Workforce management (WFM) forecasts contact volume, schedules agents to meet forecasted demand, and tracks real-time adherence — balancing customer service levels with agent utilization and labor cost. Modern WFM platforms add AI forecasting, self-service scheduling, and intraday management capabilities that improve both operational efficiency and agent experience.
Staffing decisions in the contact center affect every KPI — understaffing creates queue build-up and abandoned calls, overstaffing wastes labor cost that typically represents 70% of contact center operating expense. WFM platforms from Verint, Calabrio, NICE, and Genesys bring forecasting science and scheduling optimization to staffing decisions that too many operations still make manually. RLM advises on WFM strategy, platform selection, and forecasting model design.
A structured advisory process — from discovery and market evaluation to vendor selection and post-deployment optimization — tailored to your specific environment and objectives.
We assess your current workforce management approach — forecasting methodology, scheduling practices, intraday management, and the staffing accuracy gaps that manifest as SLA shortfalls or labor overspend.
We evaluate WFM platforms — Verint WFM, Calabrio ONE, NICE IEX, Genesys WFM, Aspect Workforce — against your interaction volume, channel mix, agent population size, and the self-service and mobile features that improve agent experience.
We design the forecasting model for your interaction patterns — handling seasonality, campaign-driven volume spikes, digital channel growth, and the AI forecasting enhancements that reduce forecast error vs. traditional Erlang models.
We design the intraday management workflow — real-time adherence monitoring, dynamic schedule adjustment triggers, and the supervisor tools that respond to volume deviations without waiting for the next scheduling cycle.
These are the dimensions that consistently separate successful CX deployments from costly ones — and the questions RLM will help you answer before any commitment.
WFM value depends on forecast accuracy. Evaluate how forecast accuracy is measured (MAPE, RMSE) and the typical accuracy range for your volume patterns — some variability is unavoidable, but consistent errors indicate modeling problems.
Scheduling agents who handle multiple channels requires WFM that understands channel mixing and blending rules. Evaluate whether the WFM platform models omnichannel staffing or treats each channel independently.
Agent satisfaction with WFM depends heavily on schedule flexibility. Evaluate self-service capabilities — shift swap, time-off requests, voluntary OT — and whether the mobile interface makes schedule management convenient.
Workforce management that accounts for quality performance — protecting agent time for coaching, QM-triggered schedule adjustments — delivers better outcomes than systems that optimize purely for efficiency.
WFM accuracy depends on realistic shrinkage assumptions — training, coaching, breaks, absenteeism. Evaluate shrinkage tracking and the process for updating shrinkage assumptions as patterns change.
"RLM helped us select and implement the right CCaaS platform in half the time it would have taken us on our own. Their vendor knowledge is unmatched — they knew exactly what questions to ask."
"We had a legacy premise system and 90 days to migrate. RLM built the plan, managed the vendors, and we hit the deadline with zero customer disruption."
Talk to an RLM advisor who specializes in CX technology. We'll help you find the right solution for your business — without vendor bias.