The Lockwood Analytical Method for Prediction (LAMP)
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Bloomsbury Intelligence Studies Open Source Intelligence in a Networked World By Anthony Olcott Sociocultural Intelligence: A New Discipline in Intelligence Studies By Kerry Patton
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BLOOMSBURY INTELLIGENCE STUDIES
The Lockwood Analytical Method for Prediction (LAMP) A Method for Predictive Intelligence Analysis
JONATHAN S. LOCKWOOD
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Bloomsbury Academic An imprint of Bloomsbury Publishing Plc 1385 Broadway New York NY 10018 USA
50 Bedford Square London WC1B 3DP UK
www.bloomsbury.com Bloomsbury is a registered trademark of Bloomsbury Publishing Plc First published 2013 Š Jonathan S. Lockwood, 2013 All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage or retrieval system, without prior permission in writing from the publishers. No responsibility for loss caused to any individual or organization acting on or refraining from action as a result of the material in this publication can be accepted by Bloomsbury Academic or the author. Library of Congress Cataloging-in-Publication Data Lockwood, Jonathan Samuel, 1955The Lockwood Analytical Method for Prediction (LAMP) : a method for predictive intelligence analysis / Jonathan S. Lockwood. pages cm. -- (Continuum intelligence studies) Includes bibliographical references and index. ISBN 978-1-62356-240-3 (pbk.) -- ISBN 978-1-62356-233-5 (hardcover) 1. Intelligence service--Methodology. 2. International relations--Forecasting. 3. Terrorism--Forecasting. 4. World politics--Forecasting. I. Title. JF1525.I6L63 2013 327.12--dc23 2013012216 ISBN: HB: 978-1-6235-6233-5 PB: 978-1-6235-6240-3 ePub: 978-1-6235-6861-0 ePDF: 978-1-6235-6782-8
Typeset by Fakenham Prepress Solutions, Fakenham, Norfolk NR21 8NN Printed and bound in the United States of America
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Contents
Foreword by Dr Mark M. Lowenthal vi List of figures and tables ix Introduction: The development of the LAMP xi
Part one The LAMP in theory 1 1 The philosophy and steps of the LAMP 3 2 A comparison of the LAMP with other techniques 23 3 The initial use of the LAMP: Case study of the former Soviet nuclear republics and nuclear weapons 39 4 Limitations and potential applications of the LAMP 59
Part two The LAMP in practice 67 5 The future of Afghanistan: Democracy, Islamic Caliphate, or warlord principalities? A predictive study on possible Afghanistan, United States, and Taliban responses 69 6 Candidate moves in the Levant: An analysis of the region’s geostrategic future using the LAMP method 129 7 The adaptability of the FARC and ELN and the prediction of their future actions 209 Select bibliography 321 Index 323
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Foreword Dr Mark M. Lowenthal
Few professions are beset by as many “flavors of the month” as is intelligence analysis. New techniques come and go, many of which are ephemeral, and many more of which are chimerical—all claiming that they can improve intelligence analysis. That word itself, “improve,” is somewhat problematic. If we were being honest about what is commonly meant by the use of this term with regard to analysis, it would mean getting it right more often than we do now. But given that we have no substantive sense of an analyst’s batting average—or of the batting average of the larger analytic community—we would be hard pressed to describe how much improved analysis should be. What it really comes down to is not making analytic errors even as we recognize that errors in analysis are part of the price of being an intelligence analyst. We do not hand out omniscience pills in the cafeteria. As I write this Foreword in the spring of 2013, the latest analytic flavor of the month is big data. Without any substantive proof, big data advocates— most of whom are IT specialists and not analysts—claim that big data, that is, the slicing, dicing and parsing of reams of data, will provide answers we did not even know we were looking for. This is problematic on several counts. First, although this may be true on Wall Street and in business where data do drive many decisions, it is much less true in intelligence analysis where the key questions are not going to be found in the data—big or small. The questions that most bother policy makers are about the plans, intentions, and capabilities of other actors. What will Kim Jong Un do next? Will Iran decide to weaponize its nuclear program? Few would argue against the centrality of these questions; few should be able to argue that the answers lie in data. The second problem with our current data-mania is this is exactly not what policy makers want. When you talk to senior civilian or military policy makers about this they will be both frank and consistent: they want knowledge and expertise, not data. Which brings us to Jonathan Lockwood’s book, The Lockwood Analytic Method for Prediction (LAMP). This book is appealing on many levels. First, Jonathan Lockwood has worked as an intelligence analyst, always a plus when trying to create a new analytic tool or technique and much more
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Foreword
vii
rare than many would suppose. Second, he recognizes some of the perils of the field into which he is entering and, unlike many of his predecessors who make exaggerated claims for what their technique will do, Dr Lockwood approaches his with a charming degree of modesty. He states quite clearly that the LAMP is not the be all and end all and that it is an analytic starting point, not an all inclusive solution. In that same vein, there is something to be said for a book that forthrightly compares its technique with others in the field (offering very good explanations for each of them) and that includes an entire chapter on the limitations of the technique. Three cheers for intellectual honesty! One of the most difficult aspects of intelligence analysis is that we are dealing with other human beings—flawed, deceptive, uncertain, mercurial— and trying to discern what they will do next. As I have written elsewhere, our goal as intelligence analysts is to study and write about these difficult creatures in such a way that we can reduce the uncertainty that our policy makers face as they both react to these other players and as they try to craft initiatives of their own. That is where the LAMP comes in. The LAMP is a 12-step analytical process clearly focused on potential political outcomes. The “P” in the LAMP (prediction) is a bit misleading because the LAMP will not come up with the one answer. But the LAMP is a very logical series of analytic steps that will allow an analyst to come up with rank orders of scenarios of possible outcomes. This is in essence what good intelligence is about, laying out for policy makers which outcomes are more or less likely, so that they can focus their attention on these as they see fit. This is a crucial service as it avoids the “single threading” of analysis that too often is so narrow that it tends to have a deadening effect on ongoing analysis. It also recognizes that the most likely scenario may not be the one that actually happens. The “scenario race” is full of successful dark horses. I will not go through all 12 steps in the LAMP, which Dr Lockwood lays out very neatly in Chapter 1. But there are several steps that are worth noting. Step 4 has the analyst lay out all possible courses of action by the actors in question. This is a key step as it does not assume that the actor is rational, only that he can and will act. The assumption of rationality is one of the biggest flaws in too much intelligence analysis, especially in a world inhabited by such actors as the Kim family in North Korea. Now, they may be rational by their own light, but if we only try to analyze the actions that we find rational then we have committed the analytic sin of “mirror imaging” and are likely to omit scenarios that may prove to be important only because “we would never do that.” We might not but they might. Step 10 requires the analyst to come up with focal events that would have to occur for our alternate future outcomes to happen. This is crucial as it creates a list of indicators that will allow the analyst or policy maker to continue narrowing the field of likely outcomes as events unfold.
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viii Foreword
One of the other appealing aspects of the LAMP is that it is not, as Dr Lockwood notes, a quantitative system. He lists this as a limitation; I see it as a plus. When I teach analysis I often point out that the best analytic tool is a knowledgeable analyst who can think and write and who needs little more than pencil and paper. Admittedly, as one gets into the more complex permutations and combinations of various LAMP scenarios, some sort of IT assistance may be in order, but the bulk of the LAMP can be done in the simplest ways imaginable. This is definitely a plus. A great deal of the book is a series of well written essays by three of Dr Lockwood’s students showing the LAMP in action. Most readers will probably dip in and out of these chapters but they are useful guides to how the LAMP works and of the range, subtlety, and sophistication of analysis that the LAMP can support. A word of praise is also in order for the authors of these chapters, Nicholas Lusas, Mary Boyle, and Drew Lasater. Dr Lockwood appropriately gives them credit in his Introduction and I wish to do the same. So, let us welcome the LAMP into the lists of analytic tools and techniques. As I have written elsewhere, good intelligence analysis is competitive. I know that Dr Lockwood does not shrink from this competition and has offered up a worthy entrant. The proof will be in the doing but I do hope that serious analysts will take the time to experiment with the LAMP, to which this book is a useful guide.
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List of Figures and Tables
Figures 1.1 Relationships between the analytic steps of the LAMP 1.2 The analytic map 5.1 Afghanistan’s ethnic diversity 6.1 72 month average retail price chart 7.1–7.3 Evolution of FARC actions 7.4–7.6 Evolution of ELN actions
8 20 76 131 240 258
Tables 1.1 3.1 3.2 5.1 5.2 5.3 5.4 5.5 5.6 5.7 6.1 6.2 6.3 6.4 6.5 6.6 6.7 7.1 7.2
Scenario 1 – Yeltsin stays in power (status quo) Scenario 1 – Yeltsin stays in power (status quo) Scenario 2 – Russian ultra-nationalists seize power Alternate future permutations Alternate futures, Scenario 1 – democratic government (DG) Alternate futures, Scenario 2 – tribal warlord (TW) Alternate futures, Scenario 3 – Islamic Caliphate (IC) Alternate futures, Scenario 1 – democratic government (DG) Alternate futures, Scenario 2 – tribal warlord (TW) Alternate futures, Scenario 3 – Islamic Caliphate (IC) Alternate future permutations Alternate futures pair-wise comparison – Scenario 1 Alternate futures pair-wise comparison – Scenario 2 Alternate futures pair-wise comparison – Scenario 3 Alternate future probabilities by rank – Scenario 1 Alternate future probabilities by rank – Scenario 2 Alternate future probabilities by rank – Scenario 3 Matrix diagram and analysis (FARC) Matrix diagram and analysis (ELN)
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10 42 50 88 89 91 92 94 95 96 158 159 161 162 163 165 166 238 257
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x List of Figures and Tables
7.3 Possible futures 273 7.4 Scenario 1 – The Colombian government withdraws from fighting 274 7.5 Scenario 2 – The Colombian government imposes a containment strategy 281 7.6 Scenario 3 – The Colombian government employs a “victory” strategy 289
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Introduction The development of the LAMP When I initially proposed in the Fall of 1991 to undertake a study of the perceptions of the Commonwealth of Independent States (CIS) nuclear republics under the aegis of the DCI Exceptional Intelligence Analyst program, the Lockwood Analytical Method for Prediction (LAMP) was nowhere near the form to be presented in this book. The methodology has gradually taken shape over a period of years since I first began my doctoral dissertation research back in 1977 at the University of Miami’s Center for Advanced International Studies. My emphasis then was on studying the perceptions of the now former Soviet Union regarding US strategy, using those perceptions as a basis for determining what were the primary factors influencing their perception of it.1 In my 1983 book, The Soviet View of US Strategic Doctrine: Implications for Decisionmaking, I took the process one step further by predicting what would be the best US strategy for deterring Soviet aggression based on their past perceptions. I had recommended US adoption of a “three-tiered” strategic defense system consisting of civil defense, ground-based antiaircraft and antiballistic missile defense, and space-based defense, predicting that this would be what the Soviets feared most. The subsequent Soviet reaction to the Strategic Defense Initiative (SDI) proved these predictions accurate.2 In our 1993 book, The Russian View of US Strategy: Its Past, Its Future, we were confronted with a new problem. While the past Russian perception of US strategy was easy enough to document and analyze from open sources, the collapse of the former Soviet Union forced us to consider the likely future effects the previous Russian perception would have on their relations with the other independent republics of the CIS, and particularly those which had inherited portions of the former Soviet nuclear arsenal (i.e., Ukraine, Belarus, and Kazakhstan). Our solution was to construct four scenarios (or alternate futures, if you will) which reflected the interaction of two main factors with two basic alternatives: 1) economic recovery versus economic collapse, and 2) reunified republics versus independent republics. We then discussed the consequences of each scenario’s occurrence, as well as their relative likelihood.3 This particular approach is also called
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xii Introduction
Alternative Futures or Hypothesized Scenarios, and is currently used within the intelligence community. The collapse of the former Soviet Union had not, despite the expectations of most observers, made the problems of arms control and disarmament easier to overcome. Nor had it lessened the problem of preventing nuclear proliferation among the former Soviet republics, particularly Ukraine, Belarus, and Kazakhstan. The diverging perceptions of these four “nuclear republics” of the CIS concerning the political utility of nuclear weapons had become a source of political conflict among these republics, and particularly between Russia and Ukraine. My research on the perceptions of the CIS “nuclear republics” concerning the nuclear weapons issue began in February 1992, shortly after The Russian View of US Strategy had been cleared by the Defense Intelligence Agency and submitted to Transaction Publishers for publication. Since I was performing my research under the nominal supervision of what was then the Defense Intelligence College (now the National Intelligence University), the DCI project would also simultaneously fulfill the thesis requirements for the Masters of Science of Strategic Intelligence (MSSI). Its focus necessarily would be the perceptions of the “nuclear republics” of the former Soviet Union (that is, Russia, Ukraine, Belarus, and Kazakhstan) concerning the political utility of nuclear weapons and how it affected relationships not only among themselves, but between each of them individually and the West. The period to be covered dated from immediately after the August 1991 coup attempt to the end of February 1993.4 Because of the rapidly changing nature of the situation within the nuclear republics, however, I decided that it was necessary to create a new “hybrid” methodology for predictive analysis, which is now known as the Lockwood Analytical Method for Prediction (LAMP).5 It was a hybrid because it borrowed some of its elements from other analytical and planning methodologies, but combined them in a unique way to produce a different approach to the problem of predictive analysis. Although the LAMP was utilized only for the first time in the DCI study/MSSI thesis, the Commandant of the Defense Intelligence College, Dr James G. Cunningham (Lieutenant General, US Air Force, Retired), deemed the LAMP to have wider potential applicability for the field of intelligence analysis, and encouraged me to pursue its development. In the intervening years, from 1993 to the present, the LAMP started to take on a life of its own. As an adjunct professor at the National Intelligence University from 1993 to 1998, I taught the LAMP initially as the centerpiece of a graduate elective course on Advanced Analytic Methods. Over 40 graduate students at the university found the LAMP sufficiently attractive as a predictive methodology that they used it as the central method for their Masters theses for the MSSI degree. In 1995, I also joined the faculty of American Military University (AMU), where I taught for the next 16 years
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Introduction
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as a graduate professor in their online Intelligence Studies degree program. One of the first courses I developed for them was a graduate level course in Analytic Methods, which covered several analytic methods, but which emphasized the LAMP as the most potentially useful. In this way I was able to reach thousands of students with the LAMP through the online medium. One of my earliest LAMP enthusiasts was Mr Niklas Oxeltoft, a British graduate of AMU who not only developed my first LAMP website but also created an early prototype of LAMP software. He was succeeded as the LAMP webmaster by Mr Mark Theby, another LAMP advocate and graduate of AMU who refined the LAMP website into its current state (www.lamp-method.org). More important was his contribution to the development of the LAMP software you are now able to use. He obtained the voluntary services of a programmer who created the LAMP software prototype at no cost. My newest LAMP webmaster is Mr Gary Gallichio, a highly skilled and experienced IT specialist who currently works for Reading Is Fundamental (RIF). He has taken charge of uploading and testing the LAMP software and further updating its host LAMP website. It is to these gentlemen that I am deeply in debt for the service they have provided in developing the LAMP and promoting awareness of it as a methodology. I am also indebted to the three students from American Military University, Nicholas Lusas, Mary Boyle, and Drew Lasater, whose LAMP papers appear in Part II of this textbook as practical applications of the LAMP. Their papers survived a long winnowing process in which dozens of LAMP papers were considered for inclusion in this first edition. They should be justifiably proud of their selection. Those who take the time to examine the LAMP website will notice a number of papers in the LAMP library that cover a wide range of topics. The LAMP library is not all-inclusive but is meant to demonstrate that the LAMP can be applied to a wide range of topics, and not just those for intelligence prediction. Three of the best LAMP papers have been selected for this book, and were produced by my former students at AMU. The book itself is organized into two main parts. Part I deals with the theory of the LAMP itself, explaining the steps in the process in detail. Chapter 1 discusses the 12 steps of the LAMP and how it is used. Chapter 2 compares the LAMP with several other analytic techniques, and shows how the LAMP either differs or has elements in common with these methods. Chapter 3 discusses how the LAMP was initially used in the case study of the nuclear republics of the former Soviet Union. It has been updated to show how the nature of LAMP analysis changes over time. Chapter 4 concludes the theory portion of the book, and discusses the limitations and potential applications. Part II focuses on the use of the LAMP in practice. Chapters 5 through 7 discuss the application of the LAMP to three different intelligence problems. The last chapter is especially noteworthy, as Drew Lasater demonstrates how
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