Page 56 - Chapter One
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24  The Management Shift




          table 1.4  A comparison between traditional and emerging management
          concepts and approaches
           Traditional management approaches  Emerging management approaches
           Newtonian paradigm            Complexity paradigm
           Machine model                 Organizations as living organisms
           Clockware (focusing on individual parts)  Swarmware (focusing on interactions
                                         amongst interconnected parts of an
                                         organization)
           Seek comfort                  Support differences
           Competition                   Balance competition and  cooperation
           Focusing on one task at a time  Multitasking
           Human resources               Talent management
                                         Diversity imperative
           Hierarchical linearity         Non-  linearity, networks, interactions
           Command and control           Distributed power, autonomy,
                                         interconnectivity
           Pyramids                      Networks
           Manage by rules               Manage on the edge
           Focus on data                 Balance data and intuition
           Control information and force agreement  Stay on the edge and use the “right”
                                         amount of information
           Focus on formal relationships  Utilize the shadow system
           Ignore tension and paradox    Embrace tension and paradox
           Focus on shareholders         Focus on customers
           Focus on share price, earnings, growth  Invest in future growth
           Grow big (economies of scale)  Be agile (flexible, adaptable)
           Plan everything in detail before taking   Have a good enough vision, take action,
           action                        learn and adapt. Balance planning and
                                         acting
           Avoid risks                   Balance safety and risk, take reasonable
                                         risks
           No experimentation, trial and error  Be open to experimentation, learning and
                                         reflection
           Know your direction in detail before action  Let direction emerge from action
           Reduce complexity, simplify models  Embrace complexity
           Settled and stable, maintain equilibrium  Question the status quo, start to change
                                         when on top
           Authority based on power      Authority based on knowledge
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