Below are my thoughts on key points from Bock [emphasis added, where italicized]. For your reference, he also gave a video interview for Wall Street Journal - How Google Decides on Hires.
The Importance of Specificity and Insight
Big Data - when applied to leadership - has tremendous potential to uncover... universal things we should all be doing. But there are also things that are specifically true only about your organization, and the people you have and the unique situation you’re in at that point in time. I think this will be a constraint to how big the data can get, because it will always require an element of human insight.
In terms of leadership, success is very dependent on the context. What works at Google or G.E. or Goldman Sachs is not going to be the right answer for everyone. I don’t think you’ll ever replace human judgment and human inspiration and creativity because, at the end of the day, you need to be asking questions like, O.K., the system says this. Is this really what we want to do? Is that the right thing?Science is about patterns and aggregate. It looks for enduring trends in phenomena, and report findings that speak to characteristics of a population. Analytics, on the other hand, is about specificity and idiosyncrasy. For example, Google can target ads based on my profile on Google+ and my activity across Google platforms. For the longest time, in contrast, marketing focused on demographics (e.g., age group).
So Bock's point about what works at Google is a crucial one. By all means, turn to Google for its repertoire of lessons learned and best practices. But think these through carefully, decide what will and will not work for your company, and modify or adapt as necessary. Thinking, deciding and adapting are all part of human insight.
After two or three years, your ability to perform at Google is completely unrelated to how you performed when you were in school, because the skills you required in college are very different. You’re also fundamentally a different person. You learn and grow, you think about things differently.
Another reason is that I think academic environments are artificial environments. People who succeed there are sort of finely trained, they’re conditioned to succeed in that environment. One of my own frustrations when I was in college and grad school is that you knew the professor was looking for a specific answer. You could figure that out, but it’s much more interesting to solve problems where there isn’t an obvious answer. You want people who like figuring out stuff where there is no obvious answer.Measures and views of people are founded on the premise that we are static, discrete and acontextual. How far from reality that is, when we consider how much we change, grow and develop over time. Academia may often be too removed from the contexts in which students will work. It's about rigor and standards, which are certainly vital, but it may not necessarily help students learn what I call meta-skills, that is, the skills of acquiring skills, and the skills to adapt what they know and what they can do in unfamiliar, more complex situations.
The Challenge of Leadership
Leadership is a perennially difficult, immeasurable problem, so suddenly people are saying, “Maybe I can measure some piece of it.”
Part of the challenge with leadership is that it’s very driven by gut instinct in most cases - even worse, everyone thinks they’re really good at it. The reality is that very few people are.These border on over-statement, even provocation - for example, leadership is not an immeasurable problem - but the import of Bock's points is well-taken. Analytics offer greater specificity and accuracy to what leaders think, decide and do vis-a-vis what they aim for or what they envision. Although he doesn't tie gut instinct to human insight, I do. The idea is not to subvert intuition with analytics, but (a) to widen the means by which we grasp and get things done; (b) to optimize the activities of both the left brain and right brain; and (c) sharpen our gut antennae and know better when or where to use it.
The Accountability of Managers
Twice a year, anybody who has a manager is surveyed on the manager’s qualities. We call it an upward feedback survey. We collect data for everyone in the company who’s a manager on how well they’re doing on anywhere between 12 and 18 different factors. We then share that with the manager, and we track improvement across the whole company. Over the last three years, we’ve significantly improved the quality of people management at Google, measured by how happy people are with their managers.
We’ve actually made it harder to be a bad manager. If you go back to somebody and say, “Look, you’re an eighth-percentile people manager at Google. This is what people say.” They might say, “Well, you know, I’m actually better than that.” And then I’ll say, “That’s how you feel. But these are the facts that people are reporting about how they experience you.”
You don’t actually have to do that much more. Because for most people, just knowing that information causes them to change their conduct. One of the applications of Big Data is giving people the facts, and getting them to understand that their own decision-making is not perfect. And that in itself causes them to change their behavior.This is good, very good. I've coached leaders on their development, and using a 360° tool is quite illuminating for them. They get feedback about their competencies, based on what they do or don't do, and it comes from upward (boss), sideways (colleagues) and downward (staff). I imagine Google has other measures of managerial performance, that is, in addition to this upward feedback survey. But what they do, which I don't see enough of with client companies, is that accountability: They confront issues, expect change, and track progress.
The Importance of Questioning
We’ve done some interesting things to figure out how many job candidates we should be interviewing for each position, who are better interviewers than others and what kind of attributes tend to predict success at Google. On the leadership side, we’re looking at what makes people successful leaders and how can we cultivate that.
We’re also observing people working together in different groups and have found that the average team size of any group at Google is about six people. So we’re trying to figure out which teams perform well and which don’t. Is it because of the type of people? Is it because of the number of people? Is it because of how they work together? Is there something in the dynamic? We don’t know what we’re going to discover.This is definitely a Big-Data look at performance, from leaders to staff. Professional basketball teams have drawn on analytics to let the coaches know which five-man combinations on the floor play best against particular situations with opposing teams and even during which time frame in the game.
The Effectiveness of Behavioral Interviewing
On the hiring side, we found that brainteasers are a complete waste of time. How many golf balls can you fit into an airplane? How many gas stations in Manhattan? A complete waste of time. They don’t predict anything. They serve primarily to make the interviewer feel smart.
Instead, what works well are structured behavioral interviews, where you have a consistent rubric for how you assess people, rather than having each interviewer just make stuff up.This ought to be old hat for HR professionals: One of the best ways to predict future success in a role is examining past performance in a similar capacity. Maybe Google was once too cute or clever with its interviewing process, and perhaps learned through its own analytic prowess that cute or clever doesn't cut the mustard.
Thank you for reading, and let me know what you think! Also, if you'd like a PDF of this article, please e-mail me at Ron.Villejo@ronvillejoconsulting.com.
Ron Villejo, PhD