Effectiveness & Efficiency in Management

Effectiveness & Efficiency in Management

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Courtesy :-The Order of Time dot com

There is an important distinction between effectiveness and efficiency in managing.

Effectiveness is doing the right things
and
Efficiency is doing things right.

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Six Sigma -Management Lessons- Basics

  • One is more than enough !


    Historical overview
    Six Sigma originated as a set of practices designed to improve manufacturing processes and eliminate defects, but its application was subsequently extended to other types of business processes as well.

    In Six Sigma, a defect is defined as any process output that does not meet customer specifications, or that could lead to creating an output that does not meet customer specifications.

    The idea of Six Sigma was actually “born” at Motorola in the 1970s, when senior executive Art Sundry was criticizing Motorola’s bad quality.
    Through this criticism, the company discovered the connection between increasing quality and decreasing costs in the production process. Before, everybody thought that quality would cost extra money. In fact, it was reducing costs, as costs for repair or control sank.
    Then, Bill Smith first formulated the particulars of the methodology at Motorola in 1986.

    Six Sigma was heavily inspired by six preceding decades of quality improvement methodologies such as quality control, TQM, and Zero Defects, based on the work of pioneers such as Shewhart, Deming, Juran, Ishikawa, Taguchi and others.

    Like its predecessors, Six Sigma doctrine asserts that:
    Continuous efforts to achieve stable and predictable process results (i.e., reduce process variation) are of vital importance to business success.
    Manufacturing and business processes have characteristics that can be measured, analyzed, improved and controlled.
    Achieving sustained quality improvement requires commitment from the entire organization, particularly from top-level management.
    Features that set Six Sigma apart from previous quality improvement initiatives include
    :A clear focus on achieving measurable and quantifiable financial returns from any Six Sigma project.
    An increased emphasis on strong and passionate management leadership and support.
    A special infrastructure of “Champions,” “Master Black Belts,” “Black Belts,” “Green Belts”, etc. to lead and implement the Six Sigma approach.
    A clear commitment to making decisions on the basis of verifiable data, rather than assumptions and guesswork.
    The term “Six Sigma” comes from a field of statistics known as process capability studies. Originally, it referred to the ability of manufacturing processes to produce a very high proportion of output within specification. Processes that operate with “six sigma quality” over the short term are assumed to produce long-term defect levels below 3.4 defects per million opportunities (DPMO).
    Six Sigma’s implicit goal is to improve all processes to that level of quality or better.

    Six Sigma is a registered service mark and trademark of Motorola Inc. As of 2006 Motorola reported over US$17 billion in savings from Six Sigma.
    Other early adopters of Six Sigma who achieved well-publicized success include Honeywell (previously known as AlliedSignal) and General Electric, where Jack Welch introduced the method.

    By the late 1990s, about two-thirds of the Fortune 500 organizations had begun Six Sigma initiatives with the aim of reducing costs and improving quality.

    In recent years, some practitioners have combined Six Sigma ideas with lean manufacturing to yield a methodology named Lean Six Sigma.

    Quality management tools and methods used in Six Sigma
    Within the individual phases of a DMAIC or DMADV project, Six Sigma utilizes many established quality-management tools that are also used outside of Six Sigma. The following table shows an overview of the main methods used.
    5 Whys
    Accelerated life testing
    Analysis of variance
    ANOVA Gauge R&R
    Axiomatic design
    Business Process Mapping
    Cause & effects diagram (also known as fishbone or Ishikawa diagram)
    Check sheet
    Chi-square test of independence and fits
    Control chart
    Correlation
    Cost-benefit analysis
    CTQ tree
    Design of experiments
    Failure mode and effects analysis (FMEA)
    General linear model
    Histograms Pareto analysis
    Pareto chart *Pick chart
    Process capability
    Quality Function Deployment (QFD
    )Quantitative marketing research through use of Enterprise Feedback Management (EFM) systems
    Regression analysis
    Root cause analysis
    Run charts
    Scatter diagram
    SIPOC analysis (Suppliers, Inputs, Process, Outputs, Customers)
    Stratification
    Taguchi methods
    Taguchi Loss Function
    TRIZ