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GM / AVP — Workforce Management & Analytics

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Onsite

GM / AVP — Workforce Management & Analytics

ICCS DigX

GM / AVP — Workforce Management & Analytics

Skills

Data AnalysisAINo-code Applications

1 month ago

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Important information


Contract type:

Permanent

Location:

Noida, Uttar Pradesh, India

Work mode:

Onsite

Published on:

16 September 2026

What they need


Role purpose

To own forecasting, capacity planning, scheduling and real-time management across all ICCS sites, and to modernise MIS and reporting through automation and AI. This role is a direct margin lever: shrinkage, occupancy and seat utilisation are where contact centre profitability is won or lost.

Key responsibilities

  • Own volume forecasting and capacity planning across all clients and sites.

  • Own scheduling, roster optimisation, intraday management and real-time adherence.

  • Drive shrinkage, occupancy and utilisation to target; publish variance analysis against plan.

  • Own seat utilisation across the delivery footprint and identify consolidation opportunities.

  • Rebuild MIS and client reporting on automated dashboards, reducing manual report preparation.

  • Deploy AI and automation for reporting, anomaly detection and forecast accuracy improvement.

  • Support new client solutioning with staffing models and cost-to-serve assumptions.

  • Lead the WFM and MIS team across locations.

Must have

  • Has owned forecasting and capacity planning — not MIS reporting alone — in a multi-site BPO.

  • Strong command of WFM fundamentals: Erlang-based sizing, shrinkage modelling, occupancy, adherence and intraday management.

  • Demonstrable improvement in a stated WFM metric that they personally drove.

  • Hands-on with WFM tooling and with BI or dashboarding platforms.

  • Strong data analytics capability — able to work with large operational datasets directly.

Preferred

  • Experience automating reporting through scripting, low-code platforms or AI tooling.

  • Exposure to outcome-based or transaction-priced commercial models and their staffing implication

  • Candidates who cannot explain how they arrived at a staffing number.

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