Why does quality matter to project managers?
First and foremost, the quality of the project you deliver reflects on you as the project manager. Just imagine if the application you deliver crashes constantly… Or if a bridge project collapses because you didn’t ask the right questions about quality. If the latter happened, you may never have the opportunity to manage another project.
Each organization has a different quality philosophy. That said, there are two quality concepts you can use as a foundation. First, product quality – is the “deliverable” of the project (e.g. the unique product, service, improvement produced by the product) of acceptable quality? Second, project quality – are your project processes and methods operating with high quality? As you can see, these quality concepts are connected. If you have a disciplined commitment to project quality, you are more likely to ship a high-quality product.
This article will focus on tools to improve product quality. With some creativity, you may also use these quality tools to improve your project plans, reports and controls.
Opening The Quality Toolbox
As you study for the PMP exam, you will be introduced to several proven quality management tools and techniques. Most of these processes were developed for the manufacturing industry. If you work in software development or some other industry, keep an open mind. These tools have been used to improve performance and eliminate errors for years – they work!
In the manufacturing environment, consistent results are important. Imagine a beer bottle production facility – each bottle must be a certain size and weight in order to be packaged and shipped economically. Control charts are a simple way to measure consistency of production. In a technology project, you can use control charts to detect the number or percentage of errors per million transactions.
Sometimes, the simplest tool is the best one for the job. The histogram displays frequency distributions or how often a given measure occurs. If your project is designed to improve a process, you could use a histogram to understand a process before you start to improve (e.g. how many days does it take the warehouse to ship various types of products?)
It’s been said that failure has many fathers. The same can be said of quality failures. A fishbone diagram is a graphical tool that helps you to visually organize various root causes of quality problems. For example, a malfunctioning application may be caused by poor requirements, suboptimal procurement and inaccurate planning. You may also identify insufficient training as another contributor to poor quality. By pushing yourself to identify each cause of quality failure, you obtain a richer understanding of the problem and possible solutions.
As you progress through your quality analysis, you may end up with dozens of possibilities to investigate. How do you make sense of all this data? Using a Pareto analysis is one of the best ways to identify the causes that matter the most. For example, you may find out that your star software developer is so overworked that the quality of her work starts to decline – her decline due to overwork may cause 80% of problems. In quality management, Pareto diagrams are also useful in identifying which quality problems are worth your time (e.g. classify the 100 most recent complaints about a product into categories and analyze which cause the greatest problems) to investigate.
Resource: For an extended treatment of the Pareto principle and how it can be used to improve your results, read “The 80/20 Principle” by Richard Koch.
How do you understand the relationship between factors when you analyze a quality problem? A scatter diagram is a helpful quality investigation tool. You can use a scatter diagram to test whether there is a relationship between two variables. For instance, you may have an effect (e.g. “the database crashes when new records are added”) and a hypothesis on the cause (e.g. “the database becomes unable after it is open for more than 100 hours”). A scatter diagram makes it easy to determine if your quality hypothesis has merit.
The checklist is a well-established tool to prevent well understood quality mistakes. For example, you may have a quality checklist for software releases that includes testing a website in three different web browsers. Many check sheets are kept in notepads or scraps of paper. For better results, use a spreadsheet like Microsoft Excel instead.
This quality analysis tool is most useful when combined with other quality tools. As an example, you may have twenty values plotted on a diagram. How do you make sense of this data? The stratification technique can be used to look for relationships between quality problems. Keep in mind that a correlation or relationship may not be conclusive on its own.
Looking For More Quality Resources?
The quality movement has made many great contributions. If you’re interested in learning more about quality and how it can improve your project results, explore the following resources:
Balancing quality versus productivity: myth or doable? [PMI]
Sharing insights on Saudi Arabia’s Saudi Aramco quality approach, this article provides an excellent overview of how quality ideas are applied in the energy industry.
A quality management case study: defects in spacecraft electronics components [PMI]
When you go to space, quality is absolutely critical because sending replacement parts and technicians is very difficult! In this article describes how the U.S. government improved quality for spacecraft and related activities.
Quality in project management–a practical look at chapter 8 of the PMBOK® guide [PMI]
How does the PMBOK Guide present quality management? This article breaks down the PMBOK into eight fundamental concepts. Note that this resource is limited to PMI members.
The quality options available to you may feel a bit overwhelming at this point. That’s a perfectly natural reaction. To simplify the process, choose one quality tool from this article and brainstorm ways to apply it to your work. If you’re not sure where to start, start collecting data on defects and other quality problems so you can analyze them further.