Published in the San Diego Union-Tribune, December 10, 2018
My current day job is working as the CEO of a software company in the big data, machine learning, deep analytics space. That made me begin to wonder on a different concept — people analytics, not data analytics. And thanks to Professor Paul Leonardi at the University of California, Santa Barbara, I have some insights that I would like to share.
His area of expertise is called “relational analytics.” In layman’s language that means identifying employees “who are capable of helping companies achieve their goals” — i.e., who are the key players on your team who you need to win the game?
In keeping with the theme of big data, the place you go to do the mining in your company is in what is called the “digital exhaust,” which is the data created by email exchanges, chats, file transfers, etc. Relational analytics is the science of human social networks. Leonardi and his partner, Professor Noshir Contractor from Northwestern University, offer us the “six structural signatures” that form the basis of this research.
The first is ideation. This means who in the company will come up with the best new ideas. The key concept here is “low constraint.” I really get this one because in the startup companies where I play, there are very few boundaries. The teams are small, and people wear lots of hats. However, when you get up to a few hundred employees, the key to continuing to innovate is to look for people who have a wide network within the company, who work the room, who wander and lunch with lots of people, who cross-pollinate. Get out of your cave.
Next is influence, and who has that influence? It is not the senior executives. It is also not the employees who give the appearance of having influence, rather it is the employees who have the “strongest connections to others, even if the number of connections is small.” And so we come to the famous Google algorithm — it is the rank of the connections’ connections and how well those are connected. Leonardi and Contractor call this “aggregate prominence.”
Next is efficiency. To solve for this, you need to measure team chemistry. The two key components are “internal density” (how long has the gang been together) and “external range” (can they call on a large number of people to help identify solutions). My little company has nine software geniuses who all worked together elsewhere for more than a decade. No drama, just great code.
Next is innovation. It seems that what is needed here is “high external range,” which again is a fancy way of saying you are looking for people with wide and diverse connections, e.g., someone with an interest in early Etruscan architecture who also plays professional poker.
Next is silos. I have railed on this one for years. Don’t get into one, and if you are in one, get out of it. End of story.
The last is the vulnerability of your company if you lose the key employee. The solution is simple — back her up. Just like you back up your code. Redundancy is the key here. The mantra for football teams is “next man up” when someone is injured. They plan for this. But it is not easy or intuitive to do this in your company. You will need to manage egos and salaries and titles and responsibilities, and if you don’t do this, prepare yourself for the inevitable “gun to your head” when the one person you cannot lose says adios, amigo.
And so we come to the core concept — the need to mine the digital exhaust. Who is saying what to whom about which initiative being promoted by which executive, and who needs to buy in and actually do the work. The answer is all there in the new science of people analytics.
I confess that I was dazzled by the research, and at the same time, somewhat challenged by how to do it. The dark sentence in the report is this one — “some employees feel that the passive collection of relational data is an invasion of privacy.” And so one wonders how the puzzle pieces of human analytics fit into the higher calling of responsible corporate leadership.
Neil Senturia, a serial entrepreneur who invests in early-stage technology companies, writes weekly about entrepreneurship in San Diego. [email protected]
Rule No. 588
“1984” — George Orwell