00 Opening Giza · Egypt · GMT+2

Youssef Selim

Regional Workforce Lead Forecasting & Analytics Automation Champ

I lead workforce planning across multi-country operations — turning forecasts, schedules, and real-time signals into service-level stability.

Currently at Intelcia · Regional Workforce Lead Begin
01 The Operator

Operating at scale.

Numbers behind the work. Countries, accounts, years, skills — each one earned.

0 + yrs

In planning & operations

From Amazon audit to Regional Workforce Lead — a continuous arc through data, ops, and leadership.

0

Countries, in parallel

End-to-end workforce planning across multi-country BPO operations — each with its own SLA grammar.

0 +

Accounts under planning

Forecasts, schedules, resource allocation — tuned to each client's SLA and seasonal rhythm.

0

Specialised skills, daily

Python, SQL, VBA, Power BI, ML, Lean Six Sigma — a stack chosen to make operations measurable.

02 The Line

From data integrity to regional planning.

2020 — 2021 Amazon

Auditor · GAM

Remote · 1y 8mo

Audited large datasets for Amazon's Egypt launch. Learned what data integrity looks like at scale — the foundation everything else was built on.

  • Data integrity
  • Large-scale audits
  • Process discipline
2021 — 2022 Intelcia

Customer Tech Support

Cairo · 11mo

Pivoted into BPO operations. Resolved complex customer issues with analytical rigour — the first lessons in how front-line work shapes the metrics planners later optimise.

  • Customer ops
  • Analytical problem solving
  • Front-line insight
2022 — 2023 Intelcia

Senior RTM

Cairo · 9mo

Owned real-time ops and SLA adherence. Led the team end-to-end — performance, development, scheduling. Where dashboards became decisions, in minutes.

  • Real-time ops
  • SLA management
  • Team leadership
2023 — 2025 Intelcia

Planning & Scheduling Specialist

Cairo · 2y 2mo

Led capacity planning across two countries and six+ accounts. Built Python forecasting models that folded ML into the planning cycle. Owned the full scheduling stack.

  • Multi-country capacity
  • Python + ML
  • End-to-end scheduling
2025 — Now Intelcia

Regional Workforce Lead

Cairo · ongoing

Promoted to lead workforce management across the region. Multi-site, multi-country scope. Where the discipline of planning meets the breadth of regional leadership.

  • Regional WFM lead
  • Stakeholder management
  • Strategic planning
03 The Stack

Tools that turn operations into models.

i.

Strategy & Planning

  • Capacity Planning
  • Green Belt Lean Six Sigma
  • Advanced Forecasting
  • Process Optimization
  • Agile Methodologies
  • Data Analysis & Insights
ii.

Data & Engineering

  • Python Programming
  • SQL Expertise
  • VBA Development
  • Power BI Mastery
  • DAX
  • Regression & Machine Learning
  • Statistical Analysis
  • Data Modeling & ETL
  • Data Processing Automation
  • JavaScript Development
iii.

Leading the work

  • Stakeholder Management
  • Team Leadership
  • Effective Communication
  • Cross-functional Coordination
  • Data-driven Decision Making
04 The Method
I don't just schedule shifts. I model the system that makes the shifts possible — the demand patterns, the agent skills, the seasonal noise, the SLA cliffs. Then I build the forecasts, the automations, and the dashboards that let the whole operation run a step ahead, instead of a step behind.
i.

Model the system, not the symptom

Real-time fires happen because something upstream wasn't modelled right. I start every problem with the demand-supply structure beneath it.

ii.

Automate the repetition out

If a planner runs the same query every Monday, that query becomes a Python or VBA job. Time saved on plumbing is time spent on judgement.

iii.

Make the numbers honest

Forecasts that flatter no one. Dashboards that show the gap, not hide it. Lean Six Sigma discipline applied to the data itself.

05 The Work

Three threads that hold the practice together.

i.

Multi-country capacity planning

Capacity for two national markets, six+ accounts, in one cohesive model. Resource allocation tuned per account SLA, seasonality, and skill mix. The model isn't perfect — it's transparent enough that the ops floor can tell me where it's wrong, and why.

  • Capacity model
  • Multi-country
  • SLA-aware
ii.

Python-driven forecasting

Forecasting models in Python — regression and statistical methods stitched together for planning that doesn't surprise anyone in week three. Outputs feed directly into the schedule engine, replacing what used to be week-long spreadsheets.

  • Python
  • Regression / ML
  • End-to-end automation
iii.

Real-time ops, modelled

As Senior RTM I owned SLA adherence in the moment. But the lasting work was turning that minute-by-minute knowledge into structural insights for the planning layer. Bottlenecks identified at real-time speed inform capacity assumptions at planning speed.

  • Real-time ops
  • SLA
  • Bottleneck analysis
06 Epilogue

Let's plan something better.

Open to conversations about workforce planning, forecasting at scale, BPO operations, or anywhere data, scheduling, and Lean discipline meet.

Start a conversation