Reduce decision latency. Build a more adaptive organization.

The advantage is not intelligence. It is the operating model that turns judgment into timely action.

One Degree helps industrial leaders, and the technology and service providers that sell to them, reduce decision latency, redesign authority and operating models, and build organizations that can adapt faster without losing control.

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What decision architecture means

The path from a signal to a stabilized result.

Every stage on that path can add delay. A dashboard improves detection. A data platform improves access. Workflow software routes an approval. None of that guarantees the whole path gets faster.

→ → → → → →
What delay at the signal stage looks like in practice

A maintenance signal appears on Monday, but no one recognizes its consequence while intervention is still cheap. By the time the plant sees the pattern clearly, the decision is no longer preventive maintenance. It is a production-loss event already underway.

Cost to intervene rises with delay The cost of acting on a signal stays low for a period after it appears, then climbs steeply once the cheap intervention window closes. Caught early $0.8M per quarter Caught late $2.4M per quarter Cost to intervene Signal appears Time since signal appeared Cheap intervention window Window closes
Cost to intervene stays flat for a while, then climbs steeply once the cheap window closes. The two figures below are the same condition caught early and caught late.
Total leakage before redesign
$14.3M per quarter
Representative industrial company near $1B revenue, carrying the full path with today’s delays.
Total leakage after improvement
$6.1M per quarter
Same company after compressing the path with clearer authority and earlier intervention.
Typical leakage before redesign
$2.4M per quarter
Loss accumulates because the signal is recognized after the cheap window closes.
Typical state after improvement
$0.8M per quarter
The same condition is caught early enough for maintenance, scheduling, and inventory to move while options are cheap.
Illustrative only: representative industrial enterprise at roughly $1B annual revenue, using One Degree leakage heuristics across the full decision path. Run your own leakage estimate ↗
Perspectives

Two perspectives. One operating problem.

The path changes depending on whether you run the enterprise or sell into it.

For industrial operators

Your decisions are waiting inside the enterprise.

You can already see more than you can act on.

  • Locate one delayed decision family
  • Price the waiting in real dollars
  • Redesign the path or intervene live
Start with diagnostics
For technology and service providers

Your offering may improve visibility without improving customer action.

The question is whether your product shortens the path or adds another screen to it.

  • Test whether the offer changes action or just reporting
  • Redesign around one customer decision
  • Adjust roadmap, packaging, or pricing if needed
See the provider path
Diagnostics

Start where the leakage actually is.

We start with one decision your organization makes over and over — capital approvals, maintenance escalations, pricing exceptions. We map where that decision loses time waiting on handoffs and sign-offs, then put a dollar figure on what the waiting costs.

Named Assessments

Not every diagnostic asks the same question.

Each one routes you straight into the conversation that matters — recognition, economics, or behavior under pressure.

Recognition

Constraint Finder

Use this when the problem feels broad but one decision family is repeatedly stalling. It tells you where the earliest unmet stage sits so the conversation starts at the bottleneck, not the loudest symptom.

Best next step: training, redesign, or intervention
Run the tool
Economics

Leakage Estimator

Use this when the organization knows something is slow but cannot yet justify action economically. It turns waiting into a rough annual leakage band with the assumptions exposed.

Best next step: quantify the case for change
Estimate the leakage
Behavior under pressure

Stress Archetype

Use this when the question is whether the system carries the work under pressure or whether the result still depends on heroic people patching broken architecture in real time.

Best next step: redesign the operating path
Classify the system
Advanced diagnostic

Antifragility Audit

A structured stress test for AI systems, agent workflows, and consequential automation. Find whether the system degrades, recovers, or improves when reality stops matching the demo.

  • For higher-stakes systems and delegated authority
  • Measures what happens after disruption, not just output plausibility
  • Returns a verdict, a failure map, and prioritized remediation
Best next step: stress-test the system before it earns more trust or authority
Explore the audit
Engaged diagnostic sequence

Every recurring decision gets plotted by how complex it is and how clear the authority to act is. That sorts them: some are ready to hand to software, others are bleeding value while they wait on approval. Click any process to see its profile.

Client-only
Selected process

Enterprise Architecture & Data Governance

High automation opportunity, but inference quality still outruns authority design. This is where software can move faster than the organization is allowed to decide.

Fragmentation40%
Permission36%
Inference52%
Value leak38%
Process Quadrant Source
See the full diagnostic toolset Open diagnostics ↗
See diagnostics Discuss a live decision
Education & mentoring

Two masterclasses, and the mentoring that follows.

Two three-hour masterclasses built on one decision architecture. The Decision Velocity Enterprise redesigns the decision system an industrial company operates inside. Designing for Decision Velocity redesigns what that company is being asked to adopt. Mentoring and board-level working sessions extend the same operating model into live executive decisions.

See both courses
Causal model explainer

A compact preview of what the course teaches: how to read a causal map, spot the loop that keeps a loss recurring, and test where one operating-model change actually moves the system.

Interactive preview
Signal quality
Weak maintenance signal
Decision geometry
Cross-functional approval climb
Consequence
$1.2M leakage event
The team can see the condition, but each escalation step enlarges the event before action is legitimate.
Delay compounds risk Authority is not pre-bounded Learning arrives after the loss
What the map shows
Three variables, one recurring failure

The course starts by making the causal structure visible enough to discuss. The point is not a prettier diagram. It is a decision system leaders can actually interrogate.

Why it matters
From explanation to intervention

Once the loop is legible, executives can test where to change authority, coordination, or evidence quality before spending into another round of delay.

The full sessions work through a real decision your team is facing right now, not a generic framework slide.
Advisory

Intervene while the decision is still moving.

Diagnostics identifies the mechanism. Education installs the model. Advisory is for the case already in front of you now, where consequence is accumulating faster than the organization can assemble evidence, locate authority, and act.

Decision architecture brief

Map one consequential path.

Where it waits, what the waiting costs, who holds authority, and what could be pre-authorized.

Offering integrity review

For providers under repricing pressure.

Does the offering reduce customer decision latency or generate more recommendations for someone else to process?

Executive preparation pack

For the room that needs a straight answer.

Built around one upcoming discussion, one decision, one causal argument, and one counterposition worth respecting.

Best fit

Start narrow, on something already costing you.

If you cannot yet name the decision family, the approval path, and the consequence of delay, start with diagnostics first.

See advisory Bring a live case
Trust and proof

Operational proof, concrete outputs, and a public body of work.

Trust here is built the old-fashioned way: one real decision, the waiting made visible, the leakage priced, and a practical next step for authority, software, and operating-model design.

“What Georgia-Pacific is doing with Causal AI is remarkable” — a 10× improvement in touchless order processing, with errors that once took days now resolved in seconds. Forbes · Steve Banker, 2024 — read the piece ↗
What the work produces
  • One recurring decision, or one customer decision, mapped end to end
  • The major latency points and the cost of waiting made visible
  • A clearer boundary between recommendation, authority, and action
  • A practical next step: training, advisory, or offering redesign
What this is not
  • A maturity score with no intervention attached
  • A generic AI talk detached from one operating decision
  • A promise that more dashboards alone will fix the problem
  • A transaction completed by software without human scoping
The Dispatch

The research layer behind the operating system.

The Dispatch explains the world, gives serious readers an entry path, and routes them back into diagnostics, education, or advisory. It is authority, not the first commercial ask.

Start with the Dispatch Explore the Radiant ↗
Live field guide
The Radiant Visual entry into the archive and argument map.
Decision latency

What the enterprise pays while it waits.

The economic argument behind the whole site.
AI and authority

Why cheaper intelligence moves the constraint.

The permission problem, stated plainly.
Software as intent

What software becomes when it can act closer to the moment.

The architecture and product implication layer.
Historical cases

Five stories where delay decided the outcome.

The narrative proof that signal-to-action distance is not a metaphor.
Credibility

Operator experience, research depth, and institutional perspective.

Each perspective here comes from someone who has operated, invested in, or governed the systems this work is built to change.

Industrial AI and causal systems
Manufacturing and operating-model redesign
Capital-markets and institutional-risk view
Product, transformation, and advisory work
Michael Carroll

Michael Carroll

Founder · AI Researcher & Investor
Leads the decision-latency thesis and the industrial AI point of view.

Industrial AI researcher, founder, investor, and board advisor best known for pioneering Causal AI and Special Purpose Intelligence at Georgia-Pacific and helping define how decision latency shows up in operating performance.

LinkedIn ↗
Ryan Cahalane

Ryan Cahalane

Managing Director, LNS Research · Founding Partner, Axiom
Brings the operator, market, and execution lens.

Industrial executive and advisor working where manufacturing, technology, systems integration, and investment meet, with a focus on scaling businesses and helping operating leaders turn strategy into execution.

LinkedIn ↗
Supporting Depth

Additional operating, analytics, governance, and transformation perspective around the core point of view.

Steve Frazier

Steve Frazier

Operational excellence & advanced analytics · OnPoint, a Koch Engineered Solutions company
Adds operational discipline and measurable economic framing.

Operator and analytics leader across manufacturing environments, with deep experience in process optimization and Bayesian approaches, and co-author of key Dispatch essays that put decision latency on the P&L.

LinkedIn ↗
Sudeep Kesh

Sudeep Kesh

Chief Innovation Officer, S&P Global Ratings
Contributes the governance and institutional-risk perspective.

Chief Innovation Officer at S&P Global Ratings, bringing a capital-markets and institutional-risk perspective to how AI reshapes judgment, governance, and decision systems.

LinkedIn ↗
Patrick Gaughan

Patrick Gaughan

Partner, Axiom Manufacturing Systems
Grounds the work in factory-floor transformation and scaling.

Manufacturing systems leader and Lean operator who helps smaller industrial companies apply Fortune 100-grade operating discipline to growth, transformation, and execution.

LinkedIn ↗
Rob King

Rob King

Manager, Supply Chain Strategy Insights · Batesville
Adds two decades of SIOP, Lean, and supply-chain execution depth.

Supply chain and operations leader at Batesville with two decades spanning SIOP redesign, Lean and Theory of Constraints transformation, and analytics-driven manufacturing strategy across planning, logistics, and plant execution.

LinkedIn ↗
Steve Tebbetts

Steve Tebbetts

Founder, STEAM Services LLC
Adds frontline Lean coaching and manufacturing training depth.

Lean and Six Sigma practitioner who coaches Michigan manufacturers through Gemba-based training and hands-on shop-floor improvement, turning operator insight into measurable process discipline.

LinkedIn ↗
Partners
LNS Research ↗ CESMII ↗ Chief Architect Network ↗
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The right one degree, held long enough, changes everything.

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