Project quality management processes

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I. Contents of project quality management processes

==================In a business, managing workflow is of utmost importance. You dont need to read the PMBOK to know that organization and quality sit high on the priority list. For those of you unfamiliar with the PMBOK, its the religious text for management and stands forA Guide to the Project Management Body of Knowledge.This textbook acts as a guide for everything that falls within the reign of management. It teaches the five process groups of management: planning, monitoring, initiating, executing and closing. It also discusses the nine knowledge areas of project management: scope, time, cost, human resource, communications, risk, procurement, stakeholders and last but not least quality. Its this last knowledge area that we will focus on in the scope of this article.Project Management Essentialsis a course that explores every aspect of cost, time and quality of a project. This course primarily focuses on the construction industry, however, the principles of quality are the same across the board.So what is quality?Simply put, and as defined by the International Organization for Standardization (ISO),qualityis the ability of a company to entirely satisfy implied and stated needs. Okay, so what doesthatmean? The long and short of it means that whatever the company is doing it needs to do it to 100% and should meet all written requirements and specifications while ensuring the products and services function as intended. Lets say you run an ice rink and you rent out skates for customers to use. As an employee, your job is to sharpen the skates, all of them, once a week to double check that the skates are still in one piece and that the blades are sharp. This is a quality assurance measure taken to avoid a lapse in product quality for your customers.To adhere to the ISO definition of quality businesses instill project quality management processes to follow. These processes arequality planning, quality assurance,andquality control.Well get into these in a minute. Project quality management uses the five management process groups, planning, initiating, monitoring, executing and closing as defined by PMBOK to see that theseproject quality management processesare used and upheld. In other words, project quality managers devise plans to assure quality and control. Weve all heard of big business uh-ohs like Toyotas 9 million vehicle recall in 2009 which was huge. (There were problems with the removable floor mats that were causing accelerators to get stuck which resulted in 52 fatal crashes!) The recall occurred because quality assurance and quality control measures were not executed properly. This not only causes Toyota to lose money but they damaged their reputation and were held responsible for52incident related deaths.So if you are wondering why quality management is important theres your answer! Learn more aboutQuality Management Techniques in this course.Quality PlanningQuality planning involves much of what the title implies. Its the steps taken to plan out how to satisfy quality requirements and specifications as dictated by the company. Without a business plan you likely couldnt start a business, right? The same thing goes for the quality plan. Without it, you have no guidelines on how to achieve those standards. The quality planning process should be thorough and include a design that soundly communicates how to meet the needs of the customer. After all, the customer is really who we are trying to serve. Trust me when I say quality matters. For example, youve got the option between buying a Brookstone massage chair with a lot of unique features for $500. That same chair is offered by a lesser-known foreign company that is notorious for low quality products for half the price. Most of us are going to choose the Brookstone chair even though its more expensive, because the company name is reputable, the quality is high and we all know the saying you get what you pay for. We rather make the investment now than potentially end up with a broken chair and be out $250. Proper quality planning allows your company to be at the forefront of your industry. However, creating a plan is only 33% of the process. Lets see what quality assurance is about.Quality AssuranceAlright, so its clear that quality planning is a crucial step toward providing top-notch quality products and services. But words on paper is only a part of it. Quality assurance entails assessing project performance to make sure whats being done is meeting the relevant quality standards. In addition to evaluating these standards, quality assurance managers are responsible for on-going quality improvement. They do this by performing quality audits and benchmarking to understand where quality may be lacking and what can be done to correct it. We can refer back to the Toyota recall for this one. Someone dropped the ball on quality assurance big time. Whether management failed to oversee the projects were meeting quality requirements, or the employees neglected to fulfill their obligation to meet quality standards, I dont know. What we do know is that this major oversight caused Toyota a lot of loyal customers and millions of dollars. Inan Introduction to Quality Management courselearn more about implementing a quality assurance program.Quality assurance management isnt just telling your employees what to do. It involves drafting a quality assurance plan that highlights the purpose, scope, organizational structure, team leaders and the procedures that are to be followed. The quality assurance team is responsible for walking through these procedures and doing quality assurance tests to verify that the techniques in place are actually feasible and beneficial.Quality ControlAt the tail end of Project Quality Management we see quality control. Its this process that ensures all of the quality planning and quality assurance measures taken arecompliantwith the overall quality goals of the company. With quality control, management and workers could mosey on through their days producing terrible quality products unbeknownst to them. Quality control management steps in to say, hey, these [fill-in-the-blank] are not up to our company standards. Where did we go wrong and what can we do to improve it?. Quality control management has a toolbox of techniques to employ when things arent looking so hot. They whip out the quality control charts, do a Pareto analysis and utilize Six Sigma. Lets go over these one by one. Quality Control ChartsAs you may have guessed, quality control charts are, well, charts. They are visual representations of the company quality output over the course of several periods. These charts illustrate whether or not a quality process is in control. If it is in control, the charts should convey a steady or upward trend in product quality results. If the process is not in control, defects will be identified. To analyze if a process is in control or not quality control managers use theseven run rule. Basically, if seven data points on the chart fall above or below the mean there is an issue. The seven points indicate that there are non-random factors at play here and consistency is lacking. All implied processes should be reassessed for assurance. Pareto AnalysisQuality control managers love graphs and charts. The Pareto Analysis uses Pareto diagrams, or histograms, to identify the few contributing factors that are causing most of the quality issues in the company or system. Its also called the 80-20 rule because 80% of the quality problems are frequently due to 20% of the causes. Using the Pareto Analysis, quality control managers can see what functions of the system could be at fault and then they can prioritize them for correction. Six SigmaThe Six Sigma, in essence, encompasses everything weve talked about with a focus on an understanding of customer needs. Through using the Six Sigma system, quality control teams can strive to sustain and maximize business success by utilizing statistics, attention to detail and discipline to execute the planning, managing, executing and initiating business processes. There is a lot of number-fiddling in this quality control technique so Ill save most of the details for another time. However, the Six Sigma target is to achieveno more than 3.4 defects per one million opportunities.In other words, if youre Toyota you messed up, big time.Within Six Sigma there is yet another set of processes to ensure that the company does not go over the meager 3.4 defects per million. This set is called the DMAIC for, define, measure, analyze, improve and control. You can guess what each of these entails. If you cant, readSix Sigma Toolsand the details will be unveiled there. In order for Six Sigma to work the company, as a whole, has to commit to it. This means every department, in every branch, under every kind of manager has to uphold the DMAIC and 3.4 rule. A lot of big name companies like Motorola, Honeywell and GE, use Six Sigma and rather effectively.Total Quality Management (TQM)Okay, so you know all about the umpteen sets of processes that go into project quality management. You know that Six Sigma is a company-wide commitment and that brings us to total quality management (TQM). Within a company there are often several departments, or branches that have different functions. The goal of the TQM approach is to fully integrate all of the quality management processes we just went over to ensure company-wide success and tobeatcustomer expectations. TQM runs from top to bottom assessing every assessment that every assessor in the company has done. At the end, there is a really well-painted picture of the overall quality the company is producing. Executive Management should be the driving force behind TQM, and believe you me they will be with the Malcom Baldridge Award at stake. (Malcom Baldridge Award is a Quality award that recognizes companies with world-class quality.) Risk management is also a part of quality management. Risk managers identify and analyze the risk of any faction of a business. Risk managers and quality managers often work closely in understanding quality processes. Learn more in the courseRisk Management.In the end we see the qualitymatters. It matters for the business and it matters for the customers. Its a two-way dialogue between the customer needs and feedback and the companys ability to meet those needs and address that feedback. Manage superior quality standards for your company; learn from the best in the courseManage Project Quality.==================

III. Quality management tools

1. Check sheet

The check sheet is a form (document) used to collect data in real time at the location where the data is generated. The data it captures can be quantitative or qualitative. When the information is quantitative, the check sheet is sometimes called a tally sheet.

The defining characteristic of a check sheet is that data are recorded by making marks ("checks") on it. A typical check sheet is divided into regions, and marks made in different regions have different significance. Data are read by observing the location and number of marks on the sheet.

Check sheets typically employ a heading that answers the Five Ws:

Who filled out the check sheet What was collected (what each check represents, an identifying batch or lot number) Where the collection took place (facility, room, apparatus) When the collection took place (hour, shift, day of the week) Why the data were collected

2. Control chart

Control charts, also known as Shewhart charts (after Walter A. Shewhart) or process-behavior charts, in statistical process control are tools used to determine if a manufacturing or business process is in a state of statistical control.

If analysis of the control chart indicates that the process is currently under control (i.e., is stable, with variation only coming from sources common to the process), then no corrections or changes to process control parameters are needed or desired. In addition, data from the process can be used to predict the future performance of the process. If the chart indicates that the monitored process is not in control, analysis of the chart can help determine the sources of variation, as this will result in degraded process performance.[1] A process that is stable but operating outside of desired (specification) limits (e.g., scrap rates may be in statistical control but above desired limits) needs to be improved through a deliberate effort to understand the causes of current performance and fundamentally improve the process.

The control chart is one of the seven basic tools of quality control.[3] Typically control charts are used for time-series data, though they can be used for data that have logical comparability (i.e. you want to compare samples that were taken all at the same time, or the performance of different individuals), however the type of chart used to do this requires consideration.

3. Pareto chart

A Pareto chart, named after Vilfredo Pareto, is a type of chart that contains both bars and a line graph, where individual values are represented in descending order by bars, and the cumulative total is represented by the line.

The left vertical axis is the frequency of occurrence, but it can alternatively represent cost or another important unit of measure. The right vertical axis is the cumulative percentage of the total number of occurrences, total cost, or total of the particular unit of measure. Because the reasons are in decreasing order, the cumulative function is a concave function. To take the example above, in order to lower the amount of late arrivals by 78%, it is sufficient to solve the first three issues.

The purpose of the Pareto chart is to highlight the most important among a (typically large) set of factors. In quality control, it often represents the most common sources of defects, the highest occurring type of defect, or the most frequent reasons for customer complaints, and so on. Wilkinson (2006) devised an algorithm for producing statistically based acceptance limits (similar to confidence intervals) for each bar in the Pareto chart.

4. Scatter plot Method

A scatter plot, scatterplot, or scattergraph is a type of mathematical diagram using Cartesian coordinates to display values for two variables for a set of data.

The data is displayed as a collection of points, each having the value of one variable determining the position on the horizontal axis and the value of the other variable determining the position on the vertical axis.[2] This kind of plot is also called a scatter chart, scattergram, scatter diagram,[3] or scatter graph.

A scatter plot is used when a variable exists that is under the control of the experimenter. If a parameter exists that is systematically incremented and/or decremented by the other, it is called the control parameter or independent variable and is customarily plotted along the horizontal axis. The measured or dependent variable is customarily plotted along the vertical axis. If no dependent variable exists, either type of variable can be plotted on either axis and a scatter plot will illustrate only the degree of correlation (not causation) between two variables.

A scatter plot can suggest various kinds of correlations between variables with a certain confidence interval. For example, weight and height, weight would be on x axis and height would be on the y axis. Correlations may be positive (rising), negative (falling), or null (uncorrelated). If the pattern of dots slopes from lower left to upper right, it suggests a positive correlation between the variables being studied. If the pattern of dots slopes from upper left to lower right, it suggests a negative correlation. A line of best fit (alternatively called 'trendline') can be drawn in order to study the correlation between the variables. An equation for the correlation between the variables can be determined by established best-fit procedures. For a linear correlation, the best-fit procedure is known as linear regression and is guaranteed to generate a correct solution in a finite time. No universal best-fit procedure is guaranteed to generate a correct solution for arbitrary relationships. A scatter plot is also very useful when we wish to see how two comparable data sets agree with each other. In this case, an identity line, i.e., a y=x line, or an 1:1 line, is often drawn as a reference. The more the two data sets agree, the more the scatters tend to concentrate in the vicinity of the identity line; if the two data sets are numerically identical, the scatters fall on the identity line exactly.

5.Ishikawa diagram

Ishikawa diagrams (also called fishbone diagrams, herringbone diagrams, cause-and-effect diagrams, or Fishikawa) are causal diagrams created by Kaoru Ishikawa (1968) that show the causes of a specific event.[1][2] Common uses of the Ishikawa diagram are product design and quality defect prevention, to identify potential factors causing an overall effect. Each cause or reason for imperfection is a source of variation. Causes are usually grouped into major categories to identify these sources of variation. The categories typically include People: Anyone involved with the process Methods: How the process is performed and the specific requirements for doing it, such as policies, procedures, rules, regulations and laws Machines: Any equipment, computers, tools, etc. required to accomplish the job Materials: Raw materials, parts, pens, paper, etc. used to produce the final product Measurements: Data generated from the process that are used to evaluate its quality Environment: The conditions, such as location, time, temperature, and culture in which the process operates

6. Histogram method

A histogram is a graphical representation of the distribution of data. It is an estimate of the probability distribution of a continuous variable (quantitative variable) and was first introduced by Karl Pearson.[1] To construct a histogram, the first step is to "bin" the range of values -- that is, divide the entire range of values into a series of small intervals -- and then count how many values fall into each interval. A rectangle is drawn with height proportional to the count and width equal to the bin size, so that rectangles abut each other. A histogram may also be normalized displaying relative frequencies. It then shows the proportion of cases that fall into each of several categories, with the sum of the heights equaling 1. The bins are usually specified as consecutive, non-overlapping intervals of a variable. The bins (intervals) must be adjacent, and usually equal size.[2] The rectangles of a histogram are drawn so that they touch each other to indicate that the original variable is continuous.[3]

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