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Home > Blog > Data Visualization > Add-ons > Google Sheets >

A Complete Guide on Control Chart vs. Run Chart

Visualizing trends in Google Sheets is one of the most important tasks you can ever undertake.

control chart vs run chart

Why?

It offers important insights into whether key metrics are on a growing or declining path. With this, you can easily find out whether the main data points are down or up-trending.

Some of the tested and proven charts for visualizing general trends in your data are:

  • Run Chart
  • Control Chart

The visualization designs (mentioned above) are amazingly easy to interpret. Besides, you can use these charts to create compelling data stories.

Google Sheets is a popular data visualization choice among professionals and business owners worldwide. However, the freemium application involves a lot of steps for creating trend analysis-oriented graphs, such as the Control Chart.

Yes, you read that right.

It turns out you can download and install a particular add-in to access ready-made and visually stunning trend-oriented visualization designs, such as Run and Control Charts.

In this blog post, you’ll learn the following:

Table of Content:

  1. What is a Control Chart?
  2. Key Components of a Control Chart
  3. What Does a Control Chart Tell You?
  4. When Should You Use a Control Chart?
  5. Benefits of a Control Chart
  6. Limitations of Control Charts
  7. What is a Run Chart?
  8. Components of a Run Chart
  9. When Should You Use a Run Chart?
  10. Benefits of a Run Chart
  11. Limitations of Run Charts
  12. Difference Between a Control Chart vs. Run Chart
  13. How to Create a Run Chart in Google Sheets?
  14. Wrap Up

Before addressing the main theme of the blog, we’ll address the following question: what is a Control Chart?

What is a Control Chart?

Definition: The Control Chart is one of the best charts you can use to examine how a process changes over time. In this chart, data is plotted in time order to analyze the data.

The chart has:

  • A central line for the average
  • An upper line for the upper control limit
  • A lower line for the lower control limit

These lines are determined using data gathered.

By comparing current data to these lines, you can easily draw conclusions about whether the process variation is consistent (in control) or unpredictable (out of control) and affected by special causes of variation.

The control chart is among the seven basic quality control tools and is used in many industries.

Control Charts are best used in pairs. The top chart monitors the average or the centering of the distribution of data from the process. And the bottom chart monitors the range or the width of the distribution.

The control chart was invented by Walter A. Shewhart working for Bell Labs in the 1920s.

The company’s engineers had been seeking to improve the reliability of their telephony transmission systems. Because amplifiers and other equipment had to be buried underground, there was a stronger business need to reduce the frequency of failures and repairs.

By 1923, engineers had already realized the importance of reducing variation in a manufacturing process.

They had realized that continual process adjustment in reaction to non-conformance increased variation and degraded quality. Shewhart framed the problem in terms of common and special causes of variation.

In 1924, Shewhart wrote an internal memo introducing the Control Chart as a tool for distinguishing between the two.

Key Components of a Control Chart

  • The chart has points displaying a statistic (example- mean, range, proportion) measurements of a quality characteristic in data taken from the process at different times.
  • A center line is graphed at the value of the mean or median of the statistic
  • Upper and lower control limits that indicate the threshold at which the process output is considered statistically ‘unlikely’ and is drawn typically at 3 standard deviations (3 SD) from the center line.

Keep reading because, in the coming section, we’ll address the differences between Control Chart vs. Run Chart. Also, we’ll address the following question: what does a Control Chart tell you?

You don’t want to miss this.

What Does a Control Chart Tell You?

A Control Chart begins with a time series graph.

A central line (X) is added as a visual reference for detecting shifts or trends – this is also referred to as the process location.

Upper and lower control limits (UCL and LCL) are computed from available data and placed equidistant from the central line. This is also referred to as process dispersion.

In the coming section, we’ll address the following question: when should you use a Control Chart?

When Should You Use a Control Chart?

  • When controlling an ongoing process by finding and correcting problems as they occur.
  • When predicting the expected range of outcomes from a process.
  • When determining whether a process is stable (in statistical control).
  • When analyzing patterns of process variation from special causes (non-routine events) or common causes (built into the process).
  • When determining whether your quality improvement project should aim to prevent specific problems or to make fundamental changes to the process.

So, what are the benefits of a Control Chart?

Benefits of a Control Chart

The Control Chart is one of the best examples of time series graph which is incredibly easy to read and interpret. Besides, the chart is incredibly easy to plot if you have the right visualization tool.

You can leverage this chart to make reliable settings, especially in the manufacturing sector.

If the process is in control, all the points will fall between the control limits. Any observations outside the limits, or systematic patterns within, suggest the introduction of a new (and likely unanticipated) source of variation, known as a special-cause variation.

Since increased variation means increased quality costs, a Control Chart “signaling” the presence of a special cause requires immediate investigation.

This makes the control limits very important decision aids. The control limits provide information about the process behavior and have no relationship to any specification targets or engineering tolerance.

The purpose of a Control Chart is to allow simple detection of events that are indicative of an increase in process variability.

The visualization design can help you find answers to the following:

  • Is the process under control?
  • Is the project moving in the right direction?
  • Are the deliverables within the specification limits?

In the coming section, we’ll address the differences between Control Chart vs. Run Chart. Also, we’ll cover the limitations of Control Charts.

Limitations of Control Charts

The chart violates the likelihood principle. However, the principle is itself controversial.

Supporters of Control Charts further argue that it’s impossible to specify a likelihood function for a process not in statistical control, especially where knowledge about the cause system of the process is weak.

Some data visualization experts critique the use of average run lengths for comparing Control Chart performance. And this is because the average usually follows a geometric distribution, which has high variability and difficulties.

The visualization design shows common cause and special cause variations. Common cause variations are normal and usually do not require intervention, while special cause variations require attention.

It may show you a false special cause variation, which wastes your time and resources.

Before unpacking the differences between Control Chart vs. Run Chart, we’ll address the following question: what is a Run Chart?

What is a Run Chart?

Definition: A Run Chart is a graph you can use to display trends and patterns in your data. You can leverage this visualization design to monitor data over time to detect trends, shifts, or cycles.

Also, you can use the graph to compare a measure before and after the implementation of the solution to measure impact.

The chart displays observed data in a time sequence. Often, the data displayed represent some aspect of the output or performance of a manufacturing or other business process. It is therefore a form of a Line Chart.

Components of a Run Chart

  • Shift

shift of run chart

Seven or eight values in succession above or below the median line are regarded as a shift. And it indicates the dramatic change in a process.

  • Runs

runs of run chart

The runs are all the data points below the median line, as shown above.

  • Clustering

clustering of run chart

Clusters are aggregated data points on either side of the median line.

  • Trend

trend of run chart

A trend occurs when seven or more consecutive points are increasing or decreasing on either side of the median line. So, when should you use a Run Chart?

When Should You Use a Run Chart?

Run Charts are an easy way to graphically summarize a univariate data set. The chart can help you to detect trends and outliers present in your data

Use the chart if your goal is to uncover hidden anomalies and errors in a process.

Check out more scenarios for using the chart.

  • Use a Run Chart to test for the presence of variability in your data
  • Also, you can leverage the visualization to test for
  • Seasoned data visualization experts use this chart to test for shifts in a process and the presence of a trend.

In the coming section, we’ll cover the benefits of a Run Chart.

Benefits of a Run Chart

You can use a Run Chart to:

  • Monitor data over time to detect trends, shifts, or cycles
  • Compare a measure before and after the implementation of a solution to measure impact
  • Focus attention on vital changes, not normal variation
  • Track useful information for predicting trends

So, what are the limitations of Run Charts?

Limitations of Run Charts

  • Run Charts lack statistical control limits; they don’t show you the upper and lower tolerance and threshold limits.
  • Also, the chart cannot show you if the process is stable and in control. To understand a Run Chart, you must understand the context around the data.

In the coming section, we’ll address the core of the blog: The difference between a Control Chart vs. Run Chart.

Difference Between a Control Chart vs. Run Chart

Control charts monitor the stability of the process.

In other words, it displays output variables over time and sees the results consistently fall within the control limits. Both upper and control limits are well defined in this graph.

On the other hand, a Run Chart focuses on displaying the shifts and trends in your data. Also, unlike a Control chart, it does not show the stability of a process.

And this is because it lacks control limits to map the upper and lower range.

In the coming section, we’ll focus primarily on the Control Chart. Also, you’ll discover how to access this chart in Google Sheets. You don’t want to miss this.

How to Create a Run Chart in Google Sheets?

Google Sheets is a trusted data visualization tool because it’s familiar and has been there for decades.

But the spreadsheet application lacks ready-made Control Charts.

We understand switching tools is not an easy task.

Therefore, we’re not advocating you ditch Google Sheets in favor of other expensive data visualization tools.

There’s an easy-to-use and amazingly affordable visualization tool that comes as an add-in you can easily install in your Google Sheets to access ready-made Control Charts. The tool is called ChartExpo.

So, what is ChartExpo?

ChartExpo is an incredibly intuitive add-on you can easily install in your Google Sheets without watching hours of YouTube tutorials.

With many ready-to-go visualizations, ChartExpo turns your complex, raw data into compelling chart renderings that tell data stories in real-time.

In the coming section, we’ll take you through how to install & use ChartExpo to create a control chart and other charts in Google Sheets.

You don’t want to miss this!

Example

This section will use a Control Chart to visualize the tabular data below.

Weeks Quantity
Week-1 121
Week-2 131
Week-3 132
Week-4 125
Week-5 141
Week-6 126
Week-7 126
Week-8 130
Week-9 143
Week-10 146
Week-11 148
Week-12 151
Week-13 152
Week-14 156
Week-15 157
Week-16 155
Week-17 157
Week-18 143
Week-19 131
Week-20 127

To install the ChartExpo, add-on for Google Sheets, click this link.

  • Open your Google Sheets application.
  • Open the worksheet and click the Extensions menu.
  • Then go to Charts, Graphs, & Visualizations by ChartExpo.
  • Finally, click the Open button in the dropdown.
open chartexpo in google sheets
  • Click the Add New Chart button to access your fully stocked library of charts.
add new chart in google sheets
  • Once ChartExpo is loaded, you will see a list of charts.
list of charts graphs google sheets
  • Look for “Control Chart” in the list of charts.
search control chart in google sheets
  • Select the sheet holding your data and select the Metrics Fill in the numerical numbers (in our case, we’ll use quantity).
  • Select the Dimensions button and fill in the dimensional data (in our example, we’ll use weeks), as shown below.
create control chart in google sheets
  • Finish the simple process by clicking the Create Chart.  In fact, it’s a Control Chart. To change the chart type, click the Edit Chart button, as shown below.
edit chart in google sheets
  • Click on the highlighted pencil icon.
  • Disable Upper Specification Limit.
disable upper specification limit 98
  • By the same method, you can disable Lower Specification Limit, Upper Control Line, & Lower Control Line.
  • You only need to show the Mean value as shown below. Once done click on Apply button.
show the mean value 98
  • Now click on the pencil (edit) icon near the Cpk value and then the go-to Label section.
edit cpk value 98
  • Disable this property so that it won’t appear on the chart.
disable cpk value 98
  • Now let’s edit the other labels which are not required in this chart.
edit mean and other values 98
  • Under the Label section, you will find a number of properties. Just keep the mean property enabled and the rest should be disabled.
disable all values except mean 98
  • Click on apply button. If you want to put the header in the chart you can click on the pencil icon showing at top of the chart. You can put the heading in the Label section’s property Line1 and click on the Show toggle button.
edit chart header 98
  • Similarly, you can put the label on X-axis and click on the Save button to find the final look of the required chart as shown below.
final control chart vs run chart

Now you can find easily the trend shown by the blue line over different weeks and the dark red line showing the mean value. Also, the mean value is explicitly mentioned at the left bottom of the chart.

FAQs:

When should you use a Run Chart?

Run Charts are an easy way to summarize a univariate data set graphically. The chart can help you to detect trends and outliers present in your data

Use the chart if your goal is to uncover hidden anomalies and errors in a process.

What is the importance of a Run Chart?

You can use a Run Chart to:

  • Monitor data over time to detect trends, shifts, or cycles
  • Compare a measure before and after the implementation of a solution to measure impact
  • Focus attention on vital changes, not normal variation
  • Track helpful information for predicting trends

Wrap Up

Visualizing trends in Google Sheets is one of the critical tasks you can ever undertake.

It provides significant insights into whether crucial metrics are on a growth or decline path. You can easily know whether key data points are down or up-trending.

Some of the tested and proven charts for visualizing general trends in your data are Control and Run Charts. The visualization designs (mentioned above) are straightforward to interpret. Besides, you can use these charts to create compelling data stories.

Google Sheets is a popular data visualization choice among professionals and business owners worldwide. However, the freemium application lacks trend analysis-oriented charts.

So, what’s the solution?

We recommend you install third-party apps, such as ChartExpo, to access ready-to-use Control Charts.

ChartExpo is an add-on for Google Sheets with insightful and ready-to-go Control Charts. You don’t need programming or coding skills to use ChartExpo.

Sign up for a 7-day free trial today to access ready-made Control Charts that are easy to interpret and visually appealing to your target audience.

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