Since the days of painting on cave walls, people have been representing information through figures and images. Nowadays, data visualization experts know that presenting information visually helps people better understand complicated data. The problem is that data visualizations can also leave you with the wrong idea—whether the images are sloppily made or intentionally misleading.

Take, for example, the bar graph presented during an April 6, 2020, press briefing by members of the White House Coronavirus Task Force. It’s titled “COVID-19 testing in the U.S.” and illustrates almost 2 million coronavirus tests completed up to that point. President Trump used the graph to support his assertion that testing was “going up at a rapid rate.” Based on this graphic, many viewers likely took away the same conclusion—but it is incorrect.

With most industries shifting to remote work due to the Covid-19 pandemic, companies are looking at how they can innovate the work-from-home experience. Toyota’s Ann Harbor, Michigan, research and development team was set to complete the automaker’s newest generation of the Sienna in March 2020. However, after the state went under lockdown, the team was forced to complete the minivan from home.

According to the team, they were still able to see a production trial of the latest Sienna at Toyota’s Indiana plant prior to the lockdown. This gave the team enough ideas on what kind of changes they needed to make to the vehicle. The real challenge was how they were going to do it from home. Toyota Chief Engineer Monte Khaer shared that the later phase involved what they call “fit-and-finish optimization,” which can be difficult to accomplish by just relying on CAD.

Toyota Engineer Kyle Steinkamp works on the new Sienna minivan with his own tools from home. (Image courtesy of Toyota)

In October 2019, I shared the news that the classroom connectivity gap in U.S. schools is effectively closed. More than 99 percent of schools nationwide have access to speedy and reliable internet, making online learning an option for their students.

Only now it doesn’t matter. School buildings are closed because of the coronavirus, and the bandwidth that powered digital learning for kids is going unused. Now, the most important connectivity statistic is that more than 9 million students do not have internet access at home.

As clients clamor for speedy results and headhunters increasingly rely on the latest data analytic tools, there is a danger of dull, predictable candidates being churned out for results that serve but do not shine.

At a recent panel on careers, a prominent headhunter said: “Search consultants, however naturally creative, find themselves stuck in a position of risk mitigation on behalf of their clients. More often than not, they end up placing the candidate who is the closest to being the carbon copy of the predecessor—minus whatever faults they were deemed to have.”

This damning statement did not sit well with us, however close it may be to reality. Although we don’t deny the importance of hiring based on skills and experience, we also believe that the potential and personality of candidates should greatly weigh on recruitment decisions. So we set out to identify audacious headhunters who have successfully advocated for outlier candidates. We hope these stories will inspire recruiters and companies alike. (Candidates’ and recruiters’ names are disguised.)

For more than 50 years, the benchmark for accuracy in measuring solid objects, whether machined, molded, die cast, welded, or forged, was the coordinate measuring machine (CMM). Typically using a solid, granite-base table along with a vertical, horizontal, gantry, or bridge-mounted arm and touch probe, measurements would be taken and compared in blocks to an engineering file, originally as 2D drawings and today as CAD files hosted in the cloud.

During the last two decades, however, a “new kid in town” has arrived on the scene, with power, size, point capability, and price value that are rapidly leaving the CMM technology in the dust.