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DIA Baggage
Handling System
Case Analysis
Prepared by
Mayukh
Mukhopadhyay
Team Members
Abhisita
Arindam
Arnab
Kaushik
Sumantra
IIT Kharagpur November 2018
Agenda
• Problem Identification
• Root Cause Analysis
• Possible Solution
• Alternative Approaches
• Final Recommendations
• Justifications
Problem Identification
• Complex Design
• Unrealistic Deadline
• Project Scope Creep
• Media and Politics
• System Failure
Root Cause Analysis
• The underestimation of complexity
• A lack of planning resulting in subsequent changes
in strategy
• Excessive schedule pressure
• Lack of due diligence
• Making firm commitments in the face of massive
risks and uncertainty
• Poor stakeholder management
• Communications breakdowns
• People working in silos
• Poor design
• Failure to perform risk management
• Failure to understand the implication change
requests might have
• Lack of management oversight
Possible Solution
• Short term solution
• Backup plans
• Reduction in complexity and
load
• Long term solution
• Acknowledge Problem
Signals
• Sprint based approach
• Maintenance of backlog and
work-breakdown structure
Alternative Approach: 3J Framework
• To identify our project
Jenga and act
accordingly.
• Apply Jiujithsu - use
the strength of
adversary to disarm
them.
• Avoid project scope
creep using sprint-
backlog Jozi.
Final Recommendations
• Proper Change control and
sufficient error margin.
• Effective stakeholder
management
• Periodic risk management
exercises
• Differentiated revenue
models of A,B and C
concourses.
• Communication
management and subject
matter expert opinion
• Effective Escalation Matrix
Justification
• To avoid revisionist tendency of human critics.
• It is more appropriate to place the troubled baggage
system's problems in the context of management and
engineering principles.
• Lastly, keeping the system's complexity down to
manageable levels save time of prolonged testing.
• Analysis, over criticism, can reduce a system catastrophe
from striking as information systems grow larger and more
liable every year.
BAE DIA Baggage Automation System - HBR Case Analyis

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BAE DIA Baggage Automation System - HBR Case Analyis

  • 1. DIA Baggage Handling System Case Analysis Prepared by Mayukh Mukhopadhyay Team Members Abhisita Arindam Arnab Kaushik Sumantra IIT Kharagpur November 2018
  • 2. Agenda • Problem Identification • Root Cause Analysis • Possible Solution • Alternative Approaches • Final Recommendations • Justifications
  • 3.
  • 4. Problem Identification • Complex Design • Unrealistic Deadline • Project Scope Creep • Media and Politics • System Failure
  • 5. Root Cause Analysis • The underestimation of complexity • A lack of planning resulting in subsequent changes in strategy • Excessive schedule pressure • Lack of due diligence • Making firm commitments in the face of massive risks and uncertainty • Poor stakeholder management • Communications breakdowns • People working in silos • Poor design • Failure to perform risk management • Failure to understand the implication change requests might have • Lack of management oversight
  • 6. Possible Solution • Short term solution • Backup plans • Reduction in complexity and load • Long term solution • Acknowledge Problem Signals • Sprint based approach • Maintenance of backlog and work-breakdown structure
  • 7. Alternative Approach: 3J Framework • To identify our project Jenga and act accordingly. • Apply Jiujithsu - use the strength of adversary to disarm them. • Avoid project scope creep using sprint- backlog Jozi.
  • 8. Final Recommendations • Proper Change control and sufficient error margin. • Effective stakeholder management • Periodic risk management exercises • Differentiated revenue models of A,B and C concourses. • Communication management and subject matter expert opinion • Effective Escalation Matrix
  • 9. Justification • To avoid revisionist tendency of human critics. • It is more appropriate to place the troubled baggage system's problems in the context of management and engineering principles. • Lastly, keeping the system's complexity down to manageable levels save time of prolonged testing. • Analysis, over criticism, can reduce a system catastrophe from striking as information systems grow larger and more liable every year.