• $1M → $14.5Msales pipeline in three months
  • $1.2M of $1.4Moverdue receivables collected in three months
  • 30 daysto hire A-players
  • 85%of our pilots stick

Is your company ready for AI, or only interested in it?

SCOPE™ by Efficiency Sprint is an operational AI readiness method, created by Luba Inz. It scores every part of a business on two scales, process and data, and places that part in one of five states. It turns AI readiness into an executable transformation plan. AI cannot reliably run work that your company cannot reliably explain.

Last updated

Find where you stand
EFFICIOS
A SCOPE™ by Efficiency Sprint result assembling: one domain, its place on the two scales, then its plan.

The verdict

  • Ready now
  • Ready after fixes
  • Not advised

The two scales

The five levels of process

  1. 1
    Lives in someone's headNot written down: only one person knows it, or each person does it differently.
  2. 2
    Written downDocumented, nobody measures whether it's followed.
  3. 3
    Owned and measuredNamed owner and a measure someone looks at.
  4. 4
    Exceptions show up on their ownInstrumented: deviations surface without anyone asking.
  5. 5
    A machine runs it, a person checksRunning in production, a person judges the exceptions.

The five levels of data

  1. 1
    No system of record
  2. 2
    A system exists, the data isn't trusted
  3. 3
    Trusted, no machine access
  4. 4
    Trusted, a machine can read it
  5. 5
    Trusted, a machine can read and write, with an audit trail

A part of the business sits at the level of its weaker score.

Same method. Separate result for every domain.

We start with six domains and shape them to your company. Not the other way round.

People
Marketing & Sales
Finance
Operations
Customer Success & Quality
Executive
The same two-axis test

Data runs upward from 1 to 5; Process runs rightward from 1 to 5. The five states band diagonally across the map: Stabilize — repair the basics; Codify — make the recipe clear; Ownership — people run it reliably; Pulse — AI watches and reports; Engine — AI acts within guardrails. A domain sits lower-left when its process and data still need repair, and upper-right when the machine can act on trustworthy work.

Data ↑
5
EEngineAI acts within guardrails
4
PPulseAI watches and reports
3
2
CCodifymake the recipe clear
OOwnershippeople run it reliably
1
SStabilizerepair the basics
1
2
3
4
5

Process →

The five states

  1. Stabilize

    Stabilize is the state where the foundation gets repaired before anything is built on it.

    The same job stops coming out differently depending on who does it.

  2. Codify

    Codify is the state where know-how becomes explicit rules.

    A new person can run the work from what's written down.

  3. Ownership

    Ownership is the state where authority and accountability are assigned by name.

    Decisions stop waiting for the owner, because someone else is allowed to make them.

    The tool for it is a decision authority matrix: every decision, one owner, one limit.

  4. Pulse

    Pulse is the state where performance and exceptions are instrumented.

    Problems arrive as exceptions in a weekly report instead of as surprises.

  5. Engine

    Engine is the state where the work executes through AI under human governance.

    The routine work runs itself, and a person judges the exceptions.

By Luba Inz, founder of Efficiency Sprint

Every term we use, one line each: see the glossary.

The delegation test

If you can't hand a task to a brand-new hire without babysitting them for a month, an AI agent won't do it either.

Take the full test

Questions

What is SCOPE™ by Efficiency Sprint?
SCOPE™ by Efficiency Sprint is an operational AI readiness method created by Luba Inz. It scores each part of a business on process and data, places it in one of five states (Stabilize, Codify, Ownership, Pulse, Engine) and turns the result into a plan with an order of work.
How do I know if my company is ready for AI?
Take one process and ask three things: could someone other than you run it from what's written down, is one named person allowed to decide the exceptions, and does one number you trust tell you weekly whether it worked. Three yeses means the routine part can be automated with a person on the exceptions. Fewer means fix first.
What should we fix before implementing AI agents?
The three problems underneath: rules that live in people's heads, decisions that can't be made without the owner, and numbers two systems disagree about. In that order, because a written rule with no owner still stalls, and an owned process on untrusted data still produces confident wrong answers.
What's the difference between SCOPE™ by Efficiency Sprint and an AI maturity model?
A maturity model scores a company's AI strategy. SCOPE™ by Efficiency Sprint scores the work itself, process by process, and ends in an executable plan rather than a grade. It's built to be acted on by the operator, not presented to a board.
Who created SCOPE™ by Efficiency Sprint?
Luba Inz, Efficiency Sprint. She spent eight years inside an owner-led company, most of it running its operations, and built the method out of the same problem appearing in every company she walked into: the business couldn't explain its own work well enough to hand it to anyone, let alone a machine.

Find where you stand.

Eight questions, about two minutes, no email to start.

Take the readiness check

The full version is the Diagnostic: two weeks, your own systems, every area scored and ranked.

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