Project 01 · Operations · Natural Resources
Wellhead: physics-informed industrial AI for upstream operations.
Premise: upstream oil & gas operates > 1.2M producing wells globally; unplanned downtime costs the industry $50–80B / yr. Pure-ML approaches have largely failed because reservoir engineers reject any tool that asks them to trust an output without a physical mechanism. Methane-intensity regulation (EPA Quad O, EU Methane Regulation, OGMP 2.0) is a parallel forcing function with a calendar deadline.
Wellhead is physics-informed by construction and edge-deployed by default. Predictions arrive with auditable mechanism explanations (mass balance, multiphase flow regime, equipment kinematics) that an engineer can defend in a morning meeting. ESG measurements are signed and lineage-tracked, exportable in EPA Quad O / EU Methane / OGMP 2.0 formats; they are the artifact filed with regulators, not an input to a separate report. The runtime operates through 30+ days of disconnected operation; cross-operator federation happens via aggregated gradients, never raw telemetry. North-star: unplanned downtime hours per asset / quarter, audited against a pre-deployment baseline. Wedge: ESP failure prediction at one major operator's brownfield asset.
Engagement for
Accenture PiP
Bain PI
BCG TURN
AlixPartners
Operations · ESG · Industrial AI
25%+ downtime reduction
Project 02 · Performance Improvement · Industrial / Manufacturing
Forge: EBITDA transformation for a mid-market manufacturer.
Premise: mid-market industrial manufacturers ($800M–$2B revenue) entered 2025 with margin compression from input-cost shocks, supply-chain volatility, and a labor market that punishes operational fragility. The default reaction has been across-the-board cost cuts that hollow out throughput. The opportunity is structural: ~80% of opportunity is captured in 20% of cost lines (direct material spend cube, factory throughput on three constraint workcenters, SG&A indirect spend), and the engagement model that wins is on-site, gainshare-priced, and audited against an attested baseline.
Forge is a 12-month performance-improvement engagement plan for a $1.2B fasteners-and-fittings manufacturer with five North American plants. Three workstreams in parallel: (1) direct-material spend cube + vendor consolidation; (2) constraint-workcenter throughput at the two plants representing 60% of EBITDA leak; (3) indirect spend / SG&A ratchet. North-star: run-rate EBITDA improvement (% of revenue) at month 12, audited against an attested pre-engagement baseline. Counter-metric: safety incident rate and on-time-in-full delivery, both monitored weekly to ensure cost cuts don't trade against operational integrity. Pricing: 30% fixed fee + 70% gainshare on validated savings.
Engagement for
Bain PI
McKinsey Ops
BCG TURN
Accenture PiP
Cost · Throughput · Spend cube
15–22% EBITDA uplift target
Project 03 · Digital Transformation · Financial Services
Vanguard: cost-to-income transformation at a mid-cap bank.
Premise: Canadian mid-cap banks ($30–80B in assets) are stuck at a cost-to-income ratio of 60%+ vs. ~45% for top-quartile peers and ~38% for the leading digital challengers. The gap is not technology spend (they spend more, in fact); it's an operating model that still routes 70%+ of customer journeys through branch + call-center while challengers route 80%+ through self-serve. Recovering even half the gap is ~$300M / yr in run-rate cost-to-serve at this scale.
Vanguard is an 18-month digital-operating-model transformation: a cost-to-serve diagnostic by customer journey (originations, servicing, claims-of-error, lending decisions), target-state operating model design with self-serve-by-default routing, vendor and platform strategy (cloud-core vs. legacy mainframe), and an agile pilot program on the three highest-volume journeys. North-star: cost-to-income ratio movement (basis points) by quarter. Counter-metrics: NPS by journey (cannot decline by more than 2 pts), digital-channel adoption rate by segment, and operational-risk-event frequency. Wedge: replatform the originations journey first, where the ROI is clearest and the risk surface is best contained.
Engagement for
Oliver Wyman
McKinsey FS
BCG FSP
EY-Parthenon FS
Cost-to-serve · Operating model · Digital
~$300M / yr run-rate target
Project 04 · Public Sector · Healthcare Operations
Helm: provincial wait-times reduction across a six-hospital cohort.
Premise: Ontario emergency departments ran at a median 8.2-hour wait time in 2024, with the worst-quartile sites averaging 12+ hours; admitted-patient hallway-wait incidents have grown ~35% over three years. The Ministry of Health has set a 6-hour median target as a measurable component of the next provincial budget cycle. The wait-time problem is not staffing — it's downstream bed-flow, EMR-driven discharge friction, and a triage protocol that hasn't been re-tuned to current case-mix.
Helm is a nine-month operations engagement across six hospitals in two LHINs: patient-flow modeling at the asset level (ED → admission → discharge → bed-turn), discharge-readiness governance (medical reconciliation + transport + community-care intake), and a re-tuned triage protocol calibrated to 2025 case-mix. The work product is operational, not advisory: visual-management boards in each ED, a daily flow huddle with clinical and ops leadership, and a discharge-readiness lookahead that moves bed turns earlier in the day. North-star: median ED wait-time across the cohort, audited against the prior 90-day baseline. Counter-metric: 30-day readmission rate and clinician-burnout index, neither of which can deteriorate.
Engagement for
McKinsey Public Sector
Deloitte Public Sector
BCG Public Sector
Bain PI Healthcare
Throughput · Patient flow · Policy
Median wait-time < 6h target
Project 05 · Commercial Due Diligence · B2B SaaS / PE
Cipher: commercial diligence on a $400M vertical-SaaS target.
Premise: a North American mid-market PE acquirer is evaluating a $400M-ARR vertical SaaS company serving construction-trades businesses. Three things are unverified in the seller's materials: (1) the TAM number assumes the trades-software TAM is undifferentiated, when in fact the addressable wedge is ~25% of the headline figure; (2) NRR of 122% is real, but cohort-level retention is degrading at the lower end of the customer base, signaling pricing-power compression; (3) the competitive moat is described as "feature breadth" but reference calls suggest the moat is actually integration-density with a fragmented field-service tooling ecosystem.
Cipher is a four-week commercial diligence sprint: customer reference call program (40 calls, weighted by ACV cohort), bottom-up TAM triangulation against three independent data sources, win/loss analysis against the four most-cited competitors, and a pricing-power test using the seller's own discount-and-uplift data. The deliverable is a partner-grade memo with a bear/base/bull recommendation and explicit deal-modifier flags (price chip, structure change, walk-away). North-star deliverable: a recommendation the IC can vote on without further analytical work; a clear answer to "what would have to be true."
Engagement for
Bain DD
OC&C
L.E.K.
EY-Parthenon
DD · TAM · Competitive moat
$400M target · 4-week sprint
Project 06 · Energy Transition · Utilities / ESG
Tideway: energy-transition capital allocation for an integrated utility.
Premise: a North American integrated utility (~$25B revenue, ~85 TWh/yr generation, ~6M customer accounts) is facing the energy-transition trilemma: a provincial 2035 net-zero-electricity mandate, rate-payer affordability constraints (politically and contractually capped), and an aging gas-peaker fleet that's both essential for reliability and a regulatory liability. Their current 10-year plan over-indexes on solar utility-scale because that's the cleanest unit cost in isolation; what it misses is the downstream cost of grid balancing, which makes the actual marginal abatement cost 2.5× the headline LCOE.
Tideway is a six-month strategic engagement: a 10-year capital allocation plan that re-optimizes against a three-objective frontier (MtCO₂ avoided, $/customer rate impact, regulator-signoff probability). Workstreams: scenario modeling across nine generation-mix futures, technology-bet sequencing (storage vs. small-modular nuclear vs. demand-response vs. transmission), regulator-engagement strategy with the provincial energy board, and a stakeholder-impact sequencing plan that orders changes to land politically. North-star: cumulative MtCO₂ avoided per $B capex, optimized along the affordability constraint. Counter-metrics: grid-reliability index (cannot deteriorate vs. baseline), median rate-payer bill impact %.
Engagement for
McKinsey Sustainability
BCG Climate & Sustainability
Bain ESG
Accenture Sustainability
Energy transition · Capital allocation · Regulator
10-yr plan · ~$40B capex re-shaped