Over time, at Azvai, we have solidified our approach to systemic innovation through “Non-Dualistic Thinking.”
In this philosophy, we recognize the importance of addressing the complexity of contemporary problems from a perspective that promotes collaboration, adaptability, and collectivity.
For innovation to be able to address complex systems, it cannot be solely based on ideas of separation (typically breaking down problems into pieces and considering the whole as equal to the sum of its parts).
On the contrary, the innovation process must be accompanied by integrative methodologies that consider the system as a whole, with emergent properties that do not exist when the parts are analyzed separately.
Communities of Practice
A Community of Practice consists of a group of people who regularly gather to address a common topic or concern, with a set of objectives, both individual and collective.
Communities of Practice are groups that self-organize and learn through the practices they engage in.
In addressing complex problems, solutions based on hierarchy (top-down) often lack the knowledge of the ground reality and do not possess the flexibility and agility to effectively adapt and solve problems.
However, if the conditions are fostered and facilitated for these groups to emerge and self-organize, without being obsessed with control, the solutions will be adaptive, and the organization’s knowledge will be better distributed at all levels.
Examples of Communities of Practice
A classic example of this in the industrial context is “continuous improvement circles.” These circles promote the self-organization of workers, granting them autonomy to solve their problems and learn collectively.
Outside the business sphere, Communities of Practice often emerge in the form of associations around common concerns (such as the environment or equality) or passions like sports or art.
At Azvai, we believe that to innovate systemically, which means solving complex problems, it is essential to set aside egos and facilitate solutions and innovation to emerge from the communities closest to these problems.
Action Research: Active Learning
Action research is a research methodology that seeks transformative change through the simultaneous process of researching and taking action. It is based on the idea that in studying social problems, the researcher can hardly avoid being a fully objective observer; instead, the researcher becomes part of the system being investigated.
Being aware of this fact opens up opportunities for research not only to generate knowledge but also to drive transformation.
System Mapping: Visualizing Complexity
System mapping is a tool that allows us to visualize and understand the complexity of a system.
By graphically representing the relationships and interconnections between the elements of a system, we can identify points of intervention and critical areas for innovation.
System mapping is a fundamental tool for comprehending complexity and effectively addressing it.
Traditional Tools and Their Relevance
While we advocate for systemic innovation, we acknowledge the relevance of traditional tools, which have their role in the innovation process.
In the process of systemic innovation, qualitative and quantitative tools must be combined.
For example, the innovation process can begin with a qualitative mapping of the system, followed by quantitative analysis, defining communities of practice that delve into specific aspects of the system, and using the Design Thinking methodology to develop a particular solution within the system.
Lean Startup / Design Thinking: Contemporary Innovation
These methodologies promote creativity and constant iteration to develop innovative solutions. The fundamental idea is to minimize the cycles of design, production, and feedback to avoid wasting resources on actions not aligned with the desired goal.
While these tools can be highly effective in finding innovative business models or solutions that meet specific needs, their focus on measurable results alone means they are not sufficient to solve complex problems.
Structured Problem Solving
Structured problem solving is a systematic approach to addressing and solving difficult problems methodically and organized. It involves breaking down a problem into its essential elements, analyzing the root causes of the problems, and developing effective solutions.
The key elements of structured problem solving typically include:
- Problem Identification: Clearly defining the problem or challenge at hand. This step involves understanding the scope, impact, and any associated constraints.
- Root Cause Analysis: Investigating the underlying causes of the problem to identify what is contributing to it. Techniques such as the “5 Whys” method are employed to delve into root causes.
- Data Gathering: Collecting relevant data and information to support the analysis and decision-making process. This may involve quantitative and qualitative data collection methods.
- Brainstorming: Generating a set of possible solutions to address the problem. This step fosters creativity and divergent thinking.
- Solution Evaluation: Assessing the feasibility, effectiveness, and potential risks of each possible solution. Cost-benefit analysis or other decision-making criteria may be applied.
- Implementation Planning: Developing a detailed plan to implement the chosen solution. This includes identifying responsible parties, setting timelines, and allocating resources.
- Monitoring and Feedback: Continuously tracking the progress of solution implementation and collecting feedback to make necessary adjustments.
- Documentation: Maintaining records of the entire problem-solving process, including problem statement, analysis, chosen solution, and outcomes.
Structured problem solving is a valuable approach in various fields, including business, engineering, healthcare, and many others. It helps organizations and individuals make informed decisions, improve processes, and efficiently solve problems. Popular problem-solving methodologies such as Six Sigma, Lean, and the Plan-Do-Check-Act (PDCA) cycle fall under this category.
However, just like the previously mentioned methodologies, these are very potent and effective in addressing technically difficult or very challenging problems, but on their own, they are not sufficient to address complex problems. The fundamental reason is that by breaking down the problem into pieces, this methodology loses information about the emergent properties of these systems.
In conclusion, through the adoption of “Non-Dualistic Thinking” and the implementation of innovative methodologies such as Communities of Practice, action research, system mapping, and traditional tools, Azvai has established a solid foundation for addressing the challenges of systemic innovation. We recognize the importance of treating complex systems as integrated wholes rather than breaking them into separate parts. This approach promotes collaboration, adaptability, and collectivity as central elements in solving complex problems.
We also value the involvement of communities closest to the problems and understand that innovation must emerge from the grassroots. Communities of Practice and action research enable solutions to be adapted, and knowledge to be better distributed at all levels of the organization.
We also acknowledge the relevance of traditional tools such as Lean Startup and Design Thinking, but we understand that, on their own, they are not sufficient to address complex problems. It is necessary to combine qualitative and quantitative tools and apply a structured approach to solving complex problems. Structured problem solving, with elements such as identifying root causes and data collection, is a valuable tool in various fields.