Decision Simulation Platform
Know the impact
before you act.
Logyc simulates how decisions move through your entire enterprise — value chain, operations, product, and finance — before capital, time, and credibility are committed.
Decision Flow
Sourcing Decision
Load-bearing node
Cost Structure
−8% COGS
Service Levels
94% fill rate
Inventory Exposure
+$12M WC
Working Capital
−$8.4M FCF
Financial Outcomes
+$18M NPV
Decision Memo · Q2 2025
Ranked Actions
VP Supply Chain
CFO
COO
Load-Bearing Assumption
⚠ Volume: +12% YoY
If volume growth falls below 8%, NPV reverses to −$3.2M
Correction Trigger
Month 3 checkpoint: If fill rate < 91%, escalate to CFO
Incomplete
Most approved capital decisions contain only part of the required decision architecture — the load-bearing components are most often missing
Rarely
Decision records are rarely preserved in a form the organization can learn from — the prediction is lost before the outcome arrives
Most
Post-mortems produce narrative instead of calibration — across 15 years of enterprise modeling engagements
Quarters → Weeks
Decision cycle compression achieved with Logyc simulation infrastructure — from multi-month approval cycles toward weeks
Observed across 15 years of enterprise decision modeling engagements
The Structural Failure
Your organization is not short of intelligence. It is short of an accurate model of reality.
Every capital commitment is a prediction about how reality will respond. The problem is not that organizations lack people capable of accurate predictions. The problem is that the machinery around those people is designed to produce approval — not accuracy.
The gap between what leadership believes is true and what is operationally real is where the most expensive surprises originate. And the gap compounds: without a mechanism to compare prediction to outcome, the organization learns nothing from its failures.
Management Presentation
Operational Reality
01
Approval Environment
The room is optimized for consensus, not accuracy. Challenge is perceived as opposition. The most important questions are never asked.
02
Advocacy Over Honesty
Business cases are written to win approval, not to produce the most accurate prediction. The assumptions are chosen to support the conclusion.
03
The Missing Load-Bearer
The single assumption whose failure most quickly damages the expected outcome is almost never named — because naming it invites the challenge the room is designed to avoid.
04
No Correction Mechanism
Without pre-agreed triggers and feedback loops, the organization cannot distinguish between a bad decision and bad execution. The lesson is lost either way.
The Platform
Decision infrastructure. Not another dashboard.
Model the business as an interconnected system across value chain, product, operations, and finance in one environment — not across disconnected spreadsheets.
Without Logyc
Expected Outcome
A revenue projection built on assumptions chosen to achieve approval, not to produce the most accurate estimate.
Load-Bearing Assumption
Not named. The business case contains 40 assumptions, none ranked by consequence.
Downside Scenario
'Revenue 12% below base case.' Still positive. No historical precedent for what actually happens when decisions of this type fail.
After the Outcome
'The market shifted.' No original prediction survives to compare against. The organization cannot distinguish bad decision from bad execution.
Decision Cycle Time
Quarters. Committee review, revised decks, re-approval cycles. The decision ages before it is made.
What You Learn When It Fails
'The market shifted.' No original prediction to compare against. Lesson lost.
With Logyc
Expected Outcome
A specific prediction: revenue at $18M NPV under base-case assumptions, with the variance range and the conditions that determine which scenario materializes.
Load-Bearing Assumption
Named explicitly: 'Volume growth at +12% YoY is the single assumption whose failure reverses the outcome. Current evidence confidence: 65%.'
Downside Scenario
Adverse scenario modeled from actual precedent: NPV −$3.2M. Conditions: volume growth below 8%. Pre-built correction trigger attached.
After the Outcome
Q4 actuals compared against Q1 prediction. Volume ran at 87% of projected. Gap measured. Assumption updated. Next model calibrated.
Decision Cycle Time
Weeks. The simulation surfaces the trade-off before the first committee meeting. Governance reviews a hypothesis, not a presentation.
What You Learn When It Fails
Velocity ran at 62% of regional baseline. The positioning did not transfer. Assumption updated in the model. Next decision inherits the calibration.
The Decision Architecture
Ten questions. All ten.
Before any commitment is made.
“Missing any one is not a minor oversight. It is a structural failure with a specific, predictable failure mode. An organization that answers seven honestly does not have 70% of a good decision. It has an incomplete one.”
Decision Architecture Diagnostic
Check each component that is genuinely present in your last major capital commitment.
Your current decisions have critical structural gaps. The most expensive failures are the ones you cannot learn from.
Decision Memory
Every major decision generates an asset. Most organizations discard it the same day.
At Approval
Prediction locked at $18M NPV. Three assumptions named and ranked. Correction trigger: Month 3 fill rate < 91%.
Month 3
Fill rate: 88.4%. Below signal threshold. Pre-agreed escalation activated. CFO notified. No emergency meeting required.
Month 6
Correction deployed: inventory buffer reduced, supplier allocation adjusted. Revised projection: $15.2M NPV.
Month 18
Actual outcome: $14.8M NPV. Predicted: $18M. Gap: 17.8%. Root cause: volume assumption overestimated by 3.2 points. Model updated. Next decision inherits this calibration.
At Approval
Business case approved. Filed.
Month 3
(No leading indicator tracked.)
Month 6
(No signal threshold. Performance concerns raised in quarterly review.)
Month 18
'The market shifted.' Post-mortem produces narrative. No original prediction survives to compare against. Lesson lost.
The decision record is not an archive. It is the raw material for calibration. An organization that preserves its predictions — and compares them to outcomes — becomes compoundingly more accurate over time. One that does not starts every decision from zero.
CREI — The Solution Layer
Logyc is the engine. CREI deploys it.
Logyc (Platform)
- Simulation infrastructure and model library
- Decision architecture enforcement (10 components)
- ERP/BI integration: SAP, Oracle, AWS, Azure, GCP
- Closed-loop learning: projected vs. actual outcome tracking
- Human-augmented ML: operator and consultant intuition encoded as testable logic
CREI (Advisory)
- Capital allocation engagements for boards, CFOs, and owners
- 6 active intelligence briefs: tariff exposure, rate/credit, energy supply, governance risk, supply chain fragility, geopolitical risk
- High-stakes capital decision support and risk advisory
- Governance and board readiness reviews
- Selective engagements — not a consulting retainer
How it works
Fits into the enterprise environment you already operate.
Logyc does not require a technology transformation to deliver value. It begins from the data, systems, and knowledge you already have — and preserves what your organization learns for the decisions ahead.
For CIOs, procurement, and legal: Logyc engagements are scoped as advisory and modeling work, not as enterprise software deployments. The Capital Decision Sprint is a defined, bounded engagement. Broader platform integration is discussed after the sprint produces a validated decision record.
Who This Is For
Built for executives who know their current process rewards approval more than accuracy.
CEO / President
The organization's decisions reflect the structure you built — or failed to build — around them. Stop approving recommendations. Start approving hypotheses, with specific predictions and pre-agreed correction triggers.
The question is not whether your team is capable of accurate analysis. It is whether the machinery around them is designed to produce accuracy — or approval.
- Establish a common decision language across functions
- Require named load-bearing assumptions before any capital commitment
- Build correction triggers into approval, not retrospect
CFO / Finance Leadership
The numbers are only as reliable as the assumptions beneath them — and the logic connecting those assumptions to the outcome. Most business cases encode optimism as fact.
Require the load-bearing assumption to be named. Attach feedback loops to the assumptions that drive the most consequential numbers. Track actuals against the original prediction — not the revised plan that obscures the gap.
- Surface the assumption that most quickly reverses the business case
- Attach actual/projected tracking to the load-bearing number
- Require an adverse scenario built from historical precedent, not base-case reduction
Board / Investors
Governance that validates strategy without interrogating the reasoning that will determine whether it succeeds is not governance — it is ceremonial review.
The six questions below separate consequential oversight from approval theater. None of them require special expertise. All of them require the willingness to ask.
- Require the load-bearing assumption named and evidence-rated before board approval
- Mandate a correction mechanism with named trigger and named owner
- Distinguish between high confidence and high evidence
Board Governance
Six questions that separate consequential oversight from ceremonial review.
Where is the single point of failure in this business case — and what is the plan if it fails?
How fragile is the expected outcome to changes in the two or three assumptions it most depends on?
What does the genuine downside look like — not a reduction from base case, but the actual failure mode based on historical precedent?
If this decision produces the worst credible outcome, will we regret having made it — or regret not having had a pre-agreed response ready?
What leading indicator, checked at what interval, would tell us the decision is on or off track before the damage compounds?
How much of the confidence in this decision is based on evidence — and how much is based on the fact that the people presenting it believe it?
The Lowest-Risk Entry Point
Capital Decision Sprint
A structured, 6–8 week engagement that runs one of your active capital decisions through the full Logyc decision architecture. You leave with a specific prediction, a named load-bearing assumption examined against actual evidence, a stress scenario built from historical precedent, and pre-agreed correction triggers.
If it works, you have a model for the next decision. If it does not produce clarity, you have not committed to a multi-year platform.
Decision record preserved at approval
Built for learning, not persuasion. The prediction, the assumptions, the logic, and the trigger — all in learnable form before the commitment is made.
Feedback loop architecture
Leading indicators attached to the load-bearing assumption. A defined checkpoint schedule. A named owner for each trigger.
Correction triggers pre-agreed
Specific thresholds defined before the sprint closes. Not constructed after the outcome diverges from prediction.
Pricing is custom and engagement-specific. Capital Sprints begin at a defined scope. Contact us to discuss.
Engagements are selective. We run a limited number of sprints per quarter.
Industries
Built for the decisions that cut across functions.
CPG & Consumer Brands
Sourcing shifts, formulation changes, and demand volatility create decisions that propagate simultaneously across operations, product, and finance. Logyc models the full system impact before capital is committed.
Active intelligence: Supply Chain Fragility & Tariff Exposure
Financial Services
Rate cycles, credit exposure, and regulatory change force decisions across business lines with interdependent risk profiles. Logyc maps the propagation path before the position is taken.
Active intelligence: Rate/Credit Risk & Governance
Industrial & Manufacturing
Capex decisions in industrial environments carry long payback periods and high irreversibility. Logyc builds the adverse scenario from actual historical precedent — not optimistic reduction.
Active intelligence: Energy Supply & Geopolitical Risk
Technology & Software
Platform investment, market entry, and build-vs-buy decisions carry assumption risk that compounds across product cycles. Logyc names the load-bearing assumption before the roadmap is committed.
Active intelligence: Governance Risk