Data-driven Decision Making

Definition

Data-driven decision making is the practice of basing strategic and operational choices on concrete data, insights, and performance metrics rather than assumptions or intuition. It enables organizations to act with greater accuracy, reduce risk, and continuously improve both innovation outcomes and business operations.

In the context of innovation, data can inform every stage — from Idea Screening to Scaling. It ensures that ideas are selected based on real value potential, user feedback, and measurable KPIs. Tools like dashboards, analytics platforms, and Idea Heatmaps help visualize insights and guide prioritization.

This approach is closely aligned with continuous learning and agile methodologies. By integrating Validation and feedback loops into the process, teams can adjust their direction with confidence and deliver results aligned with business goals and user needs.

Relevant links and use cases

  • Nosco Consultancy – advisory support to help companies embed data and evidence into innovation processes

  • VELUX Use Case – an example of how data and structured innovation frameworks drive measurable results

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Related concepts

Ideation

Ideation is the creative process of conceiving and shaping new ideas. It includes everything from the first thought or inspiration to the formulation of an idea. In the context of an innovation challenge, it refers to the initial phase in which ideas are submitted online and…

Idea management

Idea management is the structured process of managing ideas from ideation through evaluation and refinement to selection. Many companies use an idea management platform to support this process (the Nosco platform is an example of this).

Call for ideas

A call for ideas is an announcement used when an organization or person looks for ideas on a specific topic or project. In the field of innovation, it is used to describe the types of ideas welcome to an innovation challenge…