The document discusses key concepts in systems thinking and agile practices. It provides an overview of systems thinking principles like interconnectedness, synthesis, emergence, feedback loops and causality. It also describes the iceberg model in systems thinking which looks at events, trends, structures and mental models. The document then discusses value chain analysis and its use in understanding how activities within an organization add value. It outlines the value chain for software development and discusses capability optimization using the Capability Maturity Model. Finally, it covers the evolution and core values of agile methodology and lists the twelve principles of the Agile Manifesto.

1. Agile Practices
and Design
Thinking
PRODUCT DEVELOPMENT METHODOLOGY

2. System Thinking
Systems thinking is a new approach to analysis where the entire system with all its
components is considered as a whole instead of the traditional approach. The traditional
approach to problem solving considers the components as separate parts of a system and
assesses them in isolation.
Systems thinking concerns exploring the interactions and interdependencies between the
different components and elements of the whole system. It encourages us to study the
interrelationships, the boundaries and perspectives that evolve within these components
Systems thinking was defined differently by each expert. Barry Richmond called it art &
science, whereas Peter Senge called it a language to describe understanding between each
part.

3. System Thinking Principles

4. System Thinking Principles
• Interconnectedness: Systems thinking leads to a shift in mindset from linear to circular and this is driven by the notion that
everything is connected. Effectively everything in our environment is reliant upon something or the other for survival. In this
mindset, one can look at everything from a dynamic, interconnected array of relationships and feedback loops.
• Synthesis: This refers to a combination one of more components to offer something new. When two different components come
together, the derived benefit is much more than a sum of its parts.
• Emergence: From a systems perspective, emergence is what comes from the interaction of two components. It basically
occurs due to synergy between two components.
• Feedback loops: In a completed interdependent system, there is constant flow of information and feedback loop. Feedback can
be classified into reinforcing and balancing.
• Causality: Causality in system is about getting an understanding feedback loops and observing what happens as a results of
two components interacting with each other.
• Systems Mapping: Systems mapping a key tool used. It is used to map and connect the different elements within a system.

5. The Iceberg Model in Systems Thinking

6. The Iceberg Model in Systems Thinking
The Iceberg model is influenced by all the surrounding process. Focusing on root issues and fire fighting for long term mistakes. We all
know that in an iceberg, 90% of the mass remain inside and only 10% is visible outside. This is true of an organization too and Goodman
explains this using his Iceberg Model and addressing it one layer at a time. These layers are:
Events: This refers to how we perceive the world. These are the everyday events that we take for granted. For example, we wake up
and realize your health is not keeping up and immediately you can medication to tackle it. Similarly at an organization level too, you do a
simple readjustment to ensure this is taken care of but the Iceberg believes that one does not assume this readjustment can always fix
the issue.
Trends: Looking further down events, will show us trends. One may notice that an event was not just a random occurrence and on days
you’ve rested less it has affected your health. Looking for patterns or trends helps us forecast events
Structure: Below the trends, we can observe the structures that are causing these trends. Excessive pressure at work or personal life,
lack of good food, lack of a good support system can lead to these events. Professor John Kerber explains that structures can be
physical things (terrain, daily used objects), organizational (workplace, school), policies (law, rules, tax structures), ritual(habitual
behavior).
Models: Models here refers to mental models that we have developed over time. Our attitudes, beliefs, moral values, expectations, that
have been influenced by the upbringing, the environment you grow up in etc. which subconsciously impact us and we are completely
unaware of. This influences our work and thought process

7. Value Chain Analysis:
Michael Porter conceptualized the idea of value chain analysis in 1980, as a tool to
understand the competitive advantage of a business. This is a model that helps companies
understand their offerings and how it adds value to its customers. It gives companies an
understanding of how they can sell their products for a particular value and thereby
generating a profit margin

8. Value Chain Analysis
Michael Porter proposed that all the activities within an organization should be run at an
optimum to gain competitive advantage

9. Value Chain Analysis

10. Value Chain Analysis - Advantages
The primary advantage of value chain analysis is to devise a strategy to be competitive. Other
advantages are:
 It helps companies stay out of the “No Profit Zone”.
 It presents companies with an opportunity for integration.
 It helps understanding the activities and its effect on the cost and performance on one
another.
 It helps in aligning the spending and design suitable processes.

11. Value Chain for Software Development

12. Capability Optimization
Is the expansion of the capability of a system to realize the best in class performance of a
system.
Helps organizations to streamline the organizational processes to boost productivity and
encourage risk taking in development of software and services.
The Capability Maturity Model was developed to assess and streamline processes is highly
implemented across industries

13. Capability Maturity Model (CMM)
CMM for software was originally developed in 1980’s at Carenegie Mellon University to offer guidance to improve
software development process. CMM categorizes the software development process into following five phases:
1. Adhoc level: This is the initial level where there is very poor control and the expected results are not achieved in
terms of time.
2. Repeatable level: This level the basic controls are in place and the results are more consistent in terms of
schedule, time and quality.
3. Defined level: At this level, the organization understands and adapts the established software engineering
principles and practiced organization wide
4. Managed level: The defined elements from the defined level are instrumented so that the next level, optimized
level can be achieved.
5. Optimization level: This level is practiced in organizations where software development process is practiced as a
routine activity and only the events that are not performing at optimum are fixed

14. Agile Methodology - Evolution

15. Birth of Agile

16. Core values of Agile

17. Twelve Principles of the Agile Manifesto
1.Our highest priority is to satisfy the customer through an early and continuous delivery of valuable software
2. Welcome changing requirements, even late in the 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 to 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 a 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 behaviour accordingly