Operational Maturity Diagnostic

Assess your
operational maturity

A scenario-based diagnostic for any operations-driven organization. Identify where you are on the digital curve, where the gaps are, and the highest-leverage next steps.

Start Assessment

Operational Maturity Diagnostic

How the scoring scale works

Informal

No structured approach. Paper-based, manual, ad-hoc.

Reactive

Some digital tools exist, but used inconsistently. Decisions driven by experience.

Standardised

Formal systems in place. Consistent processes, centralised data, some automation.

Data-Driven

Real-time visibility. Analytics inform decisions. Systems are integrated.

Optimised

Continuous improvement through AI/ML. Predictive and prescriptive operations.

Tip: If you find yourself between two options, pick the lower one. It’s better to under-estimate and discover strengths than to over-estimate and miss gaps.

0 of 12 questions answered

Pillar 1

Connectivity & Data Collection

How your machines, systems, and data are connected - the digital foundation of your factory.

Question 1 of 12

How is production data collected from your machines?

Think about the majority of your shopfloor equipment.

Paper-based

Operators record data on paper forms or whiteboards, later typed into spreadsheets.

Manual digital entry

Operators manually enter data into a computer system (ERP, Excel) during or after shifts.

Partially automated

Some machines send data automatically, but many still require manual logging.

Mostly connected

Most machines are connected and stream data to a central platform automatically.

Fully connected

All machines stream real-time data, with automatic alerts, dashboards, and closed-loop actions.

Question 2 of 12

How well are your core business systems connected?

Consider ERP, MES, QMS, CMMS, PLM, or similar systems you use.

Standalone tools

We use standalone tools (Excel, paper) for most operational tasks. No integrated system.

Disconnected systems

We have an ERP but other functions (quality, maintenance) run on separate, disconnected tools.

Partially integrated

Key systems are in place and some share data, but manual re-entry is still common.

Mostly integrated

Most systems exchange data automatically. A single source of truth exists for core processes.

Fully integrated

All systems are fully integrated. Data flows seamlessly across planning, production, quality, and maintenance.

Question 3 of 12

How is your operational data stored and governed?

Think about where production data, quality records, and machine logs end up.

Local files

Data lives in personal files, local PCs, or paper archives. No central repository.

Shared drives

Some data is in shared drives or a basic database, but there's no formal structure or ownership.

Central database

A central database or cloud platform stores most operational data with basic access controls.

Governed platform

Data is centrally managed with clear ownership, retention policies, and role-based access.

Compliance-ready

A governed data platform with automated quality checks, versioning, and compliance-ready audit trails.

Pillar 2

Analytics & Intelligence

What you do with your data - from basic reporting to AI-powered decision-making.

Question 4 of 12

What level of production analytics do you currently use?

Think about OEE, downtime analysis, cycle time tracking, scrap rates, etc.

No systematic tracking

We don't track production KPIs systematically. Reviews are based on gut feel or end-of-month totals.

Manual KPIs

We calculate basic KPIs manually (e.g. OEE in spreadsheets) but not in real-time.

Dashboards

We have dashboards showing daily/shift-level KPIs, but analysis is mostly retrospective.

Real-time analytics

Real-time dashboards with drill-down capability. We regularly identify root causes from data.

Predictive analytics

Predictive analytics flag issues before they happen. Models continuously learn and suggest improvements.

Question 5 of 12

How does your quality control process work?

Consider inspection, defect detection, and traceability.

Manual inspection

Quality checks are manual and paper-based. Defects are caught at final inspection or by customers.

Documented procedures

We have documented inspection procedures, but data is recorded manually and analysed after the fact.

Digital checklists

Digital checklists or SPC tools are used. Quality data feeds into a system, but review is periodic.

Real-time monitoring

Real-time quality monitoring with automated alerts. Full traceability from raw material to finished product.

AI-powered

AI-powered visual inspection or anomaly detection. Quality models predict defects and adjust processes automatically.

Question 6 of 12

How are maintenance decisions made for your equipment?

Think about how you decide when to service, repair, or replace machines.

Reactive only

We fix machines when they break down. No scheduled maintenance plan.

Time-based

We follow time-based maintenance schedules (e.g. every 3 months), regardless of actual condition.

Condition monitoring

We combine scheduled maintenance with some condition monitoring (e.g. vibration, temperature sensors).

Condition-based

Condition-based maintenance is standard. Sensor data triggers work orders automatically.

Predictive

Predictive models forecast failures before they occur. Maintenance is optimised based on production schedules and risk.

Pillar 3

People & Culture

The human side of digital transformation - skills, leadership, and willingness to change.

Question 7 of 12

What is the digital comfort level of your shopfloor teams?

Think about operators, technicians, and team leaders.

Uncomfortable

Most shopfloor staff are uncomfortable with digital tools. Training is minimal.

Basic usage

Some staff can use basic software (email, ERP entry) but resist new digital tools.

Regular users

Teams regularly use digital tools (tablets, dashboards) and receive periodic training.

Proficient

Staff are proficient with digital tools and actively suggest improvements. Training is ongoing.

Digital culture

A culture of digital literacy exists. Teams self-serve data, create their own reports, and mentor others.

Question 8 of 12

How does leadership approach data-driven decision-making?

Think about plant managers, directors, and C-level executives.

Intuition-based

Decisions are primarily based on experience, intuition, or anecdotal evidence.

Data-aware

Leaders acknowledge the value of data but rarely use it systematically in decisions.

Data-supported

Key decisions are supported by data (reports, KPIs), though some rely on experience.

Data-driven

Leadership routinely uses dashboards and analytics. Investment decisions are backed by data.

Data culture

Data-driven culture is embedded. Leadership champions continuous improvement through advanced analytics.

Question 9 of 12

How does your organisation respond to change and new technology?

Think about past attempts to introduce new systems, processes, or tools.

Strong resistance

Strong resistance to change. New initiatives often fail due to lack of buy-in.

Slow adoption

Change happens, but slowly and with significant pushback. No formal change management.

Structured approach

A structured approach exists for introducing change, with some success stories.

Proactive

Change is managed proactively with stakeholder engagement, pilots, and feedback loops.

Innovation culture

Innovation is part of the culture. Teams actively seek out and experiment with new technologies.

Pillar 4

Process & Governance

How well your processes are documented, standardised, and compliant - the backbone of scalable digitalisation.

Question 10 of 12

How standardised and documented are your production processes?

Think about work instructions, SOPs, and process definitions.

Tribal knowledge

Knowledge lives in people's heads. Little or no written documentation.

Outdated docs

Some processes are documented but documents are outdated, inconsistent, or hard to find.

Maintained SOPs

SOPs exist for key processes, are maintained, and staff are trained on them.

Digitally managed

Processes are digitally managed with version control. Deviations are tracked and acted upon.

Continuously optimised

Processes are continuously optimised based on data. Digital twins or simulations test changes before implementation.

Question 11 of 12

How do you track material and product traceability?

Think about your ability to trace a finished product back to its raw materials and production steps.

No traceability

No formal traceability. If a defect is found, identifying the batch or source is very difficult.

Basic batch tracking

Basic batch tracking exists (e.g. lot numbers on paper), but end-to-end tracing is manual.

System-recorded

A system records key traceability data (batch, supplier, date), queryable but not fully automated.

Full digital trace

Full digital traceability from supplier to customer. Recall scenarios can be executed quickly.

Advanced traceability

Blockchain or advanced traceability systems provide immutable records. Automated compliance reporting.

Question 12 of 12

How do you measure and manage your environmental impact?

Think about energy consumption, emissions tracking, and sustainability initiatives.

Not measured

We don't actively measure energy use or emissions at process level.

Utility bills only

We track utility bills and overall energy costs, but not at machine or process level.

Key equipment

Energy monitoring is in place for key equipment. We report on basic sustainability metrics.

Real-time monitoring

Real-time energy monitoring per machine/line. Sustainability KPIs are part of management reviews.

Automated optimisation

Automated carbon footprint tracking integrated with production data. Optimisation algorithms minimise energy per unit.

Your results

Overall digital maturity

0.0 / 5.0

12/12 answered

Connectivity & Data Collection

0.0

3/3 questions answered

Analytics & Intelligence

0.0

3/3 questions answered

People & Culture

0.0

3/3 questions answered

Process & Governance

0.0

3/3 questions answered

Reading the pillar gaps

The most actionable insight is not the overall number - it’s the gap between pillars. A company scoring 4 on Connectivity but 2 on People has invested in technology without bringing teams along. Look for the pillar(s) where your score is lowest relative to the others - these represent your highest-leverage improvement opportunities.

What’s Next?

Share your completed diagnostic with KFactory® for a personalised readiness report with prioritised recommendations and a suggested roadmap. Submit your details and your PDF roadmap will download automatically.

Assess youroperational maturity

Operational Maturity Diagnostic

Your results

Reading the pillar gaps

What’s Next?

Assess your
operational maturity