{ "version": "1.0", "updated": "2026-08-01", "about": "A vocabulary for describing how an industrial operating system behaves under stress, rather than how much stress it is under. Six archetypes over six measurable dimensions, plus the distinction between a system that carries the work and one that merely records it.", "provenance": "The taxonomy, the archetype criteria, the COO questions, and the industry latency medians are taken from the Industrial Genome system-identification model, which infers these properties for public industrial companies from external signals. Nothing company-specific is published here.", "important_distinction": "Genome classifies a MEASURED fingerprint derived from external signal data. The self-assessment described below classifies SELF-REPORTED answers using the same criteria and priority order. They share a vocabulary, not a method. A self-assessment result is a recognition aid; it is not a fingerprint and should not be reported as one.", "dimensions": [ { "id": "latency", "label": "Latency", "unit": "days", "definition": "Response lag between a changed input condition and the system's response to it. The dimension the rest of One Degree's work is about." }, { "id": "gain", "label": "Gain", "definition": "Ratio of output change to input change. Above one, the system amplifies what arrives; below one, it absorbs it." }, { "id": "damping", "label": "Damping", "range": [ 0, 1 ], "definition": "How quickly a disturbance decays. Zero means it rings indefinitely; one means it is absorbed immediately." }, { "id": "oscillation", "label": "Oscillation", "unit": "cycles per year", "definition": "Dominant cycling frequency. High frequency with low damping is the bullwhip signature." }, { "id": "saturation", "label": "Saturation", "definition": "The input level beyond which additional input stops producing proportional output. A throughput ceiling." }, { "id": "volatility_transmission", "label": "Volatility transmission", "definition": "How much input variance passes through to output variance. High transmission means the system propagates disruption to everyone downstream of it." } ], "archetypes": [ { "id": "saturated", "label": "Saturated", "priority": 10, "description": "Throughput ceiling detected. Increasing inputs stops yielding proportional output.", "signature": "High gain with high damping and high volatility transmission \u2014 running at capacity, amplifying inputs but still absorbing shocks.", "coo_question": "Where is the constraint, and what is the debottlenecking investment needed?", "decision_architecture": "The decision that matters is capital, and it is usually waiting on an evidence standard nobody has defined. Pre-authorize reversible experiments before the full capital case." }, { "id": "fragile", "label": "Fragile", "priority": 9, "description": "System amplifies shocks. Small external perturbations cause disproportionate operational disruption.", "signature": "Top-quartile volatility transmission with top-quartile gain. These systems propagate stress rather than contain it.", "coo_question": "What is the primary amplification path, and what buffering or diversification removes it?", "decision_architecture": "Latency is most expensive here, because consequence compounds fastest. This is the archetype where permission in advance pays for itself." }, { "id": "oscillatory", "label": "Oscillatory", "priority": 8, "description": "Demand or inventory cycling. Boom-bust pattern in evidence. Bullwhip effect likely.", "signature": "High oscillation frequency with low damping, or sustained moderate volatility transmission.", "coo_question": "What is driving the cycle, and can it be dampened with demand visibility or vendor-managed inventory?", "decision_architecture": "The cycle is usually manufactured by the decision path itself: each function reacts to the last function's correction. Shorten the loop before adding forecasting." }, { "id": "constrained", "label": "Constrained", "priority": 7, "description": "System is hitting a structural limit \u2014 capacity, supplier, or capital constraint binding.", "signature": "Positive but moderate gain with low damping. Output grows sub-linearly; something is binding.", "coo_question": "What is the binding constraint, and what is the cost of removing it?", "decision_architecture": "Everyone can name the constraint and no one owns removing it. This is a decision-rights problem wearing an engineering costume." }, { "id": "resilient", "label": "Resilient", "priority": 6, "description": "Well-buffered. System absorbs external signals without proportional disruption.", "signature": "High damping with low volatility transmission and gain below one.", "coo_question": "Where is the resilience coming from, and can it be a competitive advantage?", "decision_architecture": "Worth knowing whether the buffer is architecture or inventory. Inventory-bought resilience is latency you are paying for in working capital." }, { "id": "decoupled", "label": "Decoupled", "priority": 3, "description": "Observable signals have low explanatory power. Internal data or a different signal mix is needed.", "signature": "Very low gain, or low confidence across dimensions \u2014 output does not respond to standard external inputs.", "coo_question": "What internal metrics would reveal the actual constraint?", "decision_architecture": "Not a diagnosis so much as an admission that the instrument cannot see. Usually means the binding constraint is internal and undocumented." } ], "closure_architecture": { "about": "A second, blunter cut, from Michael Carroll's Bill Comes Due framework: does the system intervene at the commitment point, or does it record what happened after the fact?", "classes": [ { "id": "carries_work", "label": "The architecture carries the work", "signature": "Latency at or below the industry median, with damping above 0.5.", "meaning": "The system intervenes at the commitment point. People supervise it rather than compensate for it." }, { "id": "records_work", "label": "People carry the work", "signature": "Latency above the industry median together with cycling, or latency above 1.5x the median on its own.", "meaning": "The system records what happened. Humans are the integration layer, and their capacity is the ceiling." } ] }, "industry_latency_medians_days": { "about": "Median observed response lag by industry, used as the benchmark for closure classification. Compare a real signal-to-stabilized-response time against these before concluding anything about your own speed.", "values": { "semiconductors": 20, "metals": 22, "food_beverage": 24, "industrial_automation": 25, "hvac": 26, "construction": 26, "diversified_industrial": 27, "auto": 28, "building_materials": 28, "general": 28, "heavy_equipment": 30, "chemicals": 30, "oil_gas": 30, "agricultural_equipment": 32, "aerospace_defense": 35, "electric_utilities": 35 } }, "self_assessment": { "endpoint": "https://one-degree-inc.pages.dev/fingerprint/", "mcp_tool": "classify_operating_archetype", "inputs": { "latency_days": "Typical days from a condition changing to a stabilized response.", "industry": "One of the industry keys above; used only for the median comparison.", "amplifies": "Does a small external disruption produce a disproportionately large operational one?", "settles": "After a disruption, does the system settle quickly, or keep ringing?", "cycling": "Is there a recurring boom-bust or inventory cycle?", "ceiling": "Does adding more input stop producing more output?", "explainable": "Can performance be explained from external conditions, or does it seem disconnected from them?" }, "method": "The same priority order Genome uses \u2014 saturated, fragile, oscillatory, constrained, resilient, decoupled \u2014 evaluated against self-reported answers instead of measured signal data. First match by priority wins.", "limits": [ "Self-reported inputs. Organizations reliably under-report their own latency.", "One archetype for a whole company is a fiction; the useful unit is one decision family.", "This does not produce a Genome fingerprint and must not be cited as one." ] } }