Take a look at the detailed course on People Analytics :

1. What is people analytics :

People analytics is the domain usually within HR / WFM  of collecting and cleaning and making sense of the data you have about your people.

And putting in a form it can be used for business decisions. You can simply look at retention and turnover. Or you can look at organizational performance and sales productivity and all sorts of other things. And so, it can start small and then grow over time.

Why is it such an important domain of business?

There are two reasons. Number one, we are in a very, very talent-constrained economy. And so, if your people are unhappy, Unproductive, misaligned. They don't know what they're supposed to work on. You keep just can't be a good company and so there's a huge demand for information about what is creating engagement? But why are people leaving? What do we do to improve productivity? So, the demand for information is huge.

The second reason that is so important is that the vast amount of data that we're collecting is probably orders of magnitude more than it ever was before. I don't know if most of you know this. But your employee badge, which most companies have is creating a stream of data about where you are. If you’re an engineer, salesperson, or Consultant in your company when you're moving from place to place.

One of the datasets that your company has is where you were where you clocked in and where you clocked out. There's all this information that companies are collecting about their employees similar to the data that we try to collect on customers.

What organizations are now beginning to realize, wow, this could be useful in understanding why this business unit is outperforming in this business yet.

2. How does it compare to AI, machine learning, and big data

There are many levels of technology and domains within people analytics so let me just quickly explain what some of these are so you understand these concepts.

The Fundamental sort of building block usually surveys.

So, one of the most common places where you have data about your people is the annual survey the pulse survey, the exit survey, the new candidates’ survey, the on-boarding survey. So, all that survey data. So, the first thing you’re going to do in people's annexes is you're going to look at that and make sense of it.

And get enough of it that it's reliable. One of the potential mistakes you can make is, people analytics is looking at one survey and drawing a very broad conclusion without making sure that it's actually statistically valid.

Beyond that, as more and more data become available in your HR department and you feel comfortable with the quality of the data. You’re going to be looking at a more sophisticated analysis. Does this particular answer to this survey correlate to sales productivity?

The or turnover or some other business or customer satisfaction in a hospital. For examples, Hospitals. Now know that data about employee happiness, has a direct correlation to actually patient outcomes, which is pretty significant issue. So, you’re going to do correlations.

And so, some background statistics and understanding what a correlation is, is going to be part of your job and as that progresses and you get better and better at it. There are more sophisticated mathematical techniques. Which fall into the domain of AI and machine learning, machine learning is a term that really refers to algorithms that can predict the future Based on data that you already have. AI is really a broader phrase that really encompasses statistics machine learning cognitive software, which actually can speak languages. And then it’s now being used to talk about visual representation understanding facial expressions, all these other ideas that are now reaching the consumer at some point, if we have cameras at work, that look at people’s faces and can tell you at the end of a meeting if it was a happy meeting or not. Companies are planning with that.

So, you’re probably going to have an opportunity as a people analytics specialist, engineer, or manager to move into some of these Advanced Technologies over time. It’s amazing to meet with HR departments around the world how quickly they are trying to adapt these new technologies to the office. So, all of that is going to be part of this domain, but you don’t have to understand all of it to get started.

3. A brief history of people analytics.

There’s actually quite an interesting history of people analytics and this will help you understand where it fits into your HR department, your IT department because if you look at the very, very beginnings of organizations design and when business was first being formed in the 1800s, there was this idea of industrial engineering. And one of the most famous industrial Engineers was a guy named Fredrick Taylor who actually studies the motion of ironworkers. And he mathematically kept track of how much weight they were carrying. Is there carrying around bolts of iron and he found that there was an Optimum weight that would if it was too heavy, they would carry more, but they would hurt themselves? It was too light, their productivity was lower.

And so that was actually, 200 years ago, the beginnings of this idea of using data optimize the workplace and from that research, which was done, really with probably pens and papers and sort of clipboards we move to a world of surveys employee survey and collecting data and computers. Often times through applicant tracking systems or even systems like that look at your resume. So companies started to develop richer and richer and richer data sets about their employees. So, we’ve evolved from this very simple industrial model of data to look at employees with all different types of data that cross over into IT.

When I got started as an analyst, there was a person in the training department. There was an analytics person in the recruiting department and there might have been an analytics person in the compensation department. Each of whom was independently looking at the data that they were managing to try to figure out what it meant.

What is this learning data mean?

Now, what we’re basically saying in people analytics is all of that should come together into one multi-functional group, that can look at the relationship between all these different types of data and that’s data coming in through IT, you’re going to learn things about your company that nobody else knows.

Because most line managers don’t know the things that you’re going to find out, you’re going to discover things about the company that is very, very important and very very strategic.

In some of the more sophisticated big companies, the people analytics person or group may migrate out of HR and work in operations because a lot of the things you’re discovering are things that affect the operational nature of the company itself. Not just HR.

4. How is people analytics is similar to Moneyball

So, one of the ways to understand people analytics is to look at the story of the book or the movies, Moneyball, which is about the Oakland A’s (Athletics), and the Oakland A’s didn’t have a big budget. They couldn’t afford to pay for the super hitters that made. And so they decided to apply some statistics in hired. Some, Ph.D. types and looked at the data on what really did cause a winning season because the goal is to win the season, not just to win one game or get a bunch of hits. And what they found and it’s interesting, the story in the movie is very, very fun to look at is that the recruiters the people that were out scouting looking for players were actually, some of the hardest people to change because they had been so ingrained in these traditional approaches to looking for players. That’s exactly what’s going on in your company.

How people are hired, who gets promoted who gets the new job who gets a raise, all the decisions are being made all the time in your company based on gutfeel. Sometimes there’s data most of the time there’s not and the impact of two or three or four or five percent improvement of those decisions is huge.

You have opportunities to improve all of those decisions that are being made all the time on the management side of your company with people Analytics. And of course, what would happen to the Oakland A’s is, they created a whole new industry basically for the baseball profession that has now become, very, very core to the whole domain and that’s what’s happening in HR.

As you start to get more sophisticated about the use of data in your company, you’re going to realize that you’re developing a competitive advantage that is helping you win games. Just as the Oakland A’s did at an ever-increasing rate. Of course, your competitors are doing the same thing. So, there is a little bit of a war going on here, for data to become smarter and smarter and smarter about what makes your company successful, but that’s why it’s such an exciting area to be affiliated with.

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5. How we can get started with people analytics

So, one of the questions are probably asking is how do I get started in this?

And I would say there’s a couple of things. If you’re a relatively small company or don’t have a dedicated team or a dedicated person rather than sit around and sort of academically figure out what you think would be an interesting problem to work on, start with your Business Leaders, start to with the line manager, start with the CEO and ask them, what are the two or three biggest issues you think we have in the company related to people? And let's go back and come up with a plan to study that problem.

Now you go back and look at the data you have. Do you have any data on that issue? Do you have turnover data? Data you have performance data chances, are you do?

If you can do one project where you can go either your CHRO or CEO however, your business counterpart is and show them that the data that you have is useful to make better decisions. You’re going to be able to go back and ask for more money, for more staff for more tools, for more sophisticated analysis.

Now that all said, a lot of you probably work in bigger companies where you already have a lot of this data. So, then the problem is usually building an integrated team that can look at the many sources of data you already collecting because what usually happens in bigger companies is, there is an analytic group that’s just doing employee surveys. There’s another analytics group that just looking at return on investment for training. There’s another analytics group that just looking at recruiting advertising spent, the candidate experience. Well, all of those great groups to have, and they’re all doing important work.

A lot of business problems cross those lines, and so, of you’re in a larger organization, the best way to get started, is to bring those groups together and start working on projects that are essential to the organization. The other thing that getting started is that you’re probably going to find that a lot of the data, you have as interesting as it is, is not that accurate, it’s not that clean, it’s not that complete. And so early on in your journey into studying the data about your organization, your people, you have to spend some time internally in HR and the IT departments, making sure the data is really high quality.

A lot of data that’s collected in HR is entered by line managers, or recruiters, or people in the HR department is entered incorrectly, it’s out of date, part of your getting started process is to make sure you have a high-quality source of data is trusted.

Again, if you don’t do that and you do all the analysis, you come up with all sorts of great graphs on what this all means. And then the business people start poking holes and find out that the data is not accurate. You’re going to lose your credibility for a long time. Unfortunately, you have to make a business case to your sponsors, whether they be the head of HR the head of the business that you must do that and that it will take time and it will cost money before you do the fancy analysis.

There’s a natural tendency for business people to say, well, go get me, the answer to this question and go find the data and they send off on a wild goose, chase to find accurate data and you find out it’s really, really hard to get it. And it’s really important to make a business case to your sponsors that we have to spend three months, six months, and a year, whatever it is creating a reliable integrated database first, and then we can do all the analysis.

It has been proven statistically through research that the companies that don’t do the core investment first, oftentimes underperform later. So that’s of getting started too.

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6. Good Examples of people analytics

There is a really inspirational example,

That will get you really excited working in this space. So, there’s a bank in Canada that has lots and lots of remote branches. And so, there is the retail bank and they also have other businesses and they found that in the retail bank, there is a fair amount of theft, people steel money. The steel cash things disappear and they found a sort of an unhappy inconsistent pattern of theft and somebody is said, we need to figure out why this is going on and so a project was initiated and it probably started in operations to figure out what can we understand about the pattern of theft in the company to reduce it.

And of course, the initial reaction to most of this problem is, let’s do more training and so they did all bunch of training, it didn’t really matter. There seemed to be no correlation between the groups that did a lot of training and the groups that had a lot of loss.

And so, the people analytics group got involved, and they started a little, look at the people-related data. Is it the tenure of the employees? Is it the management quality or that level of management, or the type of management? Is there something about these people’s background that we can use to understand why this is happening? You can imagine all the different directions, this one.

We did a bunch of analyses and they eventually came back to basic statistics of, all the data we’ve captured, what seems to be the most highly correlated with theft and sure enough they found is that the single most predictive driver of loss or theft in this bank, was the number of miles between the branch office and the distractive supervisor and they thought, well, that’s interesting. What does that mean?

Well, it turns out those branches, don’t get visited very often by the boss they’re left alone. And so, the people on those branches to get this feeling like, what, nobody’s really paying attention to what we’re doing. So, we can just like to bend the rules a little bit. And of course, once they understood that, was the problem. It was a really simple problem to solve. They just change the rotation of branch managers and they spend more time visiting these remote branches. They never would have known that they could have spent millions of dollars on training and never would have moved that needle. That’s an example of being operationally focused on people analytics doing projects that are meaningful to your company where you can add a huge amount of value in there will be immediate results.

So, leave you that example as an inspiration for working people analytics in general.

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How to use practical aspects of Data Science :

There are good ways and means to strategize into practice, take a look at the following sessions to understand in detail.

1. Art of the right people analytics gathering ( 07) 

2. How People analytics drives impact (08)

3)Setting up your organization team members for success (09)

4. Tools, techniques, and platforms (10)

5. How to Integrate with financial analytics (12)

6. Developing a career progression in people analytics (13)

Ethical considerations of People Analytics from Global WFM Forum on Vimeo.