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Benchmark Comparisons
Data visualizations often are made through comparison of values and the best way to do that is to include a reference point to evaluate data. Based on where the benchmark is located the viewer can analyze if it is above or below that point. This can help provide context to the data or it can be used to mark goals in data. In data visualization, it is important to have these indicators so that the information being presented has meaning.
The data above was pulled from an article uploaded to The New York Times called, “Where’s All the Antarctic Sea Ice? Annual Peak Is the Lowest Ever Recorded” by Delger Erdenesanaa and Leanne Abraham. The authors report that the annual peak of Antarctic sea ice has reached its lowest recorded levels. This decline in sea ice extent raises concerns about the implications of climate change for the polar region. What they did to visualize this data was to add in a “benchmark” shown as the dotted line to represent the average from 1979-2010. You can clearly see that where we are in 2023 (shown in red) that the Antarctic sea ice drops below the benchmark by an extensive amount. Based on the data shown, they are able to assess where the level should be and can make the achievement goal to be above that targeted area. https://www.nytimes.com/2023/10/04/climate/antarctic-sea-ice-record-low.html
Benchmarking Graphs
Benchmarking your data visualizations is an excellent way to convey an important
factor in your graphs, what the numbers should look like, and how they fare
in comparison to that number. Helpful in showing outliers like how something is over-
or under-performing, or showing how perfect fit a value is towards some specified goal
benchmarks are a powerful tool that can be added to most graphs.
To show you an example, the following graph tracks goods and services pre-
and post-pandemic.
https://www.nytimes.com/2023/07/27/business/economy/us-economy-gdp-q2.html
It is easy to see the strengths of the trend lines as a way to measure the expected
values for the services and goods and how they compare to the trendlines before and
after the pandemic.
The following graph makes use of a perfectly horizontal benchmark line. This makes
reading the graph even easier than trend lines as being able to reference the single
value of the benchmark reduces user effort.
https://www.nytimes.com/2023/06/08/business/economy/us-economy-inflation-fed.html
The anomaly of the employment boom following the pandemic is immediately apparent with this example, highlighting the clarity that benchmarking provides.
Finally, this benchmark is just an average of the values in the graph. While not as
easy to interpret as the other methods, this one is a near-universal improvement that
can be made to any graph.
https://www.nytimes.com/2023/10/04/climate/antarctic-sea-ice-record-low.html?searchResultPosition=4
Benchmark Comparisons
By Ryan Metch
Using visualizations such as benchmark graphs allows us to better understand different types of data. The definition of a benchmark graph according to google is a visual tool that shows how fractions compare to a whole on a number line. Going off this graph from the Wall Street Journal, we can see how prices of European and American oil compare to one another. We can clearly see when changes occur on this graph, which is why a benchmark graph is a great tool to display this type of data.
Benchmark Comparisons
Benchmarks are an incredibly fast and effective way to provide a significant amount of context to a graphical display of information. This can be done in many ways, such as with a line or single symbol indicator. Benchmarks are most often used in financial matters; however, they still may prove useful for other purposes. In financial context, evaluating benchmarks may allow for insight into shifts in business over time. Whereas establishing benchmarks can allow businesses to more accurately gauge the performance of their employees as well as provide some motivation for progress.
In a New York Times article written by Clifford Krauss, he covers the significance of the dropping fuel demand in relation to how this affects oil suppliers.
In the graph above, there is a clear trend of a dip in crude oil prices in the U.S. over the course of a little over a year. The benchmark of concern that was mentioned in the article, is $80 per barrel of crude oil. In a bold attempt to increase oil prices by cutting production, Saudia Arabia may have inadvertently caused the opposite effect to occur. Allies of the OPEC Plus cartel (Saudia Arabia included) have shown concern over this value remaining at or below $80 per barrel of crude oil. I feel as if the significance of this value may be better illustrated by highlighting this lines value differently than the others.
Benchmark Comparisons
Infographic as a whole usually display information such as sales on year by year comparison. However, these type of graphics can come in handy when looking at a benchmark. I am taking an example from National Oceanic and Atmospheric Administration’s website and few other regarding the global temperature
This first graph here is a “Yearly surface temperature compared to the 20th-century average from 1880–2022” and blue bars indicate cooler-than-average years; red bars show warmer-than-average years. One thing can be seen from this type of graph is how you can easily see how much of a difference between years. The graph only listed from -1.0 to 1.0 Celcius (30.8 to 33.8 Fahrenheit) but the short distance between the maximum and the minimum y-axis makes a small difference much more exaggerated. At first, I would have like to know the actual average temperature on a yearly basis but this would not fit in this type of graph due to the amount of spaces needed for additional data.
This graph is a similar graph comparing temperature from NASA’s website. This offer one more variable to look at is the LOWESS smoothing. By definition from NOAA’s website, LOWESS or LOESS is a nonparametric method for smoothing a series of data in which no assumptions are made about the underlying structure of the data and is effective when there are outliers in the data. However it is difficult to understand any of the scientific terms but overall just another example on how current temperature can be shown on a graph.
This graph here is “Projected Temperature Increase (°C)” from Center for Science Education. This graph is benchmarking the future temperature on a few different scenarios as listed within the graph itself. Black line and grey area perhaps are the accepted temperature change by many scientists. This graph is definitely great in comparison and it shows the temperature entirely depends on the decisions of humans. However what is missing here that makes me wonder is what is the different between CO2 amount from each scenarios such as would the highest CO2 be somewhat for an example 10 million and medium to high would be somewhere 3 million to 5 million and so on. Overall, it may seem that the actual number of CO2 because it is not the main focus of this graph.
Benchmarks: Standardized Testing
Today we will be deep diving into how different people show comparisons to the benchmark. A benchmark is a standard or point of reference in which things can be compare. A great example is when benchmark testing was taken place during schooling. This data was used to see where you compare against students the same age as you.
I will be using the college board SAT testing as an example. The college board uses benchmarking in order to determine where your test score should land based on your grade level. In the example below, they state that the benchmark is 430 for reading and 480 for math. These scores are based on if you were a 10th grader. They then breakdown the score into three categories: Red, Yellow, and Green. These sections represent how below or how above you are the benchmark.
In the article, How Perceptions Can Skew Reality: A Data Visualization Approach How NYC schools’ academic performance differs from public perception, they use benchmarking to determine where each borough of NYC lands with regards to SAT testing. In this article they take into consideration things such as poverty level.
Schools in the Bronx performed worse due to the fact that the poverty rate is much higher. I feel as if data visualizations are very important especially with regards to benchmarking. It allows for an individual to compare themselves to the norm and make adjustments where needed. Everyone has grown up with benchmarking especially with regards to academic performance on things such as standardized testing. its interesting to put this into perspective.
Benchmark Comparisons
By Marc Joseph
Source https://humanbenchmark.com/users/6523996c62704b00084820c5/reactiontime
Reaction Time Charts
There are many different ways one can use benchmarks in order to determine whether a measurable value is over or under an expected value. As shown by the reaction time benchmark from Humanbenchmark.com where I scored an average of 191 m/s which put me in the top 74.46% percentile. The graph that is darker represents my value while the lighter colors represent the standard of comparison, or the average of all the other users. As shown, my values are slightly skewed to the left which means that my reaction time is above average when compared to the values of the lighter blue.
Investing Charts
https://investor.vanguard.com/investment-products/mutual-funds/profile/vadgx#performance-fees
Another application of benchmark comparisons would be an investment or stock that generates a projected profit after a certain period of time. As portrayed by investorvanguard.com, they have a bar graph that shows the amount of returns and projected returns within a year. The darker green color represents the current value while the light green represents the expected goal. They used a darker color to bring attention to the value that they want the reader to see the most and a lighter color in order for the other value to be less distracting.
All in all, there are many different ways to shows benchmarks and simplify information. One can use bar graphs, line graphs, bell curve, and many more options in order to accurately portray data. Using the data, the audience can then make a more informed decision on their topic of interest (i.e. stocks, investing etc.). Hopefully this article gave you a good idea of the effectiveness of benchmarks and their many uses.
Benchmark Comparisons
Benchmarks are a commonly used feature in many data visualization charts, as they help to compare data in a comprehensive and easy way for viewers of all sorts. More frequently, we see benchmarks used to show things such as a budgeted/projected amount or numbers compared to the actual numbers for a specific data set, whether it be for a school, company, test, or experiment.
The unique thing about benchmarks is that they can be shown on graphs in a multitude of ways, from dotted lines and solid lines to different bars and solid colors on charts. Another notable feature about benchmarks is that there is no specific category that they have to be used for, meaning they could be used in/represent important statistical data or even smaller, less important information.
The example above is an instance where the benchmark line is used in a more serious setting and is represented by a dotted line on the line graph. The graph was taken from a New York Times article that discusses the current issue in the Antarctic Sea. As shown in the graph, this September marked the lowest ever recorded peak of sea ice, endangering wildlife. The red line represents the current levels recorded of the Antarctic Sea ice. In many scenarios, this would be considered the “actual” data in the graph/chart. In this specific graph, there are two types of benchmark (comparison) data. The first being the faded light gray lines that represent previous recordings of the sea ice level and the second is the dotted line with the average sea ice level, which is the main benchmark data and the comparison area. This chart was a great way to display this information, as it is clear to see the difference in sea ice throughout the years thanks to the comparison data/benchmark line.
As previously mentioned, benchmark data sets can be used to represent and compare serious and important data, as well as data that is simply for fun. The chart above is a different presentation of a benchmark that takes on a less serious meaning. Serena Williams is a tennis player, and last year the New York Times put together an article and data visualization to compare Serena William’s age to all of the other people she has played and either won or lost to in each match. The gray solid line going across the entire scatter plot represents the benchmark (comparison) data, in which Serena Williams was the same age as her opponents. From here, it is easier to see how she performs with people younger than her, her age, and people older than her. While this type of chart looks chaotic, it is another perfectly acceptable use of a benchmark line within a data visualization.
In conclusion, benchmarks can be created and shown on almost any time of chart or graph that is trying to compare two or more things. It is an excellent tool that people can use to provide others with a better understanding of a situation. In different articles and publications that feature graphs, you will see them presented in a variety of ways depending on how the author chooses to do it. While none of the ways to show a benchmark are wrong, some are better suited for specific presentations of data. For instance, having a bar graph with overlapping bars to show the benchmark for all of Serena Williams’s matches and ages of opponents would have been acceptable, but a lot more confusing and chaotic than the scatter plot used with a simple solid benchmark line.
Benchmark Comparisons
When I look at data one of the most important concepts for me is relativity. What does that data mean relative to other data? When we look at relative data, we begin to really see the story of that data in the context that defines it. Benchmarking is a standard or point of reference by which data can be compared. Benchmarks represent a significant portion of data representation in many fields and can assist in the application of productivity concepts such as performance and service.
One of the most common benchmarks that we see often is financial benchmarks, specifically related to the stock market. People go to many different news sources to check on their investments but you will see charts that look very similar on every site. This graph shows the performance of Home Depot stock in the past year.
https://www.wsj.com/market-data/quotes/hd
This graph shows the performance of Home Depot stock compared to the benchmark set by the S&P 500:
https://www.wsj.com/market-data/quotes/hd
While HD is up 2.99% in the past year, it is not doing great when compared to the benchmark performance of the S&P 500, which is up 18.99%.
A New York Times article exploring the effects of pandemic school closures on the math scores of students showed some interesting results. In 2019 there was a distinct pattern between the students in wealthier districts scoring above average on math tests.
In 2012 there was a shift in all scores across the board. This change happened amongst all income levels and racial groups.
I enjoyed this article and the benchmarks showed that even though the researchers did not find the results that they had expected, they presented the data because it was quite remarkable. They had assumed that the children in poorer districts and minorities would have been even further behind benchmarks but the data showed otherwise. When data is presented that is the opposite of initial assumptions I find it more interesting because it shows the importance of data science and visualization. Without data we are left with assumptions…which are sorely lacking.
Benchmark Analysis
In today’s world, many data charts have been used in the market economy and small businesses. This blog is about benchmark graphs and how they allow you to identify improvement areas to get the company on par with growth and success. With the help of a benchmark graph, it allows businesses to compare their performance against competitors. In addition, it gives strategic decision-making ideas by analyzing the performance of competitors. The benchmark graph is innovative in comparison with a regular bar graph. This blog, it’s all about “The Employment Situation in January” The number of jobs added in January came in well above market expectations after unemployment from 2020. Based on the report from the U.S. Bureau of Labor Statistics the unemployment rate ticked up by 0.1 percentage point to 4.0 percent.
Average monthly job growth over the last three months was 541,000 a fast pace.
In this graph, the target line is a three-month average, and the bar graph represents nonfarm payroll growth. Since monthly numbers can be volatile and subject to revision, the Council of Economic Advisers prefers to focus on the three-month average rather than the data in a single month. This graph is the perfect example of good benchmark analysis since some bar column is above the target line which means there is growth in the number of jobs.
Labor force participation grew by 0.8% point year-over-year, a fast pace.
The above graph is an example of labor force participation. According to the Bureau of Labor Statistics, the labor force participation rate was 62.2% in January, up from 61.4% percent a year ago. The “prime age” (25 to 54) labor force participation rate was 82% up from 81.1% percent a year ago. The Council of Economic Advisers prefers the participation rate because it is less impacted by changes in educational enrollment and the natural slowdown in labor force participation caused by the aging of the population and retirements. As we can see in the graph back in the day the labor force was above the target line and it got below the line from the year 1990 till 2020.
Overall, a Benchmark graph is a powerful tool in data visualization for businesses and other organizations to gain better performance, tracking data, and identify areas for improvement and development. This activity cleared a concept of mine towards benchmarking and how it is used at a bigger stage. Getting the knowledge of this graph will help me in every sector of economic fields.
Reference
https://www.whitehouse.gov/cea/written-materials/2022/02/04/the-employment-situation-in-january-2/