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.
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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?
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.
We have a lot to explore that can help you understand feature flags. Learn more about benefits, use cases, and real world applications that you can try.
We’re excited to accompany you on your journey as you build faster, release safer, and launch impactful products.