Building a data-driven culture requires business experimentation at scale. However, the limitations of basic controlled experiments makes standard A/B testing a poor candidates for wide-spread adoption.
Iavor Bojinov, Assist. Professor, Harvard Business School, argues that next-gen experimentation requires developing novel statistical methodologies and a new understanding of the operational implications of this seismic shift in product development.
Is a clear solution emerging? And, what can leaders do to successfully transition to the next level of experimentation?