AI and the Future of People Analytics
Did you know that Google almost got rid of their managers?
Back in 2002, Google founders Sergey Brin and Larry Page decided to experiment with the idea of getting rid of their managerial class. Popular opinion at the time was that managers were an annoyance at best and an active drain on employee productivity at worst. As engineers, they shared the view of many of their peers that managers were little more than mindless bureaucrats. They decided to make Google a flat organization and, in the process, prove that managers were unnecessary.
The experiment was a resounding failure
Employees were unable to stay on track of their projects, projects were left undelivered, and engineers had no one to turn to for help with day-to-day queries. They quickly lost sight of larger organizational goals and there were no recourses for conflict management. Turns out people need active and intelligent oversight. Brin and Page abandoned the experiment within a few months and Google returned to a more traditional management style.
Looking back on this experiment today raises some interesting questions. Experts in data analysis and predictive modeling will tell you that many of the tasks which required managers back in 2002, could be handled by an Artificial Intelligence system today. Scheduling, project management, workflow approvals, payroll, and many other tasks traditionally performed by managers can now be fully automated. Aspects of Human Resource management have also been automated. AI systems are increasingly capable of using data analytics to predict employee behavior. Thus, we find ourselves revisiting confronting an update of the question that Brin and Page raised—Can an AI make management or HR decisions? And to what extent can they replace human oversight?
What is People Analytics?
To understand better the role of AI in human resource management, we need to understand people analytics. People analytics is an emerging trend in human resources management. It focuses on developing an in-depth understanding of the processes, functions, challenges, and opportunities in an organizational structure. Though people analytics has been around since the beginning of the 19th century, people analytics today is largely AI-powered.
Large amounts of data and statistical leads, generated by employees, are analyzed by AI and other HR technology, and the results are used by organizations to drive HR-related decision making. With the rise of AI in business, people analytics has become a crucial part of business strategy.
According to Deloitte’s 2019 Global Human Capital Trends, 74% of organizations believe that HR technology is crucial for effective functioning. Companies such as Nestle, for example, have found that people analytics can play an important role in furthering their organizational objectives in new ways.
Nestle uses AI-driven People Analytics to address the gender diversity
When Jordan Pettman joined Nestle as the Global Head of People Analytics, he decided to change the way HR data was used by the organization. He wanted to use the HR data for engaging with the business, quantify the problems, and introduce data-driven insights into the decision-making process. Most interestingly, he decided to use this data to increase gender diversity at Nestle.
Using descriptive and predictive analysis tools, Nestle began to investigate gender diversity at the workplace and found, for example, that women only hold 43% of managerial positions at the organization. They also found that only 20% of senior management was female. Using these findings Nestle was able to create the Gender Balance Acceleration Plan, which aims to increase the number of women in leadership positions to 200 by 2022 and increase their presence in senior management to 30%.
The Role of Human Resources in a Data-Driven World
Using AI and data-driven analytics, Nestle was able to identify and resolve a crucial gap in gender ratios, something the Nestle HR department had so far failed to recognize or remedy. Rigorous people analytics provides insights into an organization's problems that an annual employee survey can never find. It would help you look beyond the obvious, and help you see the actual differentiators, the red flags, and identify remedies.
Many organizations today use data analytics and AI to help them measure performance, make promotion and salary decisions, address attrition and retention rates, measuring employee engagement, and many other functions which fall under the purview of the HR department. Does this mean the role of HR management has diminished due to the rise of data-driven analytics? Absolutely not. But it might be changing.
Google’s Project Oxygen
Building on the insights gathered from the failed 2002 experiment, Google launched a massive research project in 2009, dubbed Project Oxygen. The purpose of this research project was to survey their employees and get their input on what constitutes a great manager. Google began data-mining performance reviews, feedback surveys, and nominees for managerial awards. They also began to correlate relevant words of phrases, words, praise, and complaints.
Though Project Oxygen is ongoing, Google’s people analytics team were able to put together a list of qualities that Google employees felt were necessary for a manager:
Have a vision and strategy for the team
Help employees with career development
Is a good listener and can communicate effectively
Has the key technical skills required to run the department
At first glance, these findings may seem very obvious. Even Lazlo Bock, the head of HR, admitted that his first reaction was “that’s it?” But when you take another look two very interesting qualities emerge from the findings.
First, very little mention is made of the manager’s engineering skills. It appears that Google’s engineers have little value for a manager’s technical know-how and prefer someone with experience in overseeing projects to completion and handling people with empathy. To put it another way, They would rather be managed by somebody with HR skills than somebody with an engineering degree.
Second, none of the tasks that Google employees want their managers to perform can be done by AI. No matter how smart, no AI today can develop a vision for an organization, or help employees with career development, and most importantly, be a good listener. These are human qualities, and if this study proved anything, it is that the human element is still very much at the heart of HR management.
But AI has had an impact on Google’s HR department. After using people analytics to change its organizational structure and management style, Google is now using people analytics to increase productivity, engagement, and retention. When Google slowed down hiring in 2009, it focused its efforts on gaining insights into employee attrition and management approaches. They use employee performance data to identify the low-performing employees, offer intervention, and help them succeed. In this way, Google’s HR team was able to leverage their AI capabilities to better perform their core functions.
The Project oxygen research shows that though the introduction of AI and data-driven people analytics has been a huge boon to HR departments everywhere, they are not in any position to take over.
AI systems can elevate your abilities, process large amounts of data, provide you with analytical information. Machine systems that can reason, learn, and interact with people, will likely take over the performance of repetitive tasks and help the workforce be more productive. It can also free up managers to focus on more interesting tasks.
However, as much as such systems can help, eventually employees value both human connection and compassionate oversight, something AI cannot provide. AI is here to assist the HR department, not run it.
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