Aspect Intelligence puts predictive, policy-aware control at the heart of workforce operations

Aspect Announces Aspect Intelligence™: Real-time, policy-aware workforce control for operations teams

Static plans break the moment demand shifts. Aspect Intelligence™ moves operations toward live control-embedding predictive, policy-aware decisions into forecasting, scheduling, and day-to-day execution.

The goal is simple: spot risk earlier, act faster, and cut the rework that traps supervisors and planners. Less firefighting. More consistent service at lower cost.

Why this matters for operations

• Prevent disruption: Address issues before queues back up or service levels slide.
• Reduce manual churn: Fewer schedule fixes, fewer last-minute scrambles, fewer meetings to align changes.
• Increase focus time: Supervisors coach more. Agents serve customers more. Planners manage variance, not exceptions.
• Audit-ready decisions: Transparent, explainable choices with clear rules and approvals for regulated or unionized environments.

What's new in the initial release

Automatic Schedule Updates based on Adherence applies simple, policy-aligned rules to keep schedules accurate at scale-without constant supervisor intervention.

• Late logins, missed breaks, early sign-outs, and mid-shift departures trigger the correct schedule updates automatically.
• Supervisors shift from chasing corrections to coaching, quality, and live service stability.
• Rules-based guardrails ensure changes stay within policy and contract constraints.

Built for trust and real-world conditions

• Explainable automation: Every change can show what rule fired, what data was used, and who approved it.
• Policy first: Configurable guardrails respect labor rules, union agreements, and compliance policies.
• Human-in-the-loop: Approvals on high-impact actions; automation on the repetitive work.

What's coming next

• Intraday automation: Real-time staffing moves to protect service levels and reduce idle time.
• AI-driven coaching and training scheduling: Turn live performance signals into targeted sessions without blowing up coverage.

How operations teams can put this to work

• Start small: Pilot adherence-based schedule updates in one site or queue. Track schedule accuracy and supervisor correction hours.
• Codify policy: Translate labor rules, union agreements, and exception policies into explicit rule sets and approval paths.
• Wire the data: Connect WFM, ACD/CCaaS, HRIS, and timekeeping so adherence and schedule states stay in sync.
• Define thresholds: Late-login minutes, break windows, early sign-out criteria, and what requires approval vs. auto-apply.
• Audit everything: Keep a clear decision log-inputs, rules, approvers, timestamps-for compliance and root-cause analysis.

Operational scorecard to measure impact

• Schedule accuracy and adherence variance
• Supervisor correction hours per week
• Reforecast frequency and intraday change volume
• SLA attainment and abandon rate
• Occupancy, idle time, and shrinkage
• Agent engagement/NPS and coaching completion rates
• Compliance incidents and exception backlog

Practical guardrails

• Set approval for changes that affect pay, premium hours, or union-sensitive moves.
• Keep humans on schedule changes that cross teams, change skills, or affect overtime.
• Use explainability standards and model risk practices aligned with frameworks like the NIST AI Risk Management Framework.
• Monitor data quality-bad adherence inputs lead to bad schedule edits.

Where this fits

• Contact centers needing tighter intraday control without bloating workforce teams.
• Back-office and claims operations with strict SLAs and frequent exceptions.
• Field service or dispatch with union rules and dynamic day-of changes.

Next steps

• Audit your current exception volume and supervisor rework.
• Translate policies into machine-readable rules and approval tiers.
• Pilot adherence-based updates; expand to intraday moves after 4-6 weeks of stable results.
• Feed QA and performance signals into coaching calendars once schedule hygiene is steady.

Want more practical playbooks? Explore AI for Operations or go deeper with the AI Learning Path for Call Center Supervisors.