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The Pareto priority index (PPI) [1] is an index used to prioritize several (quality improvement) projects. It is named for its connection with the Pareto principle named after the economist Vilfredo Pareto. It is especially used in the surroundings of Six Sigma projects. It was first established by AT&T.[ citation needed ] The PPI is calculated as follows:
A high PPI suggests a high project priority.
In economics the Pareto index, named after the Italian economist and sociologist Vilfredo Pareto, is a measure of the breadth of income or wealth distribution. It is one of the parameters specifying a Pareto distribution and embodies the Pareto principle. As applied to income, the Pareto principle is sometimes stated in popular expositions by saying q=20% of the population has p=80% of the income. In fact, Pareto's data on British income taxes in his Cours d'économie politique indicates that about 20% of the population had about 80% of the income.. For example, if the population is 100 and the total wealth is $100xm, then together q=20 people have pxm=$80xm. Hence, each of these people has x=pxm/q=$4xm.
Project management is the process of leading the work of a team to achieve all project goals within the given constraints. This information is usually described in project documentation, created at the beginning of the development process. The primary constraints are scope, time, and budget. The secondary challenge is to optimize the allocation of necessary inputs and apply them to meet pre-defined objectives.
The Pareto principle states that for many outcomes, roughly 80% of consequences come from 20% of causes.
Vilfredo Federico Damaso Pareto was an Italian polymath. He made several important contributions to economics, particularly in the study of income distribution and in the analysis of individuals' choices. He was also responsible for popularising the use of the term "elite" in social analysis.
Zipf's law is an empirical law that often holds, approximately, when a list of measured values is sorted in decreasing order. It states that the value of the nth entry is inversely proportional to n.
The Pareto distribution, named after the Italian civil engineer, economist, and sociologist Vilfredo Pareto, is a power-law probability distribution that is used in description of social, quality control, scientific, geophysical, actuarial, and many other types of observable phenomena; the principle originally applied to describing the distribution of wealth in a society, fitting the trend that a large portion of wealth is held by a small fraction of the population. The Pareto principle or "80-20 rule" stating that 80% of outcomes are due to 20% of causes was named in honour of Pareto, but the concepts are distinct, and only Pareto distributions with shape value of log45 ≈ 1.16 precisely reflect it. Empirical observation has shown that this 80-20 distribution fits a wide range of cases, including natural phenomena and human activities.
Critical chain project management (CCPM) is a method of planning and managing projects that emphasizes the resources required to execute project tasks. It was developed by Eliyahu M. Goldratt. It differs from more traditional methods that derive from critical path and PERT algorithms, which emphasize task order and rigid scheduling. A critical chain project network strives to keep resources levelled, and requires that they be flexible in start times.
In software engineering and development, a software metric is a standard of measure of a degree to which a software system or process possesses some property. Even if a metric is not a measurement, often the two terms are used as synonyms. Since quantitative measurements are essential in all sciences, there is a continuous effort by computer science practitioners and theoreticians to bring similar approaches to software development. The goal is obtaining objective, reproducible and quantifiable measurements, which may have numerous valuable applications in schedule and budget planning, cost estimation, quality assurance, testing, software debugging, software performance optimization, and optimal personnel task assignments.
A consumer price index (CPI) is a price index, the price of a weighted average market basket of consumer goods and services purchased by households. Changes in measured CPI track changes in prices over time. The CPI is calculated by using a representative basket of goods and services. The basket is updated periodically to reflect changes in consumer spending habits. The prices of the goods and services in the basket are collected monthly from a sample of retail and service establishments. The prices are then adjusted for changes in quality or features. Changes in the CPI can be used to track inflation over time and to compare inflation rates between different countries. The CPI is not a perfect measure of inflation or the cost of living, but it is a useful tool for tracking these economic indicators.
Six Sigma (6σ) is a set of techniques and tools for process improvement. It was introduced by American engineer Bill Smith while working at Motorola in 1986.
PPI may refer to:
A performance indicator or key performance indicator (KPI) is a type of performance measurement. KPIs evaluate the success of an organization or of a particular activity in which it engages. KPIs provide a focus for strategic and operational improvement, create an analytical basis for decision making and help focus attention on what matters most.
A cost estimate is the approximation of the cost of a program, project, or operation. The cost estimate is the product of the cost estimating process. The cost estimate has a single total value and may have identifiable component values.
In probability theory, heavy-tailed distributions are probability distributions whose tails are not exponentially bounded: that is, they have heavier tails than the exponential distribution. In many applications it is the right tail of the distribution that is of interest, but a distribution may have a heavy left tail, or both tails may be heavy.
The seven basic tools of quality are a fixed set of visual exercises identified as being most helpful in troubleshooting issues related to quality. They are called basic because they are suitable for people with little formal training in statistics and because they can be used to solve the vast majority of quality-related issues.
In statistics, the generalized Pareto distribution (GPD) is a family of continuous probability distributions. It is often used to model the tails of another distribution. It is specified by three parameters: location , scale , and shape . Sometimes it is specified by only scale and shape and sometimes only by its shape parameter. Some references give the shape parameter as .
A Deep energy retrofit can be broadly categorized as an energy conservation measure in an existing building also leading to an overall improvement in the building performance. While there is no exact definition for a deep energy retrofit, it can be defined as a whole-building analysis and construction process, that aims at achieving on-site energy use minimization in a building by 50% or more compared to the baseline energy use making use of existing technologies, materials and construction practices. Such a retrofit reaps multifold benefits beyond energy cost savings, unlike conventional energy retrofit. It may also involve remodeling the building to achieve a harmony in energy, indoor air quality, durability, and thermal comfort. An integrated project delivery method is recommended for a deep energy retrofit project. An over-time approach in a deep energy retrofitting project provides a solution to the large upfront costs problem in all-at-once execution of the project.
DERs are projects that create new, valuable assets from existing residences, by bringing homes into alignment with the expectations of the 21st century
Non-uniform random variate generation or pseudo-random number sampling is the numerical practice of generating pseudo-random numbers (PRN) that follow a given probability distribution. Methods are typically based on the availability of a uniformly distributed PRN generator. Computational algorithms are then used to manipulate a single random variate, X, or often several such variates, into a new random variate Y such that these values have the required distribution. The first methods were developed for Monte-Carlo simulations in the Manhattan project, published by John von Neumann in the early 1950s.
The Lomax distribution, conditionally also called the Pareto Type II distribution, is a heavy-tail probability distribution used in business, economics, actuarial science, queueing theory and Internet traffic modeling. It is named after K. S. Lomax. It is essentially a Pareto distribution that has been shifted so that its support begins at zero.
Stochastic scheduling concerns scheduling problems involving random attributes, such as random processing times, random due dates, random weights, and stochastic machine breakdowns. Major applications arise in manufacturing systems, computer systems, communication systems, logistics and transportation, and machine learning, among others.
