The returns
Invested this much, raised the CIC score, moved the metric, returned this
Returns are return on investment (ROI): fiscally responsible intelligence and AI investments, stated in the metric the unit already reports, with the whole chain written down before the work starts. Every clause of that sentence is a measurement set up in advance, which is why it can be defended afterwards.
The chain
Written before the work, defended after it
The sentence a sponsor wants to say afterwards, and what each clause requires to be true.
| The clause | What it requires |
|---|---|
| We invested this much in the unit | A cost baseline that includes platform, people, and the run cost after go-live. |
| It raised the unit's CIC score from here to there | A scored availability profile per priority decision, before and after, by the same rubric, with an independent scorer for anything tied to money. |
| by closing these gaps for these decisions | The gap analysis, with each binding gate named and its owner. |
| That admitted these instruments | The instruments in production and used; adoption measured as the share of decisions actually taken with them. |
| which moved the unit's own metric by this much | A metric the unit already reports, a baseline, an agreed counterfactual, and a measurement window fixed at the start. |
| worth this much a year, so the returns are this | A value per unit of the metric signed off by finance before the work, and the formula written down with its assumptions. |
What to expect
Bad, good, and great, by kind of work
Returns differ by an order of magnitude depending on the kind of work and on whether the data was scored first. Stated as shapes, not figures: every number Orama publishes is a verified claim, and these are the patterns behind the numbers.
| Kind of work | Bad | Good | Great |
|---|---|---|---|
| Raising the data: connecting, conforming, governing | A lake-first build with no decision attached; nothing above it ever ships. | Instruments attached from the first wave; payback inside the planning horizon. | The platform work amortized across many decisions, each one cheaper than the last. |
| Reporting and diagnosis | Reports built and ignored; no decision changes. | Cycle times fall; one definition per metric ends the reconciliation meeting. | Decision latency drops and shows in the unit's metric. |
| Prediction | A model built and never used, or trusted and systematically wrong. | Positive, attributable returns on a decision the unit makes every week. | A decision with a high value of information and a redesigned process around the forecast. |
| Grounded answers | A pilot with no result, the modal outcome for programs that skipped the scoring. | A production use case in a workflow, with adoption measured. | Embedded in a redesigned workflow, with an outcome the unit's leader defends. |
| Agents that act | Cancelled, or an incident. | A narrow, supervised workflow with measured cycle-time and error reduction. | Agents operating for defined workflows with people on the exceptions, every action logged. |
The bad column is not rare. It is the base rate for work started without scoring the data first.
What makes it great
Two things beyond the data
The data sets the ceiling, and higher quality decisions mean better outcomes and returns. Two things decide how close a unit gets to the ceiling.
A decision worth the information
Some decisions have a high value of information: knowing more would change what you do, and the difference is large. Those are the ones to raise first. The scoring finds them.
A process that uses the instrument
An accurate forecast nobody acts on returns nothing. The great outcomes are the ones where the unit redesigned how it decides, and adoption was measured, not assumed.
A journey that compounds
Each closed gap lowers the cost of the next instrument on the same data, and every logged decision raises the next round's sufficiency. The second wave is cheaper than the first.
The measurement discipline
Seven rules that make the claim defensible
These separate the minority of programs that can prove their returns from the majority that cannot.
An instrumented baseline before any work
The metric's value, variance, and trend for at least four quarters.
A counterfactual agreed in advance
Trend extrapolation, a holdout, or a phased rollout. Before and after alone is not attribution.
A named executive owner
Someone who defends the metric and the value per unit.
A fixed measurement window
Stated at kickoff, with the ramp assumption written down.
Independent validation
Of both the scores and the attribution, for any figure that goes to a board.
Adoption measured, not assumed
The share of decision volume actually taken with the instrument.
Re-score and re-attribute on a cadence
A level that stops moving while spend continues is the earliest warning that a wave is building platform without instruments.
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.