Practice Exams:

PMI PMP Project Management Professional – Project Quality Management Part 2

  1. Considering the Cost of Quality

Let’s talk about the cost of quality. It’s not cheap to get quality into your project. Quality takes time. It takes having the right tools and equipment, the right materials. So there’s a cost associated with that. There are two terms that we need to know when it comes to the cost of quality. We have the cost of conformance to requirements and we have the cost of non conformance to requirements. The cost of conformance to requirements, sometimes just called the cost of quality, describes the monies that you have to spend in order to ascertain the expected level of quality in your project.

So safety measures, you have to do team development and training, having the right materials, the right equipment, using the right processes. That’s all the cost of conformance to requirements, the cost of quality, the cost of non conformance are all the bad things that happen when you don’t have quality because you’re not conforming to requirements. So you could have liabilities or loss of life or limb, somebody’s going to get injured and that’s no good, we don’t want that at all. You might have rework or scrap, we have to start over and go buy more materials. You might have loss of business so you have poor quality, didn’t conform to requirements, and you get fired or your company gets fired from that project.

So that’s no good. Some types of quality cost we have prevention appraisal and failure. Prevention is back to quality assurance. It’s where we’re delivering exactly what was requested. So we are taking the time, we have the training, the safety measures, having the right equipment, we’re doing the work correctly and we’re spending the money to ascertain quality. So it’s a prevention quality. Cost appraisal is the time and money you need to go out and measure and test and inspect, audit and evaluate the results of what you’ve created.

And so it’s typically appraisal, we think about time to do an appraisal. A failure is cost of nonconformance. We’ve had poor quality, so we have internal failure that’s scrap and rework. We have to throw away the stuff and start over. You’ve lost time and you’ve lost money for the material and the labor. External failure failure are loss of sales, loss of customers, downtime and even damage to your reputation. So that’s a failure cost. So prevention is QA, appraisal is controlling quality and failure is the negative outcome. The cost of poor quality. So those are some terms you should be familiar with for your exam.

  1. Creating the Quality Management Plan

Now, let’s talk about one of the primary outputs of planning for quality, the Quality management plan. The Quality management plan defines how will you control quality? How are you going to go out and monitor the results of what you’ve created for quality standards? So, poor results, we might might need root cause analysis. So why are we having these poor results? Quality control, or the process is technically called control. Quality is all about inspecting what’s been created. Managing quality is your performance has to meet quality standards. So you want to do the work correctly. This is our QA activities, quality assurance activities.

QA is typically a managerial process that it’s built into the work, it’s built into the approach. Quality improvement are corrective actions. You have to fix the problems. Now, it’s interesting. Improvement will depend on a quality philosophy in the organization. So what’s the attitude towards quality? What does quality mean in your organization? That affects our quality management plan and how we do the work. Within the quality management plan, we have our quality standards, we have our objectives for quality. What are the roles and responsibilities of quality? Who will test and inspect? Who will help implement the work correctly the first time?

So what are the roles and responsibilities? What deliverables and processes will we review for quality? What tools do we have available? And dealing with nonconformance. So we have corrective actions, we have continuous improvement procedures. So that poor quality or failure. How do you respond to it, how do you react to it and recover from that and keep your project moving forward? Also, in the quality management plan, we have metrics.

Those metrics, as I mentioned, we’re talking about the project or a characteristic of the product, how well something should conform. So that goes back to our requirements. We need to know what is good, what is fast, what is reliable, and that sets us up for our targets to have these quality metrics so we have something to measure. Quality control is used.

Remember, it’s inspection driven. And our goal here is to verify compliance. So the process of control quality, we’re looking at things like what tasks were finished on time? What’s our failure rate? How many defects happened in a given time period? What’s our downtime? How many errors did you find? And what about customer satisfaction scores? So it’s not just inspecting the deliverable, but also how we got to that deliverable. All right, that’s the quality management plan.

  1. Manage Quality

Our next process to discuss is Manage Quality. Manage Quality is ensuring that the work is done properly. So this is an executing process, that we do the work correctly. We have quality built into our approach. So Manage Quality it’s really all of our planning and the implementation. Sometimes we call it QA for quality assurance. The technical process name is manage quality. QA or Manage Quality happens before and during project execution. Continuous process improvement is part of managing quality. We want our processes to be executed properly.

Managed quality is everyone’s responsibility. That’s a good exam question. You might have a QA department and they will tell you or they will do the QA activities for your project. Let’s look at the ETOs for manage quality. The inputs, the project management plan, specifically the quality management plan. We have project documents, the lessons learned register, quality control measurements, quality metrics, and the risk report and organizational process assets. Now, tools and techniques here for managing quality, we have data gathering, specifically checklist.

We have data analysis. So we’re talking about alternatives analysis, document analysis, process analysis, and root cause analysis. We have decision making. Once again, that multi criteria decision analysis, data representation. So affinity diagrams. We’ll see a cause and effect diagram, flowcharts histog diagrams, matrix diagrams and scatter diagrams. We’ll do audits to ensure that we’re adhering to our QA policy. We’ll design for X a new term. We’ll do problem solving and quality improvement methods. Our outputs of managed quality will have quality reports. We’ll have our test and evaluation documents change request.

You’ll have updates to the PM plan, specifically your quality management plan, the scope baseline, the schedule baseline and the cost baseline. And then we have updates to our project documents like the issue log, lessons learned, and the risk register. Let’s look at some key tools and techniques. Here a checklist. We’re doing the same type of work over and over. So let’s develop a checklist so the work is executed properly. Again, alternatives analysis, documents analysis. It’s a good way of understanding what our quality requirements are.

What about process analysis? Are we doing our 49 processes correctly? And our internal processes, are they holding us back? Are they a constraint? Root cause analysis? We’ll see this again with control quality, but it’s a way of studying what causal factors are contributing to the effect, to the problem. A matrix diagram is just a table. A scatter diagram is a way of tracking two or more variables. And the closer they trend, the more likely there’s a relationship between the two. We’ll see that in quality control as well. And then a cause and effect diagram is a way to visualize our root cause analysis. Flowcharts is just order in, order out.

It’s a flow of data, a flow of information, how things interact with one another and move through a system. And a histogram is just a bar chart. It’s all a histogram is. You may have to complete a quality audit in your project. A quality audit is a way to document the best practices that were used and what you need to improve upon. So any variances what needs to be improved. So recommend some best practice practices and then we document the quality audit in Lessons Learned. So completing a quality audit okay, great job. Keep moving forward. I’ll see you in the next lecture.

  1. Design For X

A new term in the PMBOK Guide, 6th edition is designed for X, sometimes called DFX. Design for X is a philosophy and product design. That means we’re going to take the most important attribute, whether that’s excellence or reliability or throughput. And that’s what we’re building our whole design around. So it’s a specific characteristic of a solution.

So it’s what we’re designing everything for, is the ability to do this one particular solution. As I mentioned, design for X can also be called DFX. The X is some variable that you’re trying to address. The generic one is just excellence, but you might be cost or uptime return on investment. Your goal here is to identify what’s the most important element or solution and then you build around that.

So how do the other components affect the X variable? The goals are typically lowered cost, improve service, reliability, safety, just overall quality. That’s designed for X. Now tied to design for X. We might have some problem solving techniques.

So some approaches here. You want to define the problem, define your root cause, generate a solution, select the best solution for that problem, and then you implement your solution. And then you verify how effective that solution was. So define it, then define the root cause, solution, solution, select it, implement it and then verify, okay, that’s designed for X and a little bit of problem solving. I’ll see you in the next lecture.

  1. Results of Managing Quality

Let’s talk about the results of managing quality. Of course, this is a process that’s done throughout the project. So it’s not like you do it once and you’re done, but you do it throughout. So you’re going to have these outputs over and over like the quality report, your test and evaluation documentation, and then you might have change request. Other results of managing quality may be updates to your project management plan. So based on what you discover, allows you to go back and change your plan to adjust things to meet quality.

So you might update the quality management plan, you might update the scope baseline, the schedule baseline and the cost baseline. You could also have updates to your project documents like the issue log, your lessons learned register, and even the risk register. So these are the primary outputs from managing quality. Very important to note here, managing quality is an executing activity.

So recall in our project management lifecycle, you go from planning to executing and then down here we have monitoring and controlling. And then from monitoring and controlling we can go back to planning, we can also go back up to executing. So we had this iteration of plan do check and then you act. So PDCA that dimming cycle is somewhat built into our approach of planning and managing and as we’ll see coming up, controlling quality. So keep that in mind as we go through these processes. All right, good job.

  1. Controlling Quality in a Project

Our last process for quality project management is to control quality. So controlling quality in a project is all about inspection that we are monitoring and measuring the results of what we have executed. So execution, monitoring and controlling or controlling quality. When we have a problem, we need to do some root cause analysis. So root cause analysis follows quality control. If we identify a problem, we need RCA root cause analysis. This helps us determine the cause. It doesn’t solve it, but allows us to see what causal factors are contributing to the problem, to the effect. And then we apply corrective action. QC happens throughout the life of the project.

It’s part of monitoring and controlling. It goes through the whole project all the way up to scope validation. When the customer signs off, they accept what we’ve created. We do QC first, then validation. Controlling quality is for the product, of course, but also the project. Those different processes, the 49 processes we’re measuring performance, scheduling and cost and how does quality exist or does it exist and is it at our expected level? And if we have management of the project, we should be of quality. That quality is planned into the project and this includes the execution of our project management processes.

Some themes for controlling quality we need statistical quality controls. We have sampling and probability. So sampling, we go out and we test things at random and then from that we can begin to identify trends and find some probability. The goal of quality control is to keep mistakes away from the customer. Now attribute sampling and variable sampling. So two similar types of sampling here. Attribute sampling is just very simple. Is it in conformance or out of conformance? Does it conform or does it not conform? It’s that binary.

One variable sampling is where we say it doesn’t conform, but it’s just a 16th of an inch off and that’s within our range of variance. Or it doesn’t conform and it’s a quarter of an inch off and that’s too much. So how far is it to still be considered of quality? So what’s that range of variance that allowable tolerance range when it comes to the results of measuring our products, some other themes with controlling quality we need to study special causes and we’ll talk about that in a control factor. Why are we having this anomaly in the project? Why is this one area dipping out of control? Random causes will help us then determine variances and allow us to check a tolerance range. Helps us also to observe our control limits. So we’re talking about our upper specs and lower specs and then within that we have a control limit, upper and lower control limits and we’ll see that in a control chart coming up. First though, let’s look at our edo’s for control quality, our inputs.

We need the project management plan, specifically the quality management plan, project documents. These will be the lessons learned register quality metrics, test and evaluation documents, approved, change request, deliverables work performance data and EEF and OPA tools and techniques. Here we have data gathering, so checklist, check sheets, statistical sampling and questionnaires data analysis. We’ll do performance reviews, root cause analysis, inspection.

We’ll have testing or product evaluations. We’ll use multi criteria decision analysis. Then we have data representation, so, cause and effect diagrams, control charts, histograms scatter diagrams, and of course meetings, our outputs, quality control measurements, verified deliverables work performance information, change request, project management plan updates. Specifically, you’ll update the quality management plan and it will have updates to some project documents. Documents the issue log, the lessons learned, register and test and evaluation documents. So those are the Edo’s for control quality. All right, keep moving forward.

  1. Inspecting Results

The number one way to control quality to do this process is through inspection that you or your project team or a third party has to go out and inspect the results of what you’ve created. We’re inspecting the results of what was created because we want to keep mistakes out of the customer’s hands ends. We don’t want the customer to see those mistakes.

So we have to go out and do a review or a product review. You might call it an audit or a walk through, but you’re really inspecting. You’re making certain that it’s of quality, that what you’re creating is going to work and operate. That the way the customer expects. So you’re confirming that you have a conformance to a requirement and that what you’re creating is fit for use. So inspecting the results, when we inspect results, it’s an opportunity to do data gathering and to have some analysis of that data. A checklist is a great way to ensure the work is done the same way each time. Ideal for repetitive task. You have a thousand fixtures to install. Step one, step two, step three.

And the team member checks those off as they do those activities. So you might have ten different people installing these different fixtures, but if everyone follows the checklist, it’ll be done the same way each time. A check sheet is a little bit different than a checklist. A check sheet helps organize data when you have a quality issue. So you might also know this as a tally sheet. So imagine that you’re manufacturing cars. You could have a check sheet where you go out and you do a little tally of any car that has a scratch, any car that the windows aren’t rolled up all the way, any car that has a defect or a dean on the body of the car. So you have a little tally.

It’s all the different issues, but how many of each issue so you can tally up the defect? X so a check sheet do the same work over and over. See, I messed it up. A checklist is when you do the work over and over and over. A check sheet is a tally sheet. It’s totally up the number and the type of defects. Okay, good job. I’ll see you in the next lecture.

  1. Testing and Product Evaluations

We know that control quality is all about inspection. Let’s talk a little bit more about some approaches to inspect. In particular, we want to see testing and product evaluation. So testing is where we are testing the product against our quality standards. Does it meet our standards for quality which have it does. It means it’s acceptable that the customer should sign off on it in scope validation. Testing and product evaluations though, is unique to your discipline. What you test and what you evaluate in your discipline is probably different than It or healthcare or manufacturing or whatever project an individual is working in. In software development we want to find bugs and errors in construction.

 We might be looking for electrical and plumbing and HVAC issues. And then we do this throughout the project. Not just at the end, but as we create things we do testing and product evaluation. It’s real tempting to do this right before you do scope validation, but that can be costly. Might be a quick fix early on, a costly fix later because other things may be built upon that error. Statistical sampling. I mentioned this earlier, back when we talked about managing quality. Statistical sampling. We go out and we do a random selection.

So from our pool of deliverables we choose four or five items or maybe 20 or 30 items is more appropriate. And so from that, the number of defects we find in that small sampling is a reflection of what it’s going to look like in the whole population. So for example, if we had a project to install 1000 doors, new doors throughout an office building, we might go visit 200 doors and inspect how it was installed. And out of those 200, if we find 20 doors that were incorrectly installed we might say out of a thousand, then we could expect 100 doors to be installed incorrectly. So that’s an idea of statistical sampling. A very simple example, I know.

But statistical sampling is the small sampling is a reflection of the pool as a whole. Now let’s talk about a cause and effect chart. We’ve seen cause and effect a couple of times. This shows the relationship between the variables in a process and how you have causal factors contribute to poor quality. That’s the effect. The effect is the problem, the poor quality. So it will help us organize our processes, help us facilitate the conversation with the team. So to create this diagram we’re going to look at in a moment, we start out with the effect, the problem and then we begin to branch off of that with possible causes. This is also known as an ishikawa diagram or a fish bone diagram.

So let’s look at one. This is a cause and effect chart. Notice the effect there in green? That’s the problem. And then see how it looks like a fish bone. We begin to branch off with these big causes and then off of those causes we can even get more granular and have contributing causes. So it doesn’t solve the problem, but it facilitates the conversation with the team. It helps us do root cause analysis. So know this it’s a cause and effect chart, also known as a fishbone chart or an Ishikawa chart. All the same thing. All right, good job. I’ll see you in the next lecture.

  1. Creating Flowcharts and Control Charts

In the last lecture, we looked at a cause and effect chart, also known as a fishbone chart, or I know you said it right, an Ishikawa chart. So let’s look at some other charts you’ll need to know for your exam. A flow chart will illustrate the flow of a process through a system, like order in order are out or how you go about procurement. So it’s how do you flow through that system? A process flowchart. You don’t have to limit this to just our project management activities. So it could be, how do you choose a vendor in your organization or how do you deal and schedule an inspector to come out and inspect the work. So a flow chart shows how you get to that result.

This is a flow chart, could draw it out on a little napkin, have some loop backs and branching, but you probably are going to use something like visio or some other tools to show all the possible routes to the end result. So that’s just a flow chart, just how you flow through a system. A control chart is typically used in operations where we have repetitive activities like manufacturing or a call center. So it’s a way to track results of a batch or a population that we measure the defects or in compliance of each one of those batches. So we’re going to look at a control chart.

Now, within a control chart, some characteristics. Here the specs that we’re going to see in a moment on the next slide here. The specs are established by customer requirements, those metrics that we talked about upfront within the customer requirements, we have upper control limits and lower control limits. So that’s kind of the worst and the best that we expect to do. The upper control limits is typically plus or minus three sigma.

So you could say plus three sigma or six sigma. You don’t have to fall in love with these sigma values. Just know the greater the sigma, the tinier the amount of errors there are. So don’t worry about those too much for your exam. I just put these in here for an example. You can see plus or minus one sigma. We’re talking about 68%. Plus or minus two, you’re talking about 95% and then 99. 73, and then six sigma, 99. 99%. Okay, so those are our sigma values. This ties into our control chart. Those percentages. We’re talking about accuracy and defects. So here’s the scenario. So here’s a control chart, and this is the scenario I always use. It’s very easy for us all to grasp. We have a project to improve upon, a service, and the service is a call center.

The customer has said out of 1000 phone calls, you need to answer at least 980 of those correctly. So our upper spec is 1000. We could answer 1000 out of a thousand correctly. Our upper control limit is the goal of 980. That’s our control, where we should be is 980. That’s our target. Now, the lower spec, the customer says you have to you must answer at least 950 correctly. So our lower spec is 950. And then we have our lower control limit, which would be we’re going to back off of that. We could do the math, but I’m going to say it’s 970.

The mean is where we expect the results to be. So in this example, our upper control limit is 980. And our lower control limit we said was 970. So we’ll take the mean right in the average of 975 each peak in valley in the results of our measurement here, that green line going up and down, that represents 1000 phone calls. So that first one, we answered about 973. So we’re still within our control limits. And then we go up and maybe we answer 977 still in control, and then back down a little. And then we peak up. We had a whole bunch of easy calls. So we were up around 983. Technically, that 983. That one that peaks up above our upper control limit is considered out of control. Then you can see a little bit more action. And then, look, we have a big dip. Maybe there was a big problem on the network or there was a virus or who knows, but there was a big problem.

And we got a lot of phone calls all at once. And we only answered about 940. And then it took a dip and we only answered about 935. That’s also out of control, and that is an assignable, cause we went below our lower specifications here. So that’s an assignable, cause the next term to know here is the rule of seven. And it’s also an assignable, cause whenever we have the results of seven measurements in a row on one side of the mean above or below, that’s a trend. There’s something happening there. So it’s seven in a row on one side of that mean. So in this example, you know, we’re like 973-97-4971. We’re not kicking across that mean. Seven in a row. That’s non random. That’s the rule of seven. So that’s a control chart. It’s a trend that we’ve identified there. All right, good job. Know these different charts for your exam.

  1. Creating Pareto, Histograms, Scatter and Run Charts

There are still some more charts you should be familiar with for your exam. So let’s take a look at those. Now, the first one I want to show you is a Predo diagram. Predo was an Italian macroeconomist who was out picking peas in his garden and he noticed that 80% of his crop came from just 20% of his peas. 80% of his harvest came from 20% of his pea plants. So he’s the guy who developed that 80 20 rule. If you’ve ever worked on Help Desk, you know the 80 20 rule. 80% of your calls will come from 20% of the users, all right? Or 80% of your income will come from 20% of your businesses. So perto diagram, a predo diagram is a bar chart. It’s a histogram that shows categories of defects from largest to smallest. So in this example, this is the total number of failures for a tractor or for a scanner rather. And you can see the biggest number of failure we have are the skills.

People don’t understand our software. So we’ve got a problem with our software, the skills, it’s too difficult to use. And then we have the tractor, that device that will move the light back and forth, and then the actual lights burning out. Then we have a USB problem and so on. So it’s the largest category of failures down to the smallest failure. The little bar chart. You see the little connected dots you see across the top? That’s the total. Each dot represents the upstream number of failures in the current failure. So if we look at the light, the little dot above the light, that’s a total of about 380 failures. And that accounts for the light, the tractor, and the skills.

So the closer we get to 100% on the right, the more defects we’re including in this analysis. Usually we focus on the big problems first as those are resolved or they begin to diminish. Then we rearrange this order and then we attack the next big problems, rearrange it and the next big problem and so on. So that’s a pareto diagram. A pareto diagram is really a bar chart. Another name for a bar chart is a histogram. This is a histogram to show how vendors, management and different teams are performing or whatever you’re tracking here, number of change requests, where they’re coming from, or issues or what have you. But it’s just a bar chart.

So a histogram just a bar chart. Nothing to get too excited about. A Scatter diagram shows the relationship between two variables. So these dots represent the sampling. So this first one, the taller an individual is, the bigger the shoe size. So you can see those two have a pretty positive correlation that they’re tracking together pretty closely. Then we have soup sales. The colder it is outside, the more soup we’re selling. So that also has a correlation here.

And then shoe size and annual income doesn’t really look to be correlated. Just because you have big feet doesn’t mean you make more. So there’s some correlation here. You have a positive correlation that as one quantity increases, so does the other. A negative correlation. As one quantity increases, the other decreases. So the warmer it gets, the less soup you sell. Who wants soup in the summer? And then no correlation like the shoe size and your income. Those don’t necessarily correlate with one another. Then we have a run chart. A run chart is similar to a control chart. The difference is the little dots you see. The closer those dots are together. That shows the time it took to accumulate that pool that you’re measuring. So earlier we said each one of those was 1000. So you can see those dots at the top that are very close together.

That means we have a short amount of time to do those 1000 instances. The farther away the two dots are, then it took longer to accumulate 1000. So there may not be a correlation between the two. This also shows us a trend. When you have five or more data points all going up or all going down, it means you have a trend. If you have two or more at the same value, you only count one of them, especially if they’re close together.

So this is an example of a run chart that you’re running across the calendar. It’s like a control chart, but it’s across the calendar. We have a trend in this instance. All right, so those are some charts. You should be familiar with a lot of charts when it comes to quality control, or control quality, as we’ll call it, for you’re exam. All right, great job. Keep moving forward. I’ll see you in the next lecture.

  1. Completing a Statistical Sample

Let’s talk about statistical sampling. So much fun. So a statistical sample is when we go out, we get a percentage of the results. We just pick them out at random and then, based on those results, gives us some insight as to how the rest of the population will look or what we can expect for the remainder of the project. It also allows us to begin setting some goals for improvement. So it’s a percentage of results at random. So, for example, we went out and we picked 20% of all units randomly, and we checked quality on that 20%.

So that 20% would be an indicator for the remainder of the project, the other 80% of that batch of whatever we’re creating. So it has to be completed, though, on a consistent basis on a regular schedule or throughout your manufacturing or throughout your project. You just can’t randomly do this. You have a set every time there’s an opportunity to do that batch of 1000 and you’re going to go out and grab 20%, you do it. Statistical sampling can help us make changes in improvement.

So that can reduce the cost of quality control. If we had to inspect every single item, that could be very expensive. So statistical sampling, especially in repeatable processes, is a way to bring that cost of quality control down. However, if you don’t have a good testing plan, if you don’t have a regular schedule, it can be hard to do. If you want to do statistical sampling, there is a catch. What you’re inspecting has to be the same thing. So I can’t go out and inspect the installation of doors, and that would tell me if the windows are installed incorrectly.

So it’s like these water bottles here, they’re all the same. They’re all to be uniform. So when I go do a sampling, it has to reflect the rest of that population. So statistical sampling on a regular basis, you need a testing plan or a sampling plan, and you do it throughout the project on the same types of deliverables. All right, good job. That’s statistical sampling.

  1. Meet Your Quality Goals

All right, you’re doing fantastic. You’ve made it through chapter eight in the Peach Guide, 6th edition, on managing quality. In this last section, we talked about planning for quality, managing quality and controlling quality. But let’s think about those terms. In light of your PE and P exam, what’s the goal? What’s the requirement for your PMP exam?

It’s not to get a 100, it’s to pass. So quality on your PMP exam is a passing score. Now, think about the quality in your study efforts. Are you studying? But you’re also checking your phone, checking Facebook and your email. You’ve got the TV on in the background.

Surely all of those distractions are going to affect the quality of the process of studying. So keep quality in your study efforts. Get rid of those distractions and really use laser like focus on the materials in this course and on your study materials, your flashcards and your notes that you want the process to be good, you want the process to be of quality.

And that’s just going to be part of building quality in to your deliverable of passing the exam. Well, you might say, well, where does quality control come in? Where does the inspection come in? When you hit the submit button on the test, it’s going to inspect your work. It’s going to inspect your answers and give you that passing score. So quality is part of the process, quality as part of your efforts to pass the PMP. So keep up the good work, keep up the quality. Keep focusing on the material. I have confidence that you can do this. Keep pressing forward.

  1. Section Wrap: Project Quality Management

Great job finishing this section on project quality management, which correlates to chapter eight in the pinback. On quality, we talked about three processes in quality management. We talked about planning quality, assuring quality, and then controlling quality. So those were our three big themes, if you will, or three processes there about managing quality. We also looked at creating the quality management plan and then doing the process manage quality. I know I talked about assuring quality, but really, we’re managing quality. We want quality built in, not inspected in. And then we looked at controlling quality. And what does that mean? What activities do you do with controlling quality? And, you know, the most important one, of course, is inspection.

That quality control or the control quality. We inspect the work that we want to keep mistakes out of the customer’s hands. And then we talked about creating some different charts, the Petro chart, the control chart, the Fishbone diagram. So those different charts you want to be able to recognize for your PMP exam. And then you did an assignment about controlling quality. And then you and I had a frank talk about you meeting your quality goals. All right, good job. I’m really happy that you’re moving forward in the course. You’re covering a lot of material. Look how far you’ve come in the course. Already. You have covered more than what’s left, so you are making great progress, but keep it up. Keep going. I have confidence that you can do this.