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.

https://www.nytimes.com/interactive/2023/05/11/opinion/pandemic-learning-losses-steep-but-not-permanent.html?action=click&module=RelatedLinks&pgtype=Article

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.