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Digital Twin Trust & Value Assessment for Manufacturing

Measures internal stakeholder trust, perceived accuracy, and operational value of digital twins across manufacturing functions. Identifies adoption barriers and investment priorities to guide program improvements.

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Digital Twin Trust & Value Assessment for Manufacturing

Welcome, and thank you for participating in this survey about digital twins in our organization. The purpose is to understand how digital twins are used, trusted, and valued across different functions. Your participation is entirely voluntary and you may stop at any time. All responses are confidential and will be reported only in aggregate — there are no right or wrong answers. The survey takes approximately 10 minutes to complete.

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Sample questions

A preview of what’s in the template. Every question is editable before you launch.

20 questions · ~10 min
Message

Welcome, and thank you for participating in this survey about digital twins in our organization. The purpose is to understand how digital twins are used, trusted, and valued across different functions. Your participation is entirely voluntary and you may stop at any time. All responses are confidential and will be reported only in aggregate — there are no right or wrong answers. The survey takes approximately 10 minutes to complete.

Q01
Multiple Choice

What is your current level of involvement with our digital twins?

  • Hands-on user of a digital twin
  • Project owner or decision-maker
  • Collaborates occasionally with the twin team
  • Aware, not involved
  • Not familiar with digital twins
Q02
Dropdown

Which area best matches your current function?

  • Operations/Production
  • Maintenance/Asset Management
  • Quality
  • Process/Manufacturing Engineering
  • R&D/Product Engineering
  • IT/OT
  • Supply Chain/Planning
  • Other
Q03
Multiple Choice

Which data sources are currently integrated into the digital twin(s) you use or support? (Select all that apply)

  • PLC/SCADA data
  • IoT sensors (condition monitoring)
  • MES/production execution
  • ERP (orders, inventory)
  • CAD/BOM/PLM
  • Maintenance/CMMS
  • Simulation models
  • Not sure
  • Other
Q04
Multiple Choice

How are the digital twin's outputs validated in your area? (Select all that apply)

  • Compared with live production data
  • Backtesting with historical data
  • Subject matter expert sign-off
  • Automated drift/accuracy monitoring
  • Formal measurement and verification (M&V)
  • We do not validate today
  • Not sure
Q05
Opinion Scale

How accurately does the digital twin mirror current production conditions in your area?

Scale: 1 – 7
Min:Not at all accuratelyMax:Extremely accurately
Q06
Opinion Scale

Overall, how much do you trust the outputs from our digital twins today?

Scale: 1 – 7
Min:No trust at allMax:Complete trust
Q07
Opinion Scale

How useful is the digital twin for predicting or preventing production issues in your area?

Scale: 1 – 7
Min:Not at all usefulMax:Extremely useful
Q08
Opinion Scale

How useful is the digital twin for optimizing process parameters or throughput in your area?

Scale: 1 – 7
Min:Not at all usefulMax:Extremely useful
Q09
Opinion Scale

How useful is the digital twin for supporting planning, scheduling, or capacity decisions in your area?

Scale: 1 – 7
Min:Not at all usefulMax:Extremely useful
Q10
Opinion Scale

How useful is the digital twin for quality monitoring or root-cause analysis in your area?

Scale: 1 – 7
Min:Not at all usefulMax:Extremely useful
Q11
Ranking

Rank the following factors by how much they increase your trust in a digital twin (most to least important).

  1. Transparent versioning and change history
  2. Validation against ground truth data
  3. Explainable recommendations/visibility into drivers
  4. System uptime and performance
  5. Clear ownership and support model
Drag to rank
Q12
Multiple Choice

Which barriers most limit the adoption or impact of our digital twins today? (Select all that apply)

  • Data quality and availability
  • Integration with existing systems
  • User skills and training
  • Unclear ROI or business case
  • Security and compliance requirements
  • Model transparency/explainability
  • Tool usability
  • Change resistance/culture
  • Other (please specify)
Q13
Ranking

Rank the following areas by where investment would most improve digital twin trust and outcomes (most to least important).

  1. Data quality and availability
  2. Validation and accuracy monitoring
  3. Explainability and transparency
  4. User experience and training
  5. Integration and performance
  6. Governance, ownership, and support
Drag to rank
Q14
Long Text

Are there any security or compliance risks related to our digital twins that you believe should be addressed? If so, please describe them briefly.

Q15
Long Text

What is one metric you would use to judge the digital twin's usefulness in your area?

Q16
AI Interview

Based on your responses in this survey, please share any additional thoughts or suggestions on how we can improve digital twin trust, usefulness, or adoption in your area.

Q17
Dropdown

Where is your primary work location/region?

  • North America
  • Europe
  • Asia-Pacific
  • Latin America
  • Middle East/Africa
  • Multiple regions
  • Prefer not to say
Q18
Dropdown

How many years have you worked in manufacturing or industrial operations?

  • 0–2
  • 3–5
  • 6–10
  • 11–15
  • 16+
  • Prefer not to say
Q19
Multiple Choice

Which best describes your current role level?

  • Individual contributor
  • Team lead/Supervisor
  • Manager
  • Director or above
  • Consultant/Contractor
  • Prefer not to say
Q20
Multiple Choice

What best describes your primary work environment?

  • Shop floor
  • Office
  • Hybrid
  • Remote
  • Field/on-site customer locations
  • Prefer not to say
Message

Thank you for your time and insight! Your responses will help us prioritize improvements to our digital twin program.

What’s included

  • AI follow-ups

    Adaptive probes on open-ended answers that pull out detail a static form would miss.

  • Attention checks

    Built-in safeguards against rushed answers and low-quality respondents.

  • AI-drafted copy

    Wording, ordering, and branching written by the AI — tuned to your research goal.

  • Auto report

    Themes, quotes, and a plain-English summary write themselves once responses come in.

Frequently asked questions

What questions are in the “Digital Twin Trust & Value Assessment for Manufacturing” template?

The template includes 20 ready-to-use questions, starting with: “What is your current level of involvement with our digital twins?” · “Which area best matches your current function?” · “Which data sources are currently integrated into the digital twin(s) you use or support? (Select all that apply)”. The full set is previewed above, and every question is editable.

How long does this survey take to complete?

Respondents typically finish the 20 questions in about 10 minutes.

Can I customize this template?

Yes — every question, answer option, and the ordering is editable before you launch. You can add or remove questions, or ask the AI editor to rework the survey around your research goal.

Is this template free to use?

Yes. Open it in the editor and start customizing right away — no account required to try it, and the free plan covers launching your survey.

Ready to launch?

Open this template in the editor. Every part is yours to change before the first respondent sees it.

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