Meet in the Middle: How Both Mature and Agile Organizations Share a Common Need
Executive Summary
Startups pride themselves on their ingenuity, adaptability, and tenacity. But is there a way to innovate without relying solely on grit+luck? Is there a method to consistent success in scaling and diversifying innovation? Could chaos in execution be reduced such that probability of success will increase?
Big organizations and startups share a common enemy: complexity. On a paradigm of stability vs. adaptability, both must swing inward toward a hybrid model required to compete in a fast changing, unpredictable environment.
This hybrid model emphasizes the importance of networks, authority, objectives, and unity in turning information into action to achieve action. Horizontal, vertical, and diagonal networks are critical to achieving objectives. The model has four characteristics:
- Shared consciousness — objectives alignment
- Interdependence — awareness and relationships with other teams
- Speed — the rate at which information is acted on
- Empowered execution — delegated decision making
In highly agile organizations, unnecessary chaos exists due to fragmentation of teams and lack of consistent understanding of tactical and operational objectives. Especially in startups, which are requiring increasing analytical skills, a major challenge is turning raw data into useful insights aligned to strategic objectives. A variety of solutions, including diversifying networks, establishing forums, and deploying an original framework can establish the missing interdependence and shared consciousness. These solutions improve execution, leading to greater consistency and profitability.
The paper concludes with two applications:
- Startups Explains how startups might use the hybrid model to reduce chaos, increase success in scaling, and work toward profitability — without losing agility. This section also provides the operational framework D3SA “Diversify, Develop, Deliver, Support, Assess” to support the diversification of networks needed to achieve shared consciousness and interdependence.
- U.S. intelligence community Explains how the interagency intelligence community might use the hybrid model to adapt to great power competition and cyber through regulatory infrastructure already in place. This application also utilizes the D3SA framework, with a slight modification to an influence building context, D3A2 “Diversify, Develop, Deliver & Amplify, Develop.”
Told in narrative format, the author shares experiences from agile SpaceX and compares them with the agile transformation of the Joint Special Operations Command (“Task Force”) to beat Al Qaeda in Iraq. This paper is part-research, part-analysis, and part-application of the model found in Team of Teams by Stanley McCrystal and One Mission by Chris Fussell.
Two Stories: Intersecting Startup and Military Memoirs
I landed in California with all the enthusiasm of a 23-year-old. I was delighted to find SpaceX upgraded my car rental, so I sped my bright yellow Camaro from LAX to my temporary apartment in the luxurious Playa Vista neighborhood. In just two days, I would start an exciting new job at the still relatively unknown but out-of-this-world SpaceX, founded by the quirky technical genius Elon Musk.
It was through SpaceX I learned startup culture. Tech startups operate in a competitive, unpredictable environment. Many compete against better funded startups, others digitize features of big company products and hope to scale, and others solve new problems and hope enough people agree the solutions are worth money. In any case, startup culture is inundated with values of grit, luck, and the need for exponential growth. Especially SpaceX, a celebrity, charismatic leader-led, innovate-or-die, cash flow strapped fight to colonize Mars, in combat against an ancient, government subsidized industry.
While SpaceX was technically not a startup, as a 7,000 employee, 15-year-old company, it acted like it. Elon spurred the iterative innovation required to bring to market cutting edge, competitive, profitable technologies.
I did not start my career in a risk-taking, fast charging environment, quite the opposite. As a child of military personnel might be known as an “Army brat” or a preacher’s kid being a PK, I was a Dow brat. Born in Midland, Michigan, the headquarters of Dow Chemical, my father was a scientist at Dow. He retired after 35 years about the same time I retired from Dow… at three years. I successfully avoided working at the corporate headquarters in Midland (a great effort on my part), and instead was located in Houston and Indianapolis throughout the Supply Chain Rotation Program. During this program, I saw three parts of the behemoth Fortune 100 company: Lean Implementation, Supply Chain Center of Excellence, and Supply Chain Planning. The first two were corporate roles, and the latter was in a business.
The first role in Lean Implementation was as a consultant supporting operator teams in removing waste from processes, such as redesigning a warehouse flow to ensure material was consumed First In, First Out. After the redesign, it would be nearly impossible, even for a new operator, to deviate from the process.
My second role supported business-specific supply chain teams as an analyst sitting in the Center of Excellence, a centralized body providing supply chain expertise for big challenges. I built models, I ran improvement projects, and received training in the process control methodology called Six Sigma. One of my projects resulted in two manufacturing plants closed and equipment shipped to another site 1,000 miles away. Such an exceptionally expensive activity resulted in millions in freight cost savings, a result only imaginable at a company the size of Dow.
My final rotation role was planning supply (raw materials and production) so that supply balanced with demand. After the rotation program ended, I remained in the role until I left for SpaceX. This role followed a strict global Supply and Operations Planning process, with sales, supply chain, and customer service completing specific tasks on certain days of each month. For example, sales confirmed a forecast on day 6, supply chain planners balanced supply across production sites at a monthly level from Days 7–9. Sales would have a second opportunity to review forecast mid-month, for which then supply chain would fix the supply plan for the following month. Then the distribution planners and customer service agents would finalize distribution plans. This activity occurred mostly without individual communication through our enterprise resource planning system. I also ran process automation projects for replicable and high-volume processes. I also led a project that was almost silly in concept; a couple plants were transacting completed production on the wrong plant code in our system… shifting production to the correct plant code took coordination from 19 different teams across Dow. This was just to satisfy the tax accountants, as the two plant codes fed into different subsidiaries.
A global enterprise system is an attractive tool for large organizations, as these systems distribute information across the entity. This information activates pre-planned human-controlled operations. Dow paid $1 billion and took 8 years to implement SAP[1]. The system runs the company and people run the system.
It is incredibly efficient: without a single verbal or written exchange, a customer service agent may enter a customer order in India, which sends a signal to a manufacturing plant in Peru, which plans and then produces the product; then, a customer order matches against available inventory, triggering a logistics specialist to arrange shipment with a pre-approved freight forwarder. The forwarder imports the product into India from Peru and arranges shipment to the customer.
Variation and exceptions to processes were thus waste, with teams dedicated to eliminating this waste. Centers of Excellence across all functions are staffed by thousands of employees dedicating to implementing exceptionally complicated improvements to reduce inefficiencies. Process improvements are reduced to repeatable steps and coded into the system. For example, a plant might produce to an optimal “wheel” of products to reduce off-grade, carrier rates might be volume-negotiated, and process automation might remove the need for humans to transact in the system.
This is the same type of organization General Stanley McCrystal[2] inherited after assuming command of the Joint Special Operations Task Force in Iraq in 2004. “The Task Force was a large, institutionalized, disciplined military machine”1 designed to prevent a recurrence of Operations Eagle Claw in which a “Navy helicopter, flown by a Marine pilot, collided with an Air Force cargo plane loaded with Army commandos.”[3] The joint command ensured information sharing across branches, and the organization practiced 20th century scenarios until operations execution was perfect.[4] “Special operations forces were designed to employ uniquely skilled operators, in small numbers, for carefully timed raids executed with rapierlike exactitude.”[5] Like Dow, the Joint Special Operations Task Force had awesome system-based execution capabilities; but, deviations in the operating environment flummoxed the system. Al Qaeda in Iraq was one deviation on the scale of a disruptive event that forced the Task Force to change its ways.
Unlike traditional foes of the United States, the Al Qaeda organization eschewed a complicated, traditional hierarchy for a complex network of cells. As special forces teams eliminated one cell, other cells would reform relationships before intelligence exploited from raids could be analyzed by centralized intelligence agencies, disseminated to the Task Force, and a mission could be planned. Information bagged from raided insurgent sites piled up in storage rooms.[6] In a paradox, despite modern communication being instantaneous to anywhere else in the world, decisions moved slowly through the bureaucracy. The insurgents moved on. It is under this context that an average of 10 raids were conducted per month. How did the Task Force ultimately increase rate to 300 per month?[7]
The Setting: Organizations and Complexity
The terms complicated and complex are worth defining. Dow Chemical is a complicated organization. The India to Peru to India information and operations exchange is representative. Fundamentally, the Fortune 100 organization of Dow Chemical is a matrix organization with 5–7 business units, and 3–5 centralized functions supporting the business units. While difficult, this is perfectly possible to comprehend as a set of linear relationships. Complexity, however, is the extent of variables and their relationships as too great and obscure to map, model, or however else predict. The Butterfly Effect captures the complex variables of weather, originating in MIT professor Edward Lorenz’s 1960s paper “Does the Flap of a Butterfly’s Wings in Brazil Set Off a Tornado in Texas?” Often misunderstood as a deterministic philosophy, the Butterfly Effect considers the idea of a minor event inexplicably causing a major event through the impact on a series of independent variables.[8]
Machine learning, which is the “use of advanced statistical methods to predict outcomes, such that the model reduces in error with additional data,”[9] deals with non-linearity. It works so contrary to human rationality, the lack of explainability, transparency, and provability[10] are serious concerns. Yet, statistical predictions derived through machine learning techniques are highly influential in decision making, for example, used by China to track and slow the spread of Covid-19.[11]
Complexity is not worth trying to fully comprehend or predict.[12] The cost to collect additional data still may not lead to sufficient and timely insights, as minute deviations in variables within a context environment cause the outcome to change — hence, the Butterfly Effect. and the reductionist efficiency that allowed companies like GM[13] and Dow to initially scale instead reduces an organizations ability to respond to a disruptive event.[14] Organizations must deal with complexity with other tools, namely adaptability and resiliency.
One might reduce an organization to information and action. Organizations under this interpretation are thus designed to take advantage of the extent to which an environment is predictable — that is, information is perfectly available. For generations, organizations have followed a typical lifecycle, something like the following, of which the stages reflect an organization’s ability to know, influence, and respond to an operating environment.
All begin in an uncertain environment. Over time and with success, organizations begin to understand their environment and how to address it. The better it can know and influence the environment, the more it seeks reductionist efficiency. Invariably, there is a disruptive event which restarts the process, only if first the organization is sufficiently resilient to absorb the impact.
Big companies like Dow and bureaucracies like the Task Force are threatened by an increasingly complex world. This complexity has always existed, but organizations used to encounter it more slowly. This is evidenced in the declining tenure of S&P 500 companies from 61 years in 1958 vs. 18 years as of 2012.[15] Unlike the behemoth organizations in the S&P 500, startups are born into this complex operating environment.
Today’s startups were not designed with bureaucracies and complicated systems, because they were born into a complex environment. In fact, startups may naturally resist these systems. During my first lunch with my manager, I sought to understand which systems SpaceX used, what processes I might execute, what training to expect, to what databases and file shares I might find job aids and dashboards, and broader questions such as how the various functions communicated. I recall my manager being visibly annoyed with the questioning. When I rotated between jobs at Dow, these questions made me a superstar. At SpaceX, within a week, I was being told I was not “all in” and “doing what’s best for SpaceX.” I was in startup culture shock. SpaceX did not have processes, systems, and training, so why was I wasting time asking about them? There are rockets to launch!
The lack of systems at SpaceX reflected the complexity, and therefore unpredictability, of the operating environment. Rocket launching was the stuff of governments or government-subsidized companies because of the complication of rocket science and humanity’s inexperience in the final frontier. No one had ever developed systems that could rapidly iterate reusable, orbital class rocket development and manufacturing at a profit. SpaceX began and remained an agile organization, in contrast to the Task Force’s exceptional operations execution capabilities based on decades of experience.
SpaceX hires agile thinkers and competitive personalities. So, I quickly learned. To prove I was “all in,” I delivered a presentation to my manager detailing the function of my two assemblies aboard the rocket and the detailed steps necessary to manufacture the parts. In my first few months, my full-time job was babysitting two 2-ton chunks of aluminum through manufacturing — the sump and thrust cone. (The thrust cone had to bear the weight of 190,000 pounds of thrust of the Merlin vacuum engine — neat!) The lack of inventory and material handling systems meant production regularly lost the massive pieces in handoffs between 7 or so internal steps. Sometimes, a bad actor intentionally caused delays. So, I spent my time chasing down the two parts, finding an expeditor to move the parts, negotiating with technicians to work the parts in the present or next shift, and so on. Eventually, I negotiated an owner in production engineering, but I had to help that person get the training needed to move and work the part.
Over the next eight months, I took on a variety of propulsion assemblies. One day my manager sat down next to me and said, “Hey, you’re looking for more work, right?” She described the aft thermal shield our supply chain team had acquired from the structures supply chain team. Merlin (propulsion) production integrates the shield onto the octaweb (which must bear the combined thrust of nine Merlin 1D engines — neat!). It made sense for my team to manage the supply chain, as Merlin was our primary customer.
The shield was undergoing a redesign. This redesign was to improve the previous redesign from a few months earlier, with the goal of achieving 10x rocket reusability (never before been done; at the time of writing, SpaceX is on number 7 — neat!). The inaugural Falcon Heavy launch in early 2018 provided the data needed to redesign the shield to achieve this goal.
This would be for me the biggest product I had ever managed, with brand-new engineering teams, production teams, science, and supply chain. There were about 15 full time team members across supply chain, engineering, and production. We were redesigning not one, but three thermal shields (Falcon 9, Falcon Heavy Side, Falcon Heavy Core). Each shield was $1 million, the schedule at the time called for 24 shields per year made 15 days apart. The first redesigned shields were slated to Falcon Heavy side boosters for Air Force’s STP-2. Then, the Falcon 9 shield for the Air Force’s GPS III-2. Finally, the shield for the STP-2 core.
My manager made it more mysterious and critical. She said the redesign effort was hurting, the supply chain was poor, and there might be an opportunity to align the supply chain with propulsion. She said, “I don’t know anything more than that. Have fun,” and let me be.
The Punchline: Adaptability and Resiliency Model Definition
Before I continue the story, I will share the theory behind the solution. Layered into the narrative thus far has been a critical point: here are two organizations with completely different contexts. Both are facing the same menace, complexity. Failure to address this beast means compromised national security for one, and decades delay to an interstellar Manifest Destiny for the other.
Yet, each have something to learn from the other. The Task Force was an awesome machine, executing complicated and important processes with incredible precision every time. Yet, it lacked the agility to handle an unpredictable threat. SpaceX could move fast on information. Individuals independently and quickly sought out and resolved anything delaying rocket launches. However, execution was chaotic and only partially coordinated.
Imagine these organizations on a paradigm of stability vs adaptability. Each needed to find their way to the middle of a paradigm, beginning from opposite ends. Individuals, team, and the enterprise would all have to change to accomplish this task.
The Task Force did accomplish its mission. But for SpaceX, the lesson is ongoing. SpaceX is a case study on successful innovation in-of-itself, with Elon Musk revered in the startup community as an example of grit, luck, and ingenuity. He is comfortably lauded among giants like Steve Jobs.
More broadly, how might startups adapt lessons from a big, old organization like the Task Force? Could there be a path to more consistent success in scaling and diversifying innovation, just as Elon’s companies have done? Yet, while reducing the chaos caused by relying on grit+luck?
Task Force alumni made extensive effort to determine axioms from the Task Force’s transformation to agility.[16] The characteristics of a resilient and adaptable organization are (also shown in Figure 3)
- Shared consciousness — objectives alignment
- Interdependence — awareness and relationships with other teams
- Speed — the rate at which information is acted on
- Empowered execution — delegated decision making
We can see information in these relationships. What do individuals know? How do individuals gain access to information? Who acts on information? It is essential to reduce information to the individual level, as under the model, it is those who do the work that must have the authority to act on information. However, this relationship between information and action must also extrapolate to operational and strategic levels of an organization, ultimately dictating how organizations should be designed and managed.
A systems theorist might not appreciate attempt to fully distinguish resiliency and adaptability, but I find it helpful. In unpredictable, complex environments, information comes fast and from many directions; one might consider these as “inputs” to an organization. In these environments, developing multiple barriers to failure (resiliency) and capabilities to quickly change (adaptability) is critical. Resilient organizations are such that unpredictable changing conditions fit well into pre-existing capabilities, even if products/services change.[17] Adaptable organizations move quickly to adjust to observable changing conditions. A well-designed resilient system is one that can adapt and become stronger.[18] This is critical to a startup being more than grit+luck.
The reader can do a quick diagnostic on their own organization. Review the following chart, which shows the milieu of organizations with only two competencies. Red relationships indicate an organization not doing well. Yellow is an organization easily threatened by disruption. Blue indicates success in achieving one of the two coveted characteristics, but these are not worth much without the other.
Now, take a look at a slightly different chart. Each relationship is independent. The reader’s organization may have one or two of the four characteristics, but not having two creates some interesting consequences on culture.
I will now return the story. We will first look at the challenges on each organization related to these four characteristics. I will conclude the paper by broadening and applying the model to startups and the U.S. intelligence community. For the former, reducing chaos leading to profit. For the latter, in accelerating interagency coordination. I have included an operational framework, design to create the characteristics that these two organizations both lack: interdependence and shared consciousness. This framework is a resilient map that will support the diversification of information networks, applicable to everyone from tactical employees to senior leaders.
Rising Action: Two Problems
Shared Consciousness and Interdependence
For any other traditional foe, the strategic objective of the Task Force “to defeat Al Qaeda” would have been perfectly sufficient. The organization knew how to defeat foes of our past. With a complex foe, translating the strategic objective “Defeat Al Qaeda” into operational and tactical objectives was extraordinarily difficult.[19]
The Task Force was inherently tribal. Loyalty and team determination were emphasized throughout the extensive and challenging training programs that shaped these elite warriors. For example, the infamous Navy SEAL BUD/s training, with a 60% fail rate, weeds out those not caring enough to give it all to the team to finish. Not the physically unfit (only 10% of those who quit).[20] The training program ingrains team-based collaboration, with exercises requiring collaborative effort. Despite this unit-level loyalty, teams from different branches and programs competed. Individual teams then interpreted the strategic goal “Defeat Al Qaeda” according to their own unit’s interests.[21]
This tactical-level interpretation existed despite extensive centralized strategic planning. The Task Force, like many large organizations, used the strategic alignment methods popularized by Peter Drucker in the 1950s.[22] In this vertical alignment model, strategic objectives are cascaded down the organization level by level until reaching the tactical teams, who then execute. This was not enough to overcome horizontal rivalries.
At SpaceX, I quickly uncovered an unusual chaos — even for SpaceX. Supply chain ignored critical and urgent sourcing activities. Engineering had designed the previous supply chain (which was pretty bad) and threatened to do it again if supply chain did not start sourcing new suppliers. Engineering worked only on the side booster redesign (when all three should have been in work) and lacked data to create a design release plan. Production was locked out of communications; manufacturing engineers had complaints about the previous shield that design engineering and supply chain seemed to ignore. In a rare “up and over” moment at SpaceX, a production director, concerned for his team and the lack of visibility, got the engineering director to reallocate design engineering to release the assembly drawings (the Lego model per se) before releasing the component part drawings (the Legos). This unnecessarily delayed the program. Across the teams, ideas for improving the design were ignored, as no one seemed to know who to go to or how to make the decision. One Mission, p50
In these examples, both organizations are seen to lack shared consciousness and interdependence at the tactical and operational level. “Defeat Al Qaeda” and “Launch Rockets” were good strategies. But “Work with the intelligence teams, they aren’t the enemy” and “work with the supply chain team, don’t do it yourself” were foundational tactical and operational objectives that personnel struggled to follow because of tribalism. For the Task Force, the problem was caused by a focus on vertical alignment and the lack of horizontal alignment. At SpaceX, there was too much independent action by too many parts of the organization with minimal alignment at all. In both situations, chaos ensues as individual teams compete for resources and engage in redundant activities. Information does not flow as is necessary because of the competition and siloed nature,[23] both unintentional and unintentional.
Empowered Execution and Speed
Different branches of the military have utilized different personnel management methods over history. The U.S. Navy uses the acronym UNODIR, “Unless Otherwise DIRected.”[24] This acronym is unique to the Navy. It makes sense: different historical navies employed this sense of empowerment: The President of the United States bestowed his authority upon Commodore Perry in 1852 as Perry sailed to open the nation of Japan to the rest of the world.[25] Admiral Nelson at Trafalgar used a chaotic battle tactic reducing the Nelson’s ability to communicate with his fleet. In advance, he gave his captains the instruction, “No captain can do very wrong if he places his ship alongside that of the enemy.” [26] Commodore Perry and Admiral Nelson’s captains could only have such independence to make decisions after first knowing the strategy of their leadership. This is a skill that must be cultivated.[27]
Stanley McCrystal contrasts these two scenarios with one from the Task Force in Team of Teams. He described a practice that made him question his relevance. Subordinates would wake him up to rubberstamp important missions. McCrystal points out he rarely had “groundbreaking insight,” as his operational leaders had better information than he.[28] Had McCrystal’s subordinates lacked good sense, it might be in the best interests of the organization to require such an approval. McCrystal observes in the more than 100 years since these historical scenarios, despite the ability to immediately communicate anywhere in the world, executives counterintuitively sought more control. This bureaucratic, centralized decision-making reduced speed and resulted in missed opportunities to take down illusive Al Qaeda operatives.[29]
SpaceX, however, had exceptional empowered execution. There really was not an idea of who had authority to make decisions, but rather who was most helpful in making decisions. I found that sometimes the most helpful person was a technician, and other times it was a director; maybe someone in between. Titles really did not matter. This is often the case for startups and organizations born in unpredictable situations. Innovation — that is, agility — is the lifeblood of the organization, not cost-effective, reductionist efficiency.
The problem with SpaceX, and often as it is with startups, is a devolution into chaos due to the lack of awareness of objectives and general tribalism. While we could move with such speed and had freedom to make decisions independently, there was incredible friction. Despite a rocket of 800,000 parts, we had a flawed priority board that many production teams did not use. Whoever got priority was the one who made the most compelling case (and screamed loudest). But a compelling case might not result in the right priority decision. The average age at SpaceX was 29,[30] so many employees likely lacked a professional awareness of the whole company and an understanding of how its various parts function together. We were incentivized to make decisions and quickly; employees were rarely trained or otherwise coached to make good decisions.
Climax and Conclusion: How the Model Solved the Problems
Task Force Conclusion
Team of Teams outlines a variety of changes implemented to remake the functioning of Task Force. It begins with the core purpose of the Task Force to beat Al Qaeda in Iraq, and the development of the technical skills to do so. In this regard, one might say the initiative began by replacing maps with whiteboards.[31]
Traditional foes were defeated on physical battlefields. The Art of War by Sun Tzu says, “All warfare is based on deception,”[32] and encourages commanders to deceive their enemies about their movements and emplacements. Thus, maps were critical to the function of any military commander, to visualize movements in context to terrain to prepare strategies and attempt to discern the strategies of the enemy. However, with Al Qaeda, the new maps needed were not geographical, but organizational. Discerning the hierarchy and connectivity of the complex network of cells became the challenge. The Task Force filled its headquarters with whiteboards to improve the ease by which teams could draw and redraw networks based on the latest intelligence.
The Task Force needed a new way of communicating operational and tactical objectives quickly across teams and partner organizations.
As the Al Qaeda network adapted to intervention and needs, the Task Force would have to constantly and quickly realign its machinery in response. No amount of efficiency in bureaucratic channels and standardized kill chains could ever be quick enough.
So, the Task Force created a video conferencing forum, dubbed the Operations & Intelligence (O&I) brief.[33] This daily 90-minute gathering grew to thousands over people located around the world and working in a variety of military and civilian intelligence capacities. A docket of 5-minute briefs from Task Force and partner personnel were scheduled, with care shown to acknowledge individuals and connect resources and information shared to anyone relevant. Chatrooms during the meeting were vibrant, with many acting as “boundary spanners,” connecting people interested in more information to the guy who knew a guy who could provide the detail. In this regard, potential opportunities were proactively planned — a team aware of an impending raid, but not yet sure of the details, could ask the various agencies to be prepared to act, and resources would be reprioritized real-time during this meeting.[34]
The daily cadence of this meeting was critical to the functioning of the Task Force.[35] This cadence matches the pace of change in the environment with an operating rhythm aligning strategic, operational, and tactical levels of the organization. With Al Qaeda in Iraq adapting almost immediately in response to raids, the entire Task Force and interagency organizations needed daily realignment, literally establishing awareness of the objectives of the next 24 hours. The period in between O&I briefs became the realm of empowered execution. Each level provided services that they could best offer — the strategic level of the organization monitored the environment and worked to build enhanced credibility of the organization amongst partners. The tactical teams executed the daily strategy as they understood it, empowered to interpret and react to additional operational influences according to the daily strategy.
The information networks created by this forum were only starting points. The Task Force created a variety of rotations to break down tribal barriers, such as rotating high performing SEALs to spend time with Army Special Forces teams,[36] and others were sent to act as officer liaisons at embassies around the world where there might be relevant activity.[37] These individuals brokered information between the two entities and offered the support and coordination of the Task Force where relevant. These actions combined created shared consciousness and interdependence, not just within the Task Force but also to the broader interagency and military partners.
There was still the issue of bags of intelligence gathering dust in storage rooms. For this, the Task Force developed an operational framework called F3EAD[38] designed to integrate intelligence and operations. This framework needed to work for a unit deployed in the field and with senior intelligence and military leaders designing organizational systems.
F3EAD stands for Find, Fix, Finish, Exploit, Analyze, and Disseminate. F3EAD replaced an earlier model, Decide, Detect, Deliver, and Assess (D3A).[39] F3EAD became the basis for manhunting operations. The framework was a “process” of sorts: find the target, fix the target’s location, finish the target, exploit the intelligence at the target’s location, analyze the intelligence, and disseminate the intelligence. Primarily, it served as a visionary framework, providing the “scaffolding”[40] of the transformation.
F3EAD, combined with the previous explained initiatives, eliminated the bags in storage rooms. With special operations operators and analysts each knowing how they fit into the broader organization, communication and handoffs became direct, increasing the speed by which information was turned into action.[41] Additionally, intentional effort to decentralize decision making meant operators and analysts could mobilize forces and resources to immediate opportunity.
For example, a team hitting a farmhouse saw suspicious activity at a nearby farmhouse. Without rubber stamp approvals and detailed operations planning, they called in Night Stalker helicopters. The resulting raid captured an individual whose interrogation led to the airstrike that killed the leader of Al Qaeda in Iraq, Abu Musab al-Zarqawi.[42]
With objectives aligned, teams working together, a framework that improved speed, and actions taken by those who are closest to the information, the Task Force ramped up raids from 10 per month to 300 per month, with minimal resource increases. The efforts supported success in eliminating the influence of Al Qaeda in Iraq.[43]
SpaceX Conclusion
The reader might recall I began at SpaceX by quizzing my manager about systems and processes. When I joined the aft thermal shield team, I was no longer so green. I jumped right in; I asked my predecessor for a list of people to meet. I set up meetings with all 15 people over a single week. During these 30–60 minute “tag ups” (as we called them), I dug deep into their roles, what they do, how they do it, and concluded with asking about problems they saw with the shield. Post-meeting, I tracked down the right people for the problems and made sure a solution was implemented. For example, a manufacturing engineer complained a feature of a large titanium structure made it difficult to insert a screw. I took this feedback to design engineering. The designer had the exact model open on his computer and happily told me the feedback had already been incorporated. No one had told the manufacturing engineer that, so I did. He was pleased. One less conflict, and a little shoulder-to-shoulder trust was built.
The larger issues stalling the program, such as supply chain ignoring the shield and engineering therefore threatening to do the supply chain, took considerable intervention. I caught an engineer sending out Request for Quotes to suppliers. I negotiated a cease-fire over several weeks and got engineering and supply chain in the room together. The next morning, the two teams visited potential suppliers together. To satisfy all three functions, especially the oft-forgotten production, I pulled data and pieced together a design release schedule. Within a couple of months of constant intervention, which included driving five-foot titanium blanks to suppliers myself when the inventory team failed, the program was back on track.
But, that did not mean we suddenly had shared consciousness and interdependence. These two attributes had to be cultivated through multiple initiatives. It was not until years later I understood why these initiatives made the difference.
First, an olive branch was extended with engineering no longer the enemy of supply chain. I was given additional responsibility to ramp down production the previous design, which made engineering happy. Engineering also offered me a seat with their team. This was the beginning of interdependence and shared consciousness. Interdependence because I could support them, and they could support me. I fielded regular requests to calculate impact to schedule given challenges that cropped up, such as defects, supplier onboarding (which engineering initiated), and other organizational priorities. It also gave me a chance to supervise design engineering. I repeated the following conversation many times: “What are you working on? Hmm, is that the right priority? Let’s check the design release plan. No, you need to release these designs first.”
Second, I assigned ad hoc project managers from each function who would track all new product introduction initiatives within the function and feed the information to me. I began releasing weekly program-wide updates and organized weekly review meetings. The review meetings are the equivalent of the Task Force’s O&I briefing. I would prepare an executive summary — unheard of at SpaceX, executives preferred volumes of detail, given the lack of systems and accountability via metrics — functional updates led by each project manager, and a detailed review (to satisfy SpaceX executives). The meetings started small, about five or six people mostly from supply chain. By the end of the program, I had 20–40 regular attenders — a huge number for a SpaceX meeting — with technicians to from all functions. People came and went as needed. Anyone could speak at will. This facilitated interdependence — for many, it was the only time people would see others who worked in various buildings on our square-mile campus. Priorities shifted according to improved awareness of the status of our objectives. Additionally, these meetings built shared consciousness. My executive summary gave the first-ever view of the critical path to all employees. Team members could jump into help crucial objectives or call off redundant efforts.
One particularly grueling day when nothing seemed clear, I had inspiration and drew a hierarchy. I wrote “Program Manager” and my name at the top. I wrote in the three functions below and wrote in the project manager’s names under each function. I then drew in further sub-projects and the person responsible. Figure 8 shows how I thought of my self-promoted Program Manager role based on my Dow training.
I retained this thinking for two years after I left SpaceX. But this was not right. If this had been true, the program would have been less effective due to horizontal misalignment — as large organizations struggle — and it would have relied on my ability to command work be done. After reading Team of Teams, I realized the Program Manager role actually looked more like Figure 9.
In effect, I had become a broker of information through the organization. In establishing the weekly reviews — again, the Task Force O&I equivalent — I cultivated the networks and various projects, ensuring obstacles were removed, resources allocated, and efforts staffed. When I wrote that original hierarchy, my name appeared as the person responsible for too many projects. I am glad my manager told me to delegate; in effect, I actually improved the extent individual functions were empowered to execute, while increasing my own credibility as a broker of information. I simply had more time to dig deep into the data and tag up with team members to check on status and support hurting projects.
SpaceX, with its 7,000 employees, regularly breaks records. The SpaceX chaos works, even if painful. But in this doubly chaotic redesign program — three shields at the same time — the SpaceX method struggled to sufficiently meet operational objectives. I have no doubt the redesign program would eventually have been achieved, late. Instead, the redesign was delivered to integration when needed. The shield went from 0% to 100% on time, as compared to the previous design, which was regularly installed on the launch pad days before launch. We never calculated cost savings, but a total supplier overhaul improved efficiency, schedule, and cost. And the program achieved remarkable gains in reusability. The inaugural Falcon Heavy post-launch pictures showed a toasty shield — inside the rocket. Post-launch pictures of the new design revealed a pristine interior — as if the rocket had not traveled into space and back. As a result, we also reduced the refurbishment material inventory carried at the launch sites.
The story does not stop at the end of 2018, when I left SpaceX. The two years since have been a person period of reflection, synthesis, and adaptation. I would change two things about my own O&I.
First, the environment demanded a faster operating rhythm than once per week. Too many designs were released, parts entered the supply chain, suppliers were onboarded, new equipment and skills were acquired by production, downstream and upstream assembly and integration schedules adjusted, team members changed, defects and redesigns managed, etc., from week to week. The operating rhythm might have benefited from Monday and Thursday O&Is.
Second, people with my job were historically responsible for being the focal point of all information and coordinator of all teams; thus, I was explicitly expected to brief status on the entire redesign program and its component parts, even if the project managers I assigned were present. First me, then them to catch any missed details. During the redesign, the O&I was immensely successful and celebrated by all teams. But, as the shields entered ongoing production, the volume of information became overwhelming. 1,300 parts were produced and assembled nearly every 15 days, with numerous ongoing redesigns and supply chain changes from several distinct engineering teams lacking network connections. The O&I instead became a forum that amplified politics and chaos caused by unexpected executive departures, reorganizations, and a radical shift in culture which left everyone reeling. The reason for the ad hoc O&I organization and my program manager role had evaporated.
It is curious to consider an alternative: should I have fought for enhanced sense of cross-team ownership of the O&I, or should I have organized a coordinated end to the O&I at the conclusion of the redesign program? The answer is likely a hybrid of both. The operating rhythm had changed — we were no longer in the midst of comprehensive change. Multiple O&Is would have targeted the owners of the upcoming changes at a different frequency. The visibility of the O&I should have declined; strategic leaders were no longer needed, as the strategy side of the business had refocused on Starship, a radically different rocket prototype unrelated to the Falcon rocket. The O&I for production might have included new invitees. Production had recently created a new type of job, called production schedulers. These individuals might have greatly supported optimization of ongoing production, with my role in supply chain as a critical upstream partner.
Application: Chaos-Reduction Framework for Startups
In my experience, startup culture revolves around grit and luck. Throw yourself at problems and pray your solution works. It is awfully tempting to write one more SQL query to look at the operational data just one more way, to spend a few more hours checking charts, and firing off emails trying to band-aid an overwhelming cascade of problems. Just as you are about to leave the office late at night, an email comes in from another software team and you exclaim, “What? They’re implementing a UX change tomorrow? Why is this the first I’m hearing about it?” Startups enshrine chaos to their detriment, which leads to friction in the workplace, slow or failed scaling, and delayed profitability.
The Task Force and SpaceX case studies show networks, authority, and unity in translating information to objective-aligned insights are just as important as the pace by which information turns into action. Startups typically have exceptional speed (the rate at which information is acted on) and empowered execution (delegated decision making) but lack interdependence (awareness and relationships with other teams) and shared consciousness (objectives alignment). At the core of interdependence and shared consciousness are information networks and unity.
This is rather a curiosity: “Information networks, you say? But startups have data! Tons of data!” Startups often have radical information sharing architectures. For example, at SpaceX, I could query data from almost anywhere in the company — no passwords or other security. Products might look and feel radically different in just 6 months or less with the pace of this cycle.
The freedom of information sharing is a significant competitive advantage for startups, especially tech startups fighting to unseat a big, old, analog corporation. The awareness of this advantage is evident in how tech startups are designed, deploying scrappy data analysts to facilitate rapidly revolving cycles of software development, execution, and analysis. Increasingly, startups are looking for more and more analytical capability, as evidenced in publicly viewable hiring trends and descriptions of ideal candidates. The goal seems to churn big and bigger data into faster and faster insights.
The need for analytical skills is a necessity beyond basic competition dynamics. Technologies like machine learning, previously defined in this paper, are potentially at calculating complexity than humans and useful for scaling processes in a “online-merge-offline” world.[44] Online-merge-offline is the integration of digital into physical experiences. Additionally, many-to-many[45] business models are practically ubiquitous, with startups creating digital platforms to facilitate these complex networks[46], often with asymmetric information between sharing economy users[47], and earning soaring valuations as a result.[48] Data is essential for the functioning of digital products and the continual development of features accommodating millions, if not billions, of users with different needs. This aspect is also an existential threat to the U.S.’s Silicon Valley, which has tended to roll out idealistic, simple, standardized products to global markets, to then be undercut by locally developed or Chinese tech products modified to specific experiences and aesthetics.[49]
Because of the unpredictability of the operating environment and general lack of available expertise, startups poach scrappy entrepreneur-types from big companies. There is a trend for new, functionless analyst/operator roles, which seem to have replaced all prior operations titles. This trend seems to have developed since 2017, when I went to SpaceX (I did not see these roles then). These roles, shown in Figure 10, are the Strategy Manager, Strategy & Operations Manager, and Operations Manager. I have also seen Chief of Staff positions with tech companies, under either “Chief of Staff,” “Chief of Staff/Program Manager,” or “Strategy & Operations Manager.”[50]
These roles no longer just require analytical skills at the level of Excel but also database query languages (e.g., SQL) and complex visualization languages (Python, R). Many startups straight up prefer data scientists (machine learning, etc.). This makes sense — hiring a tech startup operations professional without data analysis skills is like hiring an art major as a rocket scientist.
The ability for startups to turn data into action in enshrined in incentivization for fast, exponential growth at the expense of profitability. Venture capital funding rounds seed, series A, series B, etc. jump in the $10s of millions for each round.[51] With a fast cash burn, funding standards incentivize startups to push products into the market, grow fast, and reach the next funding stage. (Also, higher valuation = higher personal wealth.) A lean startup begins with a small team testing a homegrown product for market fit, and a later stage startup consists of hundreds or thousands of 20somethings trying anything and everything to develop and sell more product.
However, the fast-growth, no-profitability era is slowly coming to a halt. This seems in contrast to the 2000 dotcom bubble burst, when “easy” money suddenly evaporated and numerous startups went bust.[52] In my opinion, from discussions in the Yale School of Management class “The Future of Global Finance,” taught by Jeffrey Garten, the more recent era has been enabled by low interest rates, since the advent of quantitative easing en masse by central banks post-2008, and the supremacy of the U.S. dollar. But, shocking failures and scandals, such as WeWork[53] and the disruption of Masayoshi Son’s Vision Fund[54], has cooled the moods of venture capital.[55] The Covid-19 disruptive event forced organizations such as Uber and Airbnb to pursue improved profits, with Airbnb radically adjusting its target market[56] and Uber spinning off its JUMP and autonomous driving units, along with other unprofitable markets.[57] The ability for companies like Tesla to consistently (at least, relative to other startups) reach quarterly profits, even during the COVID-19 pandemic,[58] is a signal of change to the startup world.[59]
The open questions facing startups — even as they hire more and more analytical employees, especially from prestigious professions like management consulting and investment banking — is how to retain innovative spirits, speed of execution, the ability to quickly scale and diversify innovation, while reaching profitability?
The pursuit of unicorn employees who can accomplish all of these things is seen through public job postings. Qualifications usually require 2–4 years management consulting or investment banking experience and an MBA. But, startups prefer professionals with less than 8 years total experience.
This is quite strange given:
- A minority of talent on social media, such as LinkedIn, has this experience
- This combination (top tier MBA and 2–4 year’s experience in consulting/banking) is quite difficult to achieve, especially in less than 8 years
- If professionals have this combination, they should be quite expensive (salary requirements in the Bay Area/New York), but startups may not have the cash to pay for this; startups must provide big equity packages and a sense of purpose if paying below market
Also strange is that despite the seniority requirement (3–8 year’s experience typically), roles almost exclusively come with “Senior Manager” or “Manager” titles (and often report to Vice Presidents or Senior Directors). It is possible this nomenclature is intended to highlight the importance of data and encourage young titleholders to act with the authority and awareness of the historical manager seniority.
Startups probably pursue young professionals from prestigious industries like management consulting and investment banking for their training in logical methods and strategic communications — as well as a high threshold for burnout. This is a bit of a departure from the time of my hiring at SpaceX, which sought Fortune 100 types with creativity and change management potential. One recent, creative posting for a chief of staff role even said something like, “the ideal candidate will be a burned-out management consultant or investment banker looking to move to the sunny California shores.”
There is potential for a cautionary tale in these job postings. After all, data is inherently historical — data can help predict what, how, and when, but only one at a time, and is susceptible to unpredictable events arising from minutiae deviations amid a complex network of comprehensive variables (remember the Butterfly Effect?).[60] Should all employees at tech startups also have advanced data analysis skills, let alone MBAs and hyper-specific and rare experiences? Is the ability to consume and iterate on vast sums of data so critical to every startup role, or is this skills misuse resulting in missed execution from paralysis by analysis? Does it reduce the resiliency of startups as they constantly review data collected in the near-term past to predict the future?
I would submit the answer is, it is fine; go for it. Especially for tech startups. But be careful: if a startup is hiring an army of young analysts, be wary to ensure raw data is being efficiently processed into usable insights aligned to organizational objectives. Analysts, especially in fragmented startups, may lack the awareness and ability to bridge organizational lines. There is always chaos in new efforts, but my point is the extent of chaos in startups is unnecessary.
The alumni of the Task Force leverage lessons to help big, cumbersome organizations become more agile. This resiliency and adaptability model — speed, interdependence, empowered execution, and shared consciousness — is just as applicable to already agile startups, but in this case, the result is reduced chaos. Reducing chaos improves consistency of success in scaling and diversifying innovation, and in improving profitability. Said another way, the model improves execution without losing agility.
Interdependence and shared consciousness are the two attributes startups lack that contribute significantly to the chaos. These two attributes mean employees within startups lack the networked connectivity — despite the freedom of data — to other teams and an awareness of tactical, operational, and strategic objectives. We have already discussed several ways in which the Task Force and I, at SpaceX, improved interdependence and shared consciousness. But what might be an F3EAD equivalent for startups?
In one of my Yale classes,[61] I teamed up with eight other students, under the guidance of Chris Fussell, to deliver a consulting product to a U.S. military client. The client was facing a period of unpredictability in a worldwide shift in the dynamic national competition. The client needed to innovate new solutions to meet global competition. We developed an operational framework to guide diversification of external partnerships at all levels of the organization, similar to the F3EAD operational framework used by the Task Force to integrate intelligence and operations. The framework also works well with startups (or, more specifically, scaleups). I have included a modified version in Figure 11, applied to startup innovation.
The D3SA operational information network framework might be pronounced as either “dee-three-es-eh” or “dee-zah.” The framework is useful to any manager who needs a scrappy way to coach analysts, program managers, and other tactical employees to increase their information networks. It is also useful to startup executives who realize a need to bridge large, siloed teams. Whatever the situation, the framework is a simple tool — among others provided — to resolve the chaos inherent to agile organizations.
The framework begins with understanding the organization and objective and ends with assessing if the understanding of the organization is sufficient to achieve the objective. Thus, the framework is meant to create a culture of ever-expanding information networks to reduce chaos in execution. This is the basis of interdependence and shared consciousness.
The middle sections — develop, deliver, and support — are more inherently obvious to scrappy, entrepreneurial team members and likely need less attention. Support is particularly important for startups, especially those staffed by younger professionals. Without clearly defined roles and processes, execution is a whole-of-team effort. Regardless of title and functional alignment, the offer to help is a critical responsibility across the startup.
At SpaceX, I might have applied this framework to the O&I. I initially met with 15 people involved in the redesign after taking responsibility for the program — I would certainly invite these to the first O&I. We would collectively coordinate a strategy for the redesign (such as developing the missing design release plan), and implement, with me supporting. According to the operating rhythm — for me, it was about four days — I would then assess if I have sufficient relationships to achieve the redesign objectives. Certainly, I would have heard of other engineering teams working on smaller, specialized portions of the shield, and would have invited them to the O&I. If I had used this framework, I might have shaved weeks of chaos off the initial intervention to restore relationships and overcome tribalism.
I once told an intern at Dow that he was not expected to execute, only recommend. He was a smart guy and was thinking about second and third order effects of what he might recommend and had been overwhelmed by the complication of execution. After hearing the advice, he visibly relaxed, eased into his work, and became an effective collaborator. He was one of the only interns hired for full time in a tight-budget year. Years later, the broader principle behind my advice still rings true: everything requires the effort of broad collaboration. In a big company, executing a tactical and clearly defined process might seem like an individual effort, but even this is not true. The D3SA cycle enshrines this critical cross-team participation.
Grit+luck (and a great product) may still be the critical ingredients to a startup. Startup employees will still work long hours. But with these tools, those hours will be more productive with less stress. Execution will improve, scaling and diversifying innovation will be a little more methodical and a little less guesswork, and profitability will be ever closer.
Application: U.S. Intelligence Community Reformation
This paper has explored information and action, the optimization of decision-making cycles through organizational design, and the resulting impact in achieving objectives. In this context, information is synonymous with intelligence. The U.S. agencies comprising the intelligence community exist to gather, analyze, disseminate, and store information. These agencies, historically coordinated by the Central Intelligence Agency Director, and now the Director of National Intelligence, are the brokers of information amongst the policy makers of the United States government. This 17-agency, $86 billion budget[62] apparatus should be the absolute envy of any private sector organization. Only in such a great power could a scaled combination of information brokers exist.
Since the National Security Act of 1947 formed the foundation of the intelligence community,[63] the budget, capabilities, and influence have adapted and grown according to the needs of the world. F3EAD was a response to the manhunt operating environment of Iraq and Afghanistan, in which the organizational structure of the insurgency was exceptionally fragmented, secretive, and adaptable. Traditional information exploitation and dissemination of intelligence from centralized intelligence agencies was simply not fast enough for the elimination of the insurgency’s middle management and eventually upper-level management. Special operations forces indoctrinated coordination with intelligence personnel into all hierarchy levels of the operations teams through F3EAD. Consequently, F3EAD altered the organizational structure of special operations, as a necessity of closer coordination between intelligence and operations.
The intelligence community, likewise, adapted to the needs of counterterrorism, not just in participation with the Task Force. The intelligence community and policy makers missed opportunities to prevent the 9/11 attacks because of miscoordination, poor regulation, and bureaucratic blockages. The 9/11 Commission report recommended splitting the role of the Director of the CIA, as both CIA director and coordinator of the intelligence community, into two roles: the CIA Director and the Director of National Intelligence.[64] President Bush staffed Ambassador John Negroponte (now at Yale) as the first Director of National Intelligence.[65]
Over time, the role provided varying results[66] in coordinating the intelligence community and acting as the President’s formal broker of intelligence. The rise of the digital era also raised moral privacy concerns about the collection, analysis, and storage of data. Countries, such as China, lack this concern and have innovated faster than the U.S.[67]
With the rise of the digital era has also come a national priority shift from counterterrorism to great power competition.[68] Our opponents, China, Russia, and a variety of other powers growing in influence, are unable to win a war against the U.S., and so have initiated activities avoiding direct confrontation. The way to gain influence over the U.S. without armed conflict is by undercutting the U.S.’s relationships with economic partners and allies.
Under this context, there are calls for reform in the intelligence community.[69] A common refrain is for Congress to enact Goldwater-Nichols legislation for the intelligence community. The Goldwater-Nichols Act reorganized the military into distinct operational and administration functions, thereby clarifying conflicts and redundancies. The same idea applies to the intelligence community.
However, this paper has provided an alternative for both large and small organizations to improve the relationship between information and action, without requiring major restructuring. Ironically, the Director of National Intelligence is theoretically intended to play the role I played at SpaceX and the Task Force played amongst the interagency cooperation necessary to execute F3EAD. Additionally, the Task Force never suggested replacing the vertically aligned bureaucracy but rather suggested a hybrid model of both horizontal and vertical networking.[70] This hybrid model recognizes the important of networks, authority, and unity in turning information into action to successfully achieve objectives. It is possible this paper and its resiliency and adaptability model offers a non-legislative solution to intra-intelligence community cooperation.
A common complaint regarding the Director of National Intelligence is curiously that the Office lacks power.[71] For the purposes of this hybrid model, this is perfect. The intelligence community does not need an additional centralized bureaucratic head setting budget and making decisions with allegedly superior awareness of the comprehensive needs of the community. Instead, the Director of National Intelligence should own the role of creating shared consciousness across and within agencies, creating an awareness of agency interdependence, improving speed by which information results in action, and empowering agencies and individuals to act between operating rhythm cycles.
The D3SA framework designed at Yale and shared under the startup section of this paper was originally developed for U.S. Special Operations Command Central (SOCCENT) as an operational influence framework for a great power competition context. Under this framework, U.S. special operations forces might play a role and support influence objectives through expanding its partner network to the myriad of global public/private entities capable of building influence. For SOCCENT, our phraseology for D3SA was D3A2 — Diversify, Develop, Deliver & Amplify, and Assess. The principles and actions around the cycle are nearly identical under either wording.
In our final presentation to the SOCCENT client, I analogized influence to Walmart, which carries typically 142,000 items per store.[72] Walmart has to carry so many items because different people want different things. Influence building is the same — different people respond to different influence measures. An organization like SOCCENT could not possibly develop 142,000 solutions, so instead, it must diversify its partnerships proactively to be ready for any situation.
The D3SA or D3A2 cycles might have the same impact on the intelligence community in intra-community cooperation. Whether in proactive or reactive intelligence operations, an operational framework might provide the same “scaffolding” required to instill in every individual the concept of expanding networks and partnerships. This framework should be implemented with other tools presented in this paper, such as the O&I, rotation programs, and increasing hiring of analytical professionals capable of handling the digital era.
Congress has already created the natural leader of this initiative, even with the same purpose — the Director of National Intelligence. Now, it is just a matter of the next Director to think differently about bureaucracy — but not abandon it. A centralized coordinator could never have enough strength, and unlikely the backing of Congress, to force unity and coordination. But a horizontally and vertically networked bureaucracy is feasible, and this change will come from the director finding ways to create cooperation and empowerment of the community’s analysts.
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[1] WSJ, Norton, 11/30/2015
[2] Team of Teams, p28
[3] Team of Teams, p48
[4] Team of Teams, p49
[5] Team of Teams, p117
[6] Team of Teams, p120
[7] One Mission, p11
[8] Team of Teams, p59
[9] Derived from interview with Paul Jeffries, former Fannie Mae data scientist
[10] PwC, shared in lecture by Yale University professor Ted Wittenstein
[11] Center for Security and Emerging Technology, Georgetown University
[12] Team of Teams, p72
[13] Team of Teams, p190
[14] Team of Teams, p193
[15] One Mission, p34
[16] One Mission, px-xi
[17] Team of Teams, p76
[18] Team of Teams, p80; Energy, Sustainability, and Society 9, article 27
[19] One Mission, p50–51
[20] Team of Teams, p95
[21] One Mission, p51
[22] One Mission, p48
[23] One Mission, p50
[24] Team of Teams, p207
[25] Team of Teams, p204
[26] Team of Teams, p30
[27] Team of Teams, p215
[28] Team of Teams, p202
[29] Team of Teams, p208–209, One Mission, p145
[30] Payscale 2016
[31] Team of Teams, p25
[32] Art of War, I-18
[33] One Mission, p87
[34] One Mission, p101
[35] One Mission, p142
[36] Team of Teams, p175
[37] Team of Teams, p177
[38] Team of Teams, p50
[39] Small Wars Journal, 1/31/2012
[40] Interview with Chris Fussell
[41] Team of Teams, p138, 167
[42] Team of Teams, p237
[43] Team of Teams, p8
[44] AI Superpowers, p118
[45] Team of Teams, 63
[46] a16z, “…Fastest-Growing Social Apps…” 12/7/2020
[47] Advances in Economics, Business and Management Research, volume 144, “Asymmetric Information of Sharing Economy”
[48] WSJ, “Sizzling Tech IPO Market Leaves Investors Befuddled,” 12/13/2020
[49] AI Superpowers, p33–40
[50] From LinkedIn
[51] Fundz.net. 12/12/2020
[52] Investopedia, “Dotcom Bubble,” 6/25/19
[53] WSJ “The Fall of WeWork,” 10/24/19
[54] WSJ, “Masayoshi Son Again Pulled SoftBank From the Brink,” 11/11/20
[55] Forrestor, “Predictions 2020,” 11/1/19
[56] WSJ, “How Airbnb Pulled Back From the Brink,” 10/12/20
[57] WSJ, “Uber Sells Self-Driving-Car Unit,” 12/7/20
[58] The New York Times, “Tesla Turns a Profit in a Pandemic-Squeezed Quarter,” 7/22/20
[59] WSJ, “Tech Startups Face New Investor Mandate: Profits Over Discounts,” 12/27/19
[60] Team of Teams, p72
[61] Yale University, Fall 2020, GLBL 842: Special Operations Forces: History, Context, and Future with Professor Chris Fussell
[62] Office of the Director of National Intelligence
[63] Encyclopedia Britannica
[64] 9/11 Commission Report
[65] Office of the Director of National Intelligence
[66] The Atlantic, “Why The Director of National Intelligence Is a Terrible Job,” 5/21/10
[67] AI Superpowers p15–17
[68] Irregular Warfare Annex to the National Defense Strategy
[69] Air Force Fellow, “Goldwater-Nichols as a Model For IR,” 2006
[70] One Mission, p26
[71] CNN, “Director of national intelligence has little real authority,” 5/21/2010
[72] Walmart
