Strategic Planning (Customer Care)

Job Description

Job ID: MJ000226

About The Role

This role owns the analytics and planning behind Customer Care cost and partners closely with Customer Care stakeholders to ensure Service Quality targets (e.g., service level, AHT, occupancy) are met as efficiently as possible. A core focus is building and continuously improving Customer Care strategy by simulating manpower orders and running multi-scenario operational with strategic plans, and continuously improving way of working and methodology. The role leverages AI tools to accelerate modelling and broaden scenario coverage, while rigorously validating every output before it informs cost or headcount decisions.

Job Responsibilities

• Own end-to-end Customer Care cost planning across manpower, technology, and internal staffing; track actuals against targets to discover and surface efficiency opportunities.
• Build, maintain, and stress-test data-driven manpower simulations and multi-scenario (what-if) plans to balance service quality metrics (e.g., service level, AHT, occupancy) against cost trade-offs.
• Leverage AI assistants to accelerate quantitative model building, scenario generation, and complex calculation logic, ensuring thorough data validation before informing leadership decisions.
• Coordinate closely with cross-functional partners—including Operations, Finance, and the CEO Office—to translate complex analyses into actionable Tableau/spreadsheet dashboards and ensure alignment with budget realities.
• Performance diagnostic analyses on operational metrics to identify root causes of anomalies, troubleshoot problems, and present clear solutions to senior management.
  
  

Job Requirements

• Bachelor's degree in a quantitative field such as Mathematics, Statistics, Industrial Engineering, Finance, Supply Chain, or equivalent.
• Has 4-5 years in workforce or capacity planning, with a strong background in budgeting, forecasting, and operational reporting.
• Proven ability to build forecasting, simulation, or optimization models completely from scratch (not just operating pre-existing models).
• Solid understanding of demand forecasting, contact center staffing mechanics (e.g., Erlang models, shrinkage, occupancy), and core unit economics like cost-per-contact.
• Proactivity and skills in using AI assistants (e.g., Claude) to optimize analysis, alongside technical comfort slicing and dicing data in Tableau and spreadsheets.
• Strong verbal and written proficiency in English and Bahasa Indonesia, with a track record of effectively translating complex data trends for non-technical senior business partners.