- What is people analytics?
- AI and machine learning in people analytics
- Adopting a data-driven mindset
- Increasing sustainability and diversity with people analytics
- AI talent analytics
- Using behavioural science to increase performance
In the words of influential American author and management consultant W. Edwards Deming, “without data, you’re just another person with an opinion.” Data is used for many business purposes, and its importance is growing and becoming more recognised across multiple industries and sectors. ‘People analytics’ is a discipline developed more recently than other forms of data analytics, yet for achieving business objectives, it is every bit as useful as more traditional forms. Organisations such as Microsoft and Google are using people analytics, particularly in HR departments, to increase retention, diversity, and other positive outcomes. However, knowing where to start with people analytics can be tricky.
What is people analytics?
People analytics, sometimes known as workforce analytics or HR analytics, is the collection and analysis of data about the people who make up a workforce. It applies scientific methods to behavioural data, such as which is commonly found in HR departments or sources like surveys. Technological advances like artificial intelligence (AI) have increased the ability to carry out accurate and insightful analytics on large datasets, and improve the efficiency of HR departments. This can improve recruitment, training, performance reviews, and other aspects of the HR experience. People analytics tools use algorithms to measure productivity and other relevant metrics, and can even make decisions related to hiring, promotion, and more. These tools can also be used to identify discrepancies in pay between employees or demographics. AI-based people analytics tools can be used to screen CVs at the sourcing and recruitment stages, and compare this data to the performance of existing employees to make predictions about the performance of a potential new hire. Apart from enabling managers to make predictions about the future of their workforce, people analytics can also improve the relationship between employees and employers by identifying issues that employees may be having.
AI and machine learning in people analytics
The use of AI devices and platforms is increasing rapidly, ranging from consumer devices like Amazon’s Alexa and Microsoft’s Cortana to Google’s Predictive Engine and other, more bespoke solutions used by various businesses. AI uses algorithms to analyse huge amounts of data and produce quick, accurate insights that can be used to identify issues and optimise business processes. However, AI is not yet advanced enough to take over HR processes entirely – organisations are likely to achieve the best results when AI is used as a tool by HR managers rather than replacing them. AI-based people analytics tools should be monitored consistently, and the criteria used to make decisions must be chosen with care. That’s not to say that AIs cannot grow in capability – in fact, machine learning (ML) algorithms become more accurate in their analyses and predictions over time and as they are exposed to more data. Algorithms can identify, with increasing accuracy, trends in behaviours, their causes, and how they affect the performance of a workforce.
Adopting a data-driven mindset
To use people analytics most effectively, leaders need to adopt a ‘data-driven mindset’. This means making predictions using tangible data, rather than simply from intuition. Shifting to a data-driven mindset isn’t necessarily an easy process. Dutch firm ASM International, which produces semiconductor devices, implemented this transformation, and its Director of Digital Analytics, Daniel Kusmanto, noted that “similar to every change management, the journey is long and we need to transform it one step at a time. At the end of the day, transformation is not a ‘big bang’. It happens bit by bit via the small interactions with data and analytics that create the ‘aha’ moments daily.” Many leaders and organisations are stalled in this by concerns around security, lack of skills among staff, risk of using the wrong solutions, and simple fear of change. However, adopting a data-driven mindset provides many benefits, and can enable organisations to make more informed decisions. Upskilling can be a worthwhile investment in this regard. Cyl Lin, Director of HR Singapore at multinational corporation Tech Data, noted how “shifting from intuition to becoming more data-informed has enabled me to unlock the power and potential of my team.” This shift was promoted across the organisation too, with data analytics training given to her team.
Vietnamese dairy producer TH Group has also made the shift to a data-driven mindset, and is building a people analytics engine. HR Director Tran Thi Quyen states that her team is “on the right track to build a good HRIS system, establish good data disciplines, and identify what we want to analyse and for what purposes.” The company now requires all operations and decisions to be driven by structured, accurate data. Instead of using intuition and then finding data to prove an idea, ideas are generated using data as the starting point. Data is gathered before being processed by the engine, which was built to allow integration and optimise data flows.
“We could have easily bought or borrowed from hundreds of existing models, but those might not truly reflect the ‘persona’ of TH leaders. Therefore, we decided to gather data, conduct interviews, and conduct analyses to develop our own.”Tran Thi Quyen, HR Director, TH Group
French energy and automation company Schneider Electric is also using people analytics with the goal of developing a data-driven HR department. The company’s 2,000 HR professionals previously worked mainly using their own intuition, but are now using people analytics to make more informed decisions. Schneider Electric’s Global Director of People Analytics Peter Ryan states: “One of the keys to transformation is driving digital into everything we do, from products to back office support functions, including HR. We want to embrace digital, technology and data to free up the energy of our employees and enable them to innovate and think differently.”
Increasing sustainability and diversity with people analytics
People analytics can be particularly useful for increasing sustainability and diversity in organisations. These are also key goals in Schneider Electric’s people analytics operations. The company carried out a pilot project using ThoughtSpot, an AI-based “data discovery and self-service analytics” platform. ThoughtSpot used workforce data around current employees, former employees, and new hires to build use cases. This data was examined through the lens of diversity, equity, and inclusion to identify any potential issues such as disparity of gender in different roles.
“Diversity is hugely important to us as it’s part of our Sustainability Index, which focuses on six areas: climate, resources, trust, equal opportunities, generations and local communities. These are underpinned by how we track and forecast using data to see if we’re on course to meet our ambitions. To be fully effective, you have to support people’s needs at the global and local level, which means setting up data to be available globally but also letting HR deep dive into it and ask the questions that are most applicable to their local environment.”Peter Ryan, Global Director of People Analytics, Schneider Electric
AI talent analytics
Talent acquisition and development are crucial for maintaining a competitive edge in any industry, and AI-based people analytics platforms can help with these. A new analytics platform from management consulting firm Korn Ferry is providing talent analytics to clients. Korn Ferry Intelligence Cloud is an AI-based talent analytics platform that produces data-driven insights to tackle challenges of talent acquisition and management. CEO Byrne Mulrooney states “When combined with labour market data and our clients’ HR information system (HRIS) data, the platform helps clients better understand and act on today’s talent shortages and design talent strategies for the workforce of tomorrow.” The platform was designed to allow HR teams to align talent acquisition with future business goals, close skills gaps, and increase talent development.
“Intelligence Cloud’s AI-enabled digital apps help organisations gain a clearer, real-time picture of their workforce. With this holistic view, they can model how the environment might change, and map the actions needed to reach their business goals. Intelligence Cloud advances traditional HR data with a greater depth of insight and guidance, which helps uncover and develop the talent and skills organisations need.”Byrne Mulrooney, CEO, Korn Ferry
Using behavioural science to increase performance
Behavioural science is a key component of people analytics. A new platform called Humu, developed by former Google SVP of People Operations Laszlo Bock, was designed to help organisations increase employee engagement, performance, and productivity. Humu is based on an AI that gives periodic ‘nudges’ to employees to carry out tasks that lead to the desired outcomes. These nudges are generated by the platform’s algorithm and are personalised to each employee. Each nudge is the result of careful research and analytics, and is tailored to be easy to understand and actionable. The US-based Silicon Valley Bank uses Humu to remind employees and managers to align their activities with the company’s broader goals, as well as carry out tasks that increase their own personal development. Silicon Valley Bank’s CHRO Chris Edmonds-Waters says that employees “don’t have to wait for management to roll out a time-intensive program. Humu provides our employees with relevant, customised feedback that’s not generic or mundane. Nudges democratise the employee engagement process; they make learning much timelier and easier for everyone involved.”
People analytics are bringing HR into a new, more efficient era. Data analytics are enabling organisations to increase employee engagement, development, retention, and productivity. For organisations to remain competitive, HR departments must evolve and adopt these strategies and tools. However, despite the technological tools available, organisations must not neglect leadership skills. People-centred leadership is the essential foundation of people analytics, and managers must keep principles of equity, diversity, sustainability, and empowerment in order for any technological solutions to be used most effectively. It is also essential, as with any use of AI, to avoid algorithmic bias and ensure that AI-based tools are programmed with accurate, objective, and unbiased data.