Hi ,
Executives don't need data scientists to tell them how to save money.
Saving money is easy - just turn off the power or hire fewer staff.
It's increasing revenue that's the difficult thing to do.
This is why, although strategies to save money may get a look, it's revenue raising initiatives that will really get executives to pay attention.
While comparing the relative importance of saving money and increasing revenue is important, understanding this is just the beginning of uncovering what truly drives executive decisions.
Through his experience leading analytics teams, AI strategist Gregory Lewandowski has identified five key executive priorities that determine which initiatives gain traction -
and which are indefinitely postponed.
For data scientists, understanding these priorities is essential to transforming technical results into real business value.
In the latest episode of Value Driven Data Science, Gregory and I discuss the five executive
priorities and their implications for data science.
This episode reveals:
- The two priorities that can unlock budget even mid-cycle (and why cost savings isn't one of them)
- How executive priorities evolve across technology adoption cycles
- Why misaligned compensation
metrics doom data science projects
- The "follow the money" framework for understanding what drives business decisions
Discover how understanding these executive priorities can transform your data science initiatives from technical exercises into strategic business assets. Listen now on Apple Podcasts or Spotify, or click the link
below:
Episode 60: 5 Executive Priorities That Transform Data Science Results into Business Value
Talk again soon,
Dr Genevieve Hayes.
