This essay originally was published on November 18, 2021, with the email subject line CT No.103: "Leverage your humanity." It's the third of three essays. The other two are listed below:
My love for troublesome, problematic expressions
The Chicago Manual of Style has an entire section dedicated to "problematic expressions," called "troublesome expressions" in previous iterations. This glossary covers word pairs frequently confused and misused, such as the differences in meanings and usage of ambiguous vs. ambivalent; obtuse vs. abstruse;* flaunt vs. flout; and, in one of my favorite entries, the distinct usage of odious, odorous, odiferous and malodorous.
The Glossary of Problematic Expressions is delightful reading for writers, a treasure trove of precision and nerd points that, if used incorrectly, will inspire a flurry of corrections that will evoke colleagues' ire. But no one likes a corrector.
When used with empathy and as a personal development tool, understanding commonly misused expressions is strength training for your writing. If you like the English language, I recommend checking out the whole Chicago Manual, but particularly the Problematic Expressions section.
The biggest drawback of the CMS glossary is it's designed for publication and book editors and not business writers. It would be fun to use both odious and odiferous more often in my professional writing, but courting opportunities for that flex seems risky.
Instead, the most misused expressions in digital business culture are passed over by the Chicago Manual, probably because the CMS staff doesn't have to edit reports and white papers written by marketing majors and data scientists who haven't taken a writing class since the one required freshman year. So today I present: a few troublesome expressions, often misused in analysis, reports, newsletters, what have you, in the business world.
Write better, more insightful analysis and reports with these.
Troublesome business expressions, often misused, inspired by the Chicago Manual of Style
Anomaly; outlier. In digital data, an anomaly is a change that's aberrant from a typical pattern, a sudden growth or decline in what has previously been steady. An outlier is a data point beyond the standard deviation, something that's off-the-charts or far from average in a static set of data. An anomaly is a deviation or shift from the norm. An outlier is not hanging out anywhere near the norm to begin with.
Benchmark; average. A benchmark is a longitudinal measurement of your owned data—independently or within a larger dataset of similar data, i.e. within an industry—created to understand current or future performance. It's a mark on the wall that indicates your company's or industry's performance during a determined period.
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