The Risky Planner™

Send us Fan Mail

A quantitative risk assessment puts a probability, a cost impact, and a schedule impact on each quantified risk. A Monte Carlo simulation then samples the full set thousands of times. The result is a range of outcomes. You fund your total risk exposure, not individual risks.

Nate Habermeyer and Albert Brier, Director, Project Controls at Dokainish, break down how a QRA works. Albert uses two six-sided dice to visualize probability. They then cover the difference between qualitative and quantitative scoring, the risk register versus the risk universe, the alternatives to Monte Carlo simulation, and Albert's advice for anyone starting to plan a capital project, since most projects dramatically undervalue risk on day one. Teams typically run a QRA before a funding or pre-execution gate, so the inputs need to be right before the model runs.

Albert uses two six-sided dice to visualize probability. They give 11 possible totals, yet no total carries a one-in-11 chance. One combination makes a two, and seven is the most likely total. Add more dice and the results grow complicated. Albert says Dokainish does a QRA by rolling many dice together, one for each risk and estimating range. Monte Carlo simulation does this thousands of times and shows where the results concentrate.

A risk register covers only the risks you named. Albert calls the full set of credible threats and opportunities the risk universe. Systemic risk comes from how your organization operates, such as a board that meets monthly with an agenda set three months ahead. Base uncertainty is the range around an estimate before any discrete risk applies. A full accounting of quantitative impact includes both.

The first simulation gives an aggregate model, and funding decisions use it. Project managers need the disaggregated view, which sensitivity runs produce by including and excluding each risk. Albert explains why you fund total exposure and not individual risks. He also describes the risk workshop, which can take a week on a register of a few hundred risks, and the three inputs the model needs, a schedule, a cost estimate, and a risk register.

Albert describes parametric estimating, which draws on historical project data, such as a large company's database of tens of thousands of capital projects. He points listeners to Bent Flyvbjerg's writing on reference class forecasting. He also covers the limits of probability times impact. That method gives the mean but no range, and it handles schedule poorly. He shares his view that the register as a large spreadsheet will probably give way to a network of causes, events, consequences, and responses.

Teams usually run a QRA before a funding or pre-execution gate. At that point the inputs can still change, and the project team is about to carry the register into execution. The workshop before the gate sets the quality of the model and of the register that follows.

Some teams treat a completed register as the full risk universe. A full accounting adds base uncertainty and systemic risk. The workshop before the gate is a strong opportunity to correct the inputs.

Read the companion blog post: https://dokainish.com/insights/what-is-a-qra/

Presented by Dokainish & Company www.dokainish.com

The Risky Planner podcast delivers expert insights on project controls, capital project management, and strategic planning for today's complex business environment. Subscribe for regular episodes featuring industry leaders and practical advice.

Send us Fan Mail

Fifteen people at the AACE conference in June answered the same five questions about AI in project controls: what they are building, what excites them, and what they have learned. Their answers split into two groups. Software vendors describe AI products already in market. Practitioners describe AI use that is early, cautious, or absent.

Albert Brier hosts this full set of interviews from the AACE Expo floor. He covers vendors building AI-driven scheduling, predictive risk models, and natural-language schedule queries, then hands the microphone to project directors, risk principals, and PMO leaders working construction, nuclear, and infrastructure programs. The pattern that emerges: vendors talk about AI as a core product feature. Practitioners talk about AI as something they are still evaluating.

Girish Bhatia of ConstructMind describes cutting schedule generation time from 25 days to 25 minutes using a "human AI human" architecture, where AI handles logic and duration calculations and humans validate the output because AI cannot take liability for the result. Philip Talbot of Nodes and Links describes AI that lets users query a schedule in natural language, isolated from the open internet so project data never leaves the client's environment. Rhys Phillips of nPlan describes predictive models trained on nearly a decade of historical project outcomes to forecast duration and risk on new projects. Rohit Sinha of SmartPM Technologies explains why his team builds custom models instead of using general-purpose tools: general-purpose models "are not very good at construction," and the stakes on projects worth hundreds of millions of dollars do not tolerate wrong answers.

The practitioners tell a different story. Justin Jacobsen of MBP says his team is still in an exploration phase, mostly using AI to help build internal software rather than to run project controls directly. Matthew Schoenhardt, who has run a quarter trillion dollars of quantitative risk analysis, says he is doing "nothing really" with AI yet, though the conference gave him ideas. Sara Horsey of Bridging Pennsylvania Constructors says her team uses AI for consolidating safety statistics but has not implemented it on the project controls side. Holly Parkis describes a risk-based, cautious approach: AI as a tool, not a driver, pending solutions to hallucination and cost problems.

Several interviews single out data centers as the sector moving fastest, with procurement backlogs running five to eight years and hyperscalers scaling teams to match. Matthew Schoenhardt connects that pace to a broader industry shift away from formal quantitative risk analysis on owner-funded megaprojects. Rachel Fleming of MBP and Diana Nada both name communication, not technology, as the lesson they carry into every project. Tracy Leung of Ontario Power Generation discusses a $700 million equity investment from the Williams Treaty First Nations into the Darlington New Project small modular reactor program, and what genuine partnership with Indigenous nations requires beyond a permitting step.

Software vendors at AACE are building AI products for scheduling, risk analysis, and predictive forecasting. The practitioners who would use those products are, by their own account, still in exploration, still cautious about data security, and in at least one case still deciding whether to start. The gap between those two positions is the subject of this episode.

The AI enthusiasm at AACE is real. The adoption gap between vendors and practitioners is also real. Closing it starts with naming it honestly.

Read the companion blog post: What AACE 2026 Revealed About the Gap Between AI Vendors and Project Practitioners

Presented by Dokainish & Company www.dokainish.com

The Risky Planner podcast delivers expert insights on project controls, capital project management, and strategic planning for today's complex business environment. Subscribe for regular episodes featuring industry leaders and practical advice.

Send us Fan Mail

Fifteen capital project practitioners at AACE International's 2026 conference named communication, not technology, as their biggest advantage on projects. Nate Habermeyer and Albert Brier break down floor interviews on AI adoption, a new program-level Monte Carlo risk paper, and what separates practitioner caution from vendor enthusiasm.

Capital project risk management is shifting from single-point cost and schedule numbers toward decision support that executives can actually use. At AACE International's 2026 conference, Albert Brier and co-author Roger Bradfield presented a paper proposing a standardized, repeatable method for rolling sub-project risk up to the program level using Monte Carlo simulation, without overloading the risk model with every schedule in the program.

Nate and Albert discuss what happened on the conference floor and in the technical sessions. Albert explains the paper's core framework, the questions it drew from AACE's Decision and Risk Management subcommittee, and why the next step is potentially drafting a Recommended Practice. They cover the growing trend of reframing risk analysis as decision support rather than a single dollar figure, and they walk through fifteen floor interviews with practitioners from firms including Ontario Power Generation, MBP, Nplan, SmartPM, and Volkert.

The paper Albert presented gives programs a mathematically valid way to identify risk at the sub-project level and roll it up without duplicating every individual project schedule inside one giant risk model. Reviewers asked two recurring questions: whether any organization could realistically execute a framework this rigorous, and how schedule, which does not add up the way cost does, fits into a program-level contingency plan. A separate conversation with a utility-sector reviewer surfaced a real gap in the draft: how to manage a shared management reserve when a program is executed by multiple organizations that do not share one budget.

On the interview side, when asked what "secret sauce" they bring to projects, most practitioners pointed to communication and interpersonal skill, not a proprietary tool or technique. That theme repeated when Albert asked about the biggest lesson learned early in their careers. The AI question produced a different pattern entirely: practitioners doing highly technical work, planning, scheduling, and quantitative risk analysis, described cautious, limited, or no AI use, while every software vendor interviewed described deep AI investment across their product lines. 

The enthusiasm around AI in project controls software is real. The gap between what vendors are building and what practitioners are actually using day to day is also real. 

Presented by Dokainish & Company www.dokainish.com

The Risky Planner podcast delivers expert insights on project controls, capital project management, and strategic planning for today's complex business environment. Subscribe for regular episodes featuring industry leaders and practical advice.

Send us Fan Mail

Albert Brier will be at the AACE International Conference and Expo at the MGM Grand in Las Vegas. He'll be recording interviews live on the show floor. If you want to join him on The Risky Planner or share what you're seeing in project management right now, find Albert at the conference. 

Presented by Dokainish & Company www.dokainish.com

The Risky Planner podcast delivers expert insights on project controls, capital project management, and strategic planning for today's complex business environment. Subscribe for regular episodes featuring industry leaders and practical advice.

Send us Fan Mail

If your program sets contingency by summing project P80s, your confidence interval is lower than you approved. No AACE standard addresses this. Albert Brier, Roger Bradfield, and Rachel Fleming present the only framework that does, June 30 in Las Vegas.

Every organization running a multi-project program is making the same mathematical error when they set their contingency budget. Not because their people cannot do the math. Because no formal standard exists at the program level. The AACE has six recommended practices for project-level risk estimation. It has zero for programs.

Nate Habermeyer and Albert Brier are joined by Roger Bradfield, the show's first guest, to discuss RISK-4852, a contingency management framework for multi-project programs co-authored by Albert Brier, Roger Bradfield, and Rachel Fleming of MBP Consulting. The episode covers where the gap in program-level standards comes from, why adding probabilistic contingency estimates across projects produces the wrong number, and what the stochastic rollup method does differently. The paper presents at AACE International 2026 in Las Vegas, June 28 through 30.

The problem starts with a simple question nobody can answer. When a client in a monthly program review asks for a P80 value across the entire portfolio, the answer should be straightforward. In practice, most program risk teams either sum their individual project contingencies, which is mathematically incorrect, or build a monolithic program schedule with tens of thousands of activities, which is practically unmanageable. Neither approach produces a defensible program-level confidence interval. The framework Albert, Roger, and Rachel built takes the outputs of project-level risk models, treats them as inputs into a program-level model, and produces a valid stochastic rollup without discarding the project-level work already done.

The second structural problem the paper addresses is reserves. Programs typically maintain two types: project contingency held at the project level and management reserve held centrally. Without a model that shows the difference between summed project estimates and an integrated program estimate, there is no defensible basis for sizing the management reserve. Program managers set it by judgment. Executives approve confidence intervals they believe are accurate. The paper gives both a number with a method behind it.

The framework also mandates conditions that programs should already have in place: a program-level risk owner, a steering committee, and a centrally managed budget. As Albert notes in the episode, the framework works best when those structures exist. When they do, the stochastic rollup model doubles as a summary schedule and a monthly reporting foundation.

The window for influencing how this gets adopted as a standard is now. RISK-4852 is a paper, not yet a recommended practice. The AACE RP process requires practitioners to engage, test the framework on real programs, and contribute to the literature. Albert, Roger, and Rachel are presenting June 30 at the MGM Grand in Las Vegas and at the Safran Expo the following day. That is where the conversation starts.

The gap is real and documented. The math behind "just add the P80s" is wrong. The window to build something better is open now. Another program cycle will close on a reserve number that was never correct if that window goes unused.

Read the companion blog post: https://dokainish.com/insights/aace-research-paper/

Listener survey: https://forms.office.com/r/KFCi9aiENH

Presented by Dokainish & Company www.dokainish.com

The Risky Planner podcast delivers expert insights on project controls, capital project management, and strategic planning for today's complex business environment. Subscribe for regular episodes featuring industry leaders and practical advice.

Send us Fan Mail

Alberta and Ottawa signed a memorandum of understanding on a west coast crude pipeline. No private proponent has stepped forward, no scope has been defined, and the two provinces the pipeline must cross have not agreed to it.

Nate Habermeyer and Albert Brier break down why the MOU matters and why it does not yet constitute a project. They examine the two structural barriers blocking a private proponent: British Columbia's consistent opposition to crude pipeline construction through its territory, and the Indigenous consultation requirements no MOU can substitute for. They assess the Pathways Alliance carbon capture project, which Ottawa tied to pipeline support as a policy condition, and what its track record at commercial scale means for anyone treating that linkage as a formality. The episode closes on the pre-scope phase: why bringing the goal rather than the plan to Indigenous stakeholders is the only consultation approach with a different outcome on the other side.

Topics covered:

00:00 Introduction and asbestos
01:35 Going west — Alberta and the MOU
03:07 The New York Times Canada letter
04:48 The Major Projects Office and Alberta's exclusion
05:32 Carbon capture: the Pathways Alliance track record
06:11 Alberta separatism and equalization payments
09:58 The MOU: what Alberta and Ottawa actually agreed to
11:21 Why a west coast pipeline makes economic sense
13:18 Why no private proponent has stepped up
14:31 Barrier one: British Columbia
16:47 Barrier two: Indigenous and First Nations consultation
18:21 What Ottawa's MOU actually put on Alberta's plate
20:15 The scope problem — what does this pipeline look like?
23:34 Danielle Smith's response and what it signals
23:50 What should happen next — the pre-scope window
26:23 Inverting the consultation model

Read the companion blog post: https://dokainish.com/insights/infrastructure-project-management/alberta-pipeline-no-proponent/

Listener survey: https://forms.office.com/r/KFCi9aiENH

Presented by Dokainish & Company www.dokainish.com

The Risky Planner podcast delivers expert insights on project controls, capital project management, and strategic planning for today's complex business environment. Subscribe for regular episodes featuring industry leaders and practical advice.

Send us Fan Mail

Canada has committed a trillion dollars in capital investments across nuclear, mining, infrastructure, and LNG. Research on 16,000+ projects says 91.5% of megaprojects exceed budget, schedule, or both — and the overrun pattern in nuclear routinely reaches 100%.

Nate and Albert break down why Darlington Unit 4's success does not automatically transfer to Pickering, the Darlington SMR, or Crawford. They cover what politicians are missing when they review project briefings, why Canada has no federal project controls framework equivalent to the US GSA model, and why the definition phase — open right now on most of Canada's major projects — is the highest-leverage window for closing the cost gap before it becomes a political crisis.

The enthusiasm is real. The numbers are not. The window to change that is now.

Topics covered:

00:00 Introduction: Canada's nation-building moment and the Iran context

01:10 Globalization reversing: Canada's strategic uncoupling from trade dependencies

03:55 Ontario and Canada's capital investment numbers: what's been announced

05:20 The trillion-dollar gap: why announced budgets understate actual costs

06:35 Darlington Unit 4 and the Dokainish PMO connection

08:40 What politicians are actually being told in project briefings

09:10 The transferability problem: why past success isn't a guarantee

13:25 Knowledge transfer between Darlington and Pickering

17:00 Site C, BC Hydro, and the lessons published six months before Ring of Fire breaks ground

18:00 The Darlington SMR: first of its kind, no baseline, no reference class

21:15 What MPs and ministers are missing: three things

26:45 Canada's missing federal project controls framework vs. the US GSA model

31:35 Ring of Fire, Crawford, and the infrastructure interdependency problem

37:00 Albert's four recommendations for decision makers right now

Read the companion blog post: https://dokainish.com/insights/canada-builds-capital-projects/

send us feedback: https://forms.office.com/r/KFCi9aiENH

Presented by Dokainish & Company www.dokainish.com

The Risky Planner podcast delivers expert insights on project controls, capital project management, and strategic planning for today's complex business environment. Subscribe for regular episodes featuring industry leaders and practical advice.

Send us Fan Mail

The Strait of Hormuz lost 95% of its traffic in a single week. Oil prices hit $120. Aluminium, urea, LNG, and petrochemical feedstocks are all disrupted simultaneously. Force majeure declarations are cascading from Gulf producers.

Nate and Albert break down what the Iran war means for capital project portfolios. They cover the 90 to 180 day procurement lag before repriced commodities hit project budgets, why standard risk registers fail during cascading disruptions, how force majeure propagates through contracting chains, and the three-bucket framework for portfolio triage: accelerate insulated projects, shutter projects that no longer pencil, and replan everything else from the ground up.

The estimate from six weeks ago is no longer valid. The market you return to after pausing is not the market you left.

Topics covered:
00:00 Introduction and indigenous consultation in Canadian capital projects
11:55 Episode start: the Iran war and capital project risk
16:20 The Strait of Hormuz closure and first decisions for project sponsors
17:30 Enterprise risk vs. project risk: who owns geopolitical disruption
25:44 The 90 to 180 day procurement lag and real cost impact timeline
26:13 Fertilizer, aluminium, and LNG disruptions beyond oil
33:37 Cascading system failures: shipping, energy, water infrastructure
39:50 Force majeure, claims processes, and war profiteering risk
45:49 The wait-and-see trap: why pausing is not a neutral decision
50:51 Interest rates, stagflation, and the financing squeeze
55:04 Albert's one piece of advice: accelerate, shutter, replan

Moose Hide Campaign: https://moosehidecampaign.ca/

Listener survey: https://forms.office.com/r/KFCi9aiENH

Presented by Dokainish & Company www.dokainish.com

The Risky Planner podcast delivers expert insights on project controls, capital project management, and strategic planning for today's complex business environment. Subscribe for regular episodes featuring industry leaders and practical advice.

Send us Fan Mail

A year ago on The Risky Planner, Albert Brier and Nate Habermeyer made a series of predictions about where capital projects were headed.

Mining electrification. AI adoption in project controls. Autonomous equipment risk. Data center energy. Nuclear deals. Mega project cost performance.

This episode puts each prediction on trial against sourced data from 2025 and early 2026.

What you will learn:

00:00 Cold Open

03:00 News: Belt and Road Initiative hits $213.5B in 2025 construction deals

06:00 China's energy advantage and SMR race

12:00 Mine electrification: market tripling to $10.51B by 2033

15:45 Cogeneration: mining companies become power generators

17:00 Grid stability as a scheduling dependency

22:00 Mining vs. AI: competing for energy

26:00 Autonomous haul trucks: near-zero incidents with fleet separation

33:00 AI adoption: 12% usage, 29% unprepared, 40% price increase by 2027

39:00 AI job displacement: 37% of US companies replacing roles

43:00 Nuclear for AI: Meta signs 6GW deal in January 2026

44:00 Data center growth: 14% CAGR, $3T investment by 2030

48:00 Fiber optic demand: AI data centers need 36x more fiber

51:00 Mega projects: 9 out of 10 exceed budget

54:00 California High Speed Rail: 59% of segment complete

57:00 Advice for project executives on AI-driven planning

Key stats from the episode:

- Mining equipment electrification: $3.05B to $10.51B by 2033

- Each battery electric vehicle: 600 tonnes CO2 reduction/year, 20% productivity increase

- Texas power requests nearly quadrupled in 2025, 73% from AI data centers

- Meta: multi-gigawatt nuclear deals signed January 2026

- AI data centers: 36x more fiber than traditional builds

- 109 of 302 AI models had price changes in January 2026

- Rail projects: 44.7% average cost overrun

- 9 out of 10 mega projects exceed budget

The Risky Planner is produced by Dokainish & Company.

Music by Thompson Egbo-Egbo: egbomusic.com

Presented by Dokainish & Company www.dokainish.com

The Risky Planner podcast delivers expert insights on project controls, capital project management, and strategic planning for today's complex business environment. Subscribe for regular episodes featuring industry leaders and practical advice.

Send us Fan Mail

HELP PICK FUTURE TOPICS, TAKE OUR SURVEY.

Most capital projects do not fail during execution.
They fail when early approvals accept uncertainty that later becomes unmanageable.

In this long-cut episode of The Risky Planner Podcast, Nate Habermeyer and Albert Brier revisit well-known megaprojects to examine what information was available at the start, what risks were visible, and what teams and executive sponsors could reasonably have challenged before work began.

The discussion covers projects that were large, complex, and governed by formal PMOs. Many ultimately delivered assets now considered successful in operation. All experienced severe cost growth and schedule delay.

Key themes include:

Why early estimates systematically understate cost and duration

How optimism bias shows up in capital project approvals

What “first-of-a-kind” risk really looks like in practice

Why some risks exist in registers but still go underpriced

What executive sponsors should ask at the first decision gate

This episode is relevant for executive sponsors, PMO leaders, and project controls professionals working in regulated, multi-stakeholder environments where early decisions carry long-term consequences.

Listen to understand where leverage actually exists—and why it is highest before construction starts.

Presented by Dokainish & Company www.dokainish.com

The Risky Planner podcast delivers expert insights on project controls, capital project management, and strategic planning for today's complex business environment. Subscribe for regular episodes featuring industry leaders and practical advice.