Kurser

Nyt10 dages kursus 

The Modern Data-driven Innovation Program

22. oktober 2025 til 17. september 2026 Aarhus
DKK  45.000
ekskl. moms
Nr. 91842
Tilmeld dig

The Modern Data-driven Innovation Program is a year-long, hands-on program for R&D specialists, product developers, and innovation managers who want to accelerate discovery and reduce risk in their projects. Through collaborative modules and peer support, participants learn to implement data-driven methods through skills in analysis, experimental design and cross-company learning - all to ensure better results and more predictable innovation outcomes for every participating organization.

What: A 10-module program teaching R&D specialists to reduce development uncertainty and accelerate discovery through systematic experimental design and modern data-driven decision making.
Why: Companies that use data-driven methods gain competitive advantage by higher innovation success rates, reduced development risk and faster time-to-discovery in uncertain environments.
Who: R&D specialists, product developers, and innovation managers who need to create new knowledge and navigate uncertainty rather than only optimize existing processes.
How: Year-long collaborative learning with immediate application to participants’ own projects, supported by peer learning across multiple companies and leadership involvement.


Target audience and value

Specific roles:
• Product developers/engineers and research scientists (2-10 years experience)
• R&D project leaders transitioning from technical to strategic thinking
• Innovation managers making go/no-go decisions under uncertainty

Prerequisites:
- Active involvement in development/innovation projects with uncertain outcomes
- Basic statistical training (STEM statistics, Six Sigma green belt or equivalent)
- Access to experimental systems (laboratory, pilot, or development environment)

Companies typically see value through:
- More predictable R&D outcomes, with clearer go/no-go decision points
- Reduced project risk, by identifying dead-ends earlier in development
- Better resource allocation, across innovation portfolios
- Faster knowledge transfer, from R&D to production teams

Udbytte

  • Align experimental strategies with business goals and stakeholder needs
  • Make evidence-based go/no-go decisions using statistical and business criteria
  • Design cost-effective experiments appropriate for R&D innovation challenges
  • Evaluate and improve data quality across organizational boundaries
  • Communicate experimental findings effectively to technical and non-technical audiences
  • Build sustainable data-driven practices within teams and organizations
  • Manage risk and uncertainty throughout the innovation process
  • Implement the tools and methods on your own on-going projects

Program format

Core learning structure, spanning October 2025 to September 2026:

  • 10 on-site modules providing frameworks, tools and methods
  • Monthly open office sessions for ongoing project support and peer learning
  • Continuous application to participants’ own innovation challenges between sessions

Key modules:
data tabel v2

*Modules intended for both specialists and their closest manager.


Continuous support between modules: The program’s open office sessions are a core feature, not an add-on. These monthly sessions provide:
- Peer feedback on participants’ ongoing experiments and challenges
- Instructor guidance on adapting methods to specific company contexts
- Cross-company learning from real implementation experiences
- Problem-solving support for practical obstacles participants encounter

Every on-site module sets aside time for participants to present progress, share challenges and receive feedback from peers facing similar innovation problems across different companies.

Practical details

Each modules lasts 9:00-16:00 at the Danish Technological Institute, Kongsvang Allé 29, 8000 Aarhus C. The program is conducted in English. Schedule changes may occur with sufficient advance notice.

What makes this different

This is collaborative capability building, not traditional classroom teaching. Participants learn methods, apply them immediately to real projects and troubleshoot implementation challenges with peers across multiple companies.

Key differentiator vs. Six Sigma: While Six Sigma optimizes what you know works, this program accelerates discovering what will work next – focusing on exploration and smart risk-taking rather than variation reduction.

Pricing

  • 1 Specialist + manager: 45,000 DKK
  • 2 Specialists + manager: 75,000 DKK
  • 3 Specialists + manager: 95,000 DKK
  • Each additional specialist: 20,000 DKK

NOTE: For technical reasons, price per participant will show as 45.000 DKK irrespective of the number of sign-ups – the above discounts will be applied before billing.

Strong discount for multiple participants to encourage critical mass of internal capability.
Software: Design Expert (~$1140) and Brownie Bee (~€828) licenses required if not available.

Detailed learning goals

Topic: From business problem to experimental plan and organizational alignment. After the program, participants can:
  • Convert real-world project goals to structured experiments that balance stakeholder needs across departments
  • Scope and design experiments that fit practical organizational constraints
  • Quantify desired improvements, translate them to business value and communicate trade-offs to different organizational levels
  • Navigate conflicting goals from R&D, production, quality and commercial teams when designing experimental strategies
Topic: Experimental design in organizational context. After the program, participants can:
  • Choose experimental designs appropriate for R&D innovation challenges (vs. process optimization)
  • Balance experiment cost against information gain while accounting for organizational risk tolerance
  • Build on historical data and diagnose when existing data quality supports experimental goals
  • Design experiments that fit into existing workflows and systems
Topic: Risk management and stakeholder communication. After the program, participants can:
  • Balance the trade-off between resource investment and risk of not finding solutions in ways that align with organizational strategy
  • Ensure analytical questions can be answered within budget and timeline constraints
  • Communicate experimental uncertainties and potential outcomes to management and other departments
  • Build support for data-driven approaches among colleagues and leadership
Topic: Measurement systems analysis and organizational data quality. After the program, participants can:
  • Evaluate data quality before running experiments, in collaboration with R&D, production, quality and IT teams
  • Understand sources of variability across organizational boundaries and implement mitigating strategies
  • Implement low-cost data quality improvements that work within existing organizational structures
  • Provide technical input on data governance to serve both innovation needs and compliance requirements
Topic: Analysis, conclusions and communication. After the program, participants can:
  • Analyze and interpret results of experiments with statistical rigor and translate findings to different organizational audiences
  • Identify when to expand, pivot or stop experiments based on both statistical and business criteria
  • Translate from scientific conclusions to business conclusions and make clear recommendations for management
  • Create compelling case studies that drive further adoption of data-driven methods
  • Build bridges between R&D discoveries and implementation teams (production, quality, commercial)
Topic: Sustainable implementation and organizational change. After the program, participants can:
  • Implement methods in ways that build organizational capability rather than individual expertise
  • Design low-risk pilot experiments that demonstrate value and build organizational confidence
  • Create workflows and SOPs that embed data-driven thinking into routine organizational processes
  • Coach colleagues and build internal networks that sustain data-driven innovation practices

Vælg dato

Aarhus
22. oktober 2025 til 17. september 2026
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