The piece below is my contribution to a special report on the revolution in intelligence affairs and was originally published by the International Relations and Security Network. Particularly insightful is the editorial by Kris Wheaton and a topic piece by Ken Egli on the potential role of academia in intelligence collection and analysis.
Cultural Revolution in Intelligence: From Government to Business Enterprise
Earlier this year, the Office of the Director of National Intelligence published a document entitled Vision 2015: A Globally Networked and Integrated Intelligence Enterprise. The first part of this bold intelligence community statement begins with an evaluation of the “shifting strategic landscape,” the defining characteristic of which is said to be uncertainty:
“We live in a dynamic world in which pace, scope, and complexity of change are increasing. The continued march of globalization, the growing number of independent actors, and advancing technology have increased global connectivity, interdependence and complexity, creating greater uncertainties, systemic risk and a less predictable future.”
Uncertainty has become one of the trendier concepts over the past few years, and is currently used profusely in the jargon of a variety of disciplines from intelligence to complexity and network sciences to corporate and risk management. The intelligence community is not the trendsetter. Originally stemming from the physical and natural sciences, the emergence of the concept of uncertainty has been accompanied by the development of a homogenized lexicon to talk about “new risks” generated and driven by globalization and network growth to a point where domains previously falling outside the scope of intelligence and security have been securitized. These domains run the gamut from society and culture to demographics and health to economics and finance to innovation and technology to natural resources and the environment. Regardless the domain, we now talk about complex adaptive systems whether we are examining conceptual physical models, bio organisms, tribes and clans, financial markets, terrorist or organized crime networks, or corporate knowledge management.
The list of globalized mashed-up vocabulary is long. It would appear that whichever way we turn, we find researchers, analysts and managers trying to detect emergence patterns, spot uncertain and unstable environments, aggregate and mine various types of data, develop systemic and holistic strategies and approaches, build resilient models, integrate systems within systems, collaborate and share knowledge across domains, form strategic partnerships, build agile infrastructures, transform organizational cultures and mindsets, and win the war for talent.
So how, apart from adapting to a new vocabulary, is the intelligence community going to achieve the transformation it so vehemently advocates? How is a largely static government enterprise to turn into a dynamic business enterprise? What is actually happening in the process of transforming the culture and mindset of the intelligence community so it may accomplish its mission to create decision advantages? What kind of education is needed to kick start the transformation? Is descriptive qualitative analysis obsolete and should the intuition-led approach be substituted with formal structured methodologies?
Vision 2015 proposes that in order for the intelligence community to transform into an enterprise able to provide decision advantage to policymakers, it must transform from a government enterprise into a “globally networked and integrated intelligence enterprise.” In other words, the intelligence community must start thinking and acting like a business. How well does the business metaphor hold in the government/national security context?
Government, critics of the business analogy have argued, is not comparable to business because it cannot be responsive to market forces since it has a higher purpose: public welfare. These critics also see the competitive advantage of intelligence in the community’s ability to “steal secrets”, which further implies a stronger emphasis on collection over analysis. Such an argument epitomizes the mentality and culture that the new vision is trying to counter. It is a snapshot, a still life if you will, of the Cold War mindset as to what characterizes intelligence. This mindset envisages a centralized national customer, promotes the obsession with secrecy, places value on the finished intelligence product rather than the process of intelligence, and treats flexibility as a foreign word.
Applying a business metaphor to intelligence processes in the national security context is not only valid; it is highly desirable. What the market is to business, international relations is to government. Are we to believe that government should not pay attention to the forces driving the developments on the international arena and respond accordingly? With globalization, where once particular domains were immune to changes outside their immediate environment, and cause-effect analysis had a more linear dimension, the interconnectedness and resulting complexity of drivers cutting across disciplines, calls for non-linear approaches both in terms of collection and analysis.
For at least two decades now it has widely been acknowledged that the so-called intelligence cycle (the process of collection, analysis and dissemination) is an idealized Platonic model that is not only obsolete in today’s environment, but also dangerous and misleading. The first step toward transforming the intelligence community from a creeping and decrepit government apparatus to a dynamic enterprise is providing whatever education necessary to curb the old mindset. Business and national security intelligence share the same strategic objectives: avoid surprises, identify threats and opportunities, gain competitive advantage by decreasing reaction time, and improve long- and short-term planning. With this in mind, the intelligence community should most certainly be responsive to market forces. It should allow for the formation and dismantlement of processes on a need basis. If a process is recognized to be “unprofitable”, it should not be allowed let to drag on for decades because government institutions have a “higher calling”!
Vision 2015 recognizes that the most difficult part of implementing the envisaged transformation is cultural change:
“The first and most significant impediment to implementation is internal and cultural: we are challenging an operating model of this vision that worked, and proponents of that model will resist change on the basis that it is unnecessary, risky, or faddish.”
Yet the real challenge of transforming the culture lies neither at the top (the Cold War veterans of the intelligence community who by the sheer force of nature are on their way out) nor at the bottom (the fresh-off-college Generation Y recruits who may have the “right” attitude and ideas but too little real world experience to know how to best apply them). The challenge lies in the lack of mid-level leadership as this is the level at which bottom-up generated ideas are filtered to form strategic direction at the top and get the buy-in from the customer. Inability to recruit and sustain competent middle management will translate into either empty rhetoric and a hodge-podge of recycled vocabulary, or in stagnation, lack of flexibility, and death by a thousand paper cuts.
If the intelligence community is serious about winning “the war for talent” (an expression around which its human capital strategy is fixed), it should aim at developing its mid-level capabilities. “Investing in our people” is a nice enough sounding cliché. This does not mean, however, ensuring competitive compensation and providing competitive benefits because in the war for talent, there will always be someone ready to offer bigger, better, more competitive compensation packages. Adequate compensation should not be a strategic human capital goal. It should be a given. Strategically speaking, investing in people should translate into offering them the opportunity to grow their potential through continuous learning, which in turn, will increase their sense of ownership and loyalty. True, one can change a culture by throwing money at it, but the resulting culture is hardly the type that is likely to stand up to the values set in Vision 2015: commitment, courage, and collaboration.
Winning the war for talent is not a silver bullet for a successful cultural transformation. If we think of information as the currency in the world of intelligence affairs, then surely we must observe fluctuations in this currency as the external environment changes. The relative scarcity of information during the Cold War era resulted in putting a high price tag on information. Not only was there a lot less information available in contrast to today’s web- and telecommunications-networked world, but this information was collected secretly by means of human intelligence (HUMINT). Hence the culture in which the intelligence community operated was one that first, placed far greater emphasis on collection than analysis; and second, created a glamourous, cult-like image of secrecy.
The “information tsunami” as information overload is figuratively referred to, together with proliferation of telecommunication and media technology, has clearly devaluated not only information as a currency, but also its attribute – “secret”, thereby creating a shift from the emphasis on collection to that of analysis. More value is now placed on sorting out relevant information from the ubiquitous noise, which has resulted in the creation of a grey area somewhere between collection and analysis, namely synthesis. Yet synthesis is no new fad. It is an analytic process that every person in academia, from a freshmen to a graduate researcher to an established professor engages in daily. While some more progressive elements of the intelligence community have supported “outsourcing” the synthesis of open source information (the most voluminous type of information) to knowledge workers outside the community, be that academic institutions, think tanks, or in some ultra-progressive cases – crowdsourcing, such initiatives are still in the single digit count.
There is some evidence of cultural change in the intelligence community of acknowledging the value of open source intelligence (OSINT) such as the creation of an Open Source Center at the Office of the Director of National Intelligence (ODNI) and the ODNI sponsored Open Source conferences in 2007 and 2008, which served as an outreach activity to bring together intelligence professionals, academic institutions, think tanks, private sector intelligence providers and the media. Nevertheless, a successful cultural transformation from obsession with classified information to a wider use (not just acknowledgement) of OSINT has not been achieved.
While one of the key design principles upon which Vision 2015 rests is adaptability and the document duly declares: “The keys to adaptability are active engagement and openness to outside ideas and influences.” The implementation plan fails to mention either OSINT exploitation or openness to collaboration and contribution by non-community members, such as think tanks and academia, where a large volume of vetted OSINT resides. Failure to take actionable steps in this regard will not serve the community well in its attempts at cultural transformation. Promoting ideas without an actionable plan is like taking one step forward and two steps back; worse – it creates a “cry-wolf” image.
All that said, it should be acknowledged that the United States is a pioneer in promoting the use of OSINT among intelligence professionals. The OSINT discussion at the EU-level is lagging behind. As for countries with alternative understanding of democracy, transparency and accountability, such a discussion is not only non-existent, but very likely sends ripples of cynical laughter in the midst of planning the next black PR campaign.
Another due acknowledgement in this discussion should be the fact that cultural transformation rarely occurs with a swipe of a blade, but undergoes various phases over a period of time. Following a re-evaluation of the definition of intelligence in the post-Cold War environment, the type of human capital the community wants to attract and retain and a makeover of inward and outward-looking operation models, is a re-evaluation of what constitutes quality intelligence products and the development of quality benchmarks. In this respect, Vision 2015 provides a bullet point under the section of adaptability actions, which reads as follows:
• Build the organic capability to conduct exercises and modeling and simulations throughout our processes (e.g., analytics, collection, mission management, etc.) to innovate and test new concepts and technologies.
For the reader unfamiliar with the intelligence community’s internal debates, the above provision might sound somewhat surprising. What? Doesn’t the community already have such capabilities? Aren’t collection and analysis done according to structured methodologies? Stephen Marrin, a CIA analyst from 1996 to 2000, reveals a different picture. In an article for the American Intelligence Journal (Summer 2007), he clearly outlines what is known in the community as the “intuition vs. structured methods” debate:
“Even though there are over 200 analytic methods that intelligence analysts could choose from, the intelligence analysis process frequently involves intuition rather than structured methods. As someone who worked at the CIA from 1996 to 2000, I possess firsthand knowledge of the kind of analytic approaches used at the time. While I was there, the reigning analytic paradigm was based on generalized intuition; an analyst would read a lot, come up with some analytic judgment, and send that judgment up the line without much focus on either the process involved in coming to that judgment, or making that process transparent to others. No one I knew – except for maybe the economic analysts – used any form of structured analytic process that was transparent to others. No quantitative methods; no special software; no analysis of competing hypotheses; not even link charts.”
For the sake of clarity, it should be said that “intuition” is meant here not in the sense of some extrasensory paranormal activity. It simply refers to arriving at a judgment by means of extensive experience that cannot be clearly demonstrated. Another word commonly used to describe this process is heuristics, or a rule of thumb. The preference of old school intelligence analysts for using intuition rather than structured methodologies stems from the historical Cold War mindset that was described above, and the reasons for its perpetuation are to be found in…human nature.
During the Cold War, the intelligence community operated in an environment characterized by opposing ideologies, the bulk of analysis constituted political analysis: political situation assessments, profiling of political leaders, etc. To attempt to quantify such analysis would rightly be considered pseudo-science. Qualitative analysis, which is often based on intuition (that is opinion vs. fact) is suitable to such an environment and to the problems it is tasked to analyze. However, with the securitization of domains previously not on the agenda of national security professionals such as energy security, environmental issues, proliferation of networked non-state actors, qualitative analysis falls short in its ability to provide the type of rigorous analysis the new vision outlines. Perhaps even more importantly, in the aftermath of 11 September, analysis based on non-structured methodologies evades both the transparency of how the analytic judgment was formed and the ensuing accountability.
Significantly, a number of academic intelligence programs have sprung up during the past decade offering advanced education in the field of Intelligence Studies. It is interesting to note that most of the advanced degrees they offer are Master of Arts degrees rather than Master of Science degrees. This indicates that the debate whether intelligence is an art or a science persists. A cultural change will not follow until people in the community stop thinking along black and white lines. Intelligence is both an art and a science. Resistance to implement structured methodologies stems from habit, from “this is not the way we do things around here” mentality, from the numerical illiteracy inherent in the Humanities and many Social Sciences, and a “if it were so great, why do you have to always prove it to me” attitude. Countering such deeply ingrained habits will take time and there are no quick fixes to this problem other than investing in people’s learning on the job. The intelligence community’s return on investment will be nothing short of realizing its lofty vision.