During my early days as a product manager I got a lot of calls from vendors pitching services or software.

They typically spoke a vernacular mined with acronyms and fancy phrases. It blanketed their pitches in a dense fog.

To make the meetings more entertaining, our group would jot down jargon and score it on a scale of 1 to 10, with 10 being the most arcane, high-highfalutin, unnecessary or nonsensical use of the word or phrase.

After the meeting we would compare notes.

Like golf, the objective was to score low.

I was reminded of that long-ago time this morning when I read a fantastic piece by Bloomberg columnist John Authers.

It highlights a Nomura research report that showed that companies whose CEOs speak in simple language outperform.

According to Authers:

The results are dramatic. The researchers analyzed the language used by execs in calls for all the companies in the Russell 1000 large-cap index, and split them into 10 groups of 100. Since 2014, the 100 companies whose officers used the most complex language averaged a return of 9.45% per year. The companies in the simplest language decile returned 15.4% per year.

The Nomura analysts leveraged the Gunning Fog index to calculate complexity.

The Gunning Fog index was one of things vendors would mention in meetings.

I went back into my files and found a list of common jargon we compiled from circa 2012.

At the time, I scored the Gunning Fog index a 7 out of 10.

Obviously, jargon depends to some degree on the ear of the beholder.

If you haven’t come across a phrase before, it strikes you.

Assigning jargon a score is subjective.

For me, it was a combination of unusual with unnecessary, the later influenced heavily by the sense that the point was to inflate one’s importance.

Language changes over time, so some of these words and phrases have become much more mainstream. Those words would be removed or scored lower today.

In some cases we would know what was generally intended by a term.

It was the gratuitousness of using the word or phrase that elevated it to the list.

Here are selections from my 2012 jargon list in ascending order:

1 point:
–A priori
–Greenfield
–Predictive analysis
–Enterprise solution
–Implementation roadmap
–Neighborhood grouping
–Call to action

2 points:
–KPIs
-Signal-to-Noise
–Taxonomy
–Metadata
–Algorithms
–Logarithmic
–Data mining
–Crawling
–Analytic environment
–Value proposition
–White paper
–Visualisations
–Natural language processing

3 points:
–Facilitate viral discovery
–Socially curating data
–Operationalize
–Rapid ideation phase
–Highly structured data
–Metadata analysis
–Ontology
–Algorithmic platforms
–Actualization
–Discovery engine
–Risk mitigation
–Value chain
–Disruptive models

4 points:
–Pattern Recognition Software
–Futurescope architecture
–End-to-end user value proposition
–“Iterate the deliverable in real time”
–Ideation phase
–Collaborative filtering
–Boundary condition
–Incorporate our visual system elements
–Adaptive algorithms
–Quantitative modeling
–Topical metadata
–Neural net
–Semantic Web
–Syntactic machine translation
–Contextually Influential
–Deprecate

5 points:
–Winsorize
–Data portability
–Hosted data solution
–Heuristics
–Matrix based reporting
–Reverse rollup
–Content creation ecosystem

6 points:
–Named entity extraction
–Complexity theory concepts
–Constituency support shifts
–Adaptive competitive angles
–Remnant ad network
–DMA geo-targeted
–Orthogonal problem
–Canonical example
–Text normalization

7 points:
–Kneser-Ney method
–Cube prunning
–Bayesian belief network
–Co-reference resolution
–Self-learning Genetic Algorithms
–Gunning Fog Index

8 points:
–Disambiguation rules
–Mechanical Turk
–Synoptic content

9 points:
–Moses hierarchical framework
–Lossy compression techniques

10 Points:
–Dublin Core Metadata Element
–Directed acyclic graph
–Lamport time clock
–Mahalanobis distance

h/t to Mark Dimont