Case Study

A New tech demo company had an internal R&D facility where similar experiments were carried out by a team of highly skilled Scientists. Experiments were performed using different methods and techniques, depending on the scientist, which meant there was a high degree of variability. it was almost impossible to  combine data sets or draw  comparisons between projects. The experimental cycle time from setup to data analysis was very long with no core structure or ownership. This resulted in long information feedback loops, unreliable data and delays to important project work.

An initial investigation uncovered several key issues:


  • No standard methods for preparing and running the experiments.
  • No standardisation of materials used in the experiments.
  • Tools and materials were not always available which resulted in ad hoc improvisation.
  • The recording of data was poor and often recorded and collated in different formats.
  • No process existed for sharing new learnings or practices.
  • There was no process development or improvement program in place.


Identified the following:

  • Best practice for experiment method.
  • Common experimental preparation and set-up.
  • Best methods for reporting experimental data.
  • Identification of correct tools and materials required.
  • Turnaround assessment experimental set-up. (SMED)


  • Defined two standard experimental set-ups for all R&D projects
  • Standardised experimental method and preparation.
  • Standard batch papers for requesting experiments
  • Implemented visual management system for materials and tools.
  • All R&D activities restricted to fully trained technicians working to standard procedures.
  • All R&D output data published in standard format.
  • Improved workplace organisation by applying 5S.


  • Quicker and reliable information feedback for Technology, Engineering and Production departments.
  • Repeatable and comparable experiments with accurate and valid data.
  • Standardised processes suitable for applying sustainable lean process improvement
  • Increase capacity and throughput of R&D facility.
  • Increased confidence in data minimising less rework.