Heller and Shannon: Covering tracks

Shannon logged into PluggedIn as “Anita” for the last time. She copied and pasted the list of Anita’s connections into an MS Word document where the name, eight-digit PluggedIn ID, Job Title and “company” were placed business-card format so she could cut them into cards to sort at her leisure.

Then she crafted a short message to post on PluggedIn

There may be a delay in my coming to America.

My father recently experienced some losses in his businesses.

-Anita

Anita and Heller spent the evening picking thirty names out of the now over-two-hundred names.

Shaquila Washington the HR person with Shannon's Credit Union and Ce’Diff were the first two names they put into the pile to seed the name-search.

Then, after talking it over with Heller, she sorted the cards into piles based on industry. In many cases it was just an educated guess as the company names were ambiguous.

• Media
• Academic/non-profits
• Government/public service
• Retail/services
• Finance
• Manufacturing

Heller sorted through the titles and culled out the ones he thought were “go-fers”. Then Shannon went through them again and did the same. They were not fishing for flunkies and menials.

Shannon raked through the pile and sorted out the ones that had left her with a major “ick” feeling. She could not define it to Heller. It was an intuition thing.

Shannon rough sorted each pile that was based on industry from “most important” to “middle management” to “least important but being rapidly promoted”.

The final thing they did was to pick one candidate from “most important” in each industry, two from “middle-management” and one from the “least important” level.

A few adjustments were made to bring the total to thirty which was the minimum number that Garth had recommended.

Shannon typed the data into a spreadsheet for Garth. Shannon was a near-world-class keyboard-entry operator. She was so good, and so error free that she could type as quickly as most people can read.

She double-checked her entries as she had been trained.

Then she sent the list to Garth who had agreed to submit the list and pay via his crypto account.

Two hours later, Garth mailed back the results.

PluggedIn had subcontracted the analysis to Gzilla.com which was managed the email and messaging side of their business. Gzilla.com was THE major player in that market. Even if the clients were not using PluggedIn email, there was a very, very good chance that the provider they used was actually Gzilla.com.

Based on the radio-buttons Garth had selected, Gzilla threw a wide net. It surveyed the emails sent-and-received by the thirty parties over the last two months. It “expanded” the set to five-hundred people and then did the nonubiquitous-keyword-string-tracking. It then converted that data to numerical matrices and the AI module selected the Lanczos algorithm to analyze the matrices. The numbers were converted back to names, ids and relationships and the top one-hundred “players” were sent back to PluggedIn.

PluggedIn included a data-visualizer tool to the package and then forwarded it to Garth.

Shannon loaded the app and data on her lap-top using a phone-based hotspot. She and Heller dinked around with it a tiny bit but they could not make heads-or-tails of the results. There were twenty windows and each window displayed a bunch of dots that were connected by lines and constellation of dots pulsed like a heart.

It was late.

Both Heller and Shannon were tired.

Playing with the data could wait.

They had better things to do with the hours they had together.