IISc MG 286 Project Management Systems Approach - PowerPoint PPT Presentation

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IISc MG 286 Project Management Systems Approach


This ppts describes the Systems Approach to Project Management, as taught by Prof Parameshwar P. Iyer at the Indian Institute of Science, Bangalore – PowerPoint PPT presentation

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Title: IISc MG 286 Project Management Systems Approach

  • Module 2
  • The Systems Approach

Some Basic Concepts/ Definitions
  • What is system?
  • It is a set of parts (components), which are
    coordinated to accomplish (achieve) a set of
    goals (objectives).
  • What is the systems approach?
  • It is a wholistic approach to problem solving
    that involves formal consideration of
  • Total system objectives Performance measures
  • System environment Fixed constraints
  • System resources Inputs
  • System components Activities, goals,
  • System management Component interactions

Systems Approach (Contd.)
  • Total system objectives (performance measures of
    the whole system).
  • System environment (fixed constraints).
  • System resources (inputs).
  • System components (their activities, goals, and
    performance measures), and
  • System management (control).

A General Systems Model
  • Inputs can be purposeful or environmental . Again
    , purposeful inputs can be controllable or
    uncontrollable .
  • Outputs can be desired or undesired outputs.
  • Design parameters are features or attributes of
    the system that will affect system behavior .

A General Systems Model
  • Constraints establish quantitative limits on each
    input , output , and design parameter .
  • Criteria for evaluation are used to establish
    relative goodness amongst several alternative
    designs or solutions .
  • Functional representation can be as follow Y( t)
    f X (t) , E (t) where t is any independent
    variable (time).

Areas of Systems Studies
1. System design Given X(t), Y(t), E(t)
Determine f   2. System Analysis Given X(t), f,
E(t) Determine Y(t)   3. System Control Given f,
Y(t), E(t) Determine X(t)
Types of Systems
  • Discrete event Vs Continuous flow
  • Discrete time (difference equation) Vs Continuous
    time (differential equation)
  • Deterministic Vs Stochastic
  • Fixed or static Vs Time variant or dynamic
  • Linear Vs Non-linear
  • X1(t)-y1(t) X2(t)-y2(t)
  • Then, aX1(t)bX2(t)---aY1(t)bY2(t)

A Project as a System The life cycle concept 
1) A project has sub-projects/work packages like
a system has sub-systems/components 2) The
sub-projects/sub-systems are inter-linked/inter-re
lated 3) We focus on overall project/system
objectives 4) Project identification is similar
to system boundary demarcation 5) Project
resources are like system inputs 6) Like the
system life cycle, a project also has a life
cycle. Major difference A system generally
implies an infinite lifetime (perhaps with
upgrading),while a project is purely temporary.
Fig 2.7 A Simple Technological innovation
chain Fig 2.8 Activity Level  Fig 2.9 Investment
and return  Fig 2.10 A Systems design
algorithm Fig 2.11 A feasibility study algorithm
System Identification (Constrained Parametric
Parameter Sub-parameter Constraint Ourput Des
ired Greater Than Undesired L
ess Than   Input Controllable
Greater Less Than Uncontrollable
Greater Less Than Environmenta
l Greater Less Than   Design Size Greater
Less Than Capacity Greater Less
Than Finance Less Than Economy Less
Than Life Greater Than   Evaluation Return/
Profit Greater Than Efficiency Greater
Than Volume Greater Than Oppurtunity Gr
eater Than
A Systems Design Algorithm
  • Primative Need gtFeasibility Study
  • Set of Feasible Solns. gtPrelimin.Design
  • Optimal Design gtComparitive Analysis of
    Particular Concepts
  • Optimal System Design gtDetailedDesign
  • Complete Description gtPlanning for
  • Production gtUse of Design

A Feasibility Study Algorithm
  • Primative Need gtgtgt Needs Analysis
  • Identified Needs gtgtgt System Identification
  • Detailed Problem gtgtgtSynthesis of Solution
  • Possible Solutions gtgtgtRealisability and
  • Analysis gtgtgt Set of Feasible

Data Definition/Technology Factors
  • Production Factors
  • Time to install
  • Degree of disruption
  • Learning curve
  • Facility/Equipment required
  • Development time and cost
  • Quality impacts

Data Definition/Technology Factors
  • Market Factors (For Sellers)
  • Size of present and potential future markets
  • Probable market share
  • Time to acquire market share
  • Impact on product/process lines
  • Consumer (buyer) acceptance
  • Technology life (up gradation)
  • Spin off technologies

Data Definition/Technology Factors
  • Financial Factors
  • Profitability
  • Net present value of investment
  • Pay back period
  • Impact on cash flows
  • Capital requirements
  • Break even (volume/time)
  • Start-up/Switch over costs
  • Risk levels

Data Definition/Technology Factors
  • Personnel Factors
  • Training requirements
  • Skill requirements
  • Skill availability
  • Resistance to new technologies
  • Effect on employment
  • Other worker reactions

Feasibility of Solutions
Technological feasibility Financial
feasibility Economic practicability User (Social)
acceptability Market (political) viability
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