Smart trial and error
Meeting the demand for rapid innovation

Gaining and maintaining competitive advantage requires today’s organizations to innovate at increasing speed. As products and processes become more complex, subject matter expertise alone does not always deliver progress at the pace demanded. Many experts working in R&D rely on a traditional approach to this problem, changing one variable at a time. It might seem to offer the structure for more predictability, but can end up constraining innovation and decreasing efficiency in the long run.

The answer for an increasing number of organizations is design of experiments (DOE). DOE is a methodology that scales regardless of the size of the problem. It provides the ability to thoroughly explore the opportunity space, creating a model that can increase understanding of the problem, drive decisions and enable consensus with other stakeholders.
The more complex a problem and the more factors involved, the bigger the opportunity space to be explored – and the greater the impact of DOE.

Tim Gardner is a scientist and the CEO and founder of Riffyn, an organization enabling scientists to easily combine DOE with efficient data management and contextualization. Gardner said recently that DoE has changed his life, just as it changed organizations where he worked in the past.  Some plants where he worked with DOE experienced a productivity boost of 10-15% and reduced time to market for new products from 15 months to three months.

Bradley Jones, Senior Research Fellow at JMP, calls DOE “active learning” and highlights how it gives organizations the ability to “fail fast”, which in turn drives rapid innovation. Perhaps reframing DOE in these terms would help to demystify it and encourage more scientists and organizations to make the leap.  

Join us for a discussion about the power of using smart trial and error to speed innovation; achieve faster, more predictable cycles; and save time.