A Project Manager in a modern organization will need to rely on an array of concepts and practices to manage a project efficiently. As a project manager, you will also need to use a range of tools that will help you in decision-making and get a clear idea about the health of the project as it progresses. If you are planning to appear for the PMP exam, preparing for the online PMP certification is a guaranteed way to ensure that you are well versed in all the tools that are used in project management.
Control charts in PMP are widely used tools to denote the health of a project or how well the project is performing when compared to estimated values and targets. So. what is a control chart in PMP and why is it so important?
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A Brief History of Control Chart
Before getting into the details of a control chart, let’s explore how it came into practice. A control chart was first used more than a century ago. It was invented by Walter Shewhart in the early 1920s at Bell Labs. The objective of the control chart is to establish measures to alert you when a process is going out of control.
Most processes see a certain amount of variation in practice. A standard mean is the average value you can expect. This is plotted as a line on a graph. Using standard deviation two more lines are plotted on the graph which represents an upper limit and a lower limit. A variation within these limits is not considered a cause for concern. The moment one of these lines is crossed, you will need to step in and find out the reason for this change.
As technology and data collection have advanced, these charts can be generated automatically and will alert you when there is a significant variation. You could add further lines within the limit when you want to exert tighter control over a process.
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Purpose of Control Chart
A control chart is used to keep track of events that signal something going wrong. You cannot manually check all numbers in a complex project to make sure that everything is going according to plan. Processes do not yield the same results every day. A certain degree of variation is to be expected. These variations are part of minor factors that do not deserve attention. These variations may not have an impact on project completion or make any significance to any stakeholder.
When the variation goes beyond a certain extent, there is an extraordinary factor at play. This needs to be investigated and corrected to make sure that the project stays on track. Our certificate course in project management equip professionals with the best practices and concepts that are used in project management.
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Basic Procedure
You can create a control chart and start using it if you have project management software that allows you to do that. In case you do not have that option, it is easy enough to do it on an excel sheet. You can create a line chart based on the average values you have collected.
The mean of the values would become on a straight line. This is the control line. Ideally, all your values should be close to the line.
The next step is to calculate the standard deviation to see how much the values fluctuate during the normal course of business.
Based on the standard deviation you will create an upper limit and a lower limit.
This needs to be significantly higher than the standard deviation. We are looking for events where there is a major and unexpected change quite different in magnitude from the normal fluctuations you expect.
Any value falling outside the control limits will need to be investigated. In the normal course, the values should fall on either side of the control line (mean) if there are seven continuous values on the same side of the line, then this also deserves an investigation.
Create a Control Chart
Let us take the case of a customer service center where there are callers handling customer queries. You are looking at the average call time and using that as a control parameter. You notice that the average call duration is 90 seconds (one and a half minutes). This is now your control line. You calculate the standard deviation and find it to be 10 seconds.
Multiplying the standard deviation by 3, you establish limits. The control chart would alert you if the average call time went beyond 120 seconds or comes down under 60 seconds. Since this is the average call time individual calls, and an exceptionally long or short call occasionally will not have much of an impact on the number.
We look at the values for the entire month of January. Then we plot the values on a chart.
| Day | Average Call Duration (in seconds) | Mean (Control Line) | Upper limit | Lower Limit |
|---|
| 1 | 95 | 90 | 120 | 60 |
| 2 | 107 | 90 | 120 | 60 |
| 3 | 90 | 90 | 120 | 60 |
| 4 | 99 | 90 | 120 | 60 |
| 5 | 99 | 90 | 120 | 60 |
| 6 | 86 | 90 | 120 | 60 |
| 7 | 91 | 90 | 120 | 60 |
| 8 | 85 | 90 | 120 | 60 |
| 9 | 88 | 90 | 120 | 60 |
| 10 | 71 | 90 | 120 | 60 |
| 11 | 91 | 90 | 120 | 60 |
| 12 | 78 | 90 | 120 | 60 |
| 13 | 100 | 90 | 120 | 60 |
| 14 | 99 | 90 | 120 | 60 |
| 15 | 86 | 90 | 120 | 60 |
| 16 | 88 | 90 | 120 | 60 |
| 17 | 89 | 90 | 120 | 60 |
| 18 | 137 | 90 | 120 | 60 |
| 19 | 93 | 90 | 120 | 60 |
| 20 | 98 | 90 | 120 | 60 |
| 21 | 93 | 90 | 120 | 60 |
| 22 | 102 | 90 | 120 | 60 |
| 23 | 89 | 90 | 120 | 60 |
| 24 | 86 | 90 | 120 | 60 |
| 25 | 88 | 90 | 120 | 60 |
| 26 | 80 | 90 | 120 | 60 |
| 27 | 72 | 90 | 120 | 60 |
| 28 | 55 | 90 | 120 | 60 |
| 29 | 73 | 90 | 120 | 60 |
| 30 | 86 | 90 | 120 | 60 |
| 31 | 96 | 90 | 120 | 60 |
For this month you will receive three alerts.
- On 18th the average call duration is above the upper limit
- On 28th the value is below the lower limit
- On 30th there are 7 consecutive values below the control line. This is also an example of the ‘rule of 7’ in project management.
Control Chart Types
You could learn about the diverse types of control charts that are used in different contexts to build on your knowledge.
There are two categories of control charts Variable and Attribute-based. Variable Control charts work by calculating the average values and measuring variations.
Attribute Control Charts deal with counts. It is used in situations where quality is checked with a pass/fail attribute.
There are further types of control charts within these subcategories that you should explore while deciding what kind of control chart works for you.
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Examples of Control Chart
Control charts are used across several projects, especially where quality control is concerned. It has proven to be a useful device over a century, and you can see the principle of application everywhere. Various stock markets across the world have measures in place where they suspend trading when the index moves beyond a certain level in either direction. This is done so that the regular can check for foul play.
During the pandemic, city administrations have been closely monitoring the rate of infections, patients requiring hospitalization and the number of beds available. When numbers shift quickly in either direction it is a cause for concern. While numbers dropping is a good thing a sudden unexplained drop is still a cause for concern. Has there been a reduction in testing? Are we testing in the right clusters? Did we change the type of tests that we were using? Understanding these factors could help in identifying issues and rectifying them.
Control charts are most extensively used in manufacturing and more specifically in quality control. It has been a mainstay in several industries helping project leaders identify anomalies and make timely decisions.
When you’re figuring out the best sources for project management training, you should also pay attention to which program covers all the project management tools. The KnowledgeHut online PMP certification preparation program works by training candidates in understanding both old and new approaches in project management with real-world examples.
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Control Charts are Here to Stay
Widely in use, control charts have evolved into distinct types to be used for different contexts depending on the type of data you are dealing with. Control charts are also popular with six sigma practitioners.
Control charts form one of the many tools at the disposal of a project manager to ensure that the project stays on track and the output matches what was promised. Using and implementing tools that are both old and new will help make the job of managing a project much easier. It will also give more transparency to all the stakeholders and increase credibility and trust across the board.
Frequently Asked Questions (FAQs):
1. What is a project control chart?
A Project control chart in PMP is designed to detect variations within the project and alert you when the values go beyond preset control limits. It helps you to identify variations and patterns that should be investigated.
2. What is the control chart used for?
Control charts are used to identify when a process is going out of control by measuring values which stray from average values. It prompts an investigation into the issue to find the root cause.
3. What is a control chart example?
Control charts are extensively used in manufacturing. Quality of products can be measured accurately once the parameters are set.
Once measurements are standardized and an expected variation is set, control charts will help you identify products or batches that don’t meet the established criteria.
4. What is the rule of 7 in PMP?
The rule of 7 is a principle according to which if there are seven consecutive values appearing on the same side of the control line, it should be investigated even if it does not breach a control line.
