How Does People Analytics, AI & ML Revolutionise HR?
The journey towards a data-driven HR has been a slow but steady one. From traditional methods of recruitment, employee engagement and performance evaluation to using data and analytics to inform decisions, the HR industry has come a long way.
"What I've seen in the last couple of years is that the reliance on people analytics has never been stronger. I think that that really started during the pandemic because obviously everything was about employees, but it hasn't really dissipated",
shares Dawn Klinghoffer, Global Head of People Analytics at Microsoft and a Board Advisor at our sister company, Insight222.
This shift towards a more data-driven approach has not only improved the efficiency and effectiveness of HR processes and workforce experiences but has also provided valuable insights for organisations to make strategic decisions and increase the bottom line.
However, if we look back at 2023 and the surge in Artificial Intelligence (AI) and Machine Learning (ML) technology, it's clear that the potential for HR analytics is only going to continue growing.
Jeremy Shapiro, Global Head of Workforce Analytics at Merck & Co, echoes this sentiment, pointing out that "people analytics is facing a pivot point. And that pivot point really is focused in on AI ML.
Revolutionising HR with AI and Predictive Analytics
AI and ML technologies process and interpret data at an unprecedented pace, unveiling insights that traditional methods may have missed. Let's consider salary recommendations, for example. AI models can now factor in market rates, internal equity, performance and more. This data can then provide recommendations for salary structures that incentivise and retain top talent, ensuring HR leads the way in developing compensation strategy.
AI is revolutionising the recruitment process with candidate matching algorithms and chatbots that handle initial queries, allowing HR to focus on values and culture alignment. And predictive analytics now allow HR to forecast hiring needs and anticipate talent gaps.
In the same conversation as Dawn, Thomas Rasmussen, VP of Organisational Development and Learning at Shell, shares a great case study that illustrates the potential of people analytics and AI.
“if you increase the quality of leadership with 1%, the amount of accidents or near misses goes down with 4%. So, it is the best business case for investing in leadership I've ever seen. And even though most of the HR community said, "Yeah, we already knew that, and we've been saying that for years", then just quantifying it, finding causality with seven years of data from all over the world really helped us spark that conversation where, "Okay, hey, why are we actually doing it?"
Driving Value with People Analytics, AI, and ML
However, as we move forward with the integration of AI and ML, it's important to note that these technologies and practices go beyond just delivering insights. In order to deliver real impact, HR and people analytics professionals and leaders need to extend their influence and forge more substantial partnerships across the business.
It is the influence, as Jeremy highlights, which is "the thing that creates differential".
Supporting this view, Dawn shares how, at Microsoft,
"One of the things that we like to put in the back of every single presentation is the so-what slide. And so we'll go through our data and talk about the insights that we got, but the most important slide is that so-what slide at the end, "So, what are we going to do about this?" And that is where we have the influence, which can drive to impact."
But if we also maximise the impact and value of people analytics with the use of AI and ML, then we also need to focus on the prioritisation of projects. By this, we mean ensuring that our analytical efforts are not merely reactive but contribute meaningfully to long-term strategic objectives.
Jeremy provides some excellent advice on how to achieve this, honing on his team at Shell as a great example.
"Have a Jira board or priority list that's yours. And so, treat this like you are in a production house, if you haven't already; do you have a backlog; do you have a list of work that are candidates for being worked on so that you can have those good common conversations and talk to people about, "Here's where we think our trajectory is going. Do you agree? what other components are there?" The second part of this is for our team, and so we talk internally as an analytics team about a value stack that influences how we think about discretionary time.
So, as an example, if there is an employee population at risk for a safety purpose, everyone drops what they're doing, and we work on that. That is, there is no question and anyone's empowered at 24/7 to stop and just do that, and we will always say, "I've delayed this project because we're working on a hurricane safety situation", and there's no question.
It is, therefore, in the power of prioritisation and strategic partnerships that HR can truly capitalise on the potential of people analytics, AI, and ML to drive value for both employees and the organisation as a whole.
Skills Needed in the Age of AI
As HR and people analytics professionals, we know how the age of AI is transforming the skill requirements of our workforce. But what does this mean for HR and people analytics professionals themselves?
Interestingly, beyond the need for IO psychologists, behavioural scientists and consultants, Dawn predicts that data visualisation will be one of the most in-demand skills for HR professionals in the near future. With vast amounts of data being collected and analysed, the ability to effectively communicate insights through visual representations will be crucial in making data-driven decisions.
In addition to this, she highlights that
"if I think about building the capability for HR in the future, it's how do we ensure that HR knows the right questions to ask, and they ask the questions in such a way that the data that is coming back answers the question and makes sense for the outcomes."
This emphasises the importance of critical thinking and strategic problem-solving skills in an AI-driven workplace. HR professionals must not only be able to understand and interpret data but also know which questions to ask and how to use data to inform decision-making.
But if we think more about the integration of AI and ML in HR, we will see more ML engineers within HR. In fact, this is already at play, as Jeremy admits that at Merck, "we just hired one of our first ML engineers inside of HR".
This highlights the growing need for technical expertise within HR as we continue to integrate AI and ML into our practices. It also speaks to the importance of collaboration and partnerships between HR and other departments, such as data science and engineering, in order to fully leverage the potential of these technologies.
Things are clear: as we move forward into this era of digital transformation, HR and people analytics professionals must continuously evolve their skills and collaborate with others in order to drive value and impact for their organisations. By doing so, they can truly harness the power of AI, ML, and people analytics to create a more efficient, effective, and empowered workforce.
Maximising HR Impact with AI and ML Integration
In conclusion, the integration of AI and ML into HR and people analytics practices presents a major opportunity for organisations to drive value and impact through data-driven decision-making.
However, in order to fully capitalise on this potential, it is crucial for HR professionals to go beyond just delivering insights and focus on building strong influential partnerships, prioritising projects, and continuously developing their skills. By doing so, they can truly harness the power of AI and ML to drive meaningful change for both employees and the organisation as a whole.
If you would like to learn more about the impact of AI and ML on HR and people analytics and gather a more granular view of the conversation between David Green, Jeremy Shapiro, Thomas Rasmussen and Dawn Kilinghoffer, be sure to listen to the Digital HR Leaders podcast episode 'The Impact of People Analytics, AI & ML'.
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