Call Center After-Call Work Time Analysis Builder

You are a contact center operations analyst. Build an after-call work time analysis for:

Organization type: [SaaS support, ecommerce, healthcare, finance, telecom, government, internal help desk]
Channels: [phone, chat, email, messaging, blended]
Dataset fields available: [interaction ID, queue, agent, team, handle time, talk time, hold time, ACW, wrap code, disposition, transfer, CSAT, QA score]
Time period: [date range, seasonality, special events]
After-call work definition: [system ACW timer, manual status, wrap duration, notes time, case update time]
Queues or issue types: [billing, technical, cancellations, claims, scheduling, escalations]
Tools involved: [CRM, helpdesk, telephony, knowledge base, order system, EHR, billing platform]
Current pain: [high ACW, staffing shortage, inconsistent notes, slow systems, compliance documentation, quality issues]
Performance constraints: [do not reduce documentation quality, regulated notes, union rules, coaching standards]
Segmentation needs: [agent tenure, queue, language, shift, location, issue complexity, customer tier]
Business questions: [capacity planning, process friction, coaching, automation, staffing model, knowledge gaps]
Reporting audience: [support leaders, workforce management, QA, training, operations, executives]
Privacy constraints: [PII, call recordings, health/financial data, employee monitoring rules]

Produce:
1. Data cleaning plan for ACW definitions, outliers, transfers, zero values, and status misuse.
2. KPI definitions for median ACW, p90 ACW, total ACW hours, ACW share of handle time, and variance by segment.
3. Segment analysis by queue, issue type, wrap code, agent tenure, shift, channel, and system used.
4. Driver analysis separating complexity, process requirements, tool friction, training gaps, and behavior patterns.
5. Dashboard layout with trend charts, distribution views, exception tables, and capacity impact.
6. Root-cause hypotheses and validation questions.
7. Recommendations grouped into process changes, knowledge base fixes, tooling improvements, training, QA calibration, and automation.
8. Experiment plan with expected impact, fairness risk, quality safeguards, and measurement window.
9. Workforce planning translation: hours recovered, staffing implications, and service-level caveats.
10. Executive summary template that avoids blaming agents without evidence.

Keep the analysis operational and fair. Do not recommend cutting ACW targets if documentation, compliance, or customer outcomes would suffer.