As many as 95% of millennials are not saving adequately for retirement.

Boulevard Consulting
6 min readOct 14, 2020


Got your attention, right? Statistics are being used more strategically these days to convince readers to act or believe in certain ideas because they drive decisions in our personal and business lives. This strategy thrives in today’s headline-driven world as readers are drawn to eye-popping statistics and form their opinions accordingly. But because of how simple it is to develop a headline and how rarely the methods used to calculate statistics are questioned, it’s one of the easiest ways we’re seeing misinformation being spread about critical issues in our community. Almost anyone with a computer can access data and publish his/her opinions, which creates more opportunity to spread misinformation, whether intentional or not. For example, the statistic above perhaps paints millennials as irresponsible but does nothing to address factors that prevent millennials from saving such as the rising cost of living, inflation, exponential increases in education costs leading to higher loans, and others.

For some issues, an intentional misrepresentation of statistics is not a big deal. Does it really matter if a “Mega” roll of toilet paper is actually 5.61x the size of the regular roll instead of the advertised 6x? Probably not. But for critical issues in our country, misleading information ultimately drives social divide and unrest. This is exactly what we see happening with issues such as police violence, the coronavirus pandemic, and voter fraud.

As discussions about the ever-present racial injustices happening in our country increase, there are individuals promoting half-true statistics which do not portray the full reality of the issue. There were just over 6,800 deaths related to police violence from 2013–2019. When we break down those deaths by race, there were 3,350 (49%) deaths of White individuals, and 1,916 (28%) of Black individuals.

Drag the Filter at the bottom to see how the number of deaths changed annually (Note: You may need to click “Run Pen” to activate the visual)

Although more White people were killed, stating that racial bias is not evident because of only the total death count by race is inaccurate. You can only make that statement if these were the findings after taking other metrics, such as population size by race, into account. Yet many leaders[1] still use only limited data and believe that statement to be true, using only those figures to disprove the existence of racial bias and discrimination[2] in the US. However, although more White people were killed, this statistic does not imply that White people are more likely to be killed by police.

Click and hover to see the annual death totals by population size (Note: You may need to click “Run Pen” to activate the visual)

Using population data will allow us to more accurately compare the likelihood of being killed by race. Using the same data and including the latest demographics into account, the numbers indicate that nearly seven out of every one million (7/1,000,000) Black people were killed through police violence, compared to 2.5 out of one million (2.5/1,000,000) White people. Black people were 2.85x as likely to be killed as White people during that time. Simply incorporating one more factor from the data into our analysis provided a more realistic understanding of the issue.

Hover over the heatmap to see population-based comparisons for each race (Note: You may need to click “Run Pen” to activate the visual)

Every article related to this topic will utilize a unique approach, reference various studies, and limit their analysis at different points to generate conclusions. It is important for readers to believe statistics and headlines only after attempting to understand the constraints the author sets, and the factors that are prioritized. Additionally, because consumers may not be skilled in data analytics, data scientists must be responsible to develop a culture where explaining the analytical process is common and expected. This will increase the integrity of our findings and easily isolate misleading statistics.

The coronavirus pandemic has been another issue plagued by misinformation, leading to more confusion and in many cases dangers for people who listened to false treatment methods. As the medical community continues to study the virus and develop a vaccine, there have been significant posts regarding false information increasing the number of deaths caused by the virus. A study published in the American Journal of Tropical Medicine & Hygiene[3] followed content on a variety of online platforms, including social media and fact-checking websites, and identified 2,276 posts containing COVID-19 rumors, stigma, and conspiracy theories in 25 languages across 87 countries during a four-month timeframe. Of those posts, 82% were false. Although efforts are being made to remove false information, a lot of the damage has already been done. For nine months, factual information was drowned out by the sheer magnitude of false information stemming from many sources, including the White House[4]. It kept the public away from following scientifically-based guidance from medical research institutions, such as the National Institutes for Health, and Center for Disease Control and Prevention.

In the next few weeks, we will continue to see information related to voting, climate change, and other relevant topics. According to analysis performed by a media insights company, in September alone, there were nearly 411k posts which discussed false information related to absentee ballots, 345k mentions of voter fraud with misleading stories of criminal conduct, and thousands of other postings intended to sway voter beliefs about the integrity of the voting system using false evidence[5]. It will take a collective effort to overcome the amount of false information we are exposed to every day and ensure we don’t believe in and spread conspiracies, non-scientific opinions, and rumors. As data scientists, we hope to increase your ability to detect and avoid articles that contain false information. Here are a few practices each of us can follow when reading news to ensure the content we come across is factual and is not created from false ideas or narratives:

  • Discuss findings with subject matter experts or students of the field prior to sharing/ spreading the content or even believing it
  • Compare article takeaways with conclusions from other articles posted on other news sources

Science and Coronavirus-related content:

  • Verify medical information by seeking names of scientific journals and organizations that support the claims
  • Speak with your doctor/ physician to see how following this advice would affect you

Political content:

  • Determine what unaffiliated/non-partisan organizations, such as academic institutions, have stated regarding the topic and the academic research claims are based on
  • Find the credentials of the author(s) and determine how this compares to previous statements they have made

As data scientists, it is our responsibility to ensure audiences have a deeper understanding of a topic, including useful insights as well as limitations and constraints as opposed to making their decisions and leading them down a path without proper understanding. Our intent is to help readers understand data better and use it to solve problems at home, work, and in the community. We at the Boulevard Consulting Group pride ourselves on providing not only the technical expertise but also the strategy and operations experience to evaluate data. If you’re interested in learning more about Boulevard’s services, or simply want to talk about the data behind any of these and other relevant topics, visit our website and reach out!






About the Authors

Shrey Tarpara is an Associate at Boulevard with a background in data analytics and change management. As a Lean Six Sigma Black Belt, he helps organizations make sense of their data and implement strategic initiatives to improve operations. He holds a B.S. in Economics from the University of Maryland and holds the patent for an illuminating wire designed to improve hardware replacement and troubleshooting processes within healthcare and commercial settings.

Amit Gattadahalli is a Consultant at Boulevard with a focus in data science. He recently graduated from the University of Maryland College Park with a B.S. in Mathematics and Statistics. His work within the consulting industry has concentrated on supervised/unsupervised machine learning, custom data science-centric algorithm development, data visualization, and general software development.

About Boulevard

The Boulevard Consulting Group, a Native American-owned, Small Business Administration (SBA) 8(a) small business, is a modern management and technology consulting firm that helps clients leverage the power of data science, operational transformation, and cutting-edge technology to build a better future. We develop highly scalable, impactful solutions by combining the latest technology trends with time-tested improvement methodologies, and with the personalized attention of a smaller firm. For more information about Boulevard and its services, visit our website at



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