PMP Basic Quality Management Tools
Quality Management Tools
There are seven fundamental quality management tools used in project quality management, understanding of which is vital for the PMP Certification Exam. A description of these quality tools is mentioned below:
Cause and effect diagram
Also called “fishbone” diagram (since it appears like a fish) or “Ishikawa” diagram (person who founded it). It is one of the most popular quality tools. It is used to determine the root cause of a defect, error, or problem. The issue report is the effect and the likely influencing reasons are the causes. For example, an integration test of a system could fail due to:
• Incorrect coding
• Unsuitable environment
• Inexperienced coder
• Inadequate bandwidth
• Improper test script
Each cause can be evaluated further for a more detailed cause-and-effect diagram.
Flowcharts: It can assist to establish the association between the process stages. This information can be used for process improvement, and to identify the source where errors or problems may occur. Flowcharts are also useful for documentation of processes.
Can be employed for ensuring that certain necessary actions are taken constantly. Check sheets can also assist for organizing data of a quality issue. For example, frequency of a particular cause is the basis of a defect, and this information is used to create a histogram or Pareto chart for prioritization of quality problems.
These are vertical bar charts for creation of a graphic demonstration of outcomes (types of defects or causes of defects) in a descendent arrangement. The aim is problems ranking based on the occurrence frequency, to establish the resolution sequence of the problems.
Histogram is also one of the popular quality management tools. It is a vertical bar chart, as in the Pareto diagram. However, the vertical bars are not plotted by frequency. The vertical bars display the distribution of an occurrence. For example, the shape of calls distribution received by a center. It indicates the range of results called dispersion, and also the mean or median.
Used to establish if a process is predictable and steady. The process planned value is represented by the center line . Normally, in manufacturing processes, +/–3 standard deviations are used, which are the upper and lower control limits for the manufacturing team. The upper and lower specification limits are those limits which are indicated in the agreement or contract by the sponsor. If a measurement is near to the control limit, the project manager should take corrective action so that it is near the center line. PMBOK defines as under:
• Control chart. A graphic display of process data plotted over time and against established control limits. It has a center line that facilitates detection of a trend of plotted values, compared with upper and lower control limits.
• Control limits. The area comprised of three standard deviations on either side of the mean or center line, of a normal distribution that indicates the desired data variation.
Specification limits. The area on either side of the mean, of data on a control chart that meets the requirements of the customer for a service or product.
Although control charts were originally used for monitoring of repetitive and manufacturing processes, they can also be effectively used for tracking of defects, schedule and cost variance, or any other project activity. These control charts are extremely useful in Earned Value Management, which is a project tool to identify cost and schedule variances.
It is a matrix that displays the plotting of two variables, to establish existence of any relationship. For example, weekly working hours and the errors noticed during this period. A correlation may exist to indicate increase in defects with increase in the working hours. Consequently, after analysis, corrective or preventive actions may be taken.
These quality tools help improve business processes as well as the product, which in turn help you satisfy the customers by delivering products that meets his expectations.
- Hits: 63