The Ackoff Center Weblog provides an opportunity to keep up with the latest research in Systems Thinking. It is also a forum where you can interact with others in the field and share your own experiences.
July 31, 2022
Susanne Kaiser on DDD, Wardley Mapping, & Team Topologies
"Wes Reisz: Great. There's so many things that are in software. What made you decide to bring these three things together to kind of a story?
Susanne Kaiser: Yes. So for me, the combination of Wardley Mapping, Domain-Driven Design and team topologies evolved naturally over time, but it was at its core driven by system thinking. So, Dr. Russell Ackoff, one of the pioneers of the system thinking movement, he stated that a system is more than the sum of its parts. It's a product of their interaction. So the way parts fit together, that determines the performance of system, not on how they perform taken separately. So, and when we are building systems in general, we are faced with the challenges of building the right thing and building the thing right. Right? And building the right thing addresses effectiveness, and addresses questions such as how aligned is our solution to the users and business needs. Are we creating value for our customers? Have we understood the problem and do we share a common understanding and building the thing right?
Focuses on efficiencies, for example, efficiency of engineering practices, and it's not only crucial to generate value, but also being able to deliver that value. How fast can we deliver changes, and how fast and easy can we make a change effective and adapt to new circumstances. So, the one doesn't go without the other, but as Dr. Russell Ackoff pointed out doing the wrong thing right is not nearly as good as doing the right thing wrong. So, by considering the whole, and having effectiveness and efficiency in mind to build the right thing right, that we need a kind of like holistic perspective to build adaptive systems. One approach out of many is combining these three perspectives of business strategy with Wardley Mapping, software architecture, and design was Domain-Driven Design, and team organization was team topologies. So, in order to build and design and evolve adaptive socio-technical systems that are optimized for fast flow of change."
“Systems Thinking” announced as 2022-2023 Common Experience theme
The Common Experience at Texas State University has announced that the 2022-2023 theme will be "Systems Thinking." Texas State presents an engaging academic theme each year, providing numerous opportunities for everyone — students, faculty, staff, and community members. Systems Thinking was chosen as the Common Experience theme for 2022-2023 because students are made of, surrounded by, and embedded in systems from the moment they enter the world. When they choose to attend Texas State, they choose to insert themselves into one of the most impactful systems of their lives — one that will allow them to change the world. When one understands a system, one can better navigate it. When one can navigate a system, one can advocate for change. As part of the Common Experience, all incoming first-year students receive a critically acclaimed book related to the year’s theme. Students discuss the book in their University Seminar class and other courses. The 2022-2023 Common Reading book is Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy by Cathy O'Neil. First-year students will receive a free copy during Bobcat Welcome Week. The Common Experience team encourages and welcomes interdisciplinary collaboration. To discuss the theme, events, and activities planned for the 2022-2023 academic year, contact (512) 245-3579 or [email protected].
I inquire about the meaning of education in our fast-changing world.
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Primary school students enjoy discovering interdependencies in the world around them.
getty
We live in a world of complex, interconnected systems. They range from big corporations and the Earth’s biosphere to social networks and our own bodies. Complex systems have many components that interact with each other in dynamic patterns. They chug along quietly and uneventfully until, one day, they unexpectedly turn our world upside down. Hurricanes and pandemics, elections and market crashes - all inevitable products of complex systems - ceaselessly remind us of our limited understanding of the world. What’s missing is the ability to notice and comprehend the counterintuitive nature of complex systems. This ability, called “systems thinking,” is recognized by educators, scientists and entrepreneurs as one of the most valuable skills for the 21st century.
The concept of systems thinking was introduced several decades ago by the late Jay Forrester of the MIT Sloan School of Management, who founded the field of systems dynamics to describe economic behavior and advance management education. Forrester recognized that systems thinking could, and should, be taught to students starting at an early age. Dr. Tracy Benson, the President and CEO of the Waters Center for Systems Thinking and one of the international leaders in the field of systems thinking education, is helping to implement Forrester’s vision. The Waters Center provides training in habits, strategies, and tools of systems thinking to educators and entrepreneurs around the world.
A recent longitudinal study conducted by the Waters Center explored the benefits of systems thinking in schools. The study found that systems thinking helped students connect their learning to real-world problems, improve their decision-making, and consider the unintended consequences of their choices. Likewise, a framework for K-12 Science Education developed by the National Academy of Sciences recommends the incorporation of concepts such as “stability and change” and “systems models” into the science syllabus. The framework, which informs state-level educational decisions, draws on the most recent scientific research on the best ways for students to learn science. However, systems thinking has yet to become a backbone for a modern school curriculum.
In the UK, the supposed panacea of good management has proved to be a chimera. The country has been training managers in the discipline of managing for decades, but very little good has come of it.
If one looks at the public and private sector one sees more bureaucracy, greater intensification of work in which fewer people have to cope with downsized operations to deliver greater shareholder value, while the public sector is not improving in spite of huge cash injections and the UK falls behind Germany, the US and France in productivity.
According to the National Audit Office, the public sector in the UK spent £7 billion on consultancy in the past three years to little effect.
Management itself has become the problem. The reason for the failure is complex. In a nutshell, it is because the UK has been following the wrong way of doing things and constantly trying to get it right. But as the systems and management theorist Russell Ackoff said: "The righter we do the wrong thing, the wronger we become. When we make a mistake doing the wrong thing and correct it, we become wronger. When we make a mistake doing the right thing and correct it, we become righter. Therefore, it is better to do the right thing wrong than the wrong thing right."
The wrong thing managers have been doing is central planning, a command-and-control management model reminiscent of the Soviet Union. On top of this essential wrongness are a host of service companies and consultancies from IT to PR who reinforce the model with their own additions and refinements.
It’s not an accident that data is the bedrock of the Data, Information, Knowledge, Wisdom (DIKW) pyramid made famous by Russell Ackoff in 1989. That expresses the shared conviction that data are the basic foundation on which all knowledge is built.
Except that’s not how data and knowledge work. It’s not even that there’s a more fundamental layer beneath data. Rather, the very shape of the pyramid reinforces a paradigm that has outlived its purpose. A pyramid is too stable, too linear, and way too one-way in its direction. It’s an Industrial Age model in which raw materials—data—are refined and transformed into a usable product.
In an age in which data is increasing exponentially, and our new technology, especially machine learning, can’t get enough of it, we need to flip the pyramid. Then we need to thoroughly rethink what data is, the context we want to use it in, and how to get the most value from it.
In the old DIKW pyramid, the line between data and information is actually a warehouse—another remnant of the Industrial Age. Data warehouses have served businesses’ predictable needs since the 1950s when the modern idea of data became prevalent in business.
Under this old definition, data are atomic elements of knowledge, siloed according to the department and application that developed them and tagged with metadata that reflected how that data was anticipated to be useful. The value extracted from them after they were delivered was likely to be forever lost
How Dynamic Conservatism Leads to Diversity Dodges
Aware of the ways in which organizations defend themselves against change that threatens their social structures, philosopher and social theorist Donald Schön noted that organizations will “fight like mad to stay the same.”5 Schön introduced the concept of dynamic conservatism to explain seemingly irrational responses by organizations to change and uncertainty, noting that great ideas that can reshape an industry or organization are almost always resisted because they upset the social hierarchy within the system. Systems thinker Russell Ackoff, a friend and colleague of Schön’s, was fond of saying that managers in organizations were rewarded for maintaining the status quo.
Schön further hypothesized that organizations resist change in proportion to its magnitude. Thus, it can be predicted that an organization that undertakes a major change, like hiring many more Black executives, will energetically resist those efforts with multiple defenses. Schön’s concept of dynamic conservatism argues that organizations make token changes in order to ward off substantive ones. This argument is especially relevant today — and the basis of the dodges that we delineate below. Here we seek to show how dynamic conservatism manifests by examining four ways that organizations avoid making substantive improvements or commitments to executive diversity — the recruitment, retention, mentoring, career development, pay equity, and promotion of Black people in senior positions.
“Managers do not solve problems,” the late University of Pennsylvania systems theorist Russell Ackoff famously said, “they manage messes.” Messes emerge because it is difficult to decipher the interconnections between and among business units and the external environment. And messes are difficult to manage because it is hard to save what is valuable without causing damage.
The systems thinker’s first task is to understand the nature of the interconnections. Take, for example, rapid and frequent changes in technology. These have implications for an organization’s human-resources policies—who should be hired, how they should be trained and managed, etc. Technological change also forces the organization to evaluate its structure and work practices: Should it have a flatter or steeper hierarchy? Should employees be given substantial autonomy? And so on.
The systems thinker’s second task is to match distinct business processes to activity within the company and to set policy directives on how every unit and activity initiates and responds to change.
The systems thinker aims to see the forest as well as the trees, looking beyond the first-order effects of changes to anticipate the size and magnitude of subsequent opportunities and constraints. He then designs a response system so that if it were to fail, it would do so in noncritical ways before failing in catastrophic ones—the engineering principle of “leak-before-break.”
The systems thinker is acutely aware that feedback loops mean that success begets success and failure begets failure. The 1980 IBM-Microsoft agreement illustrates this principle. That year, IBM asked Bill Gates and his fledgling startup, Microsoft, to develop an operating system for IBM’s new personal computer. The first part of the deal that Gates structured was standard: IBM would have to pay Microsoft a development fee of $200,000 and as much as $500,000 for incremental development work. The second part of the deal is noteworthy for Gates’s recognition of feedback effects. He gave IBM the rights to use the Microsoft operating system and several related products for no additional fees, on the condition that Microsoft had exclusive rights to license the system and related software to other manufacturers.
Why did Gates introduce this second element? In their book, The Business of Platforms, MIT’s Michael A. Cusumano, University of Surrey’s Annabelle Gawer, and Harvard’s David B. Yoffie note that Gates was aware of a growing “clone” industry and calculated that exclusive licensing could be very valuable if the market for personal computers took off. And indeed it did: an entire ecosystem of hardware and software developers emerged during the 1980s and ’90s centered around Microsoft’s operating system, which drove the company’s revenues from $16 million in 1981 to $19 billion by 1999.
The systems thinker is acutely aware that feedback loops mean that success begets success and failure begets failure. The 1980 IBM-Microsoft agreement illustrates this principle. That year, IBM asked Bill Gates and his fledgling startup, Microsoft, to develop an operating system for IBM’s new personal computer. The first part of the deal that Gates structured was standard: IBM would have to pay Microsoft a development fee of $200,000 and as much as $500,000 for incremental development work. The second part of the deal is noteworthy for Gates’s recognition of feedback effects. He gave IBM the rights to use the Microsoft operating system and several related products for no additional fees, on the condition that Microsoft had exclusive rights to license the system and related software to other manufacturers.
Why did Gates introduce this second element? In their book, The Business of Platforms, MIT’s Michael A. Cusumano, University of Surrey’s Annabelle Gawer, and Harvard’s David B. Yoffie note that Gates was aware of a growing “clone” industry and calculated that exclusive licensing could be very valuable if the market for personal computers took off. And indeed, it did: an entire ecosystem of hardware and software developers emerged during the 1980s and ’90s centered around Microsoft’s operating system, which drove the company’s revenues from $16 million in 1981 to $19 billion by 1999.
Reframing social and global problems could yield viable solutions to major issues such as climate change and gender inequality.
Being able to identify patterns in how people tend to frame problems underpins this approach.
Three such patterns include framing problems to avoid change, to blame individuals instead of the system, and to bypass "messy" realities.
Imagine you own an office building and your tenants are complaining that the elevator is way too slow. What do you do?
Faced with this problem, most people instinctively jump into solution mode. How can we make the elevator faster? Can we upgrade the motor? Tweak the algorithm? Do we need to buy a new elevator?
The speed of the elevator might be the wrong problem to focus on, however. Talk to an experienced landlord and they might offer you a more elegant solution: put up mirrors next to the elevator so people don’t notice the wait. Gazing lovingly at your own reflection tends to have that effect.
The mirror doesn’t make the elevator faster. It solves a different problem – that the wait is annoying.
Solve the right problem
The slow elevator story highlights an important truth, in that the way we frame a problem often determines which solutions we come up with. By shifting the way we see a problem, we can sometimes find better solutions.
Problem framing is of paramount importance when it comes to tackling the many hard challenges our societies face. And yet, we’re not terribly good at it. In a survey of 106 corporate leaders, 87% said their people waste significant resources solving the wrong problems. When we go to the doctor, we know very well that identifying the right problem is key. Too often, we fail to apply the same thinking to social and global problems.
Problem framing is of paramount importance when it comes to tackling the many hard challenges our societies face.
To solve big issues like climate change, we need to reframe our problems
World Economic Forum
July 19, 2021
Most of our social and global problems are multi-causal. The problem-solving scholar Russell L. Ackoff memorably used the term “messes” to describe real-world problems. But people often dislike complexity, preferring neat stories with a single, easily identifiable villain.
Take the case of gun deaths in the US. Advocates for gun ownership often use the “mental health” argument that guns don’t kill people, people do. On the other hand, people who dislike guns often see it as an access problem and call for a ban on all guns. Arguably, both of these framings are as simplistic as they are infeasible.
Contrast this with the approach described by the economist Paul Krugman in a recent New York Times column. He uses the car industry to reframe the gun debate. We fight automobile accidents through a broad suite of different interventions, which allows us to keep using our cars but in a safer way.
This approach calls for a portfolio of reasonable regulations that recognizes the political fact that many Americans want to keep their guns. This is a far stretch from the binary "access-or-mental-health" framing and, in our opinion, much more likely to create results.
In 1991, Harvard Business School professor Chris Argyris wrote, “Any company that aspires to succeed in the tougher business environment of the 1990s must first resolve a basic dilemma: Success in the marketplace increasingly depends on learning, yet most people don’t know how to learn.”1 Fast-forward 30 years and swap in “the 2020s,” and these words likely ring true for many executives today.
To be clear, learning is as high a priority as ever for corporate leaders. Before the pandemic, learning and development (L&D) efforts aimed at reskilling and upskilling workforces ranked among global CEOs’ top concerns. COVID-19 has accelerated existing trends in remote work and automation and shined a spotlight on digital skills gaps in organizations.
Despite concern at the top and significant investments in training each year, many organizations are failing to meet employees’ learning needs.2 Gallup data shows that only 4 in 10 employees strongly agree that they have opportunities at work to learn and grow.3
So where do things go wrong?
For Argyris, the learning dilemma demonstrated that organizations make two critical mistakes: First, they define learning too narrowly, and second, they fail to reflect on how internal behaviors and thought patterns block effective learning.
Over the past year, L&D teams have had to pivot quickly and reshuffle priorities in order to meet the needs of remote workforces, from moving in-person learning models online to thinking beyond a focus on technical skills to the behavioral “human skills” at the core of virtual communication and collaboration. Along the way, companies are finding that some traditional systems of learning must shift to meet new needs.
