Methodology.

Curated samples from recent engagement frameworks across three design domains.

The methodology samples below represent a curated subset of recent engagement frameworks. Each domain draws on a broader library of proprietary tools, taxonomies, and design artifacts developed across engagements.
Finance & operating model design
Assessment methodology.

OpportunityMapper™ runs a three-lens assessment across manual effort, data readiness, and preliminary ROI. Below is a sample of the methodology — how the lenses work, what the platform looks like, and how the lenses integrate into investment-grade output.

Three lenses. One integrated assessment.
01
Manual effort & process design gaps
Where is human labor concentrated in repetitive, rules-based, or pattern-matching work? Broken handoffs, over-engineered workarounds, workflows never redesigned. Activity-level scoring across 1,200+ activities.
▲ Direct cost savings through automation and process elimination
02
Data gaps & fragmentation
Is the data landscape ready to enable scaled efforts, or do siloed systems and inconsistent master data constrain every initiative? Source system inventory, master data consistency, integration layer maturity.
▲ Foundational constraint on AI performance and scalability
03
Preliminary ROI & value-based opportunities
What is the quantified path from current EBITDA to AI-enhanced operating profit? Revenue uplift sizing, COGS reduction, SG&A reduction, and a financially linked bridge.
▲ P&L walk that supports the deal thesis
OpportunityMapper™ architecture.
Data ingestion
ERP / GL · EPM / Planning · Org hierarchy · HR / People · Industry benchmarks · KPIs
Taxonomy engine
Capability → Process → Sub-process → Activity → Task · Customizable · Seeded process model · Real-time
↓
Persona layer
Role-based activity views · Cross-functional alignment · Skill & capacity insights · Links org to actual work
Analysis & output
Value chain mapping · Analytics dashboard · Opportunity identification · Spans & layers · Board-ready reporting
Worked example — how the lenses integrate.

The three lenses run in parallel. Lens 1 identifies where value exists. Lens 2 identifies what enables or blocks it. Lens 3 quantifies how much and when.

$3.8M
Lens 01 finding. 22 FTEs in manual back-office across 12 locations. AP/AR, reconciliation, and quote generation identified as highest-value targets. 14 activities automatable, 31 augmentable.
$550K
Lens 02 finding. 40% of Lens 1 use cases blocked by data fragmentation. Three CRMs, two ERPs, no MDM, no data warehouse. Remediation investment plan with prerequisite sequencing.
$17.7M
Lens 03 finding. Total EBITDA uplift over 36 months. 14.8× return on $1.2M AI investment. Eight-month payback. Investment-grade P&L walk with confidence-weighted three-horizon model.
Supplemental materials
Full assessment methodology, engagement timeline, VCM domain mapping, ProfitDriver tree framework, and sample deliverables available on request.
Integration design
Integration methodology.

The Integration Engine™ addresses three gaps that persist in even the most mature integration playbooks. Below is a sample — the diagnostic, the shift from static to designed integration, and the redesigned lifecycle.

What mature playbooks still lack.
01
Integrated dependency tracking
Workstreams are managed in silos. Cross-functional dependencies are tracked in spreadsheets — if at all — creating blind spots that cascade into delays.
02
Live linkage to target operating model
Integration plans disconnect from the TOM after Day 1. Decisions made in workstreams drift from the designed future state without real-time feedback.
03
Early risk flagging across workstreams
Risks surface only when they become crises. No mechanism exists to detect emerging risk patterns across workstreams before they compound.
From static playbooks to living integration.
Traditional
Redesigned
Static milestone trackers updated weekly
Live dependency graphs updated continuously
TOM defined pre-close, then shelved
TOM linked dynamically to every workstream decision
Risk reported quarterly in steering committees
Risk flagged in real-time with pattern detection
Siloed workstream PMOs
Orchestrated coordination across all workstreams
Manual synergy tracking
Automated synergy capture with variance alerts
Redesigned integration methodology.
Pre-close
Augmented planning
TOM design, dependency mapping, risk baseline
Day 1
Orchestrated launch
Go-live coordination, readiness dashboards
First 100 days
Living integration
Continuous TOM alignment, risk escalation
Steady state
Value capture
Synergy verification, playbook refinement
Supplemental materials
Agentic capabilities detail, evaluation framework across five dimensions, strategic imperatives for leadership, and full methodology documentation available on request.
AI operating architecture
Architecture & design framework.

Two frameworks underpin the AI Operating Architecture domain: a seven-layer enterprise hierarchy mapping operations to agentic architecture, and a six-step process design framework for redesigning legacy processes from first principles.

Seven layers from strategic intent to execution.

Each layer adds density and specialization. The deeper you go, the more granular the work becomes.

L1
Enterprise
Portfolio company — the organizational boundary
L2
Business functions
Finance & accounting · Operations & supply chain · Commercial & revenue
L3
Value chains
R2R · P2P · O2C · FP&A · Tax · Treasury — trigger-to-outcome streams
L4
Capabilities
Reconciliation · Close management · Invoice matching · Cash application
L5
Agent library
Core process · Analytical · Orchestration · Cross-cutting — organized by cognitive role
L6
Infrastructure
MCP connectors · API integrations · Data pipelines · Event streams · RAG · Hooks
L7
Data & context
Transactions · Data models · Reference context · Indexes
Six steps from first principles.

Each step produces artifacts that become input to the next. The order matters.

01
Scope
What is the boundary of the process being designed? Every subsequent question becomes ambiguous without an agreed boundary.
02
Outputs & stakeholders
What are all outputs, who consumes them, what decisions do they enable? Processes rarely have one output.
03
Sources of truth & inputs
What sources, inputs, and catalysts feed the process? Hidden dependencies live in tribal knowledge until they break.
04
Transformation logic
What steps move source to output? Start with value-add assessment: value-adding, necessary, or wasteful.
05
Resilience
What are failure modes, and how is continuity designed in? Resilience is not controls — it designs the process to keep flowing through uncertainty.
06
Governance & iteration
What becomes shared assets? How are improvements rolled forward? This turns single redesigns into compounding capability.
Supplemental materials
Full seven-layer architecture detail, value chain mapping, agent library taxonomy, infrastructure patterns, design quality scorecard, and workshop preparation materials available on request.

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