Data Analytics for Cost Engineering and Project Controls Professionals

Instructor: H. Lance Stephenson, CCP FAACE Hon. Life

Lance Stephenson is a senior leader with over 35 years of experience in the operational, capital portfolio, and project delivery environment, where he has worked for the owner, engineer, and constructor. Based on Lance’s years of experience and education in the operational and capital project delivery environment, Lance has provided direction in the areas of organizational design, process improvements, auditing, maturity assessments, and the development and implementation of best practices for improved capital portfolio and project effectiveness. Lance is a contributing member of the Technical Board for AACE International and is a Certified Cost Professional, a Project Management Professional, and a certified member of the Royal Institute of Chartered Surveyors. Lance’s past roles include director, senior manager, supervisor, PM/CM, specialist, analyst, foreman, tradesman, and life-long learner and practitioner. Lance is currently the Director of Operations for AECOM.

Instructor: Jareth Reeves
Jareth Reeves is CEO and Founder of Kaleido Projects Ltd in the United Kingdom and serves as UK Section President of AACE International. He brings over 20 years of experience in cost estimation, quantitative risk analysis, and integrated cost and schedule modeling across major nuclear, defense, and national infrastructure programs. His career spans senior advisory, estimating, and modeling roles across some of the UK's complex capital programs, working across owner, government, and contractor environments. 

Jareth has a background in Systems Engineering complemented by an MBA in Technology Management, enabling him to operate across technical and commercial domains and translate analytics into decisions that hold up under scrutiny. Within this course, he brings the practical workshop component by applying machine learning techniques across the project lifecycle alongside established Total Cost Management practice. His focus includes using classification, regression, and time-series analysis on historical data to interrogate the quality of QRA model assumptions ahead of gate decisions and applying analytical techniques alongside earned value management during execution to provide early signals of risk to project funding.

Course Overview
This intensive one-and-a-half-day training course is designed for professionals seeking to enhance their data analytics skills and apply them to Total Cost Management. Participants will delve into intermediate and some advanced techniques and tools for data analysis, visualization, interpretation, and decision-making.

Participants will examine data and analytics techniques in a real-world setting to help them refine their fluency with data concepts, challenges, and applications. By the end of the course, participants will understand the requirements to:

• Define a use case for specific organizational needs and construct a prediction model.
• Implement analytical techniques like regression analysis for predicting an outcome based on specific questions.

The course is designed to provide a comprehensive understanding of key concepts, hands-on practice with industry-leading tools, and real-world case studies to reinforce learning.

Key Learning Objectives
Understand the concepts of data analytics;
Recognize the process of problem-framing;
Identify ways analytic models have been applied;
Distinguish characteristics of analytic targets;
Frame the business problem statement into an analytics problem;
Identify steps for creating a simple analytical model;
Describe considerations for communicating analytics results and cultivating buy-in.

What you’ll get:

• Improved data literacy and the ability to communicate effectively with data analysts to determine when to use and how to interpret descriptive, predictive, and prescriptive analytics.
• Guidance on evaluating data analytics tools, such as machine learning, predictive models, regression analysis, and decision trees.
• Techniques for applying scientific thinking to business, such as examining cause and effect in data analysis.
• A deeper understanding of how to build a data-driven organization, including developing strategies to cultivate evidence-based decision-making.

Who Should Attend:
This course is designed for cost engineers and project controls practitioners who want to deepen their understanding of data and its outputs.

Prerequisites:
Given the course agenda, which covers foundational theory, practical applications, technical labs, and the strategic integration of AI into cost engineering and project controls, attendees should have:

• Basic understanding of project controls (cost, schedule, risk, and change management)
• Basic understanding of statistics
• Familiarity with Microsoft Excel
• Comfort interpreting graphs, tables, and dashboards

This ensures attendees can meaningfully participate in discussions, handle hands-on exercises, and understand how analytics integrate with project delivery processes.