Skip to content
AI course starts September 22See course

Enterprise research

Dashboard for virtual prototyping

The delivered dashboard compares prototypes, predicts consumer targets from analytical or sensory inputs, supports virtual prototyping, and exports editable presentation reports.

Macro texture sample on a glass slide with lab calipers

Evidence at a glance

Evidence type
Delivered system
Organization scope
A major CPG company
Documented boundary and output
This case documents the dashboard as delivered: prototype comparison, consumer-target prediction, virtual prototyping, and editable report export. Client specifics stay confidential.

The situation

Researchers needed one place to compare prototypes, predict consumer targets, and export editable reports from model output.

The delivered system is a modeling workbench, not a slide deck. Researchers place prototypes in the modeled product set, compute supported consumer measures from analytical or sensory inputs, explore response surfaces, and leave with editable presentation output.

The approach

  1. Compare prototypes

    Researchers place new prototypes beside the products already represented in the model.

  2. Predict consumer targets

    Analytical or sensory inputs drive the consumer measures the model supports.

  3. Explore and report

    Virtual prototyping tools show input-response relationships and compile results into editable presentation output.

System or method for this case

Dashboard capability map from sensory and analytical inputs to predictions and export

What we delivered

  • Prototype comparison against the modeled product set
  • Consumer-target prediction from analytical or sensory inputs
  • Virtual prototyping controls for input-response exploration
  • Editable presentation export from the active analysis

Technical pieces

Model-backed product comparisonPrediction path from sensory or analytical inputsInteractive exploration toolsReport compiler for editable slides

What changed

Researchers can compare prototypes, predict supported consumer measures from analytical or sensory inputs, explore input-response relationships, and export editable presentation output from one dashboard.

Discuss a comparable system

Bring the research question, data boundary, and decision the system needs to support.

Talk to a systems strategist