PMP Exam Quality Terms and Philosophies

Quality Philosophy

Quality touches virtually every piece of the project, so it is very important. It is easy to think about the quality of the product, but project managers also care about the quality of the process.

In fact, how something gets carried out is as important as the end result. The philosophy of quality is derived from several leading theories and is also a very proactive approach.

Whereas early approaches to quality relied heavily on inspection, current thinking is focused on prevention since it costs more to fix an error that it does to prevent one.

Keep in mind that you can never inspect quality into a product, but you can plan for it from the outset.

The responsibility for quality rest heavily on the project manager. Everyone on the team can contribute to project quality, however, it is management responsibility to provide the resources to make quality happen, and the project manager is ultimately responsible and accountable for the quality of the project.

It is also important to understand that some of the investment in quality is usually borne by the organization - since it would be far too expensive for each project to have its own quality program. An example here would be a company investing in a site license for a software testing product that can be used across numerous projects.

The topic of quality management is very important on the PMP Exam, and you should expect to see several exam questions related directly to your familiarity with the quality terms and theories.

Definition of Quality

The definition of quality you should know for your PMP Exam is " the degree to which a set of inherent characteristics fulfills requirements".

It is also important to know that the requirements or needs of the project may be stated or merely implied. A product may be low grade and high quality at the same time if the requirements call for a low grade product.

Total quality management (TQM)

This is a quality theory popularized after World War II stating that everyone in the company is responsible for quality and is able to make a difference in the ultimate quality of the product.

TQM applies to improvements in processes and in results, in addition, it also includes statistical process control.

TQM was invented by Walter Shewhart at Western Electric, however it was W. Edwards Deming who made it popular by implementing it successfully in Japan after World War II. Today, Japan gives the Deming Prize as their national award for quality.

TQM shifts the primary quality focus away from the product that is produced and looks instead at the underlying process of how it was produced. It involves form employees in the quality process.

In other words, how something is produced becomes more important than what is actually produced, because a good process will ultimately yield good results.

Continuous Improvement

This is also known as "Kaizen", from the Japanese management term. A philosophy that stresses constant process improvement in the form of small changes in products or services. It comes from the Plan-Do-Check-Act cycle described by Shewhart and Deming.

Continuous improvement seeks to make an ongoing series of small changes to improve the product and the process.

Just-In-Time (JIT)

This is a manufacturing methods that brings inventories down to zero (or near zero) levels. It forces a focus on quality, since there is no excess inventories on hand to waste.

ISO 9000

Part of the International Organization for Standardization to ensure that companies document what they do and do what they document. ISO 9000 is not directly attributable to higher quality, but may be an important component of the PMBOK Manage Quality process, since it ensures that an organization follows their processes.

Statistical Independence

When the outcomes of two processes are not linked together or dependent upon each other, they are statistically independent.

Rolling a six on a die the first time, neither increases nor decreases the chance that you will roll a six the second time. Therefore, the two rolls would be statistically independent.

Mutually Exclusive

This is a statistical term stating that one choice excludes the others. For example, painting a house yellow and painting it blue or white are mutually exclusive events. Likewise, flipping a coin results in an outcome of heads or tails. One result excludes the other.

Standard Deviation

The concept of standard deviation is an important one to understand for the exam. Standard deviation is a statistical calculation used to measure and describe how a set of data is organized. The following graphic of a standard bell curve illustrates standard deviation:

Standard deviation, represented by the Greek symbol sigma, is calculated first by averaging all data points to get the mean, then calculating the difference between each data point and the mean, squaring each of the differences, and dividing the sum of the squares differences by the number of data points minus one.

Finally, take the square root of that number, and you have the standard deviation for the data set.

If the data set is " normally distributed", as it is in the following chart, the following statistics will be true:

The standard deviation may be used in a few different ways in quality. For instance, the higher your standard deviation, the more diverse your data points are. It is also used to set quality levels and control limits to determine if the process is in control.

Even though you should not expect to have to perform standard deviation calculations for your PMP Exam, you will likely see questions related to the application of the standard deviation. The more you understand about this concept, the more prepared you will be for your PMP Exam.

Six Sigma

This is a popular philosophy of quality management that focuses on achieving very high levels of quality by controlling the process and reducing defects. The defect is defined as anything that does not meet the customer's quality standards.

One Sigma is defined as one standard deviation from the mean.

At the level of one sigma quality, 68.25% of all the outputs will meet quality standards.

At the three sigma quality level, that number jumps to 99.73% of all the outputs that meet quality standards.

At the six sigma level, the number is 99.99966 percent of all the outputs that meet quality standards.

This means that when quality reaches six sigma standards, the results will be such that only 3.4 out of every one million outputs do not meet quality standards.

Six sigma quality strives to make the overwhelming majority of the bell curve, consistently within customer quality limits.

Six sigma puts a primary focus on quantifying, measuring, and controlling the quality of products, services, and results. It is based on the underlying theory that anything will vary if measured to a fine enough level.

The goal is to refine the process so that human error and outside influence no longer influence results, and any remaining variations are completely random.

If done properly, the statistical outcome should follow the topic illustrated previously under the topic of standard deviation. The goal is to make six standard deviations (6 sigma's) of the outputs, fall within the customer's quality limits.

If this seems like a lot of information, the most important things to know for your PMP Exam, is that six sigma is a quality management philosophy that sets very high standards for quality.

One sigma quality is the lowest quality level, allowing 317,500 defects per one million opportunities

Three sigma quality is higher, allowing 2700 defects per one million opportunities

Six sigma quality is the highest of these, allowing only 3.4 defects per one million opportunities

Also know that six sigma quality levels may not be high enough for all projects or all industries. As an example, the pharmaceutical industry, the airline industry, and power utilities typically strive for higher levels of quality and six sigma would specify in some areas of their production and operations.

Prevention verses Inspection

Prevention is simply keeping defects from occurring, while inspection is about identifying and catching the errors that have occurred before they impact others outside the project.

Project management strongly favors prevention over inspection.

Attribute Sampling verses Variable Sampling

Attribute sampling is binary - either a work results conforms to quality or it doesn't.

Variable sampling, on the other hand, measures how well something conforms to quality. Consider for example, a production facility making prescription drugs. Using attribute sampling, they would define tolerances, a batch of product would be tested, and it would either pass or fail that inspection.

Using variable sampling, the batch of product would be rated on a continuous scale (perhaps on parts per 1,000,000,000), that showed how well the batch conforms to ideal quality.

Special Causes verses Common Causes

Within the topic of statistical process control, there's a concept of special causes and common causes.

Special causes are typically considered unusual and preventable, whereas common causes are normal.

For example, if your manufacturing process produces to one and 50 defects or one million due to assembly errors, that might be considered a special cause, whereas if your manufacturing process produced one defect in a million due to fluctuations in the quality of raw materials, that might be considered a common cause.

Special causes are considered preventable by a process improvement, while common causes are generally accepted.

Tolerances verses Control Limits

Tolerances are to do with the limits your project has set for product acceptance. For example, you may specify that any products will be accepted if it weighs between 13.7 g and 15 g. Those weights would represent your tolerances.

Control limits, on the other hand, are a more complex concept. Typically, control limits are set at three standard deviations above and below the mean. As long as your results fall within the control limits, your process is considered to be in control.

In summary, consider that tolerances focus on whether the product is acceptable, while control limits focus on whether the process itself is acceptable.

Customer Satisfaction

The concept of customer satisfaction runs throughout quality management. There are two main components to this - fitness for use and conformance to requirements.

The easiest way to think about this is to look at whether the deliverable solves the underlying need and whether it works properly. In other words, does it do the right thing, and does it do the thing right.

Management Responsibility

Everyone from the top to the bottom is responsible for quality, but it is management's job to make sure that the focus stays on quality management and that initiatives have adequate resources and funding.

Mutually Beneficial Partnership with Suppliers

In a quality driven organization, relationships with vendors and the supply chain are particularly critical. These suppliers are an extended part of the organization, and a strong, positive relationships that benefit both parties are key.

Because of this, decisions are made for the long term and not for quick advantage.

Agile Projects

Adaptive and agile methodologies' approach to quality is to get the product in the customer's hands as quickly as possible and to prioritize and adapt constantly.

Quality is an integral part of the project from the start and the focus continues throughout. To make this work, agile takes on small tasks, gets feedback from users, and improves the product.

If a problem occurs, it should be detected early and thus cost less and require fewer resources to fix them if it were detected later.

Keep an eye out for a future article covering the specific quality tools and techniques that are used during the quality management knowledge area and relevant processes.

In the meantime, check out Projex Academies' PMP Masterclass