Last month, we started going through what people analytics are, what the potential upsides are, and what some of the down sides are. Now we’ll continue with my interview with Kelly Reed, the managing director, global people & culture solutions with Lockton.

Outside of potential trust challenges of people analytics, are there any other downsides?

“Other potential downsides are if managers don’t know how to interpret the results, and there is a danger in misinterpreting people analytics findings and making bad decisions based on that misinterpretation,” she says. “Or, the risk of some shiny new technology leading organizations down the path of using it inappropriately, over-relying on the system in place of good judgment, or making an investment in a system they don’t really need.

“Data integrity and accuracy can also be a big issue – what if only 30% of the data in your source system is accurate? There is a real challenge of trying to make de-cisions based on faulty data that leaders may assume is accurate. Garbage in, equals garbage out. These systems have slick user interfaces that make the data look really believable, and provide unprecedented levels of insights; therefore, the potential for misuse now is much higher. So, unless an organization has people inside the organization who are well-trained in people analytics, they should be cautious in utilizing it and should understand the limitations of its use.

“Data privacy and security, of course, are a real concern as well. Therefore, with the above listed fears, a big challenge of people analytics is answering the ques-tion of ‘How do we give people an opportunity to opt in through informed consent?’

“Another potential downside is amazing people analytics findings aren’t enough – you need to bring business leaders along with compelling storytelling and influ-encing. You can come back with the most amazing people analytics findings, but if you can’t tell the story of why it matters, and bring along the stakeholders in a position to act on the results, it doesn’t matter.”

There definitely seem to be a number of items to work through, and there seems to be some high upsides. Kelly mentioned that Google had a really great exam-ple.

“Google had a people analytics program it ran years back,” she says. “They found out they were spending an inordinate amount of time in interviews, and they were concerned about the user experience. So, one of the folks on the people analytics team ran an analysis at what point in interview process do you have enough information to make a decision?”

Four interviews was the answer. (Four interviews was enough [for Google staff] to predict a new hire’s performance with 86% confidence at Google.) After the fourth interview, the accuracy of the mean score increases by less than 1%.

“The implications of this research were obvious: We [Google] could confidently make hiring decisions with as few as four experienced Google employees conducting interviews, and it has saved employees hundreds of thousands of hours in interviewing time, and has helped reduce the already stressful process for candidates (re: work website),” she notes.

For MEP engineers and the construction industry, this has obvious correlations, as Kelly indicates.

“The cool thing about this is anyone who is concerned about being more productive, efficient and engaged at work, people analytics can help them get there,” she explains. “More employees can be engaged and less stressed. From an employer or leader perspective, people analytics can help you get more and better talent for your organization, grow and retain that talent, and optimize engagement and performance of your people. It’s a compounding effect. Some organizations have already gotten so far so fast because they were early adopters of evidence-based people decisions. It’s kind of like saving for retirement: if you start early, the compound effect over time puts you much further ahead than if you start saving later in life.”

Seems like pretty powerful stuff to me. But the proof is in the pudding, or implementation. I started wondering if there was an increase in organizations using people analytics, and whether a majority of those organizations were having success with it. Kelly answered with a resounding yes.

“There are a number of companies using people analytics to achieve some pretty remarkable business outcomes,” she says. “More technologies are becoming af-fordable and scalable, and more leaders are becoming aware of the importance of evidence-based people decisions. Before your company gets started on people ana-lytics, it is important to assess your organization’s people analytics maturity and readiness to ensure that you start where you will get the most traction, and that you don’t introduce unnecessary risk with ‘too much too soon’.”

Of course, there has to be good, better, best people analytics, right? I asked Kelly about this, and she quickly steered me in a different direction. It wasn’t about the type of people analytics tool, but rather how it is used!

“People analytics are less about the tool, and more about the process,” she notes. “I’m a big fan of [the process of] strategic analytics. ‘What are the business pri-orities and how do those translate to our people priorities? What is the most pressing talent question we need to solve?’ Start with those questions and use them as a blueprint to direct your search. If you just start with data or the tool, you could end up tuning into more noise than signal. The questions determine the data and tools required to get the desired insights.

“Every organization has their own unique business strategy, their own unique people strategy, and their own unique people and culture makeup. It is critical to consider these factors as part of the people analytics equation. For example, Organization A may see that they have high turnover in the organization and decide to implement programs to reduce turnover. They decide to give all their employees bigger raises and bonuses. Six months later, turnover hasn’t gone down, and they can’t figure out why. Contrast that with a strategic analytics approach: you may start by determining that too much turnover in a particular job type will hinder strat-egy execution. From there, you would investigate the drivers of turnover for people in that job type based on historical turnover data, other HR systems data, and potentially through exit interviews, surveys, etc., to understand why people in that job type are leaving. Then, based on the findings, the organization might invest in targeted programs to address those specific turnover drivers for workers in that specific job type and monitor results over time. This is likely to not only be a more effective approach, but a more cost-effective approach as well.”

So, making sure you know how to use people analytics is definitely an important step. Who exactly is trained to use people analytics?

“There are three types of skill sets needed for an effective people analytics function,” Kelly explains. “First, there are data geeks — people who are extremely savvy with data and technology such as data scientists and data engineers. These are people who can extract meaningful data from information systems and build data algorithms and dashboards.

“Secondly, we have people geeks such as behavior scientists and organizational scientists; people who understand people and organizational dynamics. Typi-cally, these people have advanced degrees in industrial-organizational psychology. Finally, there are business communications geeks. These are people who understand the business, and how to tell a story that will be compelling to business leaders based on the findings from people analytics initiatives.”