Operational Analytics, Throughput and Process Improvement

Instructor: Alaa Hady · Language: English or Arabic · Suggested duration: 1–2 days · Level: Intermediate (Level 200)

Objectives

• Translate physical and digital operational workflows into measurable throughput, cycle-time, and quality KPIs.
• Apply Little's Law, Statistical Process Control (SPC control charts), and bottleneck analysis using Power BI.
• Analyze SLA compliance, backlog aging, capacity utilization, and rework/defect rates.
• Connect operational dashboards directly to Lean / Six Sigma continuous improvement routines.

Outline and contents

1. Mapping operational value streams: Inputs → Work in Progress (WIP) → Cycle Time → Output & Quality
2. Core operational metrics: Throughput, Cycle Time vs. Lead Time, First-Pass Yield (FPY), Overall Equipment Effectiveness (OEE), and SLA Attainment
3. Modelling "Events-in-Progress" data in Power BI (counting open tickets/orders between Created Date and Closed Date)
4. Backlog aging buckets, queue bottlenecks, and Little's Law (\text{WIP} = \text{Throughput} \times \text{Cycle Time})
5. Building Statistical Process Control (SPC) XmR charts in Power BI: distinguishing common-cause noise from special-cause signals (\pm 3\sigma control limits)
6. Benchmarking productivity across sites, shifts, teams, and machines fairly
7. Root-cause Pareto analysis of defects, downtime reasons, and SLA breaches
8. Hands-on Lab: Building an Operational Excellence, Backlog Aging & SPC Control Chart dashboard

Target audience

Operations managers, service delivery leads, manufacturing/logistics analysts, contact center managers, and Lean/Six Sigma professionals.

Expected outcomes

Participants can model complex open/close operational workflows, build statistical control charts to spot true process breakdowns early, and drive measurable efficiency gains.