Score Your Manufacturing Digitalization Maturity

None: everything is written on paper or entered manually at the end of a shift.

A little: one or two machines or lines report automatically, the rest is manual.

Most: the majority of lines report automatically, with some manual gaps.

Nearly all: automatic capture is the default across the plant.

By memory and a whiteboard or phone calls, with no written schedule.

In Excel, rebuilt manually whenever orders or constraints change.

In a planning tool, but constraints and changeovers are only partly modeled.

In a planning tool with real constraints, capacity and changeover logic built in.

Paper travelers or verbal instructions, with no digital confirmation.

A shared spreadsheet or whiteboard, updated manually through the shift.

A digital screen or panel at some but not all work centers.

A digital screen or panel at every work center, with real-time status.

On paper, filed and rarely analyzed afterward.

In a spreadsheet, checked periodically by a quality engineer.

In a digital system, but without automatic inspection or SPC.

In a digital system with automated inspection, SPC and traceability.

Reactively: a machine breaks, then it gets fixed.

A basic preventive calendar, tracked manually.

A CMMS with scheduled preventive maintenance and work orders.

A CMMS plus condition-based or predictive triggers on critical assets.

Regularly wrong. Physical counts often surprise us.

Roughly right, corrected through periodic manual counts.

Mostly accurate, with barcode or scanner confirmation for most moves.

Consistently accurate, with real-time confirmation for nearly every move.

Only the total plant bill, with nothing broken down.

By utility type (electricity, gas, compressed air), but not by area or machine.

By area or line, but not consistently by individual machine.

By machine or process, tied to production output.

Not at all. Decisions are made on experience and gut feel.

Basic reporting and dashboards, no predictive or AI use.

One pilot or limited use case (e.g. one inspection point or one prediction model).

Multiple production decisions are informed by models validated against real data.

Nobody. Each area or line uses whatever it has picked up over time.

An informal understanding that is neither written down nor consistently followed.

A documented standard for some systems that is not yet enforced everywhere.

A documented, actively governed standard, with a clear owner and review process.