Data-Driven Design Approaches
Reading 1.1 – System dynamics modelling: Tools for learning in a complex world Sterman
(2001)
All too often, well-intentioned efforts to solve pressing problems create unanticipated side
effects. Our decisions provoke unforeseen reactions. The result is policy resistance, the
tendency for interventions to be defeated by the response of the system to the intervention
itself.
How can one come to understand the whole system? How does policy resistance arise? How
can we learn to avoid it, to find the high-leverage policies that can produce sustainable
benefit?
Dynamic complexity = the often counter-intuitive behavior of complex systems that arises
from the interactions of the agents over time. Dynamic complexity can arise even in simple
systems with low combinatorial complexity.
Where the world is dynamic, evolving, and interconnected, we tend to make decisions using
mental models that are static, narrow, and reductionist. Among the elements of dynamic
complexity people find most problematic are feedback, time delays, stocks and flows
(accumulations), and nonlinearity.
,Time delays
Delays in feedback loops create instability and increase the tendency of systems to oscillate.
As a result, decision makers often continue to intervene to correct apparent discrepancies
between the desired and actual state of the system long after sufficient corrective actions
have been taken to restore the system to equilibrium.
,Stocks and flows
Stocks and flows – the accumulation and dispersal of resources – are central to the dynamics
of complex systems. It is only in the past decade or so that the strategic management
community has begun to consider the role of stocks and flows explicitly, as the resource-
based view of the firm has grown in popularity.
Fundamental attribution error = the tendency to blame other people instead of the system.
All dynamics arise from the interaction of just two types of feedback loops:
• Positive (self-reinforcing) loops = reinforce or amplify whatever is happening in the
system, e.g. if a firm lowers it price to gain market share, its competitors may
respond in kind, forcing the firm to lower its price still more.
→ Autocatalytic = self-stimulating processes that generate their own growth, leading
to arms races, price wars, and the phenomenal growth of Microsoft and Intel.
• Negative (self-correcting) loops = counteract and oppose change, processes that
create balance and equilibrium, e.g. the more attractive a neighbourhood or city, the
greater the migration from surrounding areas will be.
, No real quantity can grow forever. There must be limits to growth. These limits are created
by negative feedback. Negative loops are self-correcting.
Reading 1.2 – Industrial dynamics Forrester (1958)
For we can expect to gain, during the next 25 years, a far better understanding of the
dynamic, ever-changing forces which shape the destiny of a company. This understanding
will lead to better usage of available information, to improved understanding of advertising
effectiveness and the dynamic behavior of the consumer market, and to company policies
that keep pace with technological change.
In business, simulation means setting up in a digital computer the conditions which describe
a company operations.
A feedback control system exists whenever the environment causes a decision which in turn
affects the original environment.
• A thermostat receives temperature information, decides to start the furnace, and
changes the temperature.
All of these are information feedback control loops. The regenerative process in continuous,
and new results lead to new decision which keep the system in continuous motion.
Feedback theory explains how decisions, delays and predictions can produce either good
control or dramatically unstable operation. It relates sales promotion to production swings,
purchasing and pricing policies to inventory fluctuations, and typical life cycles of products to
the need for research.
To begin the study of our example, we need to know three kinds of information about the
system: its organizational structure, the delays in decisions and actions, and the policies
governing purchases and inventories.
1. Organizational structure
2. Delays in decisions and actions
3. Policy on purchasing orders and inventories
Simulation methods
Before we can determine how our system will function over a period of time, all of the
above rather general descriptions of the system must be expressed in explicit quantitative
form. The next step is to determine how the system as a whole behaves. To do so, we might
use some pattern of consumer purchases as an input and observe the resulting inventory
and production changes.
Reading 1.1 – System dynamics modelling: Tools for learning in a complex world Sterman
(2001)
All too often, well-intentioned efforts to solve pressing problems create unanticipated side
effects. Our decisions provoke unforeseen reactions. The result is policy resistance, the
tendency for interventions to be defeated by the response of the system to the intervention
itself.
How can one come to understand the whole system? How does policy resistance arise? How
can we learn to avoid it, to find the high-leverage policies that can produce sustainable
benefit?
Dynamic complexity = the often counter-intuitive behavior of complex systems that arises
from the interactions of the agents over time. Dynamic complexity can arise even in simple
systems with low combinatorial complexity.
Where the world is dynamic, evolving, and interconnected, we tend to make decisions using
mental models that are static, narrow, and reductionist. Among the elements of dynamic
complexity people find most problematic are feedback, time delays, stocks and flows
(accumulations), and nonlinearity.
,Time delays
Delays in feedback loops create instability and increase the tendency of systems to oscillate.
As a result, decision makers often continue to intervene to correct apparent discrepancies
between the desired and actual state of the system long after sufficient corrective actions
have been taken to restore the system to equilibrium.
,Stocks and flows
Stocks and flows – the accumulation and dispersal of resources – are central to the dynamics
of complex systems. It is only in the past decade or so that the strategic management
community has begun to consider the role of stocks and flows explicitly, as the resource-
based view of the firm has grown in popularity.
Fundamental attribution error = the tendency to blame other people instead of the system.
All dynamics arise from the interaction of just two types of feedback loops:
• Positive (self-reinforcing) loops = reinforce or amplify whatever is happening in the
system, e.g. if a firm lowers it price to gain market share, its competitors may
respond in kind, forcing the firm to lower its price still more.
→ Autocatalytic = self-stimulating processes that generate their own growth, leading
to arms races, price wars, and the phenomenal growth of Microsoft and Intel.
• Negative (self-correcting) loops = counteract and oppose change, processes that
create balance and equilibrium, e.g. the more attractive a neighbourhood or city, the
greater the migration from surrounding areas will be.
, No real quantity can grow forever. There must be limits to growth. These limits are created
by negative feedback. Negative loops are self-correcting.
Reading 1.2 – Industrial dynamics Forrester (1958)
For we can expect to gain, during the next 25 years, a far better understanding of the
dynamic, ever-changing forces which shape the destiny of a company. This understanding
will lead to better usage of available information, to improved understanding of advertising
effectiveness and the dynamic behavior of the consumer market, and to company policies
that keep pace with technological change.
In business, simulation means setting up in a digital computer the conditions which describe
a company operations.
A feedback control system exists whenever the environment causes a decision which in turn
affects the original environment.
• A thermostat receives temperature information, decides to start the furnace, and
changes the temperature.
All of these are information feedback control loops. The regenerative process in continuous,
and new results lead to new decision which keep the system in continuous motion.
Feedback theory explains how decisions, delays and predictions can produce either good
control or dramatically unstable operation. It relates sales promotion to production swings,
purchasing and pricing policies to inventory fluctuations, and typical life cycles of products to
the need for research.
To begin the study of our example, we need to know three kinds of information about the
system: its organizational structure, the delays in decisions and actions, and the policies
governing purchases and inventories.
1. Organizational structure
2. Delays in decisions and actions
3. Policy on purchasing orders and inventories
Simulation methods
Before we can determine how our system will function over a period of time, all of the
above rather general descriptions of the system must be expressed in explicit quantitative
form. The next step is to determine how the system as a whole behaves. To do so, we might
use some pattern of consumer purchases as an input and observe the resulting inventory
and production changes.
