Maastricht University – Master Healthcare Policy, Innovation and Management 2016-2017
HPI4008 Strategic management, leadership and organization
Summary
Case 1 Complexity and system thinking
Traditional paradigms/approaches
System thinking
Complexity theory
Complex adaptive system
System thinking in healthcare systems
Chaos theory view of healthcare systems
System dynamic modelling
Case 2 Strategic management
Strategy
Types of strategies
Competitive advantage
Strategic management
External environment – Organizational theories
External environment – Healthcare markets
Internal environment – Value chain
Inter-organizational strategies
Mergers and acquisitions
Strategic alliances
Case 3 Organizational change
Organizations
Organizational temple
Organizational structure and culture
Profession and professionalism
Professional organizations
Bureaucracy
Change
Mechanisms that surface during change
Colour strategies
Process of change
Paradigms on change
Case 4 Leadership
Leadership and management
Leaders and managers
Leader characteristics
Theories on leadership
Leadership styles
Leadership and change
Leadership and organizational culture
Physician leadership
Policy and politics
, Case 1 Complexity and system thinking
Learning goals:
1. What are system thinking and system theory? How do they relate to complexity theory?
2. What are complex adaptive systems and what are their main characteristics?
3. How does system thinking contribute to the study of organisations?
4. How does system thinking inform (and advance) the understanding of healthcare systems?
5. How does system thinking apply to health care organisations (like VHA)?
6. How does system dynamic modelling help understand complex systems?
Key terms: System thinking approach vs traditional approach = Complexity theory vs other organizational
theories = Complex adaptive systems – characteristics = Loosely coupled vs tightly coupled systems = Non-
linearity/Chaos/unpredictability/randomness = Chaos statuses = System dynamic modelling – feedback loops
= Applications of system thinking to understand: Healthcare organizations and specifically hospitals;
Healthcare systems; Strategy formulation; Leadership; Organizational change.
Traditional paradigms/approaches
Theories can be related to different period of times (Johnson):
- The modernist philosophy and Newtonian (classical) science have led to understandings of
healthcare organizations as machines that should be well run, oiled and managed.
o Focus on information gathering, correct decision making, doing the right thing.
- The reductionist approach: Understand organizations, analysing pieces and fitting them
together, predicting future outcomes of managerial behaviour, and controlling the behaviour
of workers.
Those traditional paradigms have driven the clinical side of healthcare as physicians train to provide
the proper diagnosis and proper treatment. An alternative view is needed for today’s highly volatile
and ambiguous healthcare environment (Johnson).
System thinking
System thinking: A tool that allows key actors – from national policy-makers to ‘street-level’ policy
implementers – to map and measure their health system, to identify where some of the key
blockages and challenges lie, and to design sound, synergistic and system-ready interventions
targeting those weaknesses (de Savigny).
- An approach to problem solving that views ‘problems’ as a wider, dynamic system.
- Origins in the early 20th century in field, such as engineering, economics and ecology.
- It demands a deeper understanding of the linkages, relationships, interactions and
behaviours among the elements that characterize the entire system.
- Commonly used in sectors where interventions and systems are complex.
System thinking compared to system theory: System thinking, everything as a part, is the application
or implementation of the (overall) theory.
, Usual approach Systems thinking approach
Static thinking. Dynamic thinking.
Focus on particular events. Framing a problem in terms of a pattern of
behaviour over time.
Systems-as-effect thinking. Systems-as-cause thinking.
Viewing behaviour generated by a system as Placing responsibility for a behaviour on internal
driven by external forces. actors who manage the policies and ‘plumbing’
(doorgronden) of the system.
Tree-by-tree thinking. Forest thinking.
Believing that really knowing something means Believing that to know something requires
focusing on the details. understanding the context of relationships.
Factors thinking. Operational thinking.
Listing factors that influence or correlate with Concentrating on causality and understanding how
some result. a behaviour is generated.
Straight-line thinking. Loop thinking.
Viewing causality as running in one direction, Viewing causality as an on-going process, not a
ignoring (either deliberately or not) the one-time event, with effect feeding back to
interdependence and interaction between and influence the causes and the causes affecting each
among the causes. other.
Systems thinking elements (de Savigny):
- Systems organizing: Managing and leading a system. The types of rules that govern the
system and set direction, set prohibitions, and provide permissions.
- Systems networks: Understanding and managing system stakeholders. The web of all
involved in the system.
- Systems dynamics: Conceptually modelling and understanding dynamic change. Attempting
to conceptualize, model and understand dynamic change through analysing organizational
structure and how that influences behaviour of the system.
- Systems knowledge: Managing content and infrastructure for explicit and tacit knowledge.
The critical role of information flows in driving the system towards change, and using the
feedback chains of data, information and evidence for guiding decisions.
There are 8 common systems characteristics, which influence how systems respond to external
factors or to an intervention. Understanding the fundamental characteristics of systems is crucial to
seeing how they work (de Savigny).
- Self-organizing: System dynamics arise spontaneously from internal structure. The nature of
a system is not determined by an individual agent, but by the interaction among systems/the
system’s agents. Once we see the relationship between structure and behaviour, we can
begin to understand how systems work: system structure is the source of system behaviour.
- Constantly changing: Change is a constant in all sustainable systems. As systems are adaptive
rather than static, they have the ability to generate their own behaviour.
- Tightly linked: The high degree of connectivity means that change in one sub-system affects
the others. Anticipating positive and negative effects within a context of interconnection is
key to designing and evaluating an intervention over time.
- Governed by feedback: Systems are controlled by feedback loops that provide information
flows on the state of systems. The response may alter the intervention or expected effects.
, - Non-linear: Relationships within a system cannot be arranged along a simple input-output
line. System-level interventions are typically non-linear and unpredictable, with their effects
often disproportional or distantly related to the original intentions.
- History dependent: Short-term effects of intervening may differ from long-term effects.
Interventions designed to change people’s behaviour require measuring the intervention
effects over a longer period to avoid making incorrect conclusions of no or limited effects.
- Counter-intuitive: Cause and effect are often distant in time and space, defying solutions that
pit causes close to the effects they seek to address. Interventions may not work in all
settings. E.g. an intervention may increase utilization with the risk of overwhelming services
that were not strengthened in parallel.
- Resistant to change: With all those characteristics and the complexity of their many
interactions, it is sometimes difficult and delicate to develop a priori an effective policy
without a highly astute (scherpzinnig, slim) understanding of the system. System
characteristics can render (veranderen in) the system policy resistant, particularly when all of
the actors have their own (often competing) goals.
System thinking in organizations: In designing and evaluating system-level interventions or
interventions with system-wide effects, a comprehensive assessment of the main effects (intended
or not) and the contextual factors that may help explain the success or failure of the intervention are
essential (de Savigny).
Complexity theory
A different view/theory from the traditional approaches is postmodernism:
- Postmodernism: An umbrella term for a group of philosophical ideas that challenged the
assumptions of modernism and the resultant social and historical viewpoints. All models are
only partial descriptions of reality. Focus on the role of social construction (Johnson).
Complexity science: The study of complex systems and the phenomena of complexity and
emergence to which they give rise (Johnson).
- Observational-based science, for understanding a multitude of phenomenon from immune
systems and spread of diseases to ecosystems and social economic systems.
- Better understanding of:
o The uncertain nature of reality;
o The implications of that uncertainty for managerial action;
o The nature of relationships, which apparently is critical;
o By focusing on those relationships, new alternatives for management made
themselves apparent.
- The ontology and epistemologies are often compared with and linked to postmodernism.
The relation of complexity theory with system thinking: Postmodernism, or deconstructionism, is a
paradigm. Complexity theory is so too. Those thoughts or theories are used as a basis for a model.
For the complexity theory, a higher complexity comes with the line of system thinking. So, complexity
theory can be seen as a subset of system thinking (Johnson).
HPI4008 Strategic management, leadership and organization
Summary
Case 1 Complexity and system thinking
Traditional paradigms/approaches
System thinking
Complexity theory
Complex adaptive system
System thinking in healthcare systems
Chaos theory view of healthcare systems
System dynamic modelling
Case 2 Strategic management
Strategy
Types of strategies
Competitive advantage
Strategic management
External environment – Organizational theories
External environment – Healthcare markets
Internal environment – Value chain
Inter-organizational strategies
Mergers and acquisitions
Strategic alliances
Case 3 Organizational change
Organizations
Organizational temple
Organizational structure and culture
Profession and professionalism
Professional organizations
Bureaucracy
Change
Mechanisms that surface during change
Colour strategies
Process of change
Paradigms on change
Case 4 Leadership
Leadership and management
Leaders and managers
Leader characteristics
Theories on leadership
Leadership styles
Leadership and change
Leadership and organizational culture
Physician leadership
Policy and politics
, Case 1 Complexity and system thinking
Learning goals:
1. What are system thinking and system theory? How do they relate to complexity theory?
2. What are complex adaptive systems and what are their main characteristics?
3. How does system thinking contribute to the study of organisations?
4. How does system thinking inform (and advance) the understanding of healthcare systems?
5. How does system thinking apply to health care organisations (like VHA)?
6. How does system dynamic modelling help understand complex systems?
Key terms: System thinking approach vs traditional approach = Complexity theory vs other organizational
theories = Complex adaptive systems – characteristics = Loosely coupled vs tightly coupled systems = Non-
linearity/Chaos/unpredictability/randomness = Chaos statuses = System dynamic modelling – feedback loops
= Applications of system thinking to understand: Healthcare organizations and specifically hospitals;
Healthcare systems; Strategy formulation; Leadership; Organizational change.
Traditional paradigms/approaches
Theories can be related to different period of times (Johnson):
- The modernist philosophy and Newtonian (classical) science have led to understandings of
healthcare organizations as machines that should be well run, oiled and managed.
o Focus on information gathering, correct decision making, doing the right thing.
- The reductionist approach: Understand organizations, analysing pieces and fitting them
together, predicting future outcomes of managerial behaviour, and controlling the behaviour
of workers.
Those traditional paradigms have driven the clinical side of healthcare as physicians train to provide
the proper diagnosis and proper treatment. An alternative view is needed for today’s highly volatile
and ambiguous healthcare environment (Johnson).
System thinking
System thinking: A tool that allows key actors – from national policy-makers to ‘street-level’ policy
implementers – to map and measure their health system, to identify where some of the key
blockages and challenges lie, and to design sound, synergistic and system-ready interventions
targeting those weaknesses (de Savigny).
- An approach to problem solving that views ‘problems’ as a wider, dynamic system.
- Origins in the early 20th century in field, such as engineering, economics and ecology.
- It demands a deeper understanding of the linkages, relationships, interactions and
behaviours among the elements that characterize the entire system.
- Commonly used in sectors where interventions and systems are complex.
System thinking compared to system theory: System thinking, everything as a part, is the application
or implementation of the (overall) theory.
, Usual approach Systems thinking approach
Static thinking. Dynamic thinking.
Focus on particular events. Framing a problem in terms of a pattern of
behaviour over time.
Systems-as-effect thinking. Systems-as-cause thinking.
Viewing behaviour generated by a system as Placing responsibility for a behaviour on internal
driven by external forces. actors who manage the policies and ‘plumbing’
(doorgronden) of the system.
Tree-by-tree thinking. Forest thinking.
Believing that really knowing something means Believing that to know something requires
focusing on the details. understanding the context of relationships.
Factors thinking. Operational thinking.
Listing factors that influence or correlate with Concentrating on causality and understanding how
some result. a behaviour is generated.
Straight-line thinking. Loop thinking.
Viewing causality as running in one direction, Viewing causality as an on-going process, not a
ignoring (either deliberately or not) the one-time event, with effect feeding back to
interdependence and interaction between and influence the causes and the causes affecting each
among the causes. other.
Systems thinking elements (de Savigny):
- Systems organizing: Managing and leading a system. The types of rules that govern the
system and set direction, set prohibitions, and provide permissions.
- Systems networks: Understanding and managing system stakeholders. The web of all
involved in the system.
- Systems dynamics: Conceptually modelling and understanding dynamic change. Attempting
to conceptualize, model and understand dynamic change through analysing organizational
structure and how that influences behaviour of the system.
- Systems knowledge: Managing content and infrastructure for explicit and tacit knowledge.
The critical role of information flows in driving the system towards change, and using the
feedback chains of data, information and evidence for guiding decisions.
There are 8 common systems characteristics, which influence how systems respond to external
factors or to an intervention. Understanding the fundamental characteristics of systems is crucial to
seeing how they work (de Savigny).
- Self-organizing: System dynamics arise spontaneously from internal structure. The nature of
a system is not determined by an individual agent, but by the interaction among systems/the
system’s agents. Once we see the relationship between structure and behaviour, we can
begin to understand how systems work: system structure is the source of system behaviour.
- Constantly changing: Change is a constant in all sustainable systems. As systems are adaptive
rather than static, they have the ability to generate their own behaviour.
- Tightly linked: The high degree of connectivity means that change in one sub-system affects
the others. Anticipating positive and negative effects within a context of interconnection is
key to designing and evaluating an intervention over time.
- Governed by feedback: Systems are controlled by feedback loops that provide information
flows on the state of systems. The response may alter the intervention or expected effects.
, - Non-linear: Relationships within a system cannot be arranged along a simple input-output
line. System-level interventions are typically non-linear and unpredictable, with their effects
often disproportional or distantly related to the original intentions.
- History dependent: Short-term effects of intervening may differ from long-term effects.
Interventions designed to change people’s behaviour require measuring the intervention
effects over a longer period to avoid making incorrect conclusions of no or limited effects.
- Counter-intuitive: Cause and effect are often distant in time and space, defying solutions that
pit causes close to the effects they seek to address. Interventions may not work in all
settings. E.g. an intervention may increase utilization with the risk of overwhelming services
that were not strengthened in parallel.
- Resistant to change: With all those characteristics and the complexity of their many
interactions, it is sometimes difficult and delicate to develop a priori an effective policy
without a highly astute (scherpzinnig, slim) understanding of the system. System
characteristics can render (veranderen in) the system policy resistant, particularly when all of
the actors have their own (often competing) goals.
System thinking in organizations: In designing and evaluating system-level interventions or
interventions with system-wide effects, a comprehensive assessment of the main effects (intended
or not) and the contextual factors that may help explain the success or failure of the intervention are
essential (de Savigny).
Complexity theory
A different view/theory from the traditional approaches is postmodernism:
- Postmodernism: An umbrella term for a group of philosophical ideas that challenged the
assumptions of modernism and the resultant social and historical viewpoints. All models are
only partial descriptions of reality. Focus on the role of social construction (Johnson).
Complexity science: The study of complex systems and the phenomena of complexity and
emergence to which they give rise (Johnson).
- Observational-based science, for understanding a multitude of phenomenon from immune
systems and spread of diseases to ecosystems and social economic systems.
- Better understanding of:
o The uncertain nature of reality;
o The implications of that uncertainty for managerial action;
o The nature of relationships, which apparently is critical;
o By focusing on those relationships, new alternatives for management made
themselves apparent.
- The ontology and epistemologies are often compared with and linked to postmodernism.
The relation of complexity theory with system thinking: Postmodernism, or deconstructionism, is a
paradigm. Complexity theory is so too. Those thoughts or theories are used as a basis for a model.
For the complexity theory, a higher complexity comes with the line of system thinking. So, complexity
theory can be seen as a subset of system thinking (Johnson).
