The Head Game
High Efficiency Analytic Decision-Making and the Art of Solving Complex Problems Quickly
Failed to add items
Add to cart failed.
Add to wishlist failed.
Remove from wishlist failed.
Follow podcast failed
Unfollow podcast failed
2 credits with free trial
Buy Now for ₹668.00
No valid payment method on file.
We are sorry. We are not allowed to sell this product with the selected payment method
-
Narrated by:
-
Gregory Abbey
-
Written by:
-
Philip Mudd
About this listen
Become a High Efficiency Analytic Decision maker.
We've all been there: faced with a major decision yet overwhelmed by the very data that is supposed to help us. It's an all-too-common struggle in the digital age, when Google searches produce a million results in a split second, and software programs provide analysis faster than we could ever hope to read it. Adapting the geopolitical and historical lessons gleaned from over two decades in government intelligence, Philip Mudd - an ex-National Security Council staff member and former senior executive at the FBI and the CIA - finally gives us the definitive guidebook for how to approach complex decisions today.
Filled with logical yet counterintuitive answers to ordinary and extraordinary problems - whether it's buying a new home or pivoting a failing business model - Mudd's HEAD (High Efficiency Analytic Decision-making) methodology provides listeners with a battle-tested set of guiding principles that promise to bring order to even the most chaotic problems, all in five practical steps:
- What's the question? Analysts often believe that questions are self-evident, but focusing on better questions upfront always yields better answers later.
- What are your drivers? The human mind has a hard time juggling information, so analysts need a system to break down complex questions into different characteristics, or drivers.
- How will you measure performance? Once the question has been solidified and the drivers determined, an analyst must decide what metrics they will use to understand how a problem - and their solution to it - is evolving over time.
- What about the data? Rather than looking at each bit of information on its own and upfront, an analyst can overcome data overload only by plugging data into their driver categories and excising anything that doesn't fit.