The CIC scale
The Corporate Intelligence Capability score, 0 to 10
Corporate Intelligence Capability (CIC) is how intelligently a unit can act: quality decisions, made fast, and made at scale. The CIC score, 0 to 10, says which instruments the unit's data can reliably carry today, and it is built so that the score predicts what will actually work. Here is each score on the scale, the availability profile that typically sits behind it, and what it reliably supports.
Why raise it
What a higher CIC score means for you
Every score on the scale admits a kind of instrument the unit could not trust before. Raising the score is not collecting more data or buying more tools; it is widening what the unit can decide well, fast, and at scale.
Decisions you could not make before
At each score, decisions that used to run on memory and anecdote get a reliable report, then a diagnosis, then a forecast, then a recommendation, then an answer, then an agent. The unit's own metric moves with them.
Spend that lands
The score says which instruments will work today and which will not, so intelligence and AI investments go where the data can carry them, and the return on investment (ROI) is stated before the work rather than hoped for after it.
A ceiling you can see
Nothing done with the data can show what the data did not reach: bigger models and better agents do not lift the ceiling. The score makes the ceiling visible and names the gap that raises it.
Two things the score is not. Not a list of tools: a forecasting platform whose forecasts nobody trusts is zero predictive capability. Not a property of the data alone: the same data can support a report and fail a model, so capability is always about a decision.
The CIC scale
One scale, 0 to 10, four named tiers
Scores are cumulative in the dimensions that matter for acting: accessibility, permission, currency, provenance tighten as the scale rises. The profile column describes the priority decisions' data at that score.
| Score | Label | Typical availability profile | Reliably supports | Tier |
|---|---|---|---|---|
| 0 | Non-existent | The decision's variables are not recorded anywhere. | Nothing beyond memory and anecdote. | Incapable |
| 1 | Ad hoc | Data exists in spreadsheets, paper, and local files. | Manual reporting by individuals, not systems. | Incapable |
| 2 | Fragmented | Several systems capture data; none are integrated; no shared definitions. | Departmental reports that disagree with each other. | Incapable |
| 3 | Centralizing | Raw data lands in one place; quality and meaning are still low. | Descriptive reporting, with manual cleanup every cycle. | Foundational |
| 4 | Standardized | Core entities are conformed and deduplicated; consistent definitions for the basics; owners known. | Reliable descriptive reporting; early diagnosis. | Foundational |
| 5 | Governed | Consumption-ready data with lineage, ownership, quality rules, and a decision inventory behind it. | Diagnosis that holds across the whole unit. | Foundational |
| 6 | Model-ready | Representative, labeled history at scale for the priority targets; features reusable; permission covers analytical use. | Predictive models that are trusted for forecasting and scoring. | Analytical |
| 7 | Context-enriched | One governed definition per metric; passages indexed and permissioned for retrieval; decisions and outcomes logged. | Grounded generative answers; prescriptive recommendations where decisions are logged. | Analytical |
| 8 | Real-time capable | Near-real-time freshness and unified cross-system access for the operational decisions. | Agent pilots in narrow, supervised workflows. | Autonomous |
| 9 | Autonomous-ready | Per-action permission, action-level audit, governed memory. | Agents in production for defined workflows, with people on the exceptions. | Autonomous |
| 10 | Self-optimizing | Every dimension monitored and self-healing; new sources onboarded, governed, and shaped within a release; investment ranked by decision value. | Multiple coordinating agents across units; the ceiling rises as data arrives. | Autonomous |
The named tiers
What to tell the executive
The four named tiers compress the scale into the sentence a leader needs.
Incapable, 0 to 2
No instrument tier is reliable. Spend on capture and centralization. Do not spend on AI.
Foundational, 3 to 5
Descriptive and diagnostic instruments work. Predictive and generative will be unreliable until quality, meaning, and governance reach the model-ready profile.
Analytical, 6 to 7
Predictive, prescriptive where decisions are logged, and grounded generative instruments are trustworthy. Agent pilots will fail or need heavy supervision.
Autonomous, 8 to 10
Agents can act. Only a small minority of organizations are here, and most of them got here one decision at a time.
The steep step
Why 7 to 8 is the hard one
Scores 0 to 7 raise the data's interpretability: it can be found, trusted, understood, and retrieved. Score 8 is where the data must become actionable in real time.
Currency and access jump together
An agent acts on the state of the world now, across every system it touches. Freshness and unified access both have to be near their maximum at once.
Then permission and provenance follow
From 8 to 9, an agent must be authorized per action and every action must be auditable. A wrong action is a different kind of failure from a wrong report.
The same asymmetry everywhere
Every published maturity model treats its top stage as rare and hard-won. This scale is explicit about where the difficulty is, and why.
By function
Where units usually get stuck
The binding gates cluster by function. These are the usual ones, and the metrics the journey is measured on.
| Function | Metric the unit already reports | Instruments that move it | Usual binding gates |
|---|---|---|---|
| Finance | Close-cycle days; forecast variance; audit findings | Close automation; cash forecasting | Meaning; provenance |
| Sales | Forecast accuracy; win rate; cycle time | Propensity models; account research | Quality of the customer record; outcomes logged |
| Service | Cost per interaction; first-contact resolution; satisfaction | Assistants over the knowledge base; ticket resolution agents | Currency and permission of the knowledge base |
| Supply chain | Stock-out rate; inventory days; on-time delivery | Demand forecasting; order optimization | Currency; shape; sufficiency |
| Marketing | Acquisition cost; conversion; retention | Churn prediction; spend allocation | Existence of attribution events; meaning |
| People | Time to fill; attrition; engagement | Attrition prediction; policy assistants | Permission over personal data; meaning |
| Operations | Downtime; yield; safety incidents | Predictive maintenance; dispatch agents | Existence of sensor data; currency |
Start with your decisions
Bring the decisions that matter and the data you have. The first thing we do is score them; the second is show you what moves the score.