Location: NYC Office ├─ Map/Directions: Button (if location enabled) └─ Options: ├─ 🔄 Trade This Shift ├─ 🕐 Request Time Off └─ 📞 Contact Manager Day/Week/Month Toggle: ├─ 📅 Day View ├─ 📆 Week View (default) ├─ 📊 Month View └─ Switch Views: Swipe Offline Capability: ├─ Download Schedule: Auto-sync ├─ View While Offline: Yes ├─ Add Local Notes: Yes ├─ Sync When Online: Auto └─ Notification: "Offline Mode" Time-Off on Mobile Request Time-Off Flow: 1. Tap "Request Time Off" 2. Select Type: ├─ Vacation ├─ Sick Leave ├─ Personal Time ├─ Unpaid └─ Other 3. Pick Dates (Calendar Picker): ├─ Tap start date ├─ Tap end date ├─ Dates highlight in blue ├─ Conflicts shown in red └─ Next > 4. Review & Confirm: ├─ "March 20-21 (2 days)" ├─ "Vacation" ├─ "Balance: 13 remaining" ├─ "Likely: Auto-Approved ✓" └─ Submit > 5. Confirmation: ├─ ✅ "Request Submitted" ├─ "Status: PENDING" ├─ "Check status in Profile" └─ Back to Home Notification When Approved: ├─ Push: "Your time-off approved!" ├─ Show Status: APPROVED ├─ Dates Added to Calendar └─ Sync with phone calendar (option) Mobile Notifications Push Notification Types: Schedule Changes: ├─ "Your schedule for next week updated" ├─ "New shift added: Friday 2-10pm" ├─ "Shift cancelled: Thursday" └─ Tap: Shows schedule change Time-Off Status: ├─ "Your vacation request approved" ├─ "Time-off request pending manager review" ├─ "Time-off request denied - resubmit?" └─ Tap: Shows status and details Shift Trade Activity: ├─ "Thomas accepted your trade!" ├─ "Sarah wants to trade with you" ├─ "Your trade request expired" └─ Tap: Shows trade details Manager Messages: ├─ "Message from Jane: 'Great work!'" ├─ "Schedule preference updated" ├─ "Team announcement posted" └─ Tap: Shows message/details General: ├─ "Payroll posted" ├─ "Benefits reminder" ├─ "Training available" └─ Tap: Shows details Notification Settings: ├─ Toggle each notification type ├─ Quiet Hours: (e.g., 22:00-08:00) ├─ Sound: On/Off ├─ Vibration: On/Off ├─ Do Not Disturb: Honor system └─ Save Settings: Button Mobile Preferences Settings (Gear Icon): Account: ├─ Name: John Smith ├─ Email: john.smith@... (Editable) ├─ Phone: (Editable) ├─ Password: Change (Button) ├─ Log Out: Button └─ About App: Version info Notifications: ├─ Schedule Updates: ✓ ON ├─ Time-Off Status: ✓ ON ├─ Trade Requests: ✓ ON ├─ Messages: ✓ ON ├─ Quiet Hours: 22:00-08:00 ├─ Sound: ✓ ON └─ Vibration: ✓ ON Display: ├─ Dark Mode: ☐ OFF (toggle) ├─ Language: English (dropdown) ├─ Time Format: 24-hour (toggle) ├─ Calendar View: Week (default) └─ Font Size: Normal (slider) Preferences: ├─ Sync Schedule: Every 1 hour ├─ Offline Storage: Enabled ├─ Calendar Export: iCal/Outlook ├─ Contact Manager: Phone/Email └─ Save Preferences: Button Privacy: ├─ Location Services: (Ask) ├─ Camera Access: Disabled ├─ Contacts Access: Disabled ├─ Calendar Access: Enabled ├─ Privacy Policy: Link └─ Terms of Service: Link Best Practices Portal Usage Check Regularly - Review schedule weekly Plan Ahead - Request time-off early (2+ weeks) Proper Trades - Ensure skill compatibility Clear Communication - Add notes on trade requests Respect Policies - Follow company rules Use Preferences - Set accurate preferences for fairness Mobile App Push Notifications - Keep enabled for updates Download Schedule - Offline access for reliability Timely Response - Answer trade requests quickly Update Contact Info - Keep manager in touch Feedback - Report issues to IT Security - Don't share login credentials Agent Satisfaction Empower Agents - Use system for control Transparency - Show time-off balances clearly Fast Approvals - Minimize manager review delays Clear Policies - Communicate rules openly Support - Provide help desk for issues Continuous Improvement - Listen to feedback Interview Cheat Sheet Question Answer What's agent self-service? Web/mobile portal for agents to manage schedules Desktop vs mobile? Desktop full features, mobile on-the-go convenience Can agents see schedules? Yes, up to 26 weeks forward Request time-off? Yes, desktop/mobile with auto-approval for qualifiers Shift trading? Yes, propose trades with other agents Auto-approval? Yes, if request meets criteria (balance, notice, staffing) Mobile app name? Genesys Tempo (iOS/Android) Offline access? Yes, download schedule to device Push notifications? Yes, optional for all major events Trade approval? Auto-approved if rules met, else supervisor review Can set preferences? Yes, scheduling and communication preferences View performance? Yes, adherence, quality, history Contact manager? Yes, message/chat from portal Schedule export? Yes, to Outlook/Google Calendar Key Takeaways Anytime Access - 24/7 portal on desktop and mobile Agent Empowerment - Control over schedules and preferences Work-Life Balance - Easy time-off requests and trades Automation - Auto-approvals reduce admin burden Transparency - Clear visibility of balances and requests Mobile First - Genesys Tempo app for on-the-go Offline Support - Access schedule without internet Notifications - Push alerts for all important updates Performance Visibility - Track own adherence and metrics Supervisor Relief - Reduces administrative workload significantly Additional Resources Official Documentation Agent Self-Service: help.genesys.cloud/articles/workforce-management-for-agents/ Genesys Tempo: help.genesys.cloud/articles/genesys-tempo-mobile-schedule-management/ Portal Features: all.docs.genesys.com/PEC-WFM/Current/Agent/ Support & Training Genesys University: genesys.com/training Community Forums: https://community.genesys.com Technical Support: https://support.genesys.com Document Version Info Last Updated: March 2026 Validated: Current with March 2026 release Version: 1.0