Staff to the pattern. Score every interaction.
Workforce optimization used to mean buying a second platform as heavy as the contact center itself. We engineer forecasting, Erlang staffing models, and AI-powered quality management on the Webex Contact Center data you already own.
The tools meant to optimize the workforce became the overhead
Staffing and quality are the two biggest levers in any contact center — and the two most operations still run on gut feel, because the traditional tooling costs too much and covers too little.
Schedules built on memory
Call arrival patterns shift by hour, day, and season. Without interval-level forecasting, you’re overstaffed at ten and underwater at two — every single day.
A second platform to run the first
Traditional WFO suites arrive with their own licensing, their own admin console, and their own training burden — a system as expensive to own as the contact center it optimizes.
QA that samples a sliver
Evaluators review a handful of interactions per agent per month. Everything else — the saves, the escalations, the compliance misses — goes unheard and uncoached.
Licensing by guesswork
Seats and licenses get bought on peak-day fear instead of modeled demand — and the overage quietly renews itself year after year.
Forecasting and staffing, run like an engineering problem
This is the same analysis we run inside our own engagements: your reports in, a documented staffing model out. No black box, no per-agent platform fee.
Analyze
We pull your actual reports — staffing metrics, handle time, and the call arrival pattern by hour — and map how the operation really behaves, interval by interval.
Forecast
Arrival patterns become a volume forecast by interval, day, and season — the demand curve your schedule should be shaped around, not the monthly average that hides it.
Model
We run Erlang staffing calculations against the forecast — agents required per interval, service level trade-offs made explicit, and licensing right-sized to modeled demand.
Operationalize
Forecast-vs-actual lands on the dashboards you already run, and the model is re-tuned as patterns drift — under CX TOPS managed services, month over month.
Illustrative view — volume by interval against the forecast, with the intervals that need staffing attention standing out.
What you walk away with
- An interval-level forecast — volume by hour, day, and season, built from your own history
- A documented Erlang staffing model — agents per interval, with the assumptions written down and handed over
- Licensing right-sized to demand — pay for the seats the model says you need
- Forecast-vs-actual on your dashboards — so the model stays honest after go-live
Every interaction scored. Not a sample.
Cisco has built AI quality management directly into the Webex platform. We implement it against your quality rubric — so QM stops being a sampling exercise and starts being a system of record.
Full-coverage scoring
Every interaction, on every channel, is evaluated — not the handful a human evaluator has time to pull. The calls that deserve a human review surface themselves.
Scored against your rubric
AI evaluations run on the quality standard you define — greeting, resolution, compliance, tone — so scores mean the same thing to every supervisor on every team.
Topic & sentiment analytics
Conversations are transcribed and classified into topics and trends — call drivers, emerging issues, and automation candidates — so you know why customers call, not just how many.
Coaching on evidence
Coaching moments are surfaced automatically and tied to the actual interactions — so one-on-ones run on what happened, not on anecdotes and recollection.
Cost-effective WFO, engineered on what you already own
The question isn’t whether workforce optimization pays for itself — it’s whether you need an entire second platform to get it. You don’t.
The suite model
A separate platform — licensed per agent, per month, with its own contract to negotiate and renew.
Its own administration — another console, another skill set, another training cycle for every supervisor.
Sampled quality — evaluation coverage capped by human hours, not by what the operation needs.
A black-box forecast — staffing math you can’t inspect, adjust, or take with you.
The Workflow Concepts model
- Built on Webex Contact Center — the data and dashboards your operation already runs on
- Forecasting you own — documented Erlang models and assumptions, handed over, not rented
- AI QM native to the platform — Cisco’s quality management capability implemented, not bolted on
- Tuned under CX TOPS — the model re-run as patterns drift, quarter over quarter
Workforce wins that came from engineering, not licensing
agent login replacing a multi-step Finesse process
Acadian
Agents fought a cumbersome Cisco Mobility and Finesse login sequence at the start of every shift. We engineered a custom single-click agent login — seconds to ready-state, every shift, with no misconfigured sessions. Minutes returned to every agent, every day, is workforce optimization too.
agents on one platform, scaled for the season
National Retail Chain
A national retailer consolidated 700+ agents across 150 locations onto Webex Contact Center — with the elasticity to scale headcount for the season instead of licensing for the peak. Staffing to the demand curve is the whole point of workforce optimization.
Staff to the forecast, not the fire drill
Start with a no-obligation assessment. We’ll run your call arrival patterns, model your staffing against the forecast, and show you what AI quality management looks like on your own interactions.