Putting aside the fact that, back in my day, “the Olds” referred to a car owned by someone on the brighter side of the tracks – I recognize that this term now refers to the generations beyond the one currently in fashion.  I realize that while I do not consider myself old; I do remember Watergate, the Vietnam War, the moon landing, and the deaths of all three Kennedy brothers.  And so I write to praise them, me, this holiday for a simple reason:  The Olds enjoy life more than you do.

Our holiday toasts often feature a few seconds of silence.  We aren’t grasping for words, we are connecting to memories that predate you.  We mist up easily for the same reason.  We smile at soiled toddlers because we remember the stress when we were first confronted with tiny people – you.  (Also, we are no longer responsible to remove said soil. Our joy in reminding you of this is unceasing.)

I found myself at a large sing-along last week in a small town North of Boston.  A dear friend has hosted these gatherings for over 15 years, such that now their 18th century home bursts each holiday season with guitars, pianos, a harp and violin, and nearly one hundred voices.  I was privileged this year to be holding one of those guitars, and was therefore provided a front-row seat to enjoy these many souls.  Their ages ranged from six to eighty.  The young teens sprawled like puppies for a third of the room, while the adults stood towards the back, nearer to the wine selection located back in the kitchen area.  The smiles were shared: for one evening there was no toddler whine, no teen angst, no mid-life crises, no fears of mortality, no tears of sadness.  There was only laughter, music, warmth, and love.

While all had a good time, the Olds had a better time.  Only looking back through years can one appreciate the joy of connection.  In looking across the room, I saw myself at each age – from the shy child, to the teens who only gain confidence in groups, to the later awkward attempts at self-expression, to the college students, to the young fathers, to the truly confident Lions at the peak of their game, to the Olds.  We all wonder what is next, but for the Olds that question has been answered many times.  For this one magical evening, there were no questions of what is next – there was a sharing of magic, song, and later, dance.  The season features moments like this.  When all ages are joined in the same laughter, when a stranger wandering into the home would feel right at home.  Only the Olds appreciate how rare and wonderful such evenings are.

Here’s to the holiday. Here’s to the child on Christmas morning, the young teens exiled to the kid’s table, the older teens laughing too loudly at play, the Lions reveling in their ability to sustain a home.  But more than all, here is to the Olds.  Who have lived each phase, and only now fully understand we are all One.

In the never ending search to know “what works,” we have a few choices.  We can look to theories, i.e., this ‘should’ work; or we can look to data.  Often the latter choice is considered backward looking, or stripped of context.  Data autopsies are conducted with the results analyzed and presented as a ‘case study.’  Here is what happened with BP, or Enron, or the 111th Congress.

The former choice, relying on theoretical principles, is considered by some more noble and can be expressed simply:  spread democracy, protect the borders, cut taxes, etc.  Theories that are believed to represent fundamental levers of reality – when pushed in a certain direction, desired outcomes result.  These theories are often referred to as ‘common sense.’  Of course, yesterday’s common sense included such principles as racial inequality, ignorance to environmental stewardship, ever-rising housing prices, sexual preference as a preference, etc.  It takes frightening shocks to the system to shake our faith in such levers.

Yet, ever hopeful, we press on to learn what levers control our universe.  What works, and why?  And how can we scale it?  The answer, I believe, comes from data.  But not just any data.  And not through data autopsy and case studies.

Take education.  We can approach improving education as a principled journey, applying common sense: reduce class size, return to single-gender classrooms, dress them up in uniforms, etc.  Or we can turn to data.  Yes, we can do both, but levers must be informed and confirmed by data.  As a friend tells me: The data must precede the framework.

In education, however, we have a paucity of data.  In a conversation with a senior official at the Department of Education last year, I discussed our shared idea of data platforms until he stopped me mid-sentence:  “You’re assuming we have the right data.”  No, I didn’t, but he was right.  I was designing the platform before taking on the fight to tease out relevant data about student performance.

Even that phrase, student performance, is loaded with assumptions.  Performance as measured by what? Standardized tests?  Only last year did the majority of U.S. states agree to a common set of performance standards – and only then applicable to middle-school math and English.  As to how students are assessed against these standards?  That remains in debate, currently there are two clusters of states reviewing approaches to common assessment regimes.  We are years from a U.S. approach to these fundamental levers for K-12 education:  What is the standard against which student performance is measured, and how is that performance measured?  (I should acknowledge a competing theoretical construct that opposes any national approach to education – again, I seek the data here.)

It gets worse.  Institutions of higher education find an increasing number of applicants, year over year, lacking in the skills needed to succeed in their first-year studies.  The resulting ‘remediation’ classes are nothing more an extension of high school.  However, talk with those in the field of education, and they will tell you that K-12 schools have no common tasking from higher education regarding what is considered an acceptable skill set.  While we work to get to a U.S. approach to these fundamental levers for K-12 education, this effort is not coordinated with the expectations of universities and colleges – who themselves do not agree on the answer to that basic question.

It gets worse.  A recent study by IBM surveying CEOs found that the most pressing challenge is the complexity of their enterprise and industry, and the most necessary skill is and will be creativity.  The ability to think critically, understand variables, and make decisions amidst uncertainty.  Meanwhile, the fundamental levers we believe are necessary for K-12 education are descendants of the Trivium – the triad of grammar, logic and rhetoric developed first to shape medieval liberal arts students.   A consortium of technology companies are working to develop the definition of ‘21st century skills’ they believe are necessary for their incoming labor force – but in the radically localized Education field, there is no King to accept their input.  One large government contractor laments:  we would like to remain an American company, but we need 70,000 engineers over the next ten years.  How can we accomplish both goals, when only one represents shareholder needs?  A senior education administrator meekly suggests the adoption of international standards, PISA, as a baseline for common standards only to be scolded by a peer; “But this is America!”

How do we untangle education?  By fighting over which fundamental levers matter, or turning to relevant data?

There is hope.

A student returns home from a day struggling to master Algebra as her teacher struggles to increase comprehension, while not ‘teaching to the test.’ The results of this test will drive the reputation of, and government investment in, the school district.  The reputation of the school district will drive housing prices, and shape neighborhoods. All are exhausted by the end of the school day, but the data collected at the point of learning remains tiny ovals filled in by a child’s number two pencil.

Returning home, the student unwinds by loading up a multi-player online immersive video game.  The players navigate a complex environment, their interactions driving the direction of the game, as the game algorithms respond to player progression through the landscape.  Each move is measured, assessed, and the game evolves along one of a thousand paths – this path of learning is determined by the player’s interactions, both with their computer environment and with one another.  The players are connected via voice connections, as they work as a team to navigate the game’s landscape – often matched up against a set of adversaries, a mirror-image team tackling the same challenges and competing with them.

The next morning, the student loads her textbook-laden rucksack and trudges off to sit in a classroom designed during the Victorian-era, hoping to color in the ovals correctly before Christmas.

Which experience better prepared her for the ability to think critically, understand variables, and make decisions amidst uncertainty?  What data matters in this story?

Let’s start here.

I’ve been reflecting lately on my brief sojourn into education reform prior to returning to “the world.”  Several things I learned there, including the idea that how brains work and how people interact represent new fields of study to the Field of Education. (With apologies to any of my new Ed friends, please correct me if I heard wrong!)

Yeah, I was appalled too.  Turns out it’s called there “The Learning Sciences,” and while I don’t know when it started to gain traction, people in education somewhat recently started to compare the education system we have with the stuff we’re learning from cognitive science, sociology, etc.  Pretty exciting stuff, and I can’t help but compare this welcome attention to interdisciplinary studies to the breakthrough in economics when – RECENTLY – leading economists began to realize that people are messy and don’t have consistent utility functions.  (In both cases, the system failures become a tad obvious using this lens.)

So the world is changing.  All around us.  One meme in education making the rounds is, attributed to The Learning Sciences:  “All learning is social!”  As someone mentioned this weekend on Twitter: The learning that isn’t social, isn’t worth our time studying. This remains controversial – what about human instinct, core behaviors, the idea that some of our personality traits may be inherited?  Surely these aren’t learned! But then we read that an infant, long before she can understand a language, is able to discern WHICH language is spoken by her tiny tribe.  And before she understands that she belongs to the same animal group as her parents and siblings, she can discern individual faces among primates.  Once she learns that she is one of the naked apes, the individuality among chimpanzee faces becomes invisible to her, as it is to us.

Ponder that one for a minute.  Heady stuff.

This weekend, I was struck by a logic stick.  If all learning is social, is all social learning?  We know this is not automatically so, learned that in the intro to Logic, Sets and Numbers (an actual college course I took in the 70’s).  But when we engage in a social setting, online or offline, are we ever not learning?  Let’s add in a third statement: we are constantly learning.  Even while asleep, some research indicates, the brain assembles and makes sense of what it experienced that day.  There isn’t a time when our brains aren’t rewiring themselves based on input from our environment.

We learn something from every experience.  If events occur as predicted, we reinforce that cognitive pattern for the next use (naturally, we have the ability to learn the wrong things here).  If they do not, we reconsider our pattern assessment logic.  We descend the stairs at 3 am differently once we learn the fourth step from the landing squeaks now – and will subsequently do that in another’s home without thinking.

So we’re constantly learning, and all learning is social.  (Is it?  We learned that squeaky stair avoidance thing on our own, didn’t we?  Hint:  No.)

Enter social media!  What is your social media strategy?  Does that question even make sense anymore?  Or should we ask now:  What is your learning strategy, and what role is played therein by social media, happy hours, phone calls, email, downtime, etc.?  If all social is learning, shouldn’t any associated strategy for socializing tools be focused there?

—-

24 Nov: Update, thanks to the great comments I’m getting here.  Here is a another great resource exploring this notion that all learning is social, and questioning the value of corporate training methods as a result: http://www.lifescapes.org/Papers/0212_from_training_to_learning.htm

• Facebook privacy challenges continue as applications you trusted expose data you thought was private. Facebook is alarmed and promises to fix this. Your new normal: stop playing Mafia Wars.
• The “evening news” is no longer the authoritative source for What To Know, as it was when I was a child (as nicely articulated by Clay Shirky). Media outlets frame information within a comforting tribal narrative – as research confirms that we trust scientists (and, theoretically, newsreaders) who confirm our belief system. Your new normal: commit to reading / viewing several different biased media outlets, in hopes of getting “the whole story.”
• You think telecommuting would be the dream job – then realize your home is designed for distracted comfort rather than productive work. Your new normal: rethink your sanctuary.

This isn’t new, the association of increased responsibility with increased autonomy is a constant requirement for civilization. The U.S. military adopted ancient models when it structured decision making as a distributed function, within established rules and roles. As an enlisted recruit in basic training, I was told when and how to disobey an order that could be unlawful.  It was my responsibility to disobey such an order, which meant it was my responsibility to understand the difference between lawful and not. This ‘professionalization’ of the enlisted was extraordinary (but not unique), and represented an advantage of decision agility over adversaries who employed a more autocratic decision model.

Being a technically literate and responsible citizen / internet user / driver is more important than ever, as consumer electronics and information acceleration places more responsibility on our shoulders. At a dinner recently, a friend recounted her experiences at a recent college reunion. Leafing through a friend’s photo album, she was aghast at what was considered appropriate party behavior (and costume) in the 1980s. Thankfully, this was before Facebook – so her secret is safe (until someone decides to buy a scanner). If those photos were available online, some of us would have different careers today.

Kids today aren’t more wild than we were, they just have more ways to have their past attached to their adult identity – and more ways to indulge a short attention span. Do we even know what is expected of our children, in order to manage safely their transition to adult? To be a responsible teen, children need to navigate significant ravines of risk while interacting with their friends. These ravines were puddles in the 90s, and cracks

in the sidewalk in the 60s. Gone is the long phone cord, stretched into a closet for privacy. Interactions ping them in the backpack or pocket – and can come from anywhere on Earth. And present an almost irresistible pull to teens and adults alike, even while attempting to drive a 3,000 lb automobile.

In the 70s, I balanced an AM radio on the dashboard to keep me company while driving a sales route in Manhattan. This, because the glovebox was unavailable, because that is where I stuffed an after-market 8-track player (also, the antenna needed to be closer to the windshield). Hard left turns sent the radio flying across the dash – a distraction because I wasn’t responsible enough to get the factory radio fixed. Compare this to the distractions available to drivers today. My Rube Goldberg sound system is nothing compared to the world of smart phone interactions that beckon us at every turn.

We are called upon to evolve. Faster. Develop greater discipline regarding what earns our attention, and how we make decisions. The new normal: Don’t trust anything you hear, even on cable or sent to your inbox or posted on your Facebook wall. Don’t indulge in every tempting distraction, however urgent that wall post or text seems to be. Also: don’t presume the answer is to avoid consumer electronics altogether. Government services will expect citizens to be connected and literate. Consider the broadband initiatives from the FCC – the interstate highway system of the 21st century is considered necessary to connect us to the new normals. Some advocates are seeking to prioritize these connections to favor first hospitals, libraries…and schoolhouses.

It’s idle fun for me to gaze at my grandchildren and wonder what their work and social life will be like in twenty years. I tend to forget that I expect to be around to witness it, and therefore will have some adapting of my own to accomplish.

What’s your new normal? How fast can you evolve? How do you avoid the inadvertent base jump?

Increasing “Jointness” and Reducing Duplication in DoD Intelligence

by Chris Rasmussen

with contributions from LCDR John D. Ismay, John Bordeaux, Bob Gourley, Michael Tanji

This paper was submitted to DoD’s INVEST (Innovation for New Value, Efficiency, and Savings Tomorrow) contest on September 23, 2010.

The explosive intelligence spending over the last decade initiated by the 9/11 attacks has been both a blessing and curse. The initial spending was a warranted blessing but as time passed it turned into a curse that created far too much duplication of effort, fragmentation, and sprawl throughout the United States Intelligence Community (IC). The initial infusion of cash dovetailed with a renewed focus on information sharing and “collaboration,” which was emphasized in the Intelligence Reform and Terrorism Prevention Act (IRTPA) of 2004. While modest gains have been made in breaking down “stovepipes,” the initial energy of these “collaborative” efforts has waned and increased spending has largely cemented bad habits: siloed analytic reporting that fuels massive duplication of effort. If these negative trends continue and a new “joint” business model is not adopted wholesale, the promise that sparked IRTPA is in danger of being unrealized. A move way from the newspaper-like “finished intelligence” model to a “purple intelligence” model more aligned with Internet-enabled global trends in content-centric enterprises will increase analytic “jointness” and reduce duplication–saving billions of dollars and resulting in improved intelligence insight.

Each intelligence agency still behaves much like an independent newspaper writing whatever it wants with limited coordination with other agencies. As newspapers around the world are going bankrupt due to the changes in content creation and delivery of services over the Internet, the Intelligence Community is moving in the opposite direction: more editorial control in the form of “finished intelligence” (vertically vetted projects within an agency) posted to “portals.” This trend ignores the democratizing and crowdsourcing trends of the Internet which are changing the world of personal electronics, software development, consumer spending, content delivery and creation.

The majority of the US Intelligence Community is comprised of Department of Defense (DoD) elements. The “INVEST” ideas expressed in this analysis can be applied to the broader IC, which is beyond DoD control, but the cost saving suggestions of this paper should be applied to DoD elements first to set an example. The term “IC” (Intelligence Community) throughout this paper largely refers to the intelligence agencies of DoD such as DIA, NGA, NSA, the service intelligence elements, and combatant command elements.

Observers of transformation underway in commercial organizations often note that organizations with smaller budgets deliver far greater capability. Many of these small budget commercial capabilities are not only disrupting and shifting markets, but often are delivering capabilities that are more powerful than the legacy systems they displace. Some of the greatest use cases in this area are those observed in the displacement of old-fashioned newspapers for outlets of information. “New” content sources are often of higher quality, greater relevance, and available at much lower costs (almost free!) Since the IC is in dire need of higher quality and more relevance – and all in the federal sector are in need of economical alternatives – lessons from this sector are important to consider.

The literature regarding innovation is clear – technology and process innovation can be put to use as an incremental improvement to existing operations, or can used to disrupt existing operations in pursuit of transformation. One famous case study compares the incorporation of individual online trading technology into the business models of Charles Schwab and Merrill Lynch. Lynch assigned the same brokers, with the same incentive programs, to add online trading to their portfolio. There were no individual incentives to tend to the new channel – and no disruption to the business model was expected or desired. One innovation author notes the contrast with the approach taken by Charles Schwab, which immediately “created a separate business unit to conduct online trading and made a masterful transition to the computer-centric investment management world – ultimately phasing out its original broker-based business unit…the new unit operated at much higher trading volumes and significantly lower costs than those characterizing the traditional business.” The IC cannot continue to marginalize potentially disruptive innovations and hope to thrive in a rapidly changing threat environment.

Intelink and Intellipedia

Intelink, launched in 1994, was an internal governmental response to extend the budding HTML and web browser revolution forming on the Internet to the IC. Websites began to proliferate from PACOM to the CIA to the NSA. In addition to agencies posting “their” content, some agencies started to expose traditional cable traffic – previously bound to dissemination lists – to Intelink for broader discoverability. This could be considered the IC’s “Web 1.0” phase.

In 2005, Intelink started to host a series of “Web 2.0” tools such as wikis, blogs, social bookmarking services, and document storage all of which were indexed by Google Search Appliance. This move was a surprise to many: the stodgy and security conscious IC was moving ahead of many private sector companies with its use of Web 2.0 tools behind the firewall (dubbed “Enterprise 2.0”) to increase knowledge transfer and information sharing. The flagship application in Intelink’s tool kit was Intellipedia—a wiki built upon the same software that drives Wikipedia hosted on all three security networks: JWICS, SIPRNET, and NIPRNET.

Intellipedia is a media darling. The underlying message in the press was “if the IC can use a wiki, so can our company.” Intellipedia and other Intelink 2.0 tools have impressive registration and activity rates and inspired many throughout industry, government, and academia to pursue the “wiki way.” After almost five years of “collaboration” as an industry leader, it is long past time to consider the result. Intellipedia boasts many collaborative successes by facilitating insights among analysts, but this is marginal change. The underlying assumptions regarding the prevailing finished intelligence workflow have not been questioned. In fact, much of Intellipedia’s “success” is rooted in transforming non-analytic work.

Intellipedia has proven effective at reducing the amount of email and streamlining basic administrative work common across the corporate world. Posting office and administrative content (such as concept of operation documents, requirements lists, software design de-bugging matrices, and meeting minutes) to Intellipedia is helpful, but it fails to reach the core function of the IC. The IC’s core business function is analytic output, to date unchanged by this information sharing “revolution.”

Let’s assume that every “enabler” office within an agency (such as human resources, IT, investment, legal, acquisition, logistics, training, etc.) achieves transparent office status, thereby reaping the benefits of crowdsourcing and data discovery, while the analytic core of the agency does not? The result is limited transformation: the primary function of an intelligence unit is analytic output and all “enabler” functions exist to support analysis. The “revolution” is incomplete.

From the perspective of structural analytic transformation, “2.0” tools have done little to reform the approach to analytic “production.” The analytic core is trying to use the “new web” to tell stories in a different way but is falling short for two primary reasons: 1) The “2.0” tools still remain as a complement—not an alternative—to the existing production processes used to create the 50,000 products a year published across the IC and rising. 2) A vast amount of stock content is pushed out in traditional dissemination channels with much overlap. Some have argued Intellipedia is a “knowledge base.” If it is a knowledge base then finding links to base knowledge in “official” or “tailored” content should be easy. It is not. In fact, there are very few links to Intellipedia in official agency output – because it’s not “officially” trusted.

A-Space

Launched in 2007, A-Space is a virtual work environment where analysts connect with other analysts, ask questions, and see what their colleagues are doing. The result is similar to Facebook’s news feed. A-Space is a good place to “think out loud” and ask questions in threaded forums but as Intellipedia before it A-Space is struggling because it doesn’t address reforming or replacing the finished intelligence process.

Patrick Neary, former Deputy ADDNI for Strategy, Plans & Policy, noted:
“Analytic Transformation (AT) has as its tag line ‘unleashing the potential of a community of analysts.’ While each of [its] initiatives will—if and when they are successfully deployed—improve the daily routine of community analysts, it is entirely unclear when a transformation in analysis will occur. While the AT initiatives are necessary preconditions to analytic reform, they do not address the decentralized management of analysis or the product-centric analytic process. Real reform in analysis will require agencies to give up proprietary products and share customer relationships, establish new rules facilitating on-line collaboration, and focus more on intelligence as a service than a product.”

The decentralized management of analysis manifests itself in many ways, but the most glaring is that agencies can write “products” on any topic with limited to no coordination with other agencies. They then disseminate those products to their “customers” often without the benefits of “upstream,” joint collaboration. This practice creates incredible amounts of overlap and duplication. The gusher of intelligence spending increased duplication because it simply augmented the siloed habits of analytic production.

The Washington Post series “Top Secret America” revealed: “Many security and intelligence agencies do the same work, creating redundancy and waste. For example, 51 federal organizations and military commands, operating in 15 U.S. cities, track the flow of money to and from terrorist networks.” Many in the IC argue that the “Top Secret America” series was sensationalist and some parts of the story were inaccurate, which is true. However, the observation above is accurate and is a microcosm of the larger problem of excessive duplication fueled by increased spending.

As with most public sector organizations, the application of private sector insights must be tempered by the understanding that private sector goals of efficiency will not always apply. The IC is not designed for efficiency. It’s designed instead to be effective with purposeful overlap built into the system to catch things that may slip by a single entity. A popular saying within the IC is: “one man’s duplication is another man’s competitive analysis.” This axiom is partly true but is too often used to legitimize excessive overlap. For example, five to ten units working the same topic is probably effective but no one can honestly argue that 51 organizations working on the same issue is effective. This inability to scope “sufficient” redundancy leads to uncontrolled costs and a lack of accountability. While efficiency may be sacrificed for effectiveness, this should not translate into rampant task duplication with no cost ceiling or metrics for governance.

Another expression of excessive duplication can be seen in how A-Space is currently being used. A-Space is built around “workspaces” which must be named. Analysts from across community can focus talent and energy on a topic and gain new efficiencies through a combination of “crowdsourced” workflow and the “in-house” work of their team. Unfortunately, this is not really happening. Analysts are projecting the organizational construct of offices, sub-offices and “fusion centers” working similar issues into the potentially “flat” A-Space. For example, there are over 100 workspaces dedicated to Iran. A workspace simply named “Iran” is too generic and more specific workspaces such as “Iran’s Conventional Military” are needed to manage the workflow. But, as previously noted, 25 workspaces devoted to Iranian topics would probably be effective but no one can honestly argue that over 100 is generating synergy.

Goldwater-Nichols Analogy

Many have commented that the IC needs to model the Goldwater-Nichols Act of 1986 to create more “jointness.” Prior to Goldwater-Nichols each military service “trained, acquired, and equipped” and also conducted operations virtually independently. Goldwater-Nichols took war planning and operational powers away from the military services and centralized it to a “commander” of a geographic or functional command. Goldwater-Nichols did several other things: it made the Chairman of Joint Chiefs of Staff the primary military advisor to the President replacing the confusion that resulted when each service chief gave disparate advice. Also, it mandated that flag officers serve in a joint duty assignment in order to receive further promotion. These stipulations of Goldwater-Nichols are outside the scope of this paper but I’d like to focus on the services losing operational power and apply it to the IC.

Goldwater-Nichols created jointness in the military because the services traded off some power to bolster a more effective central entity. The Intelligence Reform and Terrorism Prevention Act of 2004 created the DNI and set in motion many reforms but it did not stipulate that intelligence agencies would have to trade off any power to bolster a command or center like Goldwater-Nichols. The agencies “train, acquire, and equip” but also conduct operations independently much as the military services did prior to Goldwater-Nichols. For the most part, the IC does not conduct kinetic operations like the military, rather the IC’s “operations” are its analytic and collection functions.
Some argue something similar to Goldwater-Nichols cannot work in the IC because it’s spread across five cabinet departments unlike the military services which are all under DoD. There is some merit to this argument from a command and budgeting perspective, but this does not detract from the overall message: achieving analytic jointness and reducing duplication with a series of DoD Directives – specifically aimed at removing some of the independent analytic power of agencies, service components, and combatant commands.

Balancing the corporate voice with crowdsourcing

No single agency recognizes any of the content in Intellipedia or A-Space to be “official.” In fact, most of the interaction and content in these social tools is described as “good for collaboration but not the product.” The IC’s product-centric view of intelligence is at the heart of the analytic transformation problem and most “solutions” simply treat various symptoms. If each agency uses “2.0” tools to “coordinate,” but the content creation power lies independently within the finished intelligence process, the analytic transformation movement has gone as far as it’s going to go.

The main objections to Intellipedia and A-Space as “official” sources are that both spaces are too uncontrolled and there is difficulty determining which content “speaks for the agency” within individualized social media platforms. The “agency voice” in finished production is trusted to address issues of accountability, vetting, and records management. Some of these virtues are over-stated in the current system where slapping an agency or command logo on a report imbues the product as being more trustworthy and accountable than any social software-based content. Nonetheless, the IC’s obsession with agency logos is here to stay so a compromise was struck.

A move toward joint production

Like Intellipedia, Intellipublia’s Joint Product Line (JPL) is a wiki, but it also includes a built-in approval process and balances crowdsourced content with the agency voice. Readers can see who contributed to an article, which managers approved it, and when those activities took place.

The JPL combines official agency review with emergent content for joint or “purple” output. Users can consume and compare “authorized” versions to the emergent “living” version. Agency logos quickly denote that official vetters have reviewed the content but anyone can contribute and the article cannot be locked down. In addition to agency logos, the “authority” and roles of vetters are denoted by color-coded stamps such as “team leader” and “final authority.” Once the official vetters sign off on the content, their agency logo will become un-ghosted at the top. Ghosted logos show that someone from that agency has made edits but doesn’t have a higher vetting function. This is modified MediaWiki software and shown in the edit history mode. This software is a starting point and needs to evolve, but it’s a strong starting point because the underlying business process (not the technology per se) creates jointness and exposes duplication.

Joint Production Line Exemplar

source: http://www.flickr.com/photos/97111850@N00/4390235472

MIT business professor Andrew McAfee stated that “if you want to control the outcome, you need to control the process.” Currently, each agency, command, and fusion center controls every process associated with production and can conduct each process in a vacuum. There is no requirement to coordinate across these organizations. A DoD Directive moving some production power into the JPL network would be similar in effect and benefit to the removal of the operational and war planning powers of the military service in Goldwater-Nichols. The transparent JPL network would now “control” the analytic process. Agencies would no longer have to write using their internal, opaque systems but would would still “control” their agency’s voice – but now without locking down or “owning” every part of the process.

Transferring some analytic production away from finished intelligence posted to agency portals and cable traffic would expose the amount of duplication in the system through transparency and customer feedback loops. There will always be a need for “tailored” intelligence but tailored snapshots should be the exception not the rule and “products” should be the by-product of the collaborative process not the end state. There will always be a need for some duplication but, as previously stated, the amount of duplication is over-kill on most topics. At the limit, the IC needs an approach to understand and be held accountable for the amount and areas of duplication. Moreover, we need to re-examine what “tailoring” means in a smart phone apps and wiki world.

Reforming acquisition and shutting down intel shops

DoD’s fragmented IT acquisition process leads often to excessive duplication and waste. Every agency and command can acquire any technology in a vacuum. More times than not that specific technology often already exists somewhere else. “Not invented here” syndrome and the belief that “our data and requirements are unique” are simply over-stated default assumptions fueling waste across budgets. A-Space, C-Space (for collectors), J-Space (for non-analytic staff workers), Intellipedia, Sharepoint, Army Knowledge Online, Air Force Knowledge Online, Apps for the Army, etc. all provide some niche but most of these systems do similar things. Once again, we are not advocating for total acquisition centralization nor are we suggesting that one purple production system fits all needs. However, if production were centrally “managed” via a transparent system like the JPL we could start to see the excessive duplication of analytic effort and associated IT acquisition. If nothing else, this approach will provide the leadership with visibility into the amount of duplication by topic area.

Once duplication is exposed we can start to roll it up by shutting down unnecessary fusion centers, red cells, and analytic units. The people affected by these cuts can be re-trained or transferred but cutting billets and contracts is absolutely necessary. The HR, facility overhead, engineering, maintenance, electricity, and security costs associated with excessive analytic duplication are unwarranted and wasteful. Moving some of the production power away from the agencies to a transparent and purple network will improve the quality of analytic insight, increase jointness, reduce duplication, and will save billions of dollars. Efficiency that leads to greater effectiveness – a business principle within reach.

(Part 1 is archived at http://jbordeaux.com/raising-the-dial-tone/)

Recently, Dennis McDonald offered that transparency and collaboration should be considered as efficiency measures in the Secretary of Defense’s initiatives.  A sharp comment to this post responded by detailing the dire state of the federal procurement system, offering that the system is “completely broken, not superficially but structurally and intrinsically broken.”  The response indicated that collaboration was at best an insufficient tool to address the pathology of the system:

“The problem isn’t a communication breakdown between the people issuing requirements and those implementing them. In most cases that communication is satisfactory. The problem is that most requirements issued on federal contracts are complete birdcage liner written by people who are either totally unqualified to design a product or produced by a process/workflow that is biased toward the most verbose form of mediocrity (i.e. reams of underwhelming requirements).”

In my field of KM, there are many well-intentioned professionals who seek to increase sharing and collaboration among and across their targeted workforces.  This is a good thing.  Following what we know of network science regarding loose connectors, the amplifying effect of linked networks is primarily achieved through loose connectors, also referred to as ‘weak ties.’  This is how disparate networks form ‘small worlds.’

What are these?  Consider the social or professional groups with which you primarily associate.  You may be central to the interactions within this group, helping keep the group together and moving forward.  Network scientists call this increasing network cohesion.

The problem?  You likely spend less energy meeting people with whom you have little in common.  At the edges of your group, there are these people. The folks who don’t show up at every happy hour.  The ones who are known, but not seen as core to the group’s identity.  The accountant who is also involved in community theater.  The developer who takes long weekends in the Spring to cycle across hundreds of miles with a like-minded group.  The conversations here, for the most part, do not involve their work.

But some do.  Sometimes the accountant meets a CFO while preparing for a community production – and banter leads to a greater understanding of each other’s professional perspective.  Sometimes the developer meets an entrepreneur over dinner in a small-town diner as they restoke the cycling fires.  The conversation exposes each to the challenges of the other.  Weak ties are established across two previously disconnected social networks.

Monday morning, the accountant and the developer are back at work.  During a project meeting, they sound different.  As if they’ve been reading a different manual, suddenly expressing views that are not usually heard in the tight group.  The CFO and entrepreneur likewise return to their labors with a new perspective, a new voice tucked away in their heads.  With new contacts in their smart phones.

Who knows what may come of these chance interactions?  We cannot know, but the theory and experience both tell us that diversity in a social system leads to a healthier, more sustainable system.  From a systems science perspective, open systems are more efficient – this openness is not simply a benefit resulting from increased collaboration, but a core characteristic of a healthy system.

Connecting disparate social networks is as important – I would argue more important in many cases – than connecting within the core group.  This is the reason we speak of openness of interaction, transparency of data, and collaboration across agencies and organizations.  We do not – or rather, we should not – pretend that connecting people and opening the conversation will solve thorny systemic issues (health care, national security, acquisition reform); but we should set expectations that a wider dial tone will lead to serendipitous innovation.  Establishing weak ties across disparate networks is the first step towards finding innovative solutions to these long-standing problems.

In our new march towards efficiency, let’s continue to raise the dial tone and open systems.  This is not an end state or resolution, but a necessary path towards shared goals.

(My title comes from a former colleague who buried this bon mot in a client deliverable – if she wishes me to name her, I shall. Else, know this headline gem is just something I wish I’d written.)

I interjected myself into a listserv conversation last week, stating “documents present a barrier to knowledge – We need to move beyond the document metaphor if we’re trying to cultivate knowledge.”

I was asked to explain myself, as this is considered by some a contrarian view. I first waited a few days while those more eloquent took up the cause – but here is what I responded this morning. I believe a reasonable response is to roll one’s eyes at such talk – I don’t offer a useful alternative to documents (yet), so why attend? Simple: I am trying to shake us free from the belief that improving documents will improve somehow knowledge flows and understanding. If you’ve already begun focusing on enabling conversations rather than uploading more documents to your portal – you have the message.

One friend offered that documents are not barriers but constraints. Here is where I part company: the document may be intended as a constraining frame, but when so much of the ’system’ is omitted, this framing becomes cropping (as in image cropping). Constraint becomes distortion. The brain itself tells us why documents are cropped images of knowledge, not sufficient frames.

The brain knows spatial and temporal patterns, and predicts patterns in its environment. Language shapes expected patterns, and predisposes the brain to predict in certain ways. The marvelous thing here is that our media distinctions such as images, sound, written language, spoken language, emotion, physical response – are blended in memory. In addition: these memories are not stored as blended, but are blended at the point of recall. What is stored are fragments – all knowledge is fragmented until the point of use. An author uses her knowledge to create a document, which – if well crafted and discovered and interpreted well – will form one input for the learner.

For documents from this morning’s email to early religious texts – the context lost between author and reader is significant and meaningful. Even the term ‘context’ seems to me to be a false reference to content metadata. For the brain, context is content. This is why we know more than we can say, and we say more than we can write down. (Polanyi, Snowden.)

{ The photo below is of neolithic ‘art’ from Newgrange in southern Ireland. The meaning for these carvings is utterly absent now, as eons washed away all metadata, culture and context. }

But more than this, our brains make use of our bodies in ways we are only beginning to understand. The Bride and I sat sipping wine on the deck last night, during a difficult conversation. At one point, her reassuring squeeze on my forearm conveyed a silent message that got me thinking about haptic memory, pattern expectations, and the “non-verbal” communication that characterizes some of this transfer. (I compared this favorably to the times she kicks me under a dinner table, the forearm message was much clearer – or perhaps I was “listening” this time.)

Research into everything from micro-expressions to mirror neurons shows us that face-to-face conversation is the richest knowledge transfer experience. Given the flow of information, both conscious and not, during a conversation – the notion that a document can capture the richness of this flow is laughable. For simple problems, documents can be sufficient: (my most recent data point being the bookcase I successfully assembled from instructions penned in China, all the more remarkable if you know how useless I am at such tasks).

The reason I say documents are a barrier, then, comes from their omission of so much context/content – but also from our mistaken confidence in their ability to transfer knowledge of any depth. So long as we believe improving document structures or access will increase knowledge transfer – we will continue to erect barriers to true knowledge transfer and maintain the high error rate that we all swim through each day.