PCMPCA-Project Control Analytics Data-Driven Decision-Making 02
Introduction
As project environments become more complex, the ability to analyze and interpret project control data is crucial for optimizing decision-making. This intermediate course focuses on advanced metrics, business intelligence tools, and predictive analytics techniques to enhance project performance. It is designed for professionals with basic project control knowledge who want to leverage data analytics for proactive decision-making.
Date
Day | Time | Price | Country |
---|---|---|---|
Mon – Wed | 8:00 – 10:00 | $5/hrs | Turkey |
Tue – Thu | 18:00 – 19:00 | $5/hrs | Turkey |
Wed – Fri | 20:00 – 21:00 | $5/hrs | Turkey |
Sat – Sun | 18:00 – 19:00 20:00 – 21:00 | $8/hrs | Turkey |
This Training Course Will Highlight
- Advanced data visualization techniques for project controls.
- Integrating business intelligence (BI) tools for performance tracking.
- Predictive analytics for cost and schedule forecasting.
- Risk analytics and scenario-based project planning.
- Automating project control reporting using real-time data insights.
Objectives
By the end of this course, participants will be able to:
- Utilize advanced project control metrics for data-driven decision-making.
- Integrate business intelligence tools into project control workflows.
- Use predictive analytics to forecast project cost and schedule trends.
- Apply data-driven risk assessment techniques in project planning.
- Automate reporting and dashboard creation for real-time monitoring.
Training Methodology
- Instructor-led training with real-world examples.
- Hands-on exercises in basic project analytics tools.
- Group discussions on challenges in data-driven decision-making.
- Case study on project analytics implementation in a mid-scale project.
- Step-by-step demonstrations of data visualization techniques.
- Interactive problem-solving sessions using project data sets.
Organizational Impact
- Enhanced project efficiency through structured data tracking.
- Improved cost and schedule management using analytics.
- Strengthened stakeholder communication through data visualization.
- Better risk identification and mitigation using historical data.
- Increased transparency and accountability in project execution.
Personal Impact
- Strong foundation in project control analytics.
- Practical knowledge of key project performance metrics.
- Improved ability to interpret and use project data for decision-making.
- Enhanced reporting skills using dashboards and visualization tools.
- Career advancement opportunities in data-driven project management.
Who Should Attend?
- Entry-level project managers.
- Cost and schedule analysts.
- Project coordinators and planners.
- Engineers and site supervisors.
- Business analysts involved in project execution.
- Procurement and contract professionals.
- Professionals transitioning into project analytics.
Course Outline
Day 1
Advanced Project Metrics and Data-Driven Decision-Making- Defining and tracking complex project control metrics.
- Integrating real-time project tracking with performance KPIs.
- Data-driven decision-making for cost and schedule optimization.
- Using historical project data for benchmarking.
Day 2
Business Intelligence and Visualization in Project Controls- Overview of business intelligence (BI) platforms (Power BI, Tableau).
- Creating interactive project dashboards and real-time analytics.
- Integrating BI tools with project management software.
- Advanced visualization techniques for executive reporting.
Day 3
Predictive Analytics for Cost and Schedule Performance- Using trend analysis to forecast project cost performance.
- Machine learning applications in predictive cost control.
- Scenario-based forecasting for schedule optimization.
- Early warning indicators for potential project failures.
Day 4
Risk Analytics and Scenario-Based Decision-Making- Identifying high-impact risks using data analytics.
- Monte Carlo simulations for risk-based project forecasting.
- Sensitivity analysis for risk-adjusted decision-making.
- Optimizing contingency planning using risk data models.
Day 5
Automating Project Control Reporting and Case Study- Implementing automation in project control dashboards.
- Real-time project monitoring using AI-powered analytics.
- Aligning automated reporting with corporate governance.
- Industry best practices for continuous project performance tracking.
Cancellation policy
no refund is accepted
Certificate


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