Presentation on theme: "Lecturer Dr. Simon Poon Week 2 Lecture: Information Systems Concepts & Systems Thinking COMP5206 Introduction to Information Systems 1."— Presentation transcript:
Lecturer Dr. Simon Poon Week 2 Lecture: Information Systems Concepts & Systems Thinking COMP5206 Introduction to Information Systems 1
What is Information Systems? 2 What are the differences between IS, CS and SE?
What are some of the IS related challenges today ? Growth and Innovation Pervasiveness of IT impact on business What technology trends to watch? Sourcing and globalization Complexity and scale of IT infrastructure IT Investments--short-term and long-term Navigate complex technology landscape Multi-generational IT workforce Much more…. How should we study these issues? 3
What is a System? What is a simple or a complex system? A ‘system’ is set of inter-related components or subsystems and processes. We generally deal with ‘teleological’ (purposeful) systems. For such systems, we modify the definition: A ‘system’ is made up of inter-related components that work together to achieve the overall objectives of the whole system Systems approach or thinking refers to the study of the system as a whole in which the interdependent parts interact with each other dynamically to achieve the system’s goals 4
“Structure” of Systems Overall objective represented as concrete measure(s) of performance, Inputs and Resources Process(es) Outputs System Boundary System Environment Feedback Mechanisms 5
System Boundary and Environment Internal and external environments Boundary – interface with the external environment at the boundary 6
Feedback Outputs from the system can be channelled back as input to the systems Feedback can be positive or negative Vicious and virtuous cycles Homeostasis and self-regulation 7
Process View of Systems Input-Output Approach Inputs to the system (from the ext. envt.) Throughput processing/Transformation Outputs of the system (to the ext. envt.) Feedback Mechanisms Inter-connectedness of parts Modelling of the overall system with a view to developing optimal solution The management subsystem (in the organisational context) can be viewed as an information- processing system 8
9 An Example: Systems Analysis of An Organisation Aspects of organisation need to consider: The way jobs are broken down as specialisations The ways jobs are grouped together and managed in units The way control and co-ordination are maintained (i.e. sequential decision making process) The way information is shared and exploited and issues of ownership The way overall growth and development of the organisation is supported.
10 Systems Analysis…. Aims at achieving understanding in ‘logical’ terms of the human activities, events and actions, information transformation processes and data resources relevant to the environment of a new system. By describing in some detail the kind of processes and data that system will deal with, and the relations among them.
11 Traditional Approach Structured Systems Analysis (Since DeMarco’s structured systems analysis method (1978) System is a collection of process Processes interact with data entities Processes accepts inputs and produce outputs Data Flow Diagram
Entity-Relationship Model First designed by Peter Chen in Other variations have since appeared. Often abbreviated as “ER” or “ERD” Used to interpret, specify, and document database systems. Graphical representation of what data needs to be contained in the system.
Efficiency-oriented Approaches to Systems Thinking – PROBLEMS?? Concerned primarily with the efficiency of the system’s operations, Has its origins in what is known as ‘scientific management’ or ‘Taylorism’. Focus on eliminating all forms of ‘waste’ and ‘slack’ and eliminating them from the system to achieve cost savings. 13
Management Science/General System Theory Approach Careful description of the total system including: full specifications of the parts or the components and their coordination, identification of the measures of performance in measurable terms, definition of the system’s boundaries and by implication, its external environment. Total system objectives – performance measures for the whole system Resources available to the system – current and potential System’s environment – the fixed constraints, what lies outside the system, The components of the system; their activities, goals, and measures of performance. How they mesh with the overall measures of performance, The management of the system 14
Interdependence between Organizations and Information Systems IS and Organisation 15
S Case: Pesticide Example (by Daniel Aronson) 16 Pesticide Application Insects Damaging Crops O Short Term results Direction of causation Long Term results
IT inspired workplace Average 40hours/week (for 40 years of working life) 17
The Systems thinking approach incorporates several tenets: 18 Interdependence of objects and their attributes - independent elements can never constitute a system Interdependence Holism - emergent properties not possible to detect by analysis should be possible to define by a holistic approach Holismemergent propertiesanalysis Goal seeking - systemic interaction must result in some goal or final state Goal seeking Inputs and Outputs - in a closed system inputs are determined once and constant; in an open system additional inputs are admitted from the environment InputsOutputsclosed systemopen system Transformation of inputs into outputs - this is the process by which the goals are obtained Transformation Entropy - the amount of disorder or randomness present in any system Entropy Regulation - a method of feedback is necessary for the system to operate predictably Regulationfeedback Hierarchy - complex wholes are made up of smaller subsystems Hierarchy Differentiation - specialized units perform specialized functions Differentiation Equifinality - alternative ways of attaining the same objectives (convergence) Equifinality Multifinality - attaining alternative objectives from the same inputs (divergence) Multifinality Source:
Key System Principles Openness: - System behaviour can only be understood in relation to the external environment - Distinction between the system and the environment – systems boundary - Controllable and uncontrollable variables - Transactional environment and variables that can be influenced. - Role of leadership and managing upward in purposeful systems 20
Key Systems Principles (contd.) Purposefulness Value-guided systems Role of understanding (why actors do what they do) Rational, emotional and cultural dimensions Reaction- response- action Adaptiveness Active Role of Choice 21
Key Systems Principles (contd.) Emergent Property Property of the whole that cannot be deduced from the properties of the parts Emergent properties as the product of complex interactions among several elements Interactions among five basic processes: throughput, decision making, learning and control, membership, and conflict management. Measurement system 22
Key Systems Principles (contd.) Multidimensionality Multiple interacting dimensions Seemingly opposing tendencies not only co-exist to form a complementary relationship Plurality of structures and processes. 23
Key Systems Principles (contd.) Counter-intuitiveness Actions intended to produce certain outcomes may generate opposite results. Beyond certain point, quantitative change can lead to qualitative change – difference in degree versus difference in kind Inflection Points 24
The Systems Approach The systems approach or systems thinking is a method of analysing or thinking about complex systems from the perspective of the total system, the goals of the overall system, the individual components, and the inter- relationships and inter-dependencies between the components. 25
Systems Theory 26 Systems Theory: the transdisciplinary study of the abstract organization of complex phenomena, independent of their substance, type, or spatial, or temporal scale of existence. It investigates both the principles common to all complex entities, and the (usually mathematical) models that can be used to represent them.
What is Information Systems? IS as a product in production or in use? From the societal level From the macro economic level From the industry level (e.g. producing versus using) From the organisational level From the individual level Based on your foresights in the technological advances, what do you see University of Sydney in 10 ten years? Do you think tertiary education can be transformed into 100% online? What questions do you need to ask before implementing the online systems? 27
Understanding Organizational Systems Structural frame: Focuses on roles and responsibilities, coordination, and control. Organization charts help define this frame. Human resources frame: Focuses on providing harmony between needs of the organization and needs of people. Political frame: Assumes organizations are coalitions composed of varied individuals and interest groups. Conflict and power are key issues. Symbolic frame: Focuses on symbols and meanings related to events. Culture is important.
Week1: Social Responsibility Internet over satellite in developing nations Bridging the Digital Divide One laptop per child initiative Cuban Youth Computer Club mobile unit
Democratizing Innovation Users of products and services are increasingly able to innovate for themselves. User-centric versus manufacturer-centric innovation Innovation user and innovation manufacturer are two general “functional” relationships between innovator and innovation. Users are unique in that they alone benefit directly from innovations. Can be extended to specific functions, attributes, or features of product s and services e.g. Desktop publishing using computer User-innovators with stronger “lead user” characteristics develop innovations having higher appeal in the general marketplace Many users want custom products (heterogeneous needs) Users’ innovate-or-buy decisions Agency costs (monitor, commitment & quality) Social welfare User-innovator may value process of innovating 30
Democratizing Innovation Users and manufacturers tend to develop different types of innovations Information asymmetries Users tend to develop innovations that are functionally novel & requiring user-context information User often reveal their innovations Social efficiency is increased if users can diffuse to others what they have developed Widespread diffusion by unexpected means like “freely reveal” Innovation Communities User-innovators need to develop ways to cooperate, e.g. OSS Innovation contributors can obtain some private rewards Adapting Policy to User Innovation Social welfare implication IP (innovation investment) versus public welfare Democratising Innovation Traditional pattern of concentrating innovation-support resources on a few individual is inefficient Users will be an increasingly important source of innovation Users will increasingly substitute for or complement manufacturer-innovation activities Manufacturer may “discover” lead user innovations Firms need to understand the distributed innovation process and factors affecting lead users innovation
Chapter 5: Web 2.0 Web 2.0 is a loose collection of information technologies and applications, and the Web sites that use them. Most Common Web 2.0 Memes
Key messages The more our computers are connected, the more we realise how disconnected our information is Social computing tools can connect people, information and knowledge Use social computing tools in “smart ways” to serve growing user demand to interact directly with government Remember to concentrate on the “social”-part, not the “computing” part
IT Strategy: A Decision Making Perspective 1.“Futurity of current decisions” 2.“Recognition and response to weak signals” 3.“Allocation of scarce resources” 4.“Adapting to new context” 5.“Managing for today” while “preparing for tomorrow” 34
Preparation for next week… 35 Dynamics of Complex Systems (Pattern Formation) Source: Making Things Work: Solving Complex Problems in a Complex World(Bar-Yam 2004) How to workout the underlying process from the patterns?
Start with different structures… 36
Another structure… 37 There are total of possible 2 n structures!!!
A Model of Panic 38 A model of panic, based on local interactions. Lighter shades represent calm people; while darker shades represent panicky people. On the LHS, the person in the centre will panic; on the RHS, the person in the centre remain/become calm.
Model of crowded auditorium: 7 repetitions of the panic rule 39
Start with different structures… 40 Source: Rivkin and Siggelkow (2007), Pattern Interactions in Complex Systems: Implication for Exploration, Management Science, 53(7), pp