Management in a Changing World

Management in a Changing World

• New technologies transform products, markets, business processes, and entire industries.
• Emphasis on "soft" arts like leadership, change management, and employee motivation increases.
• Traditional scientific approach to management aimed to analyze, predict, and control complex organizations.
• The current business world is often unpredictable, uncertain, and uncontrollable.
• Traditional scientific management is becoming less useful and potentially counterproductive.
• Science itself appears less relevant to managers' practical concerns.
• The problem may be in managers' understanding of science.
• Traditional science focused on analysis, prediction, and control.
• New science emphasizes chaos and complexity.
• Scientists describe how complex systems cope with uncertainty and rapid change.

The Science Behind Scientific Management

• Frederick Winslow Taylor coined the term "scientific management" in 1911.
• Taylor's book, The Principles of Scientific Management, laid out rules for efficient industrial organization.
• Taylor addressed the problem of efficiency in organizations.
• He argued against "awkward, inefficient, or ill-directed movements of men".
• Unscientific management caused waste of human effort.
• Managers focused too much on output and not enough on work processes.
• Taylor disparaged the "initiative and incentive" system.
• Managers depended on work groups to decide how work was done.
• Traditional management was inherently unstable.
• Managers tried to boost productivity by regularly raising piece rates, which induced "soldiering".
• Taylor's solution was "the substitution of a science for the individual judgment of the workman".
• Managers were to separate work planning from execution.
• Standardized procedures would identify the "one best method" for maximum efficiency.
• Taylor urged managers to think of themselves as scientists.
• The worker played a passive role, like apparatus in an experiment.
• Taylor repeated that the "science which underlies each workman's act is so great" that the worker cannot understand it.
• The manager searches for general laws or rules to understand the true science of work.
• Taylor addressed employee motivation, arguing that managers must effect "a complete revolution in the mental attitude" of the worker.
• Scientific analysis and control could reduce "the motives which influence men".
• Psychological laws exist that apply to a large majority of men.
• Productivity improvements from scientific management should be shared with workers in higher wages.
• Suggestions included never dealing with workers as a group and assigning individual tasks.
• All techniques of scientific management share a regard for reductionism.
• Techniques include the planning department, time-and-motion study, and standardization of methods and tools.
• Taylor urged readers not to confuse techniques with basic scientific principles.
• In fast-changing markets, fragmentation of work, separation of planning from execution, and isolation of workers are a recipe for disaster.
• Managers must now rethink the fundamental elements of Taylor's system: work organization, employee motivation, and management's task.
• New managerial ideas are direct/indirect responses to Taylor's inadequacies.

Coping with Chaos and Complexity

• Scientists understood shortcomings of 19th-century scientific models.
• Within a decade of Taylor's book, new physics developments suggested Newtonian physics broke down at extremes.
• Scientists extended the message of uncertainty and unpredictability to the everyday world recently.
• 19th-century physics posited a neat correspondence between cause and effect.
• Scientists believed they could reduce complex behaviors to simple laws.
• During the past few decades, scientists found this and many assumptions to be wrong.
• Nature appears random as a throw of the dice, not predictable as clock-work.
• "Chaos theory" is the general term for this new model.
• The chief catalyst for chaos theory was Edward Lorenz.
• Lorenz developed a computer program that simulated a weather system.
• Minuscule changes caused drastic alterations in the weather pattern.
• A slight breeze in Idaho/one-degree drop in temperature in Massachusetts could change balmy weather in Florida into a hurricane.
• Scientists began experimenting with simulations of other physical systems, and they all discovered the identical phenomenon.
• Chaos theory's second basic insight: patterns lurk beneath seemingly random behavior.
• Systems don't end up just anywhere; certain paths make more sense and occur more frequently.
• Scientists call such paths "strange attractors."
• Meteorologists can estimate the probability of the kind of weather likely to occur, if not what day certain weather will occur.
• Cause-and-effect precision of traditional physics has been replaced by the statistical estimate of probabilities.
• Many scientists have had to learn a more holistic approach in place of breaking down systems.
• They focus increasingly on the dynamics of the overall system.
• They now emphasize how order emerges from the interaction of those parts as a whole.
• The quest is to gain insight into and make use of the order emerging from chaotic systems.
• The Santa Fe Institute specializes in the analysis of "self-organizing" systems.
• The institute focuses on the ways that the simple actions of independent components combine to produce complex behaviors without any central intelligence/control.
• Complex adaptive systems are among the most successful in nature.
• Examples include the ecology of tropical rain forests, colonies of ants, and even the human brain.
• Systems are consist of a network of “agents", act autonomously with no central control.
• Each brain neuron follows its own independent pattern of behavior.
• No “master neuron” in the brain controls what each neuron does.
• Agents are capable of engaging in cooperative behavior.
• Community neurons specialize in functions like language/visual recognition.
• Interaction among neurons produces human intelligence.
• Self-organizing systems "learn" through feedback by embedding learning for structural reinforcement.
• The stronger the chemical connection among the neurons (and the easier for the brain to make the connection next time).
• Self-organizing systems constantly rearrange themselves as effects of previous actions/changes in external conditions ripple through the system.
• Self-management and learning through feedback allow systems to operate by flexible specialization.
• New niches are created as external environment changes.
• It becomes meaningless to talk of agents "optimizing" behavior.
• The complex adaptive systems contain individual agents that network to create self-managed but highly organized behavior.
• Characterisitics include agents responding to feedback, adjusting behavior, learning from experience, and embedding that learning.

Toward a New Managerial Science

• Few complexity researchers have applied the concepts of their emerging field to the specific organizational problems managers face.
• One area of research at the Santa Fe Institute takes a step in that direction.
• Economists are creating computer simulations of economic transactions.
• Their goal is to model complex market behaviors by constructing them from a limited set of simple building blocks.
• It views the economy as something organic, adaptive, surprising, and alive.
• Santa Fe researchers still haven't developed a convincing computer version of an entire economy.
• They have, however, developed simulations that represent limited aspects of economic activity, and some of these simulations have produced quite realistic behaviors.
• Economists created a program that, simulates the stock market.
• The computer system learned to simulate the same bubbles and crashes that occur in real markets.
• Stock market simulation is just a start for the Santa Fe researchers.
• The computer system could be used as a "flight simulator" for economic decision making.
• Computer-based trading companies are considering incorporating AI trading decision making.
• Managers feel lost in the organizations they are a part of.
• Senge argues that the inability to cope with complexity results from tradition scientific management approaches.
• Complexity scientist Senge believes in holism.
• Managers are prisoners of the very systems they are supposed to manage.
• Managers do not understand underlying dynamics or how to influence those dynamics to achieve organizational goals.
• It wrongly assumes that someone "up there" is in control.
• This position would see an organization as an organism.
• "Systems thinking" is the fifth discipline of Senge's title.
• It should give managers capacity for "seeing wholes”.
• Senge's story of a high-tech start-up from the 1960s, based on a number of real instances.
• Managers must understand the systemic processes driving human behavior and change them
• "The art of systems thinking lies in seeing through complexity to the underlying structures generating change."
• The essential element is to effect real change.
• Microworld help create organic control work.
• These computer-based simulations reflect the principles of systems thinking.
• Scientists also use simulations of the weather or water dripping from a faucet to learn how physical systems work.
• Senge's new manager is a scientist -but, of course, a scientist of a very different sort
• Today's scientific managers must be researchers who study their own organizations.
• To day's scientific managers must be designers who create the learning processes that make self-organization possible.
• Today's scientific managers must be designers of processes essential to effective performance in the characterized by perpetual novelty and change.