The Three Cities Problem in People Analytics
Directionally Correct Newsletter
By: Cole Napper
This article is written to discuss: the inflection point between science, faith, and utility in people analytics.
Recently, on the Directionally Correct podcast, my co-host Scott and I spoke with Amber West about a Wired article, the Three Cities Problem, in our segment called the “Nerdery”. That discussion inspired me to write this article. Luke Burgis, the progenitor of the thesis behind the “Three Cities Problem'', originally discussed the concept of the “Three Cities” as the intersection of reason, faith, and utility (more on this below) on his Substack in 2021, along with mentions of iconoclasts such as Peter Thiel, Rene Girard, the Greek philosopher Tertullian. In addition, his recent Wired article states the modern world is at a crossroads because of the complexity that arises from the “Three Cities Problem”.
So what is the “Three Cities Problem”?
For the last few thousand years, there has been a tug-of-war waged between the “Two Cities Problem”; the metaphorical battle between Athens and Jerusalem — otherwise known as the debate between science and religion or reason and faith. However, as Mr. Burgis so presciently articulates, there is now a third city in the equation:
Silicon Valley and the maximization of utility.
There is no longer only a debate between reason and faith in modern society, and when it comes to the marketplace of ideas, utility is also being weighed as an increasingly important concept.
“WHAT HAS ATHENS to do with Jerusalem?” asked the Christian apologist Tertullian in the third century. By this he meant, what does the reason of philosophers have to do with the faith of believers? - Wired Article
And what about the role of utility? In this piece, Silicon Valley and utility is the stand-in for the role of the capitalistic enterprise above and beyond truth or meaning.
The Role of Faith, Science, and Utility in People Analytics
It may not seem obvious, but faith, science, and utility all play critical roles in the success of a people analytics function. Intrigued? Let me explain:
Most everyone I know working in people analytics would initially recoil at the suggestion that faith has any bearing in people analytics. Commentary on faith is frequently used interchangeably with the disdain of intuition-based judgment, an absence of reason and facts, and even religiosity. But what if I told you that every people analytics project is successful because of faith? Are you establishing your first people analytics team? Faith. Are you investing in a project that’s never been completed before? Faith. Are leaders willing to take action based on an analyst's results, to whom they don’t personally know? Huge leap of faith.
The premise of why faith plays such a large role in people analytics has little to do with religion and a lot to do with the word influence. The godfather of influence research is Robert Cialdini and his most famous book, Influence, is littered with appeals to faith; such as faith in authority (leaders and experts know better), faith in social proof (if others have tried it, it probably works), and faith in scarcity (if there is less of something, it must be more valuable). Notice, none of these characteristics are scientifically quantified; rather, they are a gut-reactions. If you really go deep enough into influence, it’s turtles all the way down until you get to pure faith. As far as I can tell, there are three primary ways that faith plays a role in people analytics:
People analytics teams, first, have to believe in what we say and do
Customers, second, have to believe in what we recommend
Third, the employees we support have to have faith in us to do the right thing
I could even make an argument that faith is the most important component of people analytics success. I can’t tell you how many times I’ve heard members of our community, myself included, complain that they are doing amazing work, but none of their stakeholders are listening, and no one is taking action based on the results. The reason? They don’t have faith in us. That’s why. The first step in changing something is recognizing the problem…We have to do better.
The fact that science plays a role in people analytics may seem self-evident to most people analytics practitioners. And yet, it is not self-evident that science plays a central role in people analytics as currently constituted. Many people analytics practitioners are not classically trained in science and research methods and – with the rise of data science and “black box” models and/or under-trained entry-level analysts – increasingly common applications in people analytics have no grounding in science or theory whatsoever.
Science and reason – although not synonymous – both play a role in the success of people analytics. I personally prefer reason as the precursor to science. I’ve written about how important the scientific method is in people analytics before, so that should stand alone. Reason is also important because of the relationship between critical & analytical thinking in breaking down a problem and subsequent success in solving the problem. My bifurcation of science vs reason is as follows:
“Science is related to the scientific method (of which I’m a big fan). Reason, however, is related to critical and analytical thinking, for which is the trait I find most desirable in the teams of which I’ve built.”
In regards to reason, I’ve also written about the value of inductive and deductive reasoning in the past. Both kinds of reasoning play a role in effective people analytics. Someone has to generate the hypotheses to test (inductive) and then test the hypotheses with data and science (deductive). First principles thinking, a subset of reason, also plays in people analytics – exhibited by my article here. A simpler version of first principles thinking, root cause analysis, can be a very helpful framework to diagnose and fix problems using science and data.
All of the above is written to say, science plays a role in people analytics. Which is probably the least controversial thing I’ve ever uttered. 😁
What is the role of utility in people analytics? Utility plays a role in people analytics because people analytics only has value to a firm if it positively influences business outcomes – usually in the form of increased data-driven and data-influenced decision-making by organizational leaders related to their human capital. This point is brilliantly articulated in Max Blumberg’s Human Capital Value Profiler shown above. The school of thought related to focusing on “business outcomes” and being “strategy-first” in people analytics of which myself, Max, CEO-affiliated researchers such as Alec Levenson, and other key leaders in our field (i.e., Alexis Fink, Mark Huselid, Tracey Smith, Andrew Marritt, etc.) subscribe to regretfully appears to be a minority view in the field. Focus on utility will be the future of people analytics, if people analytics is to have a future.
The word utility often has a positive connotation. It’s about being useful and usable. Disciplines, such as user experience (UX), have cropped up in the softer sciences as ways of attempting to increase the utility, and therefore value, of modern business practices. People analytics has often missed the memo in regards to utility. Research (or “me”-search) for no one, not moving at the speed of business decision-making, seeing humanism and the success of the business as at odds, and making tools that are inaccessible or inaccurate all hinder the utility of people analytics. People analytics can do better.
One hears many phrases in the common business lexicon related to “utility”, such as maximizing shareholder value, minimum viable products (MVPs), “agile” innovation, “disruption”, and VC-backed HR Tech “unicorns”. Since the pandemic began, the HR technology space has seen more venture capital-backed investment than in any other time in history. The value and utility of HR and people analytics is at the forefront more than any time in the past. What are we going to do with all this attention?
A past article of mine discusses how do you pay for yourself as a people analytics function. When I’ve led people analytics functions in the past, I set a firm target that our function had to tangibly pay for itself 10 times over every year. This notion is based on the aspiration that the people analytics discipline has to serve as a “profit center” rather than a “cost center” or the discipline will likely not have a future. Conventional business wisdom dictates to reduce overhead and expand profitable sectors. People analytics only survives if it adds value. Some examples of being a profit center include: improving retention at a cost structure lower than the cost of turnover, increasing the quality of hires without increasing recruiting costs, driving increased innovation with existing talent, building efficiency into HR and into the business, etc.
As one of Paul Graham’s famous essays, on how to write usefully, states that what is written must be true, novel, and important for the writing to have utility. My hope is this article meets those criteria to have utility to you. 😁
Synthesizing All Three: Faith, Science, & Utility in People Analytics
The aforementioned Wired article introduces the concept of the three body problem from physics, as to why science, faith, and utility appear to be spinning out of control in our present world. When two bodies interact, such as planets orbiting a star in physics, there is predictability of measurement between the two objects. However, once a third body is introduced into the equation, chaos ensues. I don’t see much chaos ensuing in people analytics when combining science, faith, and utility of our applications. However, I do see neglect.
It is easier, as a people analytics team, to neglect the “legs of the stool” for which you have less interest or skill. But what happens when you neglect a leg of the stool?
If you neglect faith, your work will fall of deaf ears
If you neglect science, your work will be a sham
If you neglect utility, your work will have no impact
“At a certain point, I realized that I had spent time in each of the three cities and found each of them missing a healthy degree of interaction with the others….. I thought I was required to renounce one city before stepping foot in another. That is the tragedy of the three cities: the artificial walls that trifurcate us.” - Wired Article
People analytics leaders and teams need a healthy dose of all three “cities” to be successful. We can do better. We all know we can do better. Let’s do better together.
“The reasonable man adapts himself to the world: the unreasonable one persists in trying to adapt the world to himself. Therefore all progress depends on the unreasonable man.” ― George Bernard Shaw, Man and Superman
Will you come be unreasonable with me? Let’s create a people analytics movement. Let’s change the world. Let’s do better. 💪
I hope you like this article. If so, I have a few more articles coming out soon. Stay tuned. If you are interested in learning more directly from me, please connect with me on LinkedIn.
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Cole Napper is the VP of People Analytics & Product Evangelist for the innovative people analytics & employee listening platform, Orgnostic. He has 10+ years of rapidly escalating experience building HR centers of excellence from the ground up to scale — with an expert focus on People Analytics. He creates competitive advantage using People Analytics for companies big (Texas Instruments, Toyota, PepsiCo) & not-so-big (Motive, Booster). Cole is also the Co-Host of Directionally Correct, A People Analytics Podcast with Cole & Scott. Check out Orgnostic if you haven’t already, and join their free slack community.