About WPAC

People analytics is a data-driven approach to managing people at work. Those working in people analytics strive to bring data and sophisticated analysis to bear on people-related issues, such as recruiting, performance evaluation, leadership, hiring and promotion, job and team design, and compensation.

This blog features a series of interviews with some of the experts in the People Analytics field.

The second annual Wharton People Analytics Conference will be on April 10-11, 2015 at Ritz-Carlton Philadelphia!

Interview with Xan Tanner, Co-Founder, Panorama Education

Interview by Lisa Donchak

Xan Tanner is a co-founder of Panorama Education, a Boston-based startup that helps teachers and administrators improve their schools through data analytics.  Panorama Education uses feedback surveys of students, parents, and teachers to improve teaching and school culture. In the past year, Panorama has worked with over 5,000 schools and over a million students, with clients including the Massachusetts Department of Elementary and Secondary Education, New Haven Public Schools, and Teach for America.  Before founding Panorama, Xan worked on the coaching staff of the Yale Men’s Basketball Team as the Head of Analytics. He currently is a mentor in the Harvard Graduate School of Education Doctor of Education Leadership Program and was named a member of the 2014 Forbes 30 under 30 in Education. Xan received a B.A. from Yale University in Religious Studies. He’s also a speaker at WPAC2 this year!

WPAC: Tell me a bit about your background – how did you get involved in People Analytics?

XT: My first work in analytics – and actually People Analytics – was in college basketball. I worked with the Yale men’s basketball team to create opponent scouting reports and different internal reports, based on analytics, for both the players and the coaches.

It helped shape a lot of how I think about it now – oftentimes, there’s this tendency to show as much data as possible. One of the most helpful things we did was make try to make it simpler. Instead of saying “Here are the different free throw percentages of different players,” the scouting report would say “Foul this guy.” That was my first real experience helping people improve things through analytics, which led to Panorama later on.

WPAC: “Tell me a bit about Panorama – you provide a feedback survey tool that, among other things, helps provide ratings on schools, school climate, and teaching.”

XT: Panorama Education is a Boston-based analytics company that helps schools and districts survey students, parents, and teachers. Then we provide those feedback reports to teachers, principles, superintendents, and other district staff. [These results are] used as part of goal setting, professional development, and strategic planning for the school. We help districts with everything from the design of the survey questions to the reporting back of the feedback, and that goes back to every official in the district.

WPAC: Can you give me an example of work that you did with a school you’re particularly proud of?

XT: We work pretty closely with Teach for America. Teach for America is a tremendously data-driven organization and it has been fantastic to learn from how they use surveys. For the regions that have opted into working with Panorama, their teachers go to the Panorama platform, create a survey based on the network-wide questions, their individual region’s questions, and any questions they personally want to ask. They then give that survey and get feedback from their students. Once they ship the surveys back to us, and we’ll send customized reports to the teacher and their MTLD – their Manager of Teacher Leadership and Development – basically a professional development coach. They’ll sit down and go over those variables together, and set goals off of that. And we do that three times a year. It’s a really exciting implementation for a variety of reasons.

One, it’s valuing student feedback from the outset of the teacher’s career, and establishing that the teacher should be actively seeking feedback from their students and growing from that. Two, teachers are getting that feedback frequently and setting real data-driven goals off of that feedback with their coaches.

WPAC: What’s been your biggest People Analytics-related learning [or mistake?]

XT: You can’t just present all the information. Just because you collected that data, doesn’t mean that it’s useful for someone to see it. You might have gone through quite a bit of work to do a piece of research or come up with a new metric and it seems like it should matter, but just because you did it doesn’t mean it’s all useful or worthwhile.

A lot of the hardest work that needs to be done is culling that data and that information down into something that’s meaningful for the person receiving it, so they can actually take a few, bite-sized pieces of data and turn that into actual improvement.

WPAC: What’s the future / next step in People Analytics? What trends are you most looking forward to seeing play out?

XT: The biggest thing is that we as a society are going to become more comfortable with data. Right now, People Analytics is a bit limited to the people that are comfortable with data, and have the technical skills to really understand what analytics is and how to internalize the signal . What’s cool is that I come from sports, and in the last five years, analytics in sports has gone from “no one is doing it” to “you have to be crazy not to have some sort analytics staff as part of your front office.”

What I’m excited about for People Analytics and analytics in general – analytics within management, analytics within performance, analytics within recruiting – I think that we are, as a society, gradually becoming equipped with the skills and tools in data processing to understand what all these analytics mean, and as a result, some of these areas that have never before [implemented analytics], are now going to be able to. Once we reach the tipping point of knowledge and skill set, I’m excited to see the juggernaut that is formed.

WPAC: What advice do you have for those interested in implementing People Analytics solutions?

XT: Start small. Start with a few things that are easy to track that you can really build as KPIs or monthly stock take numbers. As you see people understanding those numbers and adapting them, you can add more and more. Internally we use data quite frequently, and when we are successfully keeping track of KPIs it starts with one or two numbers, and as we understand the data we add more to help capture additional dimensions of our work.

Interview with Sean Waldheim, VP of Admissions, Teach For America

Interview by Lisa Donchak

As the Vice President of Admissions, Sean oversees the team responsible for creating and refining the processes, policies and procedures for selecting and matriculating Teach For America’s corps each year. More than 50,000 people applied to Teach For America in 2013-2014. Sean’s team carefully screened these applicants in order to select more than 5,000 individuals who comprise the 2014 corps.

Prior to becoming Vice President of Admissions, Sean spent five years leading the selection arm of the Admissions Team. His team researched the skills and attributes associated with the most effective corps members and used this research to refine Teach For America’s admissions process.

Prior to joining the Admissions Team in 2007, Sean spent five years leading more than 250 corps members in the San Francisco Bay Area as a Program Director and Managing Director of Program. Sean began his career with Teach For America teaching science at Abramson High School in New Orleans. Sean is a graduate of Macalester College, with a degree in neuroscience and a minor in political science. Sean was also a speaker at WPAC1.

WPAC: Tell me a bit about your background – how did you get involved in People Analytics?

SW: Growing up, I was always really interested in people.  What makes us tick? Why do we do the things that we do? I also was moved by the importance of doing right by people and was aware of inequities in our society.  My parents instilled the importance of doingsomething when were not treated right.

In college, I studied neuroscience, and I spent a whole lot of time learning about people and what makes us tick.  My plan was to go to medical school to continue that type of work.  However, when I heard about Teach for America, I thought this would be such a great opportunity to address what I had seen as some of the biggest inequities in our country. I knew the education system did not give everyone an equal opportunity and I felt really motivated to do something about it.  That’s how Teach For America brought me into education 14 years ago.

My experiences teaching high school and coaching new teachers strengthened my conviction that education is, indeed, the biggest civil rights issue facing our country. I saw many talented students not getting the opportunities they deserved, even as many teachers and principals worked incredibly hard and did great things for students.  I saw an education system that failed to provide the fundamental things that students and teachers needed.  When I saw first-hand the impact this had on students, families, and teachers, it felt incredibly wrong.

I knew I wanted to stay in education and focused on the what I cared about most – the people.  Education is fundamentally about people since most of our spending goes toward human capital.  We have a very long and proud history in our country around public education, and it felt very important to figure out how we can take scientific techniques to understand the teachers who are having the very biggest impact on students and how to recognize that potential at the stage of hiring.

I knew Teach for America was (and still is) on the cutting edge of that work.  That’s what drew me to my current position leading the Admissions Team at Teach For America.

WPAC: Where is Teach for America in terms of implementing People Analytics solutions? What is the impact of People Analytics on your organization?

SW: The most important thing – the biggest idea or takeaway – is that People Analytics isn’t something you arrive at. It’s an ongoing quest for improvement. Within Teach for America, we have a foundational question that grounds our work: “What differentiates our most effective teachers in terms of their impact on students, and how can we recognize that potential at the stage of hiring?”

It’s fair to say we’re obsessed with that question. It’s not something we ask ourselves once and think we’ve got it, or ask ourselves once a year and think we’ve got it. The work we’re doing is constantly about that question. We keep track of all the different skills and attributes that we can observe at the stage of hiring, and we frequently test new things that we think might help us identify excellent teachers.

To be clear, we can’t just look at the data.  As we try to figure out all the complex set of things that drive impact with the student and teacher, we do significant qualitative research – observations, speaking with the people who work closely with our teams, reading scientific literature, brainstorming.  However, the data component absolutely grounds our research and fuels this ongoing exploration around this key question around how we can identify teachers and their impact in terms of students.

WPAC: Is there anything your team is working on that you’re particularly excited about, related to People Analytics?

SW: There’s so many! If I was to highlight one piece – this is not a new thing, but it makes this work particularly important and unique – we’re particularly focused on how we can identify teachers likely to work with their students in a culturally responsive manner. That’s critical research that relates directly to the development of students.  There’s a lot of important research about the attributes of culturally responsive teachers, such as the work of Ana Maria Villegas and Tamara Lucas.  They identify actions like understanding there are multiple ways to see the world, learning about students, viewing different worldviews as assets (not liabilities) in the classroom.  There’s already some ground breaking research, so our charge is to figure out how to apply these principles to hiring in our context.  [I’d argue these ideas are broadly applicable to almost any field.]

In the world of hiring, there’s a lot written about things like SAT scores, GPA, etc. There’s frankly less – there is some great research such as some of the work mentioned above, but less – about how to identify those things that influence how someone works successfully across lines of difference, how to identify teachers who specifically approach their students in an asset-based and affirming manner, etc.

That’s not new research for us, but that is research that we’re very focused on and is a key part of everything we’re striving to learn.

WPAC: What’s been your biggest People Analytics-related learning [or mistake]?

SW: There’s no silver bullet. That sounds so obvious to say, but I think the thing I find most complicated is that when we have big breakthroughs, it’s tempting to over-focus on that breakthrough. In space of hiring, it’s a breakthrough when we find, statistically speaking, that people who do better in whatever it is that we’re talking about are more likely in our context to have a big impact as a teacher with students, but there’s still many, many individual exceptions.

I think it can be tempting to focus on the latest breakthrough and think, whatever it is, thatis the key, and everyone who does well in that thing is going to do great, and everyone who doesn’t do as well in that attribute is going to struggle.  That is just is not true. Humans are incredibly complicated.

That leads me to our biggest learning: our teachers who have the biggest impact have multiple, deep strengths they leverage on behalf of their students, but those strengths are not all in the same things.  There’s no single profile of a highly effective teacher.

In People Analytics, sometimes we unintentionally think we found the silver bullet, and it’s important as we make major breakthroughs to remember that there are many, many exceptions, and we want our hiring screens to not lose those exceptions.

WPAC: What’s the future / next step in People Analytics? What trends are you most looking forward to seeing play out?

SW: I’m obsessed with this idea of uncovering deeper insights about, in our instance, teachers and leaders who work in a culturally responsive manner and who, in whatever their job, can work very effectively across lines of difference.  If we look at our country today, there are very serious struggles across lines of race, class, and many other things. For us, it’s incredibly important we find teachers and leaders who deeply understand these inequities and who have the conviction and skills to work toward ending them.  I’d like to see many more organizations and companies focus on identifying and developing leaders who will work to a more equitable and just world.

WPAC: What advice do you have for those interested in implementing People Analytics solutions?

SW: Don’t get lost in the data. In our hiring process, I strive for a process that’s both qualitatively rich and quantitatively rich.

To give an example of what I’m getting at, we do use fairly sophisticated statistical analysis to build a quantitative model that informs our admissions decisions. That is all accurate and true. At the same time, that model is only going to be as precise as the quality and robustness of the data that is collected. That’s where the qualitative component comes into play.

What I really obsess about when I’m thinking about a candidate is not what the data is telling me, but, “Have I uncovered this individual’s full story? Have I really understood all the different strengths and also the different areas of growth that the individual might bring to the classroom as a teacher?”

Even as I’m using the quantitative inputs to guide what I do, I constantly have to ask myself:  “Would I want this individual teaching kids for whom I care about deeply?” I’m not a parent, so I can’t ask the question, “Would I want this person teaching my own kids?” But if I were a parent, that would be the question I’d be asking.

It’s so unbelievably critical that our work is not locked to the data, but that it is qualitatively robust, and that we’re really understanding the reality of the stories, complexity of the people that are working for us.

Connect with Mr. Waldheim on LinkedIn.

Interview with Ben Waber, CEO of Sociometric Solutions

Interview by Lisa Donchak

Ben Waber is recognized worldwide as an expert in people analytics, collaboration, and wearable technology. He is the leader of Sociometric Solutions, a behavioral analytics company that uses wearable sensing technology to transform how companies are managed. He is also a visiting scientist at the MIT Media Lab, where he received his PhD, and he was previously a senior researcher at Harvard Business School. Ben has been featured in Wired, CNN, The  New York Times, and the Wall Street Journal, among other outlets, and his work was selected for the Harvard Business Review’s List of Breakthrough Ideas and the Technology Review’s Top 10 Emerging Technologies. His book, People Analytics, is an international bestseller and was released in 2013 by the Financial Times Press. He’ll also be speaking at WPAC2 in April!

WPAC: You’ve been working in this space for a while – tell me a bit about your background and how you got involved in People Analytics.

BW: I come from a computer science and social psychology background. I got my BA and MA doing computer vision research – using video to understand how people are behaving in the real world. When I went to MIT, I started to get into this wearables and sensors space. By chance, we’d been using next generation wearable sensor badge technology in the lab, called Sociometric badges to understand salary negotiations – how much money you might actually make based on your tone of voice, how much you interrupt someone …

These badges collect data on how people talk to each other- not content, who talks to whom, location, and movement data.  They’re essentially next generation company ID badges.

We got approached by some professors at MIT Sloan who were working with some large banks in Germany. They were collecting survey data, but they thought face-to-face interaction was the most important, and they asked if we could measure this.

The early version of the Sociometric Badges looked like a tie. We brought these to this bank – we didn’t really know what we were doing, because nobody had collected this kind of data before. We said to ourselves: with surveys, we can collect data on social networks. Let’s look at that – who people talk to at work.

[At this bank], they had really good job satisfaction data, and we were able to look at it day by day, and look at what behaviors that predicted how happy people were.

At the same time, we were collecting email data. We collected survey data every day. The surveys were super inaccurate. We asked [employees] how productive they feel – those sorts of things – it was a little 15-second survey.

What was really interesting was that all the metrics that these professors from Sloan were collecting, all this email data, had some predictive power in terms of figuring out how productive and happy people were. But the Sociometric badges … just looking at a few of those features, were about six times more predictive than all of those other measures. We were predicting over 50% of the variance of those outcomes. For those scientists out there, that’s a pretty big number. Insane number.

[The bank] reorganized their entire company based on that first analysis we did. A big, multi-billion dollar company changed they way they work. And that’s what made us think we had something.

Over the next five years at MIT, we continued to develop the technology, going from company to company, not only showing that we could do better than we’d done at first, but also that we could measure the effect of that change we enacted.

A few years later, my coworkers and I graduated with PhDs, and companies came to us asking us to do this. And that’s when we founded Sociometrics.

We look at things like measuring stress, predicting turnover, and we don’t have to wait a year to publish a paper on it. We can look across dozens of technologies using our technology today … and quickly roll out and test these hypotheses. Just like Amazon does with their [A/B web design] testing, that’s what we’re allowing our customers to do with their people. I will know [in a week] week if something changed … I’ll just see it.  That’s where People Analytics and HR is going to go.

WPAC: What cool research is happening in People Analytics? Anything you specifically are working on that you’re excited about?

BW: There’s a few things – short term things – I’m excited about, and long term things I’m excited about.

In the short term, I’m very excited about this idea of rapid A/B testing of management. With individual data and sensor data coming in rapidly, you can very quickly test out ideas that today are based on gut instinct. You can say “I don’t know how to lay out an office. Let’s try five different models and see how they affect key metrics. Let’s test that out.”

There are very few companies that are doing this today. Even Google, which is doing A/B testing, typically rely on surveys – not to say that’s wrong or bad, but it’s still orders of magnitude slower than what other technologies [allow]. There will be a sea-change – you’ll see people from machine learning, big analytics shops, PhDs in organizational behavior, consultants and  programmers, that will subsume traditional HR today.

The next area is gonna take a little bit longer. Kent Larson over at MIT Media Lab is doing something really interesting. He’s created an office that is essentially robotic [ed. note – called CityOffice]. You have tables and chair that can move themselves around and reconfigure [the office layout]. You want to make a cubicle [setup] for 10 people, you have this little bot that will transform [the space]. If you want to have a meeting, it will rearrange into a circle. There’s a whole variety of transformations they can do. Today you sort of manually configure it.

The step beyond this is having data drive those transformations. It’s having humans in the loop for setting goals on what you want collaboration to look like. You can configure the environment in such a way that it will encourage interactions, and the space will optimize around specific behaviors. Every year, every quarter, every month, you can rearrange things. Imagine coming in tomorrow and things are just a little different.

These changes can allow you to dial in rapidly and very quickly improve performance. These slight changes are responsible for a huge amount of how people communicate at work. This is something we have a lot of research on. Our HBR article talked about data we collected, that showed that the likelihood of you talking to someone is based on how long it takes you to walk to a person’s desk.

We’re starting to see a lot of tech companies realize this intuitively. A lot of companies, based on their gut, believe a good workplace is desirable, but the next step is not believing – or proving – that it’s true, but really utilizing data and space to dramatically improve collaboration, and use People Analytics to drive how people operate at a fundamental level.

WPAC: What barriers do you see for adoption right now?

BW: We work a lot with Fortune 500 companies, with heads of global services who oversee corporate real-estate and HR. There’s a broad realization that things as they are need to change – indeed, these divisions are increasingly marginalized and not appreciated for what they do. Also, [HR organizations] are not able to adequately impact or reflect the impact they have on the business.

Overall, you see people in these situations where they oversee functions in HR, or are starting a People Analytics group – which is happening at a lot of companies, and I’m sure we’ll see them at PAC – traditionally, these divisions of large companies don’t have a budget set aside for People Analytics.

You won’t see heads of HR or People Analytics say data doesn’t matter at all – they do [say that], even if they haven’t been to PAC or one of these events. The difference is, when it comes to building a team, investing in the tech to make this happen … [People Analytics] hasn’t existed before, and you don’t have that kind of money set aside.

Typically, the way these [HR] organizations are viewed – they’re viewed as a cost center. The [HR] orgs that are gonna succeed, they’re the ones where the CEO says, “this is a strategic priority for us.” They’re gonna hire people with these capabilities, buy technologies like sensors and email analytics. These are the companies that are forward thinking and are gonna succeed. You need to get buy-in from the rest of the C-suite to make it happen.

WPAC: What advice do you have for those interested in implementing People Analytics solutions?

BW: It’s a good question. Really, you do need buy-in from leadership in the company.

If you run a division yourself, maybe you can bring in a few people in-house to build a People Analytics capability. Really, to get serious about it, you need to hire a whole bunch of people to make it happen, and bring on a lot of technology to make it happen. Relying on surveys is a stopgap solution. When you’re presenting to a CEO and you want to show an ROI of what you’ve done, things like surveys are a lot harder to sell. Things like email analytics, sensor data – you can really put hard numbers on that in terms of improving performance, improving retention.

There’s a lot around analysis of resumes to staff people better. That is  important. Long term, though, it’s not about bringing in the most brilliant people in the world. If we hire a pretty good group of people, get them to collaborate effectively and share ideas, that’s where the benefit of People Analytics really comes in. That’s what companies need to emphasize, and what people need to emphasize to their leadership.

If you invest today in hiring people with these capabilities, people from machine learning, big analytics shops, PhDs in organizational behavior, consultants and programmers, it’s a big investment. But in ten years, everyone is going to do this.

Twenty years ago, Amazon was doing A/B testing on their website. Everyone thought it was crazy and a lot of effort.

But we’re seeing greater benefits in the workplace [from People Analytics solutions] – the smallest improvement our customers have seen is a 7% increase in sales. If you look at other companies that are doing email analysis, you’re still seeing a big lift you can’t ignore.

In 10 years, everyone’s will have to do this. But if you wait until then, organizations will be changing day-by-day based on their analytics. In the years you’re catching up, your competitor is growing 20-30% more per year.

You need to do it in the next couple of years, otherwise you’re going to be left behind.

WPAC: Anything else you want to share?

BW: [People Analytics] is hard to do today, [and] that’s why you need to do it. Which is weird, because typically you want to wait to do things like this. But it’s similar to marketing. People in traditional HR departments need to think about how it’s structured moving forward. You can’t get by going on gut instinct anymore. You maybe have a few years of that left. You can see leaders [in this space] and companies who are doing poorly, and the middle of the pack will come in the next few years.

Okay, so Google’s doing it, and they’re weird. When a big, French company does it – the point is, even those kind of companies are doing this. And that’s very validating.

To learn more about Dr. Waber’s work, connect with him below:

Twitter: @bwaber
Website: www.socio-metric.com
MIT Media Lab: http://web.media.mit.edu/~bwaber/

Interview with Andrew Stern – Leadership, Learning, and Organizational Development at Bloomberg LP

Interview by Lisa Donchak

Andrew Stern works on the Leadership, Learning, and Organizational Development team at Bloomberg LP in New York. Andrew is currently building a new global leadership development program and community for Bloomberg’s individual contributors. He also leads the firm’s senior executive onboarding efforts globally, and previously managed Bloomberg’s global new hire onboarding program. Prior to joining Bloomberg, Andrew worked as a human capital consultant for Deloitte, where he advised Fortune 100 HR organizations on talent strategy, learning and development, and leadership programs. Andrew graduated from Wharton in 2010 with a concentration in Organizational Effectiveness. He was also a speaker at WPAC1!

WPAC: Tell me a bit about your background – how did you get involved in People Analytics?

AS: After graduating from Wharton in 2010 with a concentration in Organizational Effectiveness, I went to work for Deloitte’s human capital consulting practice in New York. While the majority of my projects pertained to learning and leadership programs, change management, and career development initiatives, I was especially engaged by my final project with the firm that introduced me to the As One leadership alignment diagnostic. The methodology and user-friendly technology were my first window into the power of people analytics to support strategy selection and implementation, in this case. Our team was tasked with helping clients identify pockets of their senior leadership teams that weren’t actively committed to the firm’s strategy and could inhibit successful strategy execution down the road. Equipped with this knowledge, senior executives could proactively work to address concerns in certain business units, regions, or other groups. Our team empowered leaders to complement their big-picture thinking with precise change / stakeholder management approaches, making them and their firms more successful.

WPAC: Where is Bloomberg in terms of implementing People Analytics solutions? What is the impact of People Analytics on your organization?

AS: As a company built on providing transparent, real-time, and actionable data to our clients, Bloomberg sees great potential in this space and is excited to see how it will transform discussions across our business units. I’m particularly excited about the potential for people analytics to demonstrate the value of learning, leadership, and career development programs, enabling HR to even more clearly communicate its value as a strategic business partner / enabler in organizations.

WPAC: Is there anything your team is working on that you’re particularly excited about, related to People Analytics?

AS: In 2014 I led the construction and global rollout of Bloomberg’s first individual contributor-focused leadership development program. While building the program, our team made a conscious effort to elevate the rigor of the assessments used before, during, and months after the experience. In addition to measuring changes in participants’ confidence across the topic areas we explore in the program, we also ask the participants’ managers to evaluate changes in their direct reports’ demonstrated levels of competence across these same topic areas.

WPAC: What’s been your biggest People Analytics-related learning [or mistake]?

AS: Coming to the 2014 People Analytics Conference (WPAC1) exposed me to the best-in-class, aspirational people analytics strategies other companies and researchers are already practicing. I’ll always remember when Wharton professor Adam Grant shared, “Don’t lose the art in the science of people analytics,” among other gems. Part of that art is knowing how much change your organization can handle at one point in time. Introducing or advocating for certain people analytics strategies simply because other companies already have them in place doesn’t always make sense, and represents my biggest learning.

For example, at WPAC1 I met numerous HR leaders whose companies employ peer reviews when employees attend certain learning and leadership development programs. In other words, when an employee attends a training program, his or her teammates may be asked to assess whether they notice sustained behavioral change following their teammate’s experience. I proposed a similar approach when our team was designing the aforementioned individual contributor-focused leadership program, and was met with resistance. There was concern that such peer surveys may be confused with other employee assessments Bloomberg administers. People analytics fans must still strive to meet their organizations where they are.

WPAC: What’s the future / next step in People Analytics? What trends are you most looking forward to seeing play out?

AS: There are three people analytics movements underway that excite me. First, research by leaders like Mike Housman will hopefully continue to disprove certain inaccurate hiring stigmas. At WPAC1, for example, contrary to what many might expect, Mike shared research that past job hopping behavior doesn’t predict whether a new recruit will leave your company quickly. Similarly, he shared that there is no evidence that companies are at greater risk by hiring the long-term unemployed. Second, I hope we’re able to expand pre-hire assessment offerings beyond personality tests. I’m curious to see what tools emerge that can measure various types of fit before an initial resume or phone screen is even undertaken. The challenge for assessment designers is to build products that prevent or illuminate “gaming” by respondents, and for organizations to actually grow comfortable using such data in their hiring processes. Third, as more organizations adopt and gather results from people analytics, I hope that we’re able to, as Adam Grant put it at WPAC1, “overcome our organizational uniqueness biases.” If more companies followed Google’s lead by publishing results from their people analytics efforts, might we as a society benefit? Could we identify new topics to teach in universities, new fields of research, new performance evaluation criteria?

WPAC: What advice do you have for those interested in implementing People Analytics solutions?

AS: I have two pieces of advice for individuals looking to introduce people analytics to their organizations. First, as John Boudreau shared at PAC1, HR leaders are more likely to receive buy-in for this kind of initiative if it is framed in terms the CEO typically considers. For instance, instead of talking about “using people analytics to identify high potentials for development opportunities,” people analytics advocates may receive a warmer reaction if they position their investment pitch as being similar to customer / audience segmentation efforts that a marketing team may pursue before a product launch. Second, HR leaders looking to introduce people analytics to their organization should start by identifying a handful of research questions to which they would actually like the answers. For example, Google’s Project Oxygen was launched to discover whether managers matter and produced a list of eight key attributes the best managers possess. I would encourage those interested to start by identifying a few points of inquiry / curiosity – where they are also open to acting on the results – and let the solution search follow that.

To learn more about what Andrew is working on, connect with him below:

LinkedIn: https://www.linkedin.com/in/andrewustern
Twitter: @AndrewUStern

Interview with Bruce Fecheyr-Lippens, Solution Head of People Insights, a McKinsey Solution

Interview by Lisa Donchak.

Bruce Fecheyr-Lippens currently manages and leads People Analytics at McKinsey (both internally and developing client solutions). He works for McKinsey & Company in the Brussels office, after a detour of 2.5 years in McKinsey’s New York office. Prior to becoming manager of People Analytics, Fecheyr-Lippens has been a generalist consultant for many years doing projects in Europe and North America across sectors (mainly Telecom, Financial sector, Healthcare and Pharma) and topics. Over the past years, Fecheyr-Lippens’s interest and expertise converged to the People, Talent and workforce Management space. From talent acquisition and recruiting, to employee retention, performance management, leadership development and diversity. Fecheyr-Lippens strongly believes in the power of analytics & data and hence explore ways to bring a true data-driven approach into HR through People Analytics as well as latest innovation in organization behavior and science.

WPAC: Tell me a bit about your background – how did you get involved in People Analytics?

BF-L: I was a generalist consultant, but quickly figured out I was passionate about everything around talent management. And so, that’s what I started doing as soon as I could at McKinsey.

I found my mission a few years ago, which is making a difference in the world of talent management. My aspiration is to bring innovation to talent management. I think you can do that in many ways, but one really exciting way is through people analytics. It’s a hot topic, and it’s something that brings real insights into the world of talent management. Above all it creates a win-win: A win for the employees as it enables executives to make better talent decisions, which in turn leads to higher motivation and engagement. Who doesn’t want to come to work engaged and have the time fly without noticing? This then translates to a win for the organizations as well in lower turnover, boosted productivity, and sometimes even lower retention costs. Ultimately I want to create positive change for the workforce. That’s what really excites me.

Three years ago, we did a people analytics study for a client and were so excited about the impact it had that we said, “We should do this for McKinsey internally.” We did the first analysis in our spare time, and the results have been so positive that it’s a key part of our approach to managing talent now.

WPAC: Where is your organization in terms of implementing People Analytics Solutions? What has the impact of People Analytics been on your organization?

BF-L: We are going from incubation to scaling. Senior leaders are seeing the value and are really excited about the power of people analytics. As a result, we are building out our team to meet two objectives: applying people analytics internally and developing a portfolio of client solutions driven by people analytics, which we call “People Insights.”

WPAC: Is there anything your team is working on that you’re particularly excited about, related to People Analytics?

BF-L: Yes. Two things.

First, when we apply people analytics internally, we focus on retaining our talent. We’ve found a few real insights that we are now implementing and that are having impact. One is that coaching and mentoring is even more important than we thought it was: when people are satisfied with their coaching and mentoring relationships, they’re 20-40% less likely to leave. Knowing this led us to further strengthen our already strong coaching and mentoring programs, especially for our younger colleagues. Two, we found that if you’re in a functional program (for example in organization, operations, or marketing and sales) you’re three times more likely to stay, because these practice areas tend to have access to a strong internal community of people, more opportunities for specialized training, and greater access to senior leaders. This insight led us to increase awareness and offering of those training programs.

Second, we’re building a really distinctive portfolio of client solutions called “People Insights”. One offering in the portfolio is our Retention Solution, which predicts the clusters of employees who are at risk of leaving and what specific characteristics they have. It also identifies the key factors that drive retention. We’re also building a performance predictor to identify future high performers, a leadership characteristics identifier and a resume screening algorithm. And many more to come. I am very excited about how much positive impact we’re having — and will have — on thousands of people at organizations around the world.

WPAC: What’s been your biggest People Analytics-related learning [or mistake?]

BF-L: That is a good question. I think it’s useful to highlight a few things that become clear to organizations that apply people analytics that aren’t always obvious at the outset.

First, IT is not a silver bullet to uncovering and solving people issues. In fact, doing people analytics will inform your IT needs.

Second, you can find talent to drive the effort in surprising areas. On my team, among others, I found talent from our risk practice and a generalist consultant who happen to have background in organizational psychology and was a head assessor at the military before joining McKinsey.

Third, machine learning algorithms are far more powerful than regression models to unlock hidden patterns and opportunities. It’s pretty amazing what the new tools can do.

Finally, and perhaps most importantly, involve your end-users. Bring them along, listen to their realities. Hearing them early and often will make adoption far smoother.

WPAC: What’s the future / next step in People Analytics? What trends are you most looking forward to seeing play out?

BF-L: I think we’re only at the beginning of the curve. I’m very excited about the future. I’m excited for a few things.

The major thing is just seeing much wider adoption. Today, only a very small percentage of companies are doing predictive analytics in HR. We expect that to increase rapidly as technology enables advances in this space.

I also think we’re going to see many companies treating talent management much like they approach customer relations. We’ll see HR policies that are highly tailored by employee segment and even by individual.

WPAC: What advice do you have for those interested in implementing People Analytics solutions?

BF-L: In addition to the lessons learned I mentioned earlier, I’d add one key thing: Tackle the questions that matter most to the business. Then senior management will listen and engage. Whether that’s retention, leadership, recruiting or something else, figure that out first before starting.

WPAC: Anything else? 

BF-L: People analytics has the power to completely change how we approach talent management. It’s a wonderful thing, however, it can never replace human decision making. It should inform and equip our decision makers to make better decision on talent.

Interview with Peter Cappelli – George W. Taylor Professor of Management; Director, Center for Human Resources, The Wharton School

Interview by Lisa Donchak.

Peter Cappelli is the George W. Taylor Professor of Management at The Wharton School and Director of Wharton’s Center for Human Resources. He is also a Research Associate at the National Bureau of Economic Research in Cambridge, MA, served as Senior Advisor to the Kingdom of Bahrain for Employment Policy from 2003-2005, and since 2007 is a Distinguished Scholar of the Ministry of Manpower for Singapore. He has degrees in industrial relations from Cornell University and in labor economics from Oxford where he was a Fulbright Scholar. He has been a Guest Scholar at the Brookings Institution, a German Marshall Fund Fellow, and a faculty member at MIT, the University of Illinois, and the University of California at Berkeley. He was a staff member on the U.S. Secretary of Labor’s Commission on Workforce Quality and Labor Market Efficiency from 1988-’90, Co-Director of the U.S. Department of Education’s National Center on the Educational Quality of the Workforce, and a member of the Executive Committee of the U.S. Department of Education’s National Center on Post-Secondary Improvement at Stanford University.

Professor Cappelli has served on three committees of the National Academy of Sciences and three panels of the National Goals for Education. He was recently named by HR Magazine as one of the top 5 most influential thinkers in management and was elected a fellow of the National Academy of Human Resources. He received the 2009 PRO award from the International Association of Corporate and Professional Recruiters for contributions to human resources. He serves on Global Agenda Council on Employment for the World Economic Forum and a number of advisory boards.

In addition to teaching one of the required core management classes in the MBA program – which this interviewer really enjoyed! – Professor Cappelli also spoke at WPAC last year.

WPAC: You’ve been working in this space for a while – tell me a bit about your background and how you got involved in People Analytics.

The idea of using data to understand employee behavior and performance has been around since WWI. There may be new terms for it, but what is new is:

1. New data and more of it about performance and about attributes that could relate to it, and
2. New people looking at it, typically people who don’t have any priors about human resources – no preconceived notions.

WPAC: What cool research is happening in People Analytics? Anything you specifically are working on that you’re excited about?

I’d say generally there are efforts to look at all kinds of individual attributes, voice to measure emotions, games to test reactions to work-like simulations, the nature of interactions employees have with each other. Anything that can be measured.

WPAC: What are the trends you see in People Analytics right now?

Mainly it’s about trying to predict who will be a good hire, a question that has been studied for ever but it is where the money is.

WPAC: What impact does People Analytics have on an organization? What barriers do you see for adoption right now?

The big barrier is that top executives haven’t been persuaded that people management practices matter much. The prevailing view is to hire cheap and fire frequently.

WPAC: What’s the next step in People Analytics? What excites you about the future of the industry?

Getting better at managing the huge data sets that some companies have on attributes like employee interactions has been holding up a lot of analyses.

WPAC: What advice do you have for those interested in implementing People Analytics solutions?

I think the action at the moment is in the start-up world and more generally in vendors who have the resources to look at some of these interesting questions. Most employers are unwilling to put the budgets behind the research needed to answer them.

You can learn more about Professor Cappelli’s work and research here.

Interview with Michael Housman, Chief Analytics Officer at Cornerstone OnDemand

Interview by Lisa Donchak.

Michael is the Chief Analytics Officer at Cornerstone OnDemand, where he applies state-of-the-art statistical methodologies and econometric techniques to databases consisting of hundreds of millions of employee records in order to answer two questions: (1) what keeps people on the job longer?; and (2) what allows them to perform better?

Dr. Housman has over ten years of experience engaging in econometric research and has had his work published in numerous peer-reviewed journals, international conferences, and has had his research featured by such media outlets as The New York Times, Wall Street Journal, The Economist, and The Atlantic Monthly. Dr. Housman received his doctorate in Applied Economics and Managerial Science from The Wharton School of the University of Pennsylvania and a bachelor’s from Harvard University.

Dr. Housman also spoke at WPAC last year. We’re excited to feature him as our very first WPAC interviewee!

WPAC: Tell me a bit about your background – how did you get involved in People Analytics?

MH: My background is a little unusual in that I was trained (at Wharton) as an Economist with a focus on health care management and economics. I began studying organizational behavior within healthcare organizations and found it to be fascinating: when doctors and nurses work well together and build a culture that’s oriented towards patient safety, it literally saves lives and there’s a documented impact on never-events like wrong-site surgeries, retained instruments post-surgery, medication errors and even falls.

From there, I decided to take a little break from health care to see if this same approach could help organizations in other industries like telecommunications, finance, retail, hospitality, etc. I joined an early-stage company called Evolv and we began applying predictive models to predict tenure and performance within large populations of frontline employees. It’s been an exciting ride and I’ve loved every minute of it!

WPAC: Where is your organization in terms of implementing People Analytics Solutions? What is the impact of People Analytics on your organization?

MH: Again, I’m a little bit of an unusual case because I work for a vendor that is very much focused on helping our clients applying people analytics to their HR data and extract value from it. We encounter organizations at very different stages of maturity but my sense is that most organizations are still very early-on in their journey and are trying to make sense out of the data they already have. I personally believe that there is tremendous potential in going down this path and have seen tenure improvement in the range of 10-20% and performance improvements in the 5-10% range when organizations have really embraced this philosophy.

WPAC: Is there anything your team is working on that you’re particularly excited about, related to People Analytics?

MH: Now that we’ve been acquired by Cornerstone OnDemand, we’re working on adapting our Insights product to their suite of talent management products. What’s exciting about that is that we’ll get access to TONS of new data from different modules that they already maintain: learning management, compensation, succession planning, recruiting, etc. So that means we’ll be able to answer a range of questions that we’ve never been able to answer before: Does compliance training (around things sexual harassment or financial malfeasance) actually work? What is the variance in hiring outcomes across different recruiters? What type of goal setting activities get the most out of employees?

WPAC: What’s been your biggest People Analytics-related learning [or mistake?]

MH: When we’re talking about the assessment platform, applicants are assigned a color-coded score (Red, Yellow, Green) that assesses their likelihood of success for a given role. When we’ve delivered results to clients, they’ve sometimes come back to us and said: “The platform doesn’t work because we hired a Green last week and she walked off the job during week one” or “You may need to fine-tune your algorithms because one of our best sales people scored a Red on the assessment.”

What I have to remind our clients is that these are probabilistic methods and not deterministic ones. The confidence interval around a single point estimate is very large but it narrows significantly when you’re looking at a population of employees. In the aggregate, we can show them performance bands for each of the color-coded scores that are very clearly differentiated.

WPAC: What’s the future / next step in People Analytics? What trends are you most looking forward to seeing play out?

MH: Here are my two predictions for where the industry will end up going:

1. Right now, it feels like everyone is developing flight risk models – which is great because it’s a huge step forward from where we’ve been – but I think people will discover that it’s too late to intervene with a candy bar, pat on the back, or raise once someone is disengaging. What’s more valuable is looking earlier in the employee lifecycle and using a guided “what if” analysis to fine-tune the different knobs and dials (e.g., supervisors, wages, overtime, etc.) BEFORE they check out mentally.
2. My sense is also that most people tend to be focused on the individual rather than the collective when deploying these solutions. Yes, the employee matters but our research suggests that their relationships with managers and co-workers is a much bigger driver of their tenure and performance than the knowledge, skills, and abilities they bring to the job. So I personally think that focus will shift once people realize that we’re fundamentally social beings that thrive on positive interaction with others.

WPAC: What advice do you have for those interested in implementing People Analytics solutions?

MH: Don’t try to eat the elephant in one bite. Start small, generate some quick wins, and then build off of those successes in order to evangelize the entire organization. I’ve seen massive deployments of talent management software that fail before they even start. It’s important to recognize that this is a journey and not a quick sprint to the finish line.

To learn more about what Dr. Housman is working on, connect with him below:

URL: http://www.michaelhousman.com
Twitter: http://www.twitter.com/michaelhousman

How Effective Is a Number-crunching Approach to Managing People? Interview with Wharton’s Cade Massey

Human resource professionals have begun to use sophisticated data analysis for all sorts of people-related issues ranging from recruitment and performance evaluation to promotion and compensation. People analytics, as this approach is called, is making waves because it is said to eliminate biases that exist in human judgment. Cade Massey, practice professor of operations and information management at Wharton, works at the intersection of psychology and economics and has focused on this approach. His expertise is judgment under uncertainty, looking at optimism, overconfidence and learning. Massey’s research is based on both laboratory experiments and archival studies of real-world behavior, such as the draft picks of professional football teams and the investment decisions of employees holding stock options.

Massey is one of the key speakers at a conference on People Analytics being hosted by The Wharton School on March 28. In this discussion with Knowledge@Wharton, Massey talks about the potential of this data-driven approach, its limitations and the lessons we can learn from the sports arena, which has been applying the discipline long before the corporate world.

The video is above, and the full transcript can be found here.