CHAPTER 6

Agility

Being Fast and Responsive

It is better to act quickly and err than to hesitate until the time of action is past.

—Carl Von Clausewitz

In the previous chapter, you read about the need to win and the role agility plays in it. This chapter continues the discussion. You’ll see how agility-thinking has evolved historically and discover why agility is necessary in your organization also.

6.1 The Emergence of Agile Management from Twelve Ideas

In agile management, continuous adjustment and improvement are central. Of course, this way of working didn’t just fall from the sky. Agile management has a long history, based on twelve ideas, which are briefly shown below as a time line in Figure 6.1.

Figure 6.1 The historical development of agility-thinking

Idea 1: The Scientific Method

Agility-thinking can actually be traced back to 1620, when Francis Bacon—strongly influenced by his contemporary Galileo—puts the scientific method down on paper. The concept is refined, between 1870 and 1930, by Pierce, James, Lewis, and Dewy, whose approaches of Pragmatism and Empiricism¹ eventually merge into the, now well-established, Empirical Cycle². In short, the scientific method sets down an iterative cycle of specific activities to develop knowledge. This cycle can be repeated infinitely to deepen understanding. The fixed steps within the cycle are:

• Observation: You do the process and see what happens.
• Induction: Based on your observations, you develop a general theory to explain them.
• Deduction: You translate this general theory to predictions, in the form of specifically formulated, testable hypotheses.
• Testing: You run an experiment to test your hypothesis.
• Evaluation: You evaluate the results of your experiment and, based on these, confirm or reject your hypotheses (also called verification and falsification).

After each iteration of the cycle is completed, you will have gained more insight into your question. This insight becomes the starting point for a new iteration. And so it continues.

This method is still standard in science, and as you will see it is also used, in a modified form, in business.

Idea 2: Darwinism

The influence on contemporary management theory of Darwin’s vision of adaptivity cannot be overestimated. We discussed this in detail in Chapter 2.

Idea 3: The 80/20 Rule

It is not a boring year, 1848. It sees France, the Netherlands, Belgium, and the German, Italian, and Habsburg countries experiencing huge popular uprisings. In the history books, it becomes known as the “Revolution Year.” It can hardly be a coincidence that precisely in that year, late in his life, someone in the world is making a revolutionary discovery.

Born in Paris, to an exiled Genoese marquis called Pareto and his French wife who, inspired by the German revolution, call their son Fritz Wilfred. Ten years later, the family returns to Italy and his parents decide to change his name to Vilfredo Federico. Vilfredo appears very eager to learn and, at just 21, he earns his doctorate in engineering. He starts work as a civil engineer for the Italian railway and moves on to manage several metal factories. He is politically very active, has a sharp pen, and is a feared opponent in duels with sword or pistol.

Around forty, after the death of his parents, he changes course radically. He quits his job, marries a Russian (who unfortunately leaves him in 1902 and takes up with their young servant) and moves to Switzerland. His academic curiosity begins to bubble up again, this time focused on economics and sociology. This leads to a professorship in Lausanne, where his research is increasingly focused on the distribution of money and political power. Many of his ideas are later used by his best student, in his own political career. This student just happens to be called Benito Mussolini.

In 1906, Vilfredo publishes some remarkable research. He finds that in Italy 80 percent of the assets are owned by 20 percent of the population. He concludes that this population, thereby, actually holds all the power and decides to call this group by the term “elite.”

Apparently reassured by this insight, he decides that it is the time to let his lifestyle reflect his own wealth. He finds a new wife, buys a huge villa—which he fills completely with the most expensive art—assembles one of the largest wine and spirits collections in Europe and surrounds himself, for no apparent reason, with a huge number of Angora cats. He devotes himself in his final, elitist, years to mathematics, beauty, and pleasure. He dies in 1923, childless.

Pareto’s name actually became particularly well known thanks to an American management consultant, Joseph Juran. In 1941, Juran encounters Pareto’s work and decides to apply it to the issue of quality. He discovers that the 80/20 ratio applies to many different managerial phenomena and renames it the Pareto Principle. It becomes widely known as Pareto’s Law, the 80/20 rule, the rule of the “Vital Few and Trivial Many,” the Law of Imbalance and the Principle of Least Resistance (a derivative application developed by George Kingsley Zipf).

In general, the 80/20 rule means that 80 percent of the effect is caused by 20 percent of the input. This is not an empirically proven rule, but you can see it often and easily. The two numbers may also have a different relationship and not necessarily add up to 100. There may also be a ratio of 90–30, 70–40, and 50–5 (the latter means that, for example, there is a high amount of ineffective activity), but 80–20 will be by far the most common.

Some practical examples:

• 80 percent of profits come from 20 percent of customers
• 80 percent of pop music can be played using 20 percent of the chords
• 80 percent of sales in a restaurant come from 20 percent of the menu items
• 80 percent of data bandwidth is allocated to 20 percent of users
• 80 percent of users use 20 percent of software functionality
• 80 percent of complaints come from 20 percent of customers
• 80 percent of time spent in a supermarket involves 20 percent of the shopping
• 80 percent of traffic accidents are caused by 20 percent of road users
• 80 percent of downloaded music comes from 20 percent of performers
• 80 percent of cost is caused by 20 percent of the production process.

What does this mean now for agile management? First of all, the 80/20 rule forms the basis for the so-called minimum viable product (which is discussed further in Chapter 11). Here you strive to offer a proposition, at a minimal investment, which gives the customer an acceptable picture of the final product or service. So here you want to focus on the 20 percent of the functions that deliver 80 percent of his experience.

Secondly, logic says that, based on the 80/20 rule, time-use can also have an optimal point, and that benefit from additional time-use decreases rapidly. You can continue to analyze infinitely, because it can never be complete, but this leads to analysis paralysis. Or worse, to death by analysis: if you’re not careful every initiative or idea is rejected on the basis of analysis. You have to dare to accept that your analysis, at a given moment, is complete enough, that you have spent enough time on it and that it is good enough. You just need to start somewhere, to dare to push the boat out. This touches a bit on Parkinson’s Law, which states that work expands to fill the time available to do it. You can prevent this by setting time limits and sticking to them.

Thirdly, the 80/20 rule forms the basis for prioritization of development and improvement projects. If you invest in such projects, investment yield decreases rapidly as you move away from the 80/20 point. The always-scarce resources of time and money should be used with optimum efficiency, focusing on the factors that have maximum impact on the result. This requires managing different criteria, as you can read in chapter 10.

In addition to the above, there are a pair of unusual aspects of the 80/20 rule. The first is the self-fulfilling prophecy, defined by sociologist Robert Merton, in 1948, as follows:

“The self-fulfilling prophecy begins with a false definition of the situation, which evokes a new behavior that confirms the original false definition as true. The apparent accuracy of the prediction maintains a false misrepresentation of the situation. The predictor will point to what eventually happened as evidence that he was correct at the beginning.”

The economy is a prime example, where media coverage about a faltering economy greatly contributes to the start of economic decline, or leads to predictions of a rise in stock prices, which actually cause the increase. Google searches are a good example of how it manifests in marketing and sales; the top 3 results commanding circa 63 percent of the click-throughs. Due to this popularity, they return, in subsequent searches, again in the top 3, and so on. The principle applies to all kinds of popularity rankings (such as the music Top 40), leading to the phenomenon whereby if something has been judged as popular, it will continue to be seen as such and perhaps become even more popular. A self-maintaining system. Probably, in your organization, the best-selling products or services get the most attention and the biggest communications budget, because in general businesses focus more on short rather than long-term sales. Obviously, this carries the risk that the full potential of existing or new products and services is unlikely ever to be realized, as they never get a chance to prove themselves. It is important to be aware of this.

The second special unusual aspect of the 80/20 rule is that of the long tail, a mathematical concept which became famous after Chris Anderson’s 2004 article in Wired magazine.³ In statistics, a long tail (or fat-tail) means that a larger proportion of the population rests within the long tail of a probability distribution than in a normal distribution. Companies like Spotify, iTunes, Netflix, and Amazon are taking full advantage of this. Due to low marginal costs, and the transparency caused by good search capabilities, they can offer a huge amount of online “niche”-content and products. When added together, this realizes more than half their income. So, this is actually a clever reverse application of the 80/20 rule. As an Amazon employee so aptly put it: “Today we sell more books that weren’t selling well yesterday, than books that were flying off the shelves yesterday.” Hooray for the lost souls of slow-moving inventory.

Idea 4: Scientific Management

Around 1900, an important part of the scientific method is first applied within companies: Frederick Taylor, the founder of scientific management, introduces a way of doing business which aims to achieve performance improvements based on detailed analyses. Decisions should be made on purely rational grounds; central to this philosophy is measuring performance and comparing the results to objective standards. Taylor’s vision is supported, among others, by Frank Bunker Gilbreth. He is a pioneer in using time and method studies to improve performance, for which he develops the now widely used visual approach of process flow mapping.

Idea 5: Continuous Manufacturing

Taylorism and the time and method study approach are picked up by Henry Ford. In 1903, following two bankruptcies, the carmaker founds the Ford Motor Company and is quite successful with his Model A. It’s now 1908 and a new era is dawning. Until then, owning a car was reserved only for the rich, but Ford decides to make the car accessible to the masses and introduces the Model T Ford. This becomes very successful when, in 1910, he moves the Ford factory to a new place where he has the space to realize his brilliant creation: the assembly line. It is the first in history.

His continuous-production line greatly shortens assembly times for the Model T, allowing him to dramatically reduce the price from $950 to $680 dollars (the assembly line was also “responsible” for the famous quote, “A customer can have a car painted any color that he wants, so long as it’s black,” as this was the only paint available that dried fast enough for the new production speed). Ford knows how to continuously optimize his manufacturing processes, giving him a decades-long cost advantage over the competition. During World War II, the United States war effort benefits tremendously from this process, quickly scaling-up production of ammunition, weapons, and equipment to previously unimaginable levels.

Idea 6: The PDCA Cycle

The same US government sends the professor and statistician W. Edwards Deming, in 1950, to Japan as a quality-management advisor to help with the country’s postwar reconstruction. Deming’s premise is that improving quality leads to a reduction in spending and an increase in productivity and market share. His work is inspired by the physicist Walter Shewhart who, in 1939, developed the first fully scientific approach to process improvement. The Shewhart Cycle has three distinct steps: specification, production, and inspection. While in Japan, Deming develops this into what we now know as the Plan–Do–Check–Act cycle (PDCA) or the Deming Wheel. The cycle now has four steps, as follows:

1. Plan: Establishing improvement goals and the processes to achieve them.
2. Do: Implementing processes and measuring the output and results.
3. Check: Comparing the actual and expected results, and looking for discrepancies between planned and actual implementation of the processes.
4. Act: On the basis of insight gained, determining whether the approach outlined in the Plan-phase was an improvement over the previous approach (aka the standard or baseline). If so, then this becomes the new standard; if not, then the current baseline is kept. In both cases, there is still something to learn, which means that you can start a new iteration of the PDCA cycle.

A unique feature of the PDCA cycle is that it can facilitate both major breakthroughs and frequent small improvements. Deming was convinced that what is not measured is not managed, let alone able be improved. He was always seeking a factual basis for decisions. His motto was: “In God we trust; all others bring data.”

Idea 7: Toyota Production System (Lean)

What country, in your opinion, produces the best-quality cars overall? Chances are your first thought is Germany. Understandable, with all those expensive premium brands like BMW, Audi, and Mercedes. But it is Japan. Every year, organizations such as the Consumers’ Association, the Dutch ANWB, British AA and RAC, and the USA’s AAA compile data on millions of cars, to establish their monthly costs for maintenance and repair, and then compare these costs with the list price, age of the car, and the mileage. This totally objective scoring system has, for many years, shown that Japanese brands such as Honda, Nissan, and Mazda are by far the best. Toyota even stands head and shoulders above the other Japanese brands.

Toyota Motor Corporation is founded just before the Second World War, but struggles well into the fifties with the problem that weak homeland demand forces them to produce many different models in small numbers. The successful American production approach originated by Ford, focusing on large numbers and efficiency, isn’t applicable: Toyota needs a highly flexible production system. At the same time, founder Kiichiro Toyoda’s vision is to build the best cars in the world. His production chief Taiichi Ohno is inspired by the way American supermarkets allow customers to pick the products they want from the shelves and then, based on the quantities sold, buy new stock. Together, Toyoda and Ohno develop a management philosophy that focuses on creating value by achieving the lowest cost, highest quality, and shortest lead times. Central to this is kaizen, a continuous-improvement approach based on Deming’s PDCA cycle. Around this core, they create a profound culture, which makes use of a very large set of instruments such as teamwork, waste reduction, just-in-time, and jidoka (quality control).⁴ They cleverly structure the daily work of managers and employees around these methods, so that they are constantly making small improvements in their work processes. Although this costs little time and effort, the long-term cumulative benefits are considerable.

This makes Toyota very successful, yet the company is modest about its achievements. Eventually, it grows into the largest car manufacturer in the world, with the highest brand value and, as we’ve already seen, the highest quality.

Their success, of course, did not go unnoticed by western car manufacturers. In the early eighties, the Toyota Production System is translated into a western approach, known as Lean. The success of Lean sees it applied in the production processes of other sectors and, gradually, it finds its way into the “soft” sectors such as services.⁵

Idea 8: OODA Cycle

We’ve seen, from the Churchill story, that agile management learned valuable insights from warfare. In the seventies and eighties, we see something similar occurring in the US military, in the person of John Boyd. Boyd was an Air Force pilot who, around the fifties, flew missions in Korea. After his active service, he was appointed head of the education section of the USAF Weapons School, for which he authors its tactical manuals. Soon he gets the nickname Forty Second Boyd because he dares to bet every fighter pilot that, as their instructor and starting at a disadvantage, he can beat every opponent within forty seconds.

Over the years, he becomes fascinated by the theories behind air-to-air tactics. He is so passionate that his nickname slowly changes to the Mad Major (other nicknames circulating are Genghis John—because of his confrontational style of debate—and the Ghetto Colonel because of his spartan lifestyle.) We can assume he wasn’t boring. Boyd immerses himself over a long period in military history: he examines guerrilla warfare and Hitler’s blitzkrieg; the tactics of Clausewitz and the Romans, and even goes as far back as the 6^th Century BC to Sun Tzu. He studies philosophy, history, and science and what we now know as chaos and complexity theory. He also develops mathematical models for simulating combat situations and is able predict the results of alternative tactics. On this basis, he formulates his energy-maneuverability theory.

His outspoken nature has made him many enemies in his immediate vicinity (most instructors in the elite Top Gun program, for example, would have been happy to see him dead.) However, successive US Secretaries of Defence are impressed by his theories, in particular for the development of new combat jets. Boyd makes a transition to the ministry and his theories are the basis for the new F-16 fighter. In the early nineties, he is even the architect behind the plans for Operation Desert Storm in Iraq.

But what vision was the foundation for his theories? On the basis of all his study, Boyd concluded that the key to victory lies in the ability to create situations in which a person or organization can make and execute the right decisions faster than the enemy. So everything revolves around responsiveness and speed of decision-making. The fastest pilot will win because his opponent is responding to a situation that has already changed. In the case of the F-16, Boyd wanted to build a fast, short, highly maneuverable combat fighter with superb all-round visibility from the cockpit, and quick-to-read instruments. To this end, he develops an aircraft that is very light, has a flexible and responsive engine, and is also the first to provide graphical cockpit-displays, fly-by-wire operation, and a canopy without metal frames offering seamless vision.

All this allows the pilot to continuously apply Boyd’s OODA decision-making loop with maximum speed and quality. Boyd argues that all intelligent organisms and organizations undergo a continuous process of interaction with their environment. He describes this on the basis of four connected and overlapping steps, each passing seamlessly into the next

1. Observation: Data collection through the senses.
2. Orientation: The synthesis and analysis of data in order to form the current mental perspective.
3. Decision: Choosing an approach from the current mental perspective.
4. Action: The output of the approach.

Boyd’s position was that this cycle is central to adaptivity and is crucial for survival and, in this case, in a much shorter timescale than Darwin thought. He believed that organizations such as companies or governments should have a hierarchy of OODA cycles: strategic, tactical, and operational. This would necessitate an optimally decentralized decision-making structure, one based on goal-oriented commands rather than action-driven (achieve this, in place of do this), to maximize the intellectual capacity and creative ability of employees. The latter is also known as Power to the Edge and aims to dynamically synchronize operations within organizations, in order to achieve maximum agility and optimize decision-making processes in a network organizational structure.

To achieve organizational goals, Boyd also suggested a combination of four main success factors: variation, speed, harmony, and initiative. He meant the following:

• Variation: The flexibility to easily switch from one operation to another, or to perform multiple actions simultaneously if necessary.
• Speed: The ability to respond quickly and to increase or decrease this speed as needed.
• Harmony: The competence to allow actions appropriate to the circumstances, and speed of developments, so that these actions positively influence each other in their development (co-evolve).
• Initiative: The willingness to assume leadership and take action to identify problems at the right time and resolve them.⁶

In short, Boyd’s insights are fundamental to achieving agility.

Idea 9: The Spiral Model

In 1986 and 1988, Professor Barry Boehm publishes two papers which have a huge impact on the future of software development. As we saw in section 3.1, Boehm had discovered that it is most effective, in the development process, to make as many errors as possible (or to prevent them), as often as possible, and as early as possible, after the start of the process. This minimizes the need to fix problems at a later time, so the total failure, prevention, and repair costs are kept to a minimum. Boehm notes that the traditional waterfall method in which prolonged, static phases of design, construction, and testing occur individually and chronologically does not deliver optimal efficiency.

In order to put his insight into practice, he develops his Spiral Model, which he presents in an academic paper. Central to his model is an iterative process of prototyping, consisting of four steps:

1. Setting goals
2. Identifying and eliminating risks
3. Developing and testing
4. Planning the next iteration.

Via these four iterative steps, the prototype and related activities are refined until the final version of the software can de detailed and implemented. Boehm assumes, therefore, that certain important conditions are fulfilled. First, there must be enough time for all the iterations to complete. He also attaches great importance to the requirements. These must be agreed in advance and meet the expectations of the customer, after which they should change minimally, if at all. Additionally, the developers must have a common picture of the architecture that will meet the requirements. In essence, all of this comes together in the idea that the software must be developed and delivered in the smallest functioning parts possible.

In the decade after the launch of Boehm’s approach, software development will change fundamentally. This approach is, therefore, also another foundation stone for future agile development.

Idea 10: Agile Development

In a meeting in 2001, a group of seventeen software developers, calling themselves the Agile Alliance, create a manifesto based on ideas that have been around since the late nineties. These ideas are a reaction to the traditional “waterfall” or “cascade” methods, which developers experience as bureaucratic, slow, ineffective, and hindering creativity. The manifesto covers several agile movements such as Scrum, Kanban, Extreme Programming, Adaptive Software Development, Dynamic Systems Development Method, Crystal, Feature-Driven Development, Pragmatic Programming, and Lean Software Development.

The purpose of the group is to create a development process that can adapt quickly to changing realities, such as the wishes of a client. In addition, the aim is to deliver software in the smallest possible working parts, so that it can be quickly tested, improved, and extended. In this iterative, incremental, and adaptive way of working, we can see a very short-cycle variation of the PDCA learning process. The Manifesto for Agile Software Development 2001⁷ defines four values: that developers “prefer individuals and interactions over processes and tools, working software over comprehensive documentation, customer collaboration over contract negotiation, and responding to change over following a plan”.

On the basis of these four values, the developers also formulate a dozen principles that they want to apply in practice.

1. The highest priority is to satisfy the customer through early and continuous delivery of valuable software.
2. Welcome changing requirements, even late in development. Agile processes harness change for the customer’s competitive advantage.
3. Deliver working software frequently, from a couple of weeks to a couple of months, with a preference for the shorter timescale.
4. Business people and developers must work together daily throughout the project.
5. Build projects around motivated individuals. Give them the environment and support they need, and trust them to get the job done.
6. The most efficient and effective method of conveying information to and within a development team is face-to-face conversation.
7. Working software is the primary measure of progress.
8. Agile processes promote sustainable development. The sponsors, developers, and users should be able to maintain a constant pace indefinitely.
9. Continuous attention to technical excellence and good design enhances agility.
10. Simplicity—the art of maximizing the amount of work not done—is essential.
11. The best architectures, requirements, and designs emerge from self-organizing teams.
12. At regular intervals, the team reflects on how to become more effective, then tunes and adjusts its behavior accordingly.

Agile software development, and especially Scrum, has taken off and is now increasingly used, for example, in engineering, innovation, and marketing (there is even an agile marketing manifesto⁸). It also constitutes the most important pillar of the Lean Startup methodology.

Idea 11: Marginal Gains

In Section 5.2, we discussed the spectacular results Brailsford managed to achieve in British cycling with his “marginal gains” approach. This case shows the power of an investigative mentality combined with striving for continuous improvement. Many are convinced that change is only worthwhile if it results in a large, visible outcome, but Brailsford’s approach proves otherwise.

The crux of continuous improvement lies in the fact that if you make improvements in a process, the results do not simply add up, they multiply (this effect is called “potentiation”). And this occurs in three ways:

1. Within the actual improvement, through infinite iterations.

   For example, in aviation, the thickness of the paint on the fuselage and wings has been gradually reduced, making the aircraft lighter and therefore more fuel efficient.

2. Interaction between the improvements, because improvement in one part can lead to an improvement within another part (or process).

   Example: by developing more-economical engines, the aircraft needs to carry less fuel. This makes the aircraft lighter and, again, more economical, so that it needs to carry less fuel and so on.

3. Combining improvements.

   Example: by flying the lighter aircraft a little slower, fuel economy is improved.

Through these effects, rapid, small changes cause a large multiplication in improvements. Figure 6.2 shows how this leads to an exponentially-increasing accumulative result.

Figure 6.2 Repetition or combination of small improvements, resulting in strong growth performance

The top line in Figure 6.2 is based on improvement steps of 1 percent and, after 200 iterations/ factors/interactions, leads to an improvement of 632 percent (increasing the steps to just 2 percent, for example, massively accelerates improvement to 5,148 percent). Although 200 iterations might seem high, experience has shown that a large number of multiplications can be achieved very quickly.

Idea 12: Lean Startup

Lean Startup is a method for setting up new companies, presented in 2011 for the first time, by Eric Ries.⁹ Ries’s method combines two approaches: the first is agile development, for rapidly developing workable online concepts; the second is the customer discovery and validation approach of Steve Blank, where identifying customer needs and creating propositions that meet them are central. Blank’s approach is, in turn, largely based on the scientific method, which is used to test propositions with (potential) customers. Within Lean Startup, the PDCA cycle is again central, albeit in a slightly modified form. Ries calls this “validated learning” and therein uses the three steps of building, measuring, and learning. Just as in PDCA this is a continuous, iterative process, based on testing hypotheses and measuring the results in order to continue improving the propositions and the underlying business model.

The Lean Startup methodology has become very popular among technology start-ups in Silicon Valley and even has an international movement of discussion forums and events. Although Lean Startup focuses on online business, with some modifications, the method is also applicable to offline channels and tangible products. Even within governments, the method is being used successfully.

6.2 The Benefits of Agile Management

This short history shows that agile management is a way of working based on sound scientific evidence, wherein logic, experimentation, and measurement are crucial factors. Also, implementing agile management usually generates a sound business case. Unfortunately, at this time, the only “agile” studies published are in the context of software development. While one cannot simply project these onto wider applications of agile management, they do give an indication. The annual survey by Version One¹⁰ shows that organizations implementing Agile derived the following benefits:

• 87 percent adapted better to changing priorities
• 84 percent saw higher team productivity
• 79 percent observed higher team motivation
• 78 percent noted higher work quality
• 77 percent realized shorter time-to-market
• 75 percent saw better alignment between IT and business.

Based on various studies on the deployment of agile, experts assume that the ratio of investment to outcome is, at the very least, 1:10, and that this result is not only achieved at the end of the deployment, but gradually, right from the start. In addition to the advantages listed above, organizations also benefit from greater agility, higher added value, better predictability and control over results, and increased customer satisfaction. It is not about efficiency, but about efficacy: the flow-speed in the value chain. Value flow, delivery speed, and customer satisfaction are also important indicators for measuring your organization’s agility.¹¹

Now that you understand the origins of agility and what it can deliver, it is high time we defined exactly what agile management is and what it is not. This is the subject of Chapter 7.

By reading this chapter, you’ll have discovered the following:

•  Agility is important for organizations that want to perform optimally in the future. Toyota’s huge success is a very clear example.

•  Agile management is not a hype that has rapidly emerged and will disappear just as rapidly. It is based on principles from four centuries ago and has been refined from many different perspectives. It is, therefore, firmly grounded in science and practice.

•  Research in the context of IT strongly suggests that implementing agile management will yield a high return on investment.

References

1.  Moen, R., and C. Norman. (1990). Evolution of the PDCA Cycle.

2.  de Groot, A. D. (1994). Methodology; Foundations of Research and Thinking in the Behavioral Sciences. Assen: Van Gorcum.

3.  Anderson, C. (2004). “The Long Tail.” Wired Magazine.

4.  Liker, J. K. (2004). The Toyota Way. New York: McGraw-Hill.

5.  Womack, J. P., and D. T. Jones. (2003). Lean Thinking. London: Simon & Schuster.

6.  Hammond, G. T. (2012). On the Making of History: John Boyd. The Harmon Memorial lecture. US Air Force Academy.

7.  See agilemanifesto.org

8.  See agilemarketingmanifesto.org

9.  Ries, E. (2011). The Lean Startup. New York: Crown Publishing.

10. Version One. (2014). 9th Annual State of Agile Survey. Version One.

11. Solingen, R., and R. van Lanen. (2013). Scrum for Managers. Academic Service.