Philip Mudd - The HEAD Game: High-Efficiency Analytic Decision Making and the Art of Solving Complex Problems Quickly

THE HEAD GAME

HIGH EFFICIENCY ANALYTIC

DECISION-MAKING

AND THE ART OF SOLVING

COMPLEX PROBLEMS QUICKLY

PHILIP MUDD

L IVERIGHT P UBLISHING C ORPORATION

A DIVISION OF W. W. NORTON & COMPANY

NEW YORK LONDON

This book is for Meredith and Dave.
And for those little ones, Jacob and Nora.
You all bring such joy. Thank you, every day,
for letting me into the family. I love you guys.
What else is there to say?

CONTENTS

Analysts often acquire data and knowledge without carefully considering how that expertise helps a decision maker solve a problem. Many experts fail to bridge this gap, the transition from capturing knowledge for a presentation to anticipating the decision makers needs. The best analysts think backward, providing decision advantage by molding briefings, papers, e-mails, and other communications so that they answer a decision makers question with maximum efficiency.

Analysts often believe that questions are self-evident. Experts studying political stability in a foreign country might focus on a simple question: Will the opposition movement succeed? Focusing on better questions (How can we understand those characteristics that might decide whether this opposition movement threatens the government?) leads to better answers. The questions are the hardest part of many analytic problems, but they are the analytic step most frequently ignored by analysts.

The human mind has a hard time juggling mounds of information simultaneously, so all of us revert to weighing just a few pieces of knowledge when we answer everyday questions. To break down hard questions analytically, we need an approach that allows us to escape the limitations of our minds and look at many characteristics of problems simultaneously. We will call these characteristics drivers, to emphasize that these elements of a problemsuch as the characteristics you might look for when you buy a housedrive how analysts break down and answer hard questions.

Experts with years of experience apply intuition to every problem they face: With a wealth of experience, what does my personal compass tell me about where this problem is headed? Without metrics to measure how an analytic problem is changing over time, expert or intuitive judgments about complex problems risk using yesterdays events to explain tomorrows.

Increasing amounts of data can be unmanageable, and the problem of sorting through data overload may only worsen in this digital era. Rather than looking at each bit of information as a discrete data point, we want to look at our drivers and sort the data according to which driver it supportsin other words, sort the data into each of the half-dozen or so driver categories, so analysts have a few piles to deal with rather than a thousand discrete data points.

At some point in this thinking process, we have to step back and make a basic assumption: complex analysis isnt easy, and even a highly trained analyst can make a mistake. How can we assume that an analytic process is flawed and then find ways to check for gaps and errors?

The steps through the analytic process in the book start with thinking about the decision maker first and then breaking down the decision makers question into manageable parts, before we finally sort data. At the conclusion, we want to put all these pieces of an analytic puzzle back together into one multistep process that we can use to attack a wide variety of analytic problems.

Disclaimer: All statements of fact, opinion, or analysis expressed are those of the author and do not reflect the official positions of the CIA or any other US government agency. Nothing in the contents should be construed as asserting or implying US government authentication of information or agency endorsement of the authors views. This material has been reviewed by the CIA to prevent the disclosure of classified information.

S ometimes lifes choices are overwhelming. Start with the data explosion we all live with, from Google searches that produce a million results in a split second to software programs that generate data analyses faster than we can read them. You would think that with all this data at our fingertips life would become more manageable, and decisions might come easier. It hasnt worked out that way in the digital age. As any Google search will tell you, more data can mean more complexity, and more information to sort. Do you want to buy a car? Three hours after you start your search, youve compared dozens if not hundreds of vehicles, but you may be no closer to a decision. In fact, theres a good chance you feel more overwhelmed than ever, drowning in a sea of data.

I walked into my first management job at the Central Intelligence Agency in the late 1990s, when the agency was already living in the world of data overload. I had started nearly fifteen years earlier, as the CIA transformed rapidly from paper to the digital age. Throughout my career, most of the information we sifted throughwe being me plus the thousands of other analysts and managerswas classified top secret data. My own responsibility was the unit tasked with analyzing Iraqs politics, military capabilities, stability, and economy, in the years before anyone conceived that a war to oust Saddam Husayn might be around the corner. The analyses we prepared were based on data from every corner of the planet, supplied to us by a network of secret human informants, media reports, intercepted communications, satellite photos, background from friendly foreign security services, and an intelligence soup of other material.

The questions we wrestled with were as varied as the data sources that streamed in every hour of every day. What was Saddams intent toward Kuwait, a country he had invaded in 1990? Would he ever try to retake this neighbor to the south? What did we know about internal stability in Baghdad and elsewhere across the country? Was there any chance Saddam would be under threat himselfthat he might face the same type of bloody insurrection that Syrias President Assad later faced, or that brought down President Mubarak in Egypt? Was Iraqs military capability a growing threat to neighbors, or a declining shadow of its former might? What were the possible ramifications of Saddams relationships with the Russians and Chinese? How was Saddam attempting to erode sanctions? And, of course, did Saddam have weapons of mass destruction (WMD)? If so, how was he hiding them? And where?

After formulating these big questions, we would then turn to sift through piles of information, hunting for the clues and nuggets that might lead us to answers or at least a slightly clearer understanding of what was happening behind Saddams curtain. In the case of prewar Iraq, this pile of secret intelligence included information on tactical military movements by Iraqi forces, press reports detailing Saddams speeches, debriefings of informants about Iraqs diplomatic maneuverings, messages from friendly security services, reports from Iraqi defectors and opposition groups outside the country, intercepts of official Iraqi communications, and satellite images of Iraqi military and government facilities. Altogether, this volume of data totaled hundreds of thousands of pages, enough to fill up your local library. How can you make sense of this morass of material? Whats important, and what gets dumped?

Data overload isnt, of course, unique to the secret world of intelligence. If youre buying a house, look in the For Sale ads in your local newspaper, or glance at any online realty website. Start leafing through this information, asking the same questions we all might ask ourselves: Which of these houses looks the best? Whats in my price range? Which offers the shortest commute? How are the schools in each neighborhood? Are these prices fair? Then walk through fifty of the houses you choose, visiting so many that you forget, by the time you get to the end of your list, what you looked at when you started.