The HEAD Game

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 be buying a new home or pivoting a failing business model—Mudd's "HEAD" (High Efficiency Analytic Decision-making) methodology provides readers 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 up front 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 up front, an analyst can only overcome data overload by plugging data into their "driver" categories and excising anything that doesn't fit.

• What are we missing? Complex analysis isn't easy, so it is imperative to assume that the process is flawed, while also knowing how to check for possible gaps and errors, such as availability bias, halo effects, and intuitive versus analytic methodologies.