How confident are you that your EVMS is helping to proactively manage risk and performance? In this interactive workshop, participants will be introduced to the Integrated Project/Program Management (IP2M) Maturity and Environment Total Risk Rating (METRR), a rigorous framework for assessing Earned Value Management Systems (EVMS) effectiveness on large, complex capital endeavors. Participants will learn how to evaluate EVMS implementation, identify performance risks, and prioritize opportunities for improvement. With practical examples, the workshop will also highlight how IP2M METRR assessments result in statistically significant cost and schedule impacts, demonstrating the value of strengthening EVMS execution through IP2M METRR.

Cost and schedule variance have anchored program performance measurement for decades, but mature integrated project and program management, EVMS included, is only as strong as the environment surrounding it. IP2M METRR is a maturity and environment framework that turns that idea into a measurable second dimension of environment alongside the maturity score. This session introduces environment: twenty-seven factors across four categories, culture, people, practices, and resources, shaping whether surroundings strengthen or undermine a program. It gives project controls professionals a starting point for evaluating their program's environment alongside its maturity.

Building on the data foundation explored in From Integrated Controls to Predictive Insight: Building the Foundation for Complex Programs, this session moves from data readiness to practical AI application in project controls. It will explore how AI can learn from project data to provide greater confidence in forecasts through predictive analytics, as well as how role-based AI agents can guide project controls professionals through complex day-to-day workflows and required actions. Together, these capabilities demonstrate how trusted, integrated project data can be transformed into more intelligent, consistent, and proactive project controls.

Construction estimators frequently receive scope information distributed across bid-package narratives, drawings, specifications, asset inventories, equipment schedules, addenda, and clarifications. Transforming that information into a structured and defensible estimate requires more than performing calculations. Estimators must interpret the scope, organize the work, identify applicable quantities, select appropriate productivity relationships, document assumptions, and preserve the basis for each decision. This session presents a practical approach for creating a connected estimating evidence chain from source documents through the work breakdown structure, work packages, estimate calculations, and basis-of-estimate narrative. A construction maintenance example will demonstrate how scope requirements can generate multiple types of work—including planning, inspection, preventive maintenance, certification, deficiency reporting, and closeout—while a normalized asset inventory supplies reusable quantity roll-ups. The same quantity can support multiple task-specific estimating archetypes, each with its own cost estimating relationship, frequency, crew mix, rates, and assumptions.

A baseline schedule today takes 20–25 days, not because the process demands it, but because assumptions get guessed rather than calculated, and stakeholder input arrives scattered across emails and calls. This session isn't another AI speed pitch. Following one composite project through a six-month arc, baseline to delay claim, it shows what actually changes when assumptions become checkable and reviews become real checkpoints, for both planners and the PMOs reviewing their work. Grounded in patterns from 2,000+ real projects and 15 years of consulting, not a demo trick. The real question was never speed. It's trust.

The data center industry is expanding at unprecedented speed, bringing complex challenges in supply chain, power delivery, community relations, regulatory requirements, and skilled resource availability. In this joint presentation, EdgeConneX share their real-world journey of business and digital transformation, with Omega 365 serving as a key enabler. Building on lessons from large-scale enterprise rollouts, they discuss practical strategies for navigating these challenges while improving project controls execution. They will openly discuss: • Key business and client challenges in hyperscale data center delivery • Business transformation strategies and organizational change • Digital transformation tools and processes, including deep integration with Omega 365 and Primavera P6 • Practical approaches to user adoption and breaking down silos • Where AI fits into forecasting, risk management, and decision-making

You have the controls data. The challenge begins when that analysis needs to drive a decision and gets reduced to a summary table that strips away the context behind it. By the time information reaches stakeholders, much of the rigor that project controls teams worked to produce has been lost. As programs become more interconnected, leaders need more than static reports. They need to understand how schedule, cost, risk, and dependencies interact across the portfolio and explore those relationships in real time. In this session, you'll learn how organizations are connecting controls outputs into a live portfolio layer that preserves context, improves stakeholder understanding, and enables more informed decisions. The result is a portfolio view leadership can navigate in the room, not a report that arrives after the meeting.​ What you’ll learn:​ Techniques for connecting P6, cost, and risk data into a unifed view. ​ Ways to visualize where schedule risk intersects with cost exposure and portfolio dependencies.​ Approaches that move organizations from reactive reporting to proactive portfolio navigation. ​ Practices for delivering executive-ready portfolio briefings without rebuilding data for every meeting.​ Methods for revealing interdependencies that static EVM reports often fail to show.

The project management landscape is undergoing a paradigm shift driven by disruptive technologies redefining how projects are planned, executed and delivered. This presentation explores how the strategic integration of AI, BIM, Blockchain, AR, Reality Capture, IoT and Power BI is not an aspirational concept — but a practical reality.  .Real-world examples demonstrate how these technologies solve long-standing industry challenges. BIM creates a single source of truth. IoT enriches it into a live tracking model.. Blockchain function as a smart contract. Power BI transforms data into actionable intelligence. The future of project management is not a distant vision. It is here.

The success of Complex Projects & Program Delivery depends on making the right decisions early and maintaining alignment between scope, cost, schedule, risk, and funding throughout the project lifecycle. As programs become larger and more complex, organizations must manage not only individual projects, but also the interdependencies, priorities, resources, and investment decisions that drive overall program success. This presentation explores how AI-powered conceptual estimating can improve early decision-making, establish realistic budgets, and reduce the risk of cost overruns before detailed design begins. The session will also highlight the importance of linking estimating, design, project controls, and construction into a continuous process. As projects progress from concept through design and construction, costs, risks, schedules, and funding requirements are continuously refined to improve cost certainty, support reliable cash flow forecasts, and enable informed investment decisions. This iterative approach helps organizations improve predictability, align funding with project needs, and increase confidence in the successful delivery of complex capital programs.

Planning and scheduling are universal disciplines, but they are practiced within vastly different environments. While defense programs and construction projects share common objectives—delivering complex work on time and within budget—the approaches to planning, governance, risk management, and execution often reflect very different priorities and constraints. Drawing on firsthand experience leading planning and scheduling for large-scale defense programs, this session explores the similarities and differences between defense acquisition and construction project controls. Attendees will gain insight into how defense organizations leverage integrated master schedules, technical performance, earned value management, and structured governance to manage complexity, while also examining the agility, field-driven decision-making, and execution focus that characterize successful construction projects. Rather than suggesting one industry has the “better” approach, this presentation highlights the strengths of each and identifies practical lessons that can be applied across both. From schedule architecture and risk integration to stakeholder communication and executive decision-making, participants will discover ideas that improve schedule credibility, enhance project visibility, and strengthen project outcomes regardless of industry. Whether you work in construction, infrastructure, energy, aerospace, or defense, this session will challenge conventional thinking about project controls and demonstrate how cross-industry perspectives can elevate the planning and scheduling profession.

Megaprojects carry complexity rarely seen elsewhere: thousands of interdependent activities, dozens of subcontractors, shifting site conditions, expectations measured in billions. Forecasting a job at this scale is a serious undertaking. Yet a project's real cost is how long it takes, not how long we forecast. The best in the space don't stop at predictions. They work closely with the people running the job to influence each week and each day. This panel brings together senior voices responsible for delivering major projects to discuss how project controls can drive velocity by building a culture of accountability and problem solving.

Complex capital programs rarely operate from a single schedule. Owners, contractors, designers, consultants, and other stakeholders often maintain separate schedules developed for different purposes, levels of detail, assumptions, and reporting requirements. While each schedule may serve its intended function, differences in milestones, data dates, work breakdown structures, interfaces, and forecasts can make it difficult to establish a clear and consistent view of overall project delivery. This session explores a practical approach to bringing multiple schedules into alignment without attempting to replace them with yet another schedule. It focuses on establishing common milestones and interfaces, mapping critical information across schedules, identifying meaningful variances and exceptions, and translating those findings into a single, credible view of delivery for project teams and leadership. The session will also explore how AI-assisted schedule reconciliation could support this process by identifying potential milestone matches, missing interfaces, forecast discrepancies, and significant changes across schedule updates. Rather than replacing professional judgment, these capabilities can help project controls teams focus their attention on the exceptions that require analysis and action. Ultimately, the objective is not to force every stakeholder to work from one schedule, but to ensure that everyone is working from one shared understanding of project delivery

This session will begin by establishing a clear definition of the Controls Framework and the key success factors that underpin effective program delivery. It will then explore the drivers behind redefining the Controls Framework, including evolving infrastructure delivery models, shifts in procurement strategies, and rapid technological advancements that are transforming the industry. Looking ahead, the session will examine the future of the program controls workforce and the capabilities required to succeed in an increasingly complex environment. The discussion will conclude with key takeaways and an interactive dialogue. Designed as a workshop, this session encourages active participation, engagement, and the sharing of perspectives to collectively shape the future of program controls.

As infrastructure and capital mega programs continue to grow in scale and complexity, traditional Program Management Offices (PMOs) are being challenged to move beyond project reporting and administrative oversight toward proactive, data-driven decision support. At the same time, advances in AI are creating new opportunities to transform how PMOs monitor program performance, identify emerging risks, allocate resources, and support executive decision-making. This presentation explores how AI is reshaping the role of the PMO across the lifecycle of major capital programs. The session examines AI tools that are either actively being used or are in development related to submittal analysis, schedule review, meeting documentation that are all becoming key inputs for the PMO to manage interdependencies across projects, and surface risks before they escalate into major issues or disputes. Through practical examples drawn from large infrastructure programs, attendees will learn how AI-enabled PMOs can improve portfolio visibility, strengthen governance, enhance cross-project coordination, and provide executives with more timely and actionable insights.

Earned Value Management (EVM) is built on a simple principle: integrating scope, schedule, and cost to provide a more complete view of project performance than schedule or cost data alone. Many projects emphasize one dimension over the other, often avoiding full integration in the absence of a contractual EVMS requirement. While compliance with Federal Acquisition Regulations and standards such as EIA 748e may drive adoption, organizations can still realize meaningful benefits through a scaled approach. Attendees will learn how to: • use existing schedules to build baselines for effective performance tracking • improve forecast accuracy • analyze cost and schedule variances • scale EVM to capture its benefits without the burden of a fully compliant system See how EVM can be introduced using project management practices your organization likely already has in place.

Project controls quietly saves every megaproject from itself — yet in the US, it remains a hand-me-down skill picked up between crisis meetings. The UK and Australia recognised this years ago. With trillions flowing into infrastructure, chips, data centres and energy projects, the US is staffing programmes with people who learned EVM from a YouTube video. That is not a strategy. This session makes the case for accredited university project controls programmes — covering cost and schedule integration, risk quantification, AI literacy, commercial awareness and governance. AI won't replace project controls professionals. It will free them — if we build the pipeline now.

Progressive Design Build (PDB) requires project teams to commit to a Target Price while design evolves — placing intense pressure on estimating, planning and risk management. Traditional report-driven Project Controls cannot support the rapid decision-making this demands. This presentation draws on practitioner lessons from the Scarborough Subway Extension (SSE SRS) — a Canadian transit megaproject delivered by Scarborough Transit Connect (an Aecon JV) for Metrolinx — to show how Project Controls functioned as a confidence engine, not a back-end reporting function. Through an integrated operating system combining governance, estimating, production planning and risk, the team achieved Target Price with confidence despite evolving design maturity. Winner — PCE Mega Project of the Year 2025.

The Department of Defense is transforming how it develops, acquires, and sustains complex defense capabilities. While operational communities increasingly rely on real-time, data-driven decision environments, acquisition governance remains largely rooted in periodic reporting cycles, static baselines, and retrospective Earned Value Management constructs. This structural mismatch creates decision latency, limits early risk visibility, and constrains proactive performance management in an era defined by software intensive systems, rapid integration, and compressed delivery timelines. This paper presents Integrated Program Management 2.0 as a governance framework and operating process for modernized Integrated Program Controls. IPM 2.0 is not a software application or standalone technology tool. It is a structured performance management framework that defines how cost, schedule, technical maturity, supplier readiness, manufacturing progress, and risk information are integrated and used to inform decision making. The framework aligns processes, roles, metrics, and decision forums to enable continuous insight across programs and portfolios. Central to IPM 2.0 is the concept of a disciplined Digital Data Fabric that integrates authoritative execution data across domains. This integrated data environment supports a Unified Performance Ledger, a continuously updated representation of program reality that preserves traceability and transparency. Within this governance construct, advanced analytics such as forecasting, anomaly detection, and dependency analysis generate forward-looking performance intelligence. Capability Threads connect engineering maturity and integration readiness directly to mission outcomes, shifting performance discussions from artifact completion to capability emergence. These multidimensional signals are synthesized into an Integrated Performance Index that enables portfolio-level comparability and executive prioritization. A Common Operating View presents integrated data, indices, and predictive indicators in a shared environment that supports structured, decision-oriented governance sessions. IPM 2.0 reframes Integrated Program Controls as a continuous, collaborative process rather than a periodic compliance activity. It reduces data latency and fragmentation, strengthens forecast credibility, and enables earlier risk intervention without increasing reporting burdens on industry partners. Instead of focusing on variance explanations after the fact, oversight shifts toward anticipatory risk shaping and outcome-oriented decision making.

Project controls has a credibility paradox. The technical rigor that earns a planner or cost engineer a seat at the table is the same rigor that can keep them stuck beside it. They are trusted to report performance, but rarely invited to shape the strategic decisions that data should inform. The profession too often monitors delivery rather than influencing portfolio outcomes and benefits realization. This session presents a practical career-architecture model for developing controls professionals across four altitudes of influence (project, program, portfolio, and enterprise) without trading away the technical foundation that underpins their authority. Drawing on competency-framework design and measurable outcomes, it maps the shift required at each transition: from producing data to interpreting it; from interpreting it to translating it into an executive narrative; and from advising on decisions to owning them. Attendees leave with a diagnostic for identifying individuals and teams on the technical-to-strategic continuum, a competency model built around career progression rather than static job descriptions, and tactics for the hardest transitions: translating cost and schedule insights into board-level decisions, navigating organizational politics, and leading multidisciplinary functions.

What truly differentiates high-performing scheduling organizations from the rest? This session explores the defining behaviors and capabilities of leading teams, with a focus on people, process, and systems. We’ll examine how effective organizational structures and clear translation of contractual requirements drive successful outcomes—while exposing the common pitfalls that hold others back. Drawing on real-world experience across Europe and the US, and spanning Rail, Defense, Commercial, and Heritage sectors, this session offers practical insights you can apply immediately.

On 7 Nov 2025, the Secretary of Defense announces a series of Acquisitions Reforms centered on requirement reform and accelerating fielding of systems to the warfighter. US Congress codified a significant number of the changes in Dec 2025 with the passing of the Fiscal Year (FY) 2026 National Defense Authorization Act (NDAA). Over the past 10 months, the transformation has proceeded at lighting speed creating significant change in how capital assets are planned and managed since the Goldwater Nichols changes in 1986. A significant focus is the wholesale change from program to a strategic portfolio management approach with the creation of portfolio scorecards. The prior 40-year Program Executive Officer structure is transforming to a Portfolio Acquisitions Executive (PAE) construct with significant effects on delegated power structures across contracting, financial/budget, performance management while also attempting to link systems direction to combatant missions with the goal of accelerating how gaps are closed. The talk will provide you an update on the different approaches being taken and the potential effects on commercial industry. US Defense approaches, given its mega size, has historically been a leading indicator of future expectations across many industries in Project Controls.

A project controls platform is only as valuable as the visibility and accountability it enables for the owner. This panel brings together product and professional services perspectives to examine what it takes to successfully implement project controls technology. Panelists will explore key considerations including governance, configurability, data access, process alignment, user adoption, and organizational readiness, while sharing lessons learned from real-world implementations. Attendees will leave with a practical checklist for owners and government sponsors: what to demand before signing, what to establish during implementation, what to watch for during rollout, and how to know their technology is delivering meaningful public value.

Railway network upgrade programmes are among the most complex infrastructure deliveries — executed within live operational environments, constrained access windows, high system interdependency and evolving stakeholder requirements. Conventional deterministic schedules and static cost baselines are structurally inadequate for managing this uncertainty. This presentation advances a risk-integrated framework for target pricing and project controls, tailored to collaborative alliance-based delivery models and grounded in AACE RPs, FTA guidance and EN 50126 RAMS standards. Through Quantitative Schedule and Cost Risk Analysis (QSRA/QCRA), uncertainty is modelled into confidence-based outcomes — P50, P80 — replacing fixed estimates with dynamic, risk-adjusted target prices. The central finding: the primary limitation is not lack of data — but lack of integration.

City of Baltimore department of Public Works is exploring the use of Artificial Intelligence (AI) for real time performance monitoring and risk analysis. The objective of this exploratory study is to enhance predictive forecasting, flag early warning of delays and cost overruns, recommend corrective action based on past project behavior and historic data. AI tools/software were used to model possible construction sequences using resource constraints and activity logic to help identify and optimize the schedule by running a 3-point estimate model (optimistic, most likely and pessimistic) per activity or production rate. This results in side-by-side comparison for crew size, methods and sequencing. In addition, AI tools are useful in doing ‘what-if’ scenarios within minimal time. Overall, the analysis is critical in making informed decisions by providing an early warning system that identifies high-risk items, gaps in resources allocation and validates the sequence of construction. Although this is a limited study of about three projects, this study shows a promising outcome and the use of AI may be expanded to the whole portfolio.

AACE International’s Cost Estimate Classification System aligns estimate purpose with project maturity to support stage-gate decisions. Estimates traditionally progress from Class 5 to Class 1 as scope definition, engineering detail, and cost data increase, with accuracy refined through risk analysis and documented in the basis of estimate. The growing use of artificial intelligence is transforming this process. Applications such as automated quantity extraction, machine learning–based parametric modeling, and real-time probabilistic analysis can accelerate estimate maturity and provide continuous confidence updates. However, they also introduce challenges related to data integrity, model reliability, and transparency that must be addressed to maintain credibility. This paper examines how AI may supplement the classification of estimates and enhance decision-making practices. It proposes an “AI-aware” framework with three dimensions: information fitness index (IFI), model risk grade (MRG), and automation level (AL) to integrate AI while preserving governance, accountability, and decision confidence.

Capital improvement programs often struggle with outdated or inconsistently applied project controls processes, resulting in cost overruns, schedule delays, design quality issues, and increased claims exposure. This presentation introduces an integrated phase-gate project controls process that modernizes construction management by aligning cost, schedule, risk, and quality/claims management across the full project lifecycle. The session will examine common root causes of process failure, outline a practical methodology for evaluating and improving existing organizational processes, and demonstrate how structured gate reviews can strengthen governance, improve decision-making, and support design-to-budget and design-to-schedule outcomes. Attendees will gain a practical framework for improving predictability, transparency, and overall performance in capital improvement program delivery.

We will briefly outline the quantitative risk workshop process. Then take a deeper dive into how project participants can best engage with the risk process to inform decisions and achieve better project outcomes. It requires the active and informed participation of the owner, owner’s rep, design team, contractor, and other stakeholders to receive maximum benefit from the risk management process.

This session explores what owners truly need from contractor schedules: a shift from simply reporting progress to actively managing it. By using the schedule as a genuine forecasting tool rather than a static report, teams can move from reactive updates toward real predictability — giving owners the confidence to make informed decisions.

Change orders and claims for delay are more quickly and effectively resolved when the project record clearly reflects what happened, when it happened, and how it affected the project. This session will focus on proactive schedule management strategies to keep schedule updates aligned with project reality, accurately reflect the impact of delay events, and ensure that project documentation tells a complete and consistent story. The goal is to reduce surprises and establish a clear basis for entitlement to support earlier project-level resolution, so delay discussions can focus on duration and cost rather than arguments over whether the issue caused delay at all.

What does an "under control" project actually look like in the real world? This session brings together experts from the US and UK to break down the behaviors, metrics, and management styles that lead to successful delivery. Walk away knowing exactly which controls are essential, how to spot the earliest indicators of trouble, and which processes you should consider eliminating today.

Effective and ineffective ways to plan and schedule work with field personnel.

Schedule requirements and reviewer comments are usually well intended, but they may not always be in alignment with the project's best interests. This presentation will focus on the common project requirements and schedule comments contractors receive through the lifecycle of a project schedule that if rigidly enforced will actually be a detriment to the quality of project schedule and the success of the project. This session will present the contractor's perspective on these challenges and how to work together towards the best outcome for the project.

The federal government manages one of the largest capital construction portfolios in the world. The U.S. Army Corps of Engineers, Naval Facilities Engineering Systems Command, Air Force Civil Engineer Center, U.S. Coast Guard, and the Department of Veterans Affairs collectively oversee thousands of active projects annually — spanning hundreds of installations, multiple delivery methods, and some of the most complex reporting requirements in the industry. The challenge isn't a shortage of data. It's that the right data rarely reaches the right people at the right time. Project teams produce it. Leadership needs it. And somewhere between the field and the executive briefing room, visibility breaks down. This plenary session brings together senior leaders from across the federal construction enterprise to discuss how their agencies are confronting that gap — standardizing data across non-standard portfolios, meeting federal reporting mandates without sacrificing field-level flexibility, and leveraging technology to turn project data into program intelligence.

The most capable project controls teams still struggle when their technology doesn't match the way they work. Rigid platforms force process changes. Disconnected systems fragment data, restrict visibility and introduce cybersecurity risk. When you don't control your data, you don't truly control your project outcomes. This session explores how a new generation of connected, configurable construction management platforms are fundamentally changing how project teams operate (leveraging AI to shift from reactive controls to predictive, proactive delivery). Attendees will leave with a practical evaluation framework built around two criteria: connectivity (who controls and governs the data) and configurability (how well the platform adapts to your team).

Project controls teams capture enormous volumes of data — timesheets, cash flows, risks, progress, quantities, RFIs — yet benchmarking across projects, programs and organizations remains stubbornly manual. The data exists; it just isn’t comparable. Every organization names, structures and classifies its records differently. This session presents UniPhi Chrysalis, a working data transformation pipeline that turns live project data from many independent SaaS deployments into a single, governed benchmarking dataset. We walk through the architecture end to end: scheduled extraction from each client instance via API into a medallion-structured data lake; metadata enrichment; and the core of the transformation — an AI-assisted classification engine that maps every record to a common classification system — Uniclass 2015 (EF, Ss, Pr, Ac) in our case, though the pattern applies equally to OmniClass, UniFormat or MasterFormat. Deterministic rules handle clean, repeatable mappings; a large language model proposes candidates for the fuzzy remainder; every code carries a confidence score, with below-threshold matches routed to human review — nothing lands in the benchmark silently. Confirmed matches feed back into the rules layer, so the system improves with use. The result is the “butterfly effect”: data captured once, at the point of work, re-emerges as self-service asset benchmarking — estimated costs, phasing and classification-aligned breakdowns drawn from real delivered projects.

Construction project controls have long been defined by a fundamental tension: the data needed to make good decisions exists somewhere in the project record, but finding it, reconciling it, and presenting it in time to act on it is a full-time job in itself. Submittals pile up. RFIs multiply. Change orders accumulate. And somewhere in that volume of documents, the signals that should be driving owner decisions get buried. Agentic AI is changing that equation — not as a distant promise, but as a practical capability that leading capital program teams are deploying today. This session takes a ground-level look at how AI is being used to automate the collection, classification, and reconciliation of project data across the full document ecosystem. Attendees will see how agentic workflows can extract structured information from submittals, RFIs, change orders, and other construction documents, cross-reference it against established values and source records, and surface the discrepancies and trends that matter most to owners and project controls professionals. Drawing on real-world examples from university capital programs, the session will walk through the before and-after of an AI implementation: what the data environment looked like before automation, what the pilot targeted, how it was scoped and deployed, and what measurable outcomes resulted. The goal is to give attendees a concrete and honest picture of what AI can and cannot do for project controls today. Attendees will leave with a practical framework for identifying the workflows in their own programs most ripe for automation, a strong understanding of the technological capabilities available, and a clear methodology for building the business case needed to win internal buy-in. Whether you are early in your exploration of AI or already piloting solutions, this session will sharpen your thinking and accelerate your path to implementation.

Most Prediction AI in project controls forecasts schedules and costs. But roughly 65% of project failures trace to management and people issues, governance breakdowns, decision latency, and contract behavior no schedule model can see. That is the gap the xPM Strategic Decision Engine closes. Built on 25 years across 13+ countries and over $6B in projects, and doctoral research on neural networks for cost intelligence, the Engine is a 7-layer Prediction AI architecture for every scale of construction, every delivery model, and every stakeholder seat: from project owner to specialty sub, pre- to post-construction. Each project is read through seven expert layers, Strategic Value Core, Governance Protocol, Capital Memory, Contract Risk Reality, Organizational Force Field, Physical Truth, and Digital Nervous System. A Cross-Layer Synthesis Agent then runs Conflict Detection, Compounding Risk, Priority Matrix, Systemic Weakness, and a composite xPM Score, compressing 169 techniques, 16 domains, 84 decision methods and 9 PM knowledge areas into one executive view. Four governing questions drive every output: What should be? What happened? What is happening? What will happen? turning data into expectation, history, present truth, and prediction owners and executives can act on with confidence. You will leave with a working framework for predicting failure before it surfaces in the numbers, and the language to brief your owner, your board, and your project team with certainty.

Delivering hyperscale data centre programmes demands excellence across risk, schedule and cost management. Yet even the most advanced tools fail when organisations face entrenched processes, siloed teams and resistance to change. Tom Phythian and Hasanthi Wijeratne — who together led the full lifecycle rollout of Omega 365 at Microsoft across one of the world's largest hyperscale data centre portfolios — share real-world lessons on the people and process dimensions of technology-enabled transformation. Key topics include overcoming organisational resistance, breaking down silos, change management at enterprise scale, and measured outcomes across hyperscale capital deployments. The session also highlights how Microsoft is applying AI to augment risk identification, forecasting and decision-making.

A time impact analysis (TIA) that sources the current update when a delay event arises, before having been superseded by the next update, is a near-real-time prospective TIA. A TIA time- distant from an unresolved delay that sources the update current when the TIA is performed is a deferred prospective TIA. Per RP 52R-06, at some point, deferring preparation and approval so diminishes the value of a prospective TIA that performing a retrospective, forensic TIA becomes appropriate. This presentation identifies considerations for deferring a prospective TIA and provides causal modeling and analysis guidance.

Sustainability reporting on capital projects is often disconnected from the systems used to manage cost, schedule, and performance. This session presents a different approach: integrating greenhouse-gas and other sustainability metrics directly with CPM schedules and project-controls data. By linking the carbon impact of a project to the CPM schedule’s activities, project teams can move from standalone carbon reporting to active management. The presentation will examine how existing technology can be leveraged to improve data reliability, identify sustainability impacts of schedule and scope changes, support executive reporting, and make carbon performance part of the same decision-making framework used for cost and schedule.

Complex programs are under growing pressure to move from retrospective reporting to earlier, predictive insight—but analytics can only be as reliable as the project controls environment beneath it. Drawing on the Dodge digital maturity research and lessons from real-world adoption patterns, this session explores how integrated cost, schedule, change, and forecast data create the foundation for trustworthy program intelligence. Attendees will learn what distinguishes a controls environment that is simply collecting data from one that is ready to support meaningful predictive analytics.

As infrastructure programs grow in scale, complexity, and stakeholder expectations, the role of Program Management is evolving beyond traditional delivery oversight. Today's clients require strategic partners who can integrate governance, technology, data, risk management, stakeholder engagement, and organizational alignment to achieve successful outcomes. This presentation will explore AECOM's journey in shaping the future of Program Management through a client-centric and outcome-driven approach. Drawing on experiences from some of the world's most complex infrastructure programs, we will discuss how Program Management is transforming from a coordination function into a strategic capability that enables organizations to navigate uncertainty, improve decision-making, and deliver lasting value. The session will highlight emerging trends, lessons learned, and innovative practices that are redefining how programs are initiated, governed, and delivered. Attendees will gain insights into how integrated Program Management approaches can strengthen resilience, enhance collaboration, leverage digital solutions, and support clients in achieving their strategic objectives while delivering complex programs with greater certainty and confidence. As the industry continues to evolve, Program Management must move beyond managing projects to enabling outcomes. This presentation will demonstrate how AECOM is helping shape that future and partnering with clients to address the challenges and opportunities of the next generation of infrastructure delivery.

The Future of Major Program Delivery is the most extensive, current research on megaproject delivery analyzing 5,000+ present-day mega programs upwards of $1 billion, many over $10 billion. It examines why 90% of major programs fail to meet cost, schedule, and/or ROI targets. For an unprecedented $15 trillion invested in active megaprojects—wherein failures place $1.5 trillion of economic growth at risk—the report finds systemic delivery barriers and success measures proven to improve delivery certainty and catalyze long-term value, including collaborative models and multidisciplinary management aligning people, organizations, processes, data, and tech with digital AI to optimize outcomes.

Artificial intelligence is rapidly changing how organizations plan, monitor, and deliver complex projects. However, adopting AI tools does not automatically create better decisions, stronger controls, or more predictable outcomes. Without reliable data, aligned governance, prepared teams, and clear accountability, AI can accelerate existing weaknesses just as easily as it can improve performance. This presentation examines why project controls is uniquely positioned to serve as the bridge between AI adoption and successful project delivery. Project controls professionals operate at the intersection of data, cost, schedule, risk, change, performance, and leadership decision-making. That position gives the function a critical role in assessing whether an organization is truly ready to use AI responsibly and effectively. Using a practical AI Readiness framework, the session explores three foundational areas organizations must address before scaling AI: data readiness, organizational capability, and strategic alignment. It also introduces the E³ approach—Empower, Execute, and Elevate—as a structured method for preparing people, implementing AI-enabled workflows, and continuously improving performance. Attendees will learn how project controls can move beyond reporting and transactional execution to become a strategic decision-support function that strengthens project predictability, risk visibility, workforce readiness, and delivery confidence. The presentation will also identify common readiness gaps, practical actions leaders can take immediately, and the essential role of human judgment in an increasingly AI-enabled project environment.

Project controls teams do not need another black-box forecast, built from shaky project data and processes. The basics of project controls is the driver of success. A monthly update cycle that takes six-plus weeks, built on undocumented baselines, unapproved changes, and skipped assurance means late decisions based on poor data. This session shows AI coworkers running that update process in hours, not weeks. Turning documents and site records into traceable schedule updates, assuring supplier programmes, and writing impact analyses.

Facility owners have traditionally managed capital construction and ongoing maintenance using separate systems, creating fragmented data, duplicated effort, and limited visibility across the asset lifecycle. As organizations face aging infrastructure alongside continued capital investment, the need for an integrated approach to facilities information management has become increasingly important. This presentation explores how a unified project and facilities management platform can support both capital project delivery and deferred maintenance within a single governance framework. By leveraging shared asset data, standardized business processes, configurable workflows, and integrated reporting, organizations can seamlessly transition information from design and construction into operations without manual re-entry or loss of institutional knowledge. The session will examine practical approaches to managing two interconnected lifecycles: capital project delivery and operational maintenance. Attendees will learn how facility condition assessments can be transformed into prioritized maintenance backlogs, enabling organizations to quantify deferred maintenance, evaluate risk, allocate funding, and execute renewal programs using consistent data and decision-making processes. Real-world implementation strategies will demonstrate how standardized workflows, portfolio-level visibility, and integration with enterprise financial and work management systems improve planning, governance, and long-term asset stewardship. Participants will leave with a framework for consolidating facilities data into a single source of truth that supports informed investment decisions, improves operational efficiency, and strengthens the connection between new construction and ongoing asset management.

Managing complex capital programs requires absolute network stability and proactive enterprise oversight across the entire asset lifecycle, spanning from initial baseline development through to final project closeout. Traditional schedule tracking often isolates critical network updates, causing project participants to operate in information silos where the true lifecycle impact of delays remains hidden. To resolve this, this presentation introduces a practical governance framework centered on AI Algorithmic Forward Path Activity Analysis. By filtering the master schedule into distinct operational vectors, this methodology delivers immediate strategic advantages across communication, stakeholder management, transparency, and risk reduction. Crucially, it maps and identifies the hidden logic dependencies between diverse stakeholders, subcontractors, and engineering disciplines, equipping them with the clear visibility to independently review their specific activity blocks and evaluate how their localized timelines interface with the macro project network at any stage of execution.This comprehensive operational transparency establishes a rigorous foundation for proactive change control, closeout management, and predictive risk engineering. Enhanced communication between different stakeholders is a core outcome of this approach, transforming adversarial relationships into collaborative alignments. By streamlining communication across all project participants, the framework removes administrative noise and brings immediate clarity to complex project modifications. For executive leadership, this methodology completely revolutionizes downstream decision-making, forensic analysis, and commercial accountability. When combined with advanced 5D advancements, owners and directors gain absolute logical surety to visually simulate scope variations and stress-test contract amendments. This predictive data integration provides unprecedented change order and Time Impact Analysis (TIA) clarity to executives, driving high stakeholder involvement, reducing macro-project volatility, and establishing an empirically defensible mechanism to confidently govern contract adjustments and closeout documentation without jeopardizing key project milestones.

Traditional acquisition cost estimation uses a waterfall path: slow queues and reviews. We built a market-like alternative using agile methods, pricing work by information and speed. The Sprint lane time-boxes short tasks into user stories with ready/done criteria: data pedigree, traceable estimates, and acceptance checks. Every three weeks we deliver an MVCE that evolves through risk dials and what-if trades, giving leaders choices on scope, risk, and time. The Kanban lane handles deeper work: Life-Cycle Cost Estimates and method development, managed with WIP limits and flow metrics to maintain rigor. We combine cost estimation, agile methods, and economic thinking in one framework and tie decisions to sprint cadence. Across 17 sprints the team delivered dashboards, tools, and deep dives and absorbed unplanned demand. The Kanban lane cleared 1,300 points with fewer task switches and higher rigor, enabled by a cost backlog, MVCE gates, traceable tickets, and dual-hatted leads aligned with contracting needs.

A Schedule or Cost Risk Assessment can be an intimidating exercise... but it does not have to be! This session will help to demystify Risk inputs and reporting for all levels of experience. We will discuss the best methods of gathering inputs, including one vital prerequisite. Further, we will examine risk assessments in the session and gain consensus on the likely conclusions, ultimately equipping the group to be able to perform these while empowering analysts to brief their team using their own unique style. After this session, attendees will: • Understand the most commonly used risk inputs for a monte-carlo based Risk Assessment • Explain the distinction between a Risk Exposure Histogram and a Risk Drivers Tornado Chart • Quickly assess charts to be prepared to brief risk in an impromptu fashion • Steer Program Managers and Executives to the most important Enterprise and Project threats to mitigate so that the appropriate decisions can be made.

Mega capital programmes are delivered through complex contracting strategies, multiple stakeholders and accelerated schedules — introducing significant uncertainty in cost and schedule outcomes. Risk management is frequently treated as a parallel activity rather than an integrated component of project controls. Risk registers are developed and workshops conducted — yet outputs remain disconnected from cost forecasts, schedule updates and contingency management. This presentation introduces a practical framework connecting risk identification, structured risk registers and periodic reviews with core project controls processes — including Cost & Schedule Risk Analysis (CSRA). Drawing on EPC and EPCM programme experience, attendees will learn how to embed risk thinking directly into forecasting and decision-making — moving beyond standalone risk registers.

Forensic delay analysis often presents the challenge of distinguishing critical project impacts from hundreds of minor schedule variations within a given window. This presentation introduces Arrows Analysis, methodology built into Steelray Delay Analyzer, designed to provide schedulers with a fair, logic-driven approach to measuring activity delays and project finish impact.

In today’s rapidly evolving climate landscape, traditional risk management is no longer enough. This presentation reveals practical strategies for integrating climate risk into project controls and risk registers, empowering organizations to anticipate, adapt, and thrive amid uncertainty. Attendees will explore proven tools like climate scenario analysis, stakeholder engagement, and real-world case studies to identify both acute and chronic risks, enhance resilience, and unlock value for their projects. From leveraging climate data to embedding best practices for regulatory compliance and stakeholder confidence, this session provides a step-by-step roadmap from Risk to Resilience. Join us to learn how organizations are transforming risk registers into dynamic tools that safeguard investments and ensure long-term success.

Artificial intelligence (AI), particularly large language models (LLMs), are rapidly entering construction cost estimating and project controls, promising faster data synthesis, earlier decision support, and standardized workflows. Yet these same systems can produce hallucinations: confident, fluent, but factually incorrect or fabricated assertions. Hallucinations differ from ordinary software defects in that they are opaque (difficult to trace), highly persuasive (professional tone, formatted outputs), and contextually embedded (surrounded by otherwise correct content). In high stakes estimating contexts, this combination creates a systemic risk of false confidence that can propagate into budgets, contingencies, bids, and claims. This paper explains why hallucinations occur and how they manifest in estimating practice; offers tight narrative examples from other industries to show real world consequences; and proposes AI-Assisted estimate validation framework, a defense in-depth mitigation framework aligned to NIST’s AI Risk Management Framework (AI RMF 1.0), ISO/IEC 23894 (AI risk management), and ISO/IEC 42001 (AI management systems). The paper concludes with an implementation roadmap and a practitioner checklist that embeds human in the loop validation, data provenance, structured prompting, retrieval augmented generation (RAG), and auditability into everyday estimating workflows.

Projects rarely fail for lack of information. More often the data was fragmented, accepted without challenge, or summarized into more confidence than the evidence justified. A dashboard shows green while untested assumptions, weak schedule logic, understated cost, and disconnected risks build beneath the surface. This session examines how independent assurance exposes the gap between reported performance and actual project health. The issue is not whether reports are technically correct—it is whether schedule, cost, risk, and scope tell the same story. Each control function can perform its role flawlessly while no one reconciles the outputs as a single body of evidence. Drawing on cost estimating, scheduling, and program governance experience across major federal programs, this session identifies the conditions that let hidden risk go undetected, and shows how assurance strengthens resilience by surfacing problems early enough to act. Attendees leave with practical questions to challenge reported status.

On megaprojects, dashboards can remain green while the project is silently losing control. The warning signs often appear first in unresolved design reviews, slow or incomplete decisions, fragmented teams, and reports that describe problems without driving action. Drawing on more than two decades of project and contract management experience across oil and gas, mining, power, transportation, and heavy infrastructure, this session examines why sophisticated project controls do not automatically create delivery certainty. Across industries and delivery models, the same patterns repeat: design reviews become open-ended, value engineering continues too late, operations and stakeholders enter after key decisions, and accountability disappears across organizational boundaries. The session reframes design review as a critical project-controls interface where scope, cost, schedule, risk, constructability, operability, and commercial exposure converge. It also explores why stable teams, clear decision rights, and concise decision-ready recommendations matter as much as the underlying data.

This presentation introduces the agency’s mission and responsibilities, then introduces the role of project controls in supporting successful project delivery. It defines project controls, outlines the key areas they cover, and explains how these practices help manage project performance throughout the project lifecycle. We will discuss recurring challenges—including cost creep, design delays, construction cost overruns, and construction delays—that affect budgets, schedules, and outcomes. These challenges establish the need for a proactive and consistent approach to identifying potential risks before they escalate. The presentation will focus on the development of the Risk Identification Tool (RIT), highlighting its purpose and role in improving early risk identification, supporting informed decision-making, and strengthening the agency’s overall project control practices.

In design-build delivery, disproportionate risk allocation drives cost overruns, schedule delays, forecast volatility, litigation, adversarial relationships, insurance coverage gaps, compromised deliverables, and claims. Misaligning risk with control compromises project controls processes, including estimating, scheduling, and cost forecasting. The Design-Build Institute of America (DBIA) emphasizes that successful design-build projects require equitable risk allocation to the best-equipped party, enhancing predictability, integrity, and contingency effectiveness. This session examines practical mechanisms influencing performance, including limitation of liability, consequential damage waivers, pre-bid scope definition, integrated project delivery principles, contingency allocation, and coordinated insurance. These are discussed as levers for improving transparency, reducing uncertainty, and strengthening cost and schedule control. The session also explores innovations like data-driven tools and predictive analytics for early risk identification before they materialize into cost and schedule impacts. Attendees will gain actionable strategies to align contractual risk with project controls, boosting forecast confidence and promoting proactive risk management for better results.

Artificial intelligence is transforming how project delivery organizations manage schedule, cost, risk, reporting, documentation, and performance visibility. However, its potential often fails to translate into sustained operational value. Pilot initiatives frequently succeed in isolation but struggle to scale, while tools are deployed before organizations are fully prepared to use them responsibly. As a result, project controls professionals are left without clear guidance on where AI fits, how to validate its outputs, and who is accountable when issues arise. This presentation introduces a practical AI–PMO Organizational Readiness Framework for project-driven organizations. It positions the Project Management Office (PMO) as a natural starting point for AI adoption, given its role at the intersection of project data, governance, procedures, reporting, quality assurance, and executive decision support. The framework outlines eleven key readiness dimensions required to move from controlled pilot initiatives to scalable organizational adoption: leadership and sponsorship, workforce capability, data readiness, workflow redesign, role alignment, responsible AI governance, technology integration, change adoption, value measurement, scale-up readiness, and AI agent quality assurance.

Developing a ten-year capital roadmap for a major public utility is more than an engineering exercise; it is a complex financial and operational puzzle. This presentation delivers an inside look at how the San Francisco Public Utilities Commission (SFPUC) successfully established its $12.5 Billion Capital Improvement Plan (CIP) for FY 2026–27 through FY 2035–36 amid unprecedented market headwinds. Attendees will learn how the SFPUC moved away from siloed planning by launching the cross-enterprise Capital Planning Improvement Initiative. Faced with initial project requests that drastically outpaced revenue limits, the agency instituted a strict, multi-phase governance framework to bridge the gap between engineering needs and ratepayer affordability constraints. Key takeaways and focus areas include: · Data-Driven Prioritization: How the SFPUC utilized risk-based validation models to separate critical infrastructure demands from lower-priority project requests. · Rigorous Deliverability Analysis: The method the Engineering Management Bureau (EMB) used to stress-test the plan against actual human resource constraints, factoring in vacancy rates and a citywide hiring freeze. · Predictive Cost Controls: Real-world application of compounding escalation rates and a proactive +5% market condition factor to insulate the portfolio against evolving U.S. import tariff shocks. · Portfolio Synchronization: The process of aligning contractor capabilities, public works coordination, and software data workflows (P6, Unifier, and SharePoint) to drastically reduce unspent carry-forward balances. Ultimately, this session demonstrates how robust program controls turn a massive, volatile wish list into a realistic, deliverable, and politically viable $12.5 billion baseline.

Availability, maintainability, and reliability are the main tenets of the standard OSD RAM-C report. The RAM-C report documents and tracks the sustainment and support metrics of a fielded system throughout its lifecycle. How are these metrics determined, and how do they relate to the overall concept of system affordability? The methodology behind these optimizations is rudimentary but are informative for both cost analysts and systems engineers involved in conducting trade-off analysis during early-life cycle conceptual design of a system. This topic will illustrate these interactions through a time-stepped simulation of system use, maintenance, failures, repairs, and associated costs

Capital projects executed by the National Nuclear Security Administration (NNSA) often experience drastic cost growth across all phases of a project despite extensive planning. As part of a detailed exploration of this phenomenon, the NNSA Office of Programming, Analysis, and Evaluation (PA&E) identified cost growth within specific Work Breakdown Structure (WBS) elements. To achieve this, PA&E mapped project Earned Value Management (EVM) data to a standardized WBS using a hierarchical classification machine learning model. The team verified and validated the model outputs, tracking cost growth across numerous WBS elements of NNSA projects over multiple years of post-baseline execution. Study findings confirm that EVM data serves to enable first-time analytics into which lower-level cost elements tend to experience more growth in the NNSA. PA&E’s detailed WBS cost growth framework facilitates estimators to better quantify cost growth risks early, identify mitigation strategies, ultimately leading to more informed mission execution.

Government agencies have long struggled to understand when specific work occurs throughout project execution relative to when it is planned. This study defines phasing estimating relationships across lower-level WBS elements using time-phased EVM data from the NNSA infrastructure portfolio. By aligning performance to a standardized WBS framework, consistent timing and sequencing patterns were developed, identifying how elements of cost execute across the project lifecycle. These relationships establish the ability to benchmark expected execution timing. The framework enables evaluation of baseline feasibility and assessment of spend plan realism, equipping decision-makers with actionable insight to drive more reliable program execution.”

Many project challenges can be traced to decisions made before risks, costs, and value opportunities are fully understood. This session introduces the fundamentals of a phase-gate project controls framework and explains how risk management and value engineering work together to support better project decisions. Attendees will learn how structured gate reviews help teams evaluate scope, cost, schedule, and project risks before advancing to the next phase. Using practical infrastructure examples, this presentation provides young professionals with a simple, repeatable approach to improving project outcomes, reducing rework, and delivering greater value throughout the project lifecycle.

Extension of Time (EOT) claims are a fundamental part of construction project management, requiring both contractual compliance and sound schedule analysis. This session introduces the core principles of evaluating project delays using dynamic schedule analysis that reflect changing project conditions rather than static schedule assessments. It explains how changes in the critical path and near-critical activities can influence EOT entitlement and why understanding these concepts is essential. Through practical examples and industry best practices, the session provides young professionals with a foundation for understanding dynamic schedule analysis and its role in fair, transparent, and well-supported EOT evaluations.

Cost, schedule, and scope are the three fundamentals every project controls practitioner is trained to manage. Yet on too many projects, they're tracked in isolation. Cost reports live apart from schedule updates. Percent-completes get reported without tying back to either. The result is data without control. Without a performance measurement baseline that integrates all three, teams end up reacting to problems instead of predicting them. Earned Value Management gives practitioners something few other methods can: an objective, integrated view of cost, schedule, and scope performance that supports early trend identification, reliable forecasting, and defensible decision-making. This session examines how EVM operationalizes these core project controls principles, resulting in relevant data management can act on. Rather than framing EVM as a compliance exercise, this session makes the practitioner's case for it: Why integrating cost and schedule performance measurement produces better project outcomes, and what it takes to apply EVM effectively as a working discipline rather than a reporting formality. Attendees will leave with practical arguments for elevating earned value from a nice-to-have to a foundational project controls practice.

Traditional Earned Value Management (EVM) has significant limitations for schedule control because its schedule measures are cost-based, aggregate, and can lose meaning at project completion. This presentation introduces Earned Time Management (ETM), a fully time-based method that measures schedule performance from the activity level through lags, overlaps, paths, and the critical path. ETM does not require cost or resource loading and can be used with tools such as Primavera P6 and Microsoft Project. The presentation also demonstrates how ETM forecasts finish dates under diEerent performance assumptions and supports schedule-recovery decisions

Capital programs invest heavily in PMIS platforms, scheduling tools, and AI-enabled solutions, yet project teams still rely on spreadsheets and offline trackers to manage critical information. These shadow systems are rarely technology failures. They are symptoms of weak project controls fundamentals: gaps in governance, work breakdown structures, change control, data ownership, and reporting quality. Drawing on lessons from large-scale digital transformations, this session shows how technology amplifies strong project controls processes but cannot replace them. Attendees will learn to identify the control deficiencies behind shadow systems, apply a simple diagnostic framework, and strengthen the fundamentals that drive predictable outcomes.

The construction industry has often adopted new technologies unevenly across capital project delivery. As artificial intelligence reshapes capital planning, project controls, and project execution, many organizations continue to struggle to achieve the outcomes they expect. While AI promises to transform forecasting, reporting, risk management, and decision-making, stakeholders often lose confidence when these capabilities are applied to fragmented workflows, disconnected systems, and inconsistent data. This session outlines a practical roadmap for AI adoption in regulated capital infrastructure environments by addressing the critical relationship between process, data, and technology transformation. Before AI can deliver measurable value through automated reporting, predictive analytics, and intelligent risk management, organizations must establish standardized delivery processes and harmonize information across project controls, project delivery, capital investment planning, financial management, and business objectives. The result is a connected data foundation that reduces inconsistency across the broader asset lifecycle. The success of deploying AI in regulated, safety-critical environments rests on three foundational elements: establishing repeatable and disciplined business processes, creating trusted and integrated data, and implementing a phased approach to technology transformation. In simple terms, process creates repeatability, data creates visibility, and AI creates leverage. By connecting project intelligence to the broader capital infrastructure and asset management ecosystem,

Get up to speed on the Project Management Institute (PMI) updates to ANSI Standards on Project (2025), Program (2024) and Portfolio (2027) and Standard for EVM (2019. This session, taught by John Driessnack, who was involved in 3 of the last 4 ANSI standard updates, will provide a mapping across the standards and key insights. Understand the impact of the standards migrated to a Principle/Performance Domain format. The PMI Process Guide (2023), which is a cut down reprint of PMBOK 6th will also be discussed along with how this effect the broader project control environment.

What Happened? Building a Project Memory Before You Need It It’s easy to remember what happened on a project last week. But what about last month? Last year? Five years ago? When a project requires a time impact analysis, delay claim or dispute the answers are often buried in hundreds—or thousands—of weekly reports, meeting minutes, schedules, emails, RFIs, submittals, and change documents. Reconstructing the project history can become a painstaking exercise in searching for individual pieces of information and trying to determine what actually happened, when it happened, and why. What if we documented the project in a way that continuously preserves its history as the project evolves? Rather than focusing solely on producing the next weekly report, this presentation explores practical methods for creating a structured, evolving record of project events, decisions, schedule changes, impacts, and milestones. The goal is to establish a “project memory” that allows the team to quickly understand not only where the project stands today, but how it got there. The session will explore how consistent documentation standards, meaningful milestone tracking, schedule comparisons, and email chains can transform years of project information into a usable history. Most importantly, we will discuss whether project teams should establish a common standard for what must be tracked, how it should be tracked, and how that information should evolve throughout the life of a project. Because when the question eventually becomes “What happened?”, the answer should not depend on who happens to remember—or how long it takes to find the report.