Littal Shemer Haim

People Analytics, HR Data Strategy, Organizational Research – Consultant, Mentor, Speaker, Influencer

Key takeaways from Unleash, Paris 2019 – Part 3: The People Analytics Journey

A four-blog series that covers key takeaways from Unleash, Paris 2019. The 1st blog is focused on the future of work and learning. The 2nd covers new technologies for career paths. The 3rd is about the People Analytics journey. The 4th explores insights into the digital transformation of HR.
Photography by Littal Shemer Haim ©
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This blog is a part of four blog series that covers my key takeaways from sessions and demos at Unleash, Paris 2019. The 1st blog was focused on the future of work and learning. The 2nd covered new technologies for career paths. The future blog will explore insights about the digital transformation of HR. But for now, in this blog, let us discuss the state of affairs in People Analytics. We’ll start with an overview based on industry research, and then explore the exceptional case studies. As all People Analytics consultant knows, case study curations in conferences are usually success stories, that do not represent the struggle of most organizations. But that’s good, as the presenting companies offered a lot to learn from.

A gap between investments and perceived impact

As I wrote during the last year, People Analytics as a discipline moves from research projects to analytics products. In order to anticipate trends and stay ahead, organizations must learn to manage their workforce with new tools. Gut feelings are out, informed decisions based on internal and external data are in. David Mallon, Chief Analyst at Bersin by Deloitte, offered a review of the overlapping market for People Analytics solutions. He highlighted findings from Bersin’s latest People Analytics market research, including what prospective buyers should understand about the market today and an analysis of common and differentiated capabilities.

The most prominent findings in this research, in my opinion, were the gap between investments in People Analytics and the perceived impact gained by those practices. As Mallon puts it, while 72% of organizations invested in improving People Analytics, less than 30% of organizations have reported an impact of People Analytics on employee engagement, cost of efficiency, or productivity.

 Common use cases are not targeted at individuals – yet

Among other insights about this market that Mallon offered, two caught my attention: Most People Analytics technology automates descriptive activities, and solutions are still designed around HR and business leaders and leaves behind the employees. Common People Analytics use cases deal with retention, engagement, inclusion, learning, high potentials, productivity, collaboration, and future of work planning. Only the last three are targeted at individuals.

If you are equipped with a comprehensive market review, you may find broader perspectives in any discussion among People Analytics experts. Such was the panel of our four colleagues: Melissa Kantor, VP of People Analytics and Insights at LEGO Group; Robert Carruthers, Senior Director Talent Acquisition Operations at Celgene; David Shontz, Global Head of Workforce Analytics & Organization Management at Nokia, and Lexy Martin, Principal Research at Visier, who moderated the session.

The discussion was focused on gaining a return on investment in People Analytics. The panel mix did not contradict the findings aforementioned, as it included different stages of People Analytics maturity. People Analytics solutions cost, and so, organizations need to create their ROI on efficiency gains. However, the best outcome of People Analytics implementation is bringing the value of data directly to the bottom line of the business.

Relevance for senior management decisions

According to Martin, research reveals that European organizations with People Analytics function outperform all others on return on equity by over 50% and on profit margins by 48%. The panelists, whether Visier clients or not, shared their journey to value from achieving cost efficiencies with cloud solutions to improving HR effectiveness on metrics important to HR, to achieving business outcomes on metrics that matter to the C-suite. They also discussed the process of hypothesis, discovery, curation, journalism, and collaboration that they have used to ultimately get to successful interventions that drive bottom-line value.

The People Analytics journey, as the panelists agreed, has its peak at the c-suite level. Indeed, using people’s data as an enabler for strategic business decisions is the most important aspect of People Analytics in practice. Heine Zahll Larsen, SVP HR at Danske Bank, shared how People Analytics changed HR. He presented some of the considerations on how to make People Analytics relevant for senior management decisions and showcased some examples of how new technology provided valuable business intelligence on how the Bank relates to source pools compared to peers. What most impressed me was the usage of external data, like keywords analytics, to explore gaps between external and internal perceptions about the bank as an employer.

The data science of HR

People Analytics at its best is actually the data science of HR. Claudia de Andrés-Gayón, Group Head HR Services at Deutsche Bahn AG, presented first-hand insights about unlocking the power of HR data science. HR data science is a key driver of workplace transformation. However, many organizations are still struggling to gain a true understanding of what data science in HR is all about, and its actual relevance in driving business success. The session included key success factors but also stumbling blocks of implementing HR data science into the business and provide practical advice along with some HR data science use cases at Deutsche Bahn.

The HR data science approach focuses on use cases that deliver quick and tangible value. The most impressive example was the use case of location: Which are the optimal locations for employing new train drivers, considering both commuting distance and job market supply. Andrés-Gayón shared the output of a cluster analysis algorithm. I consider her presentation as a great emphasis on the importance of storytelling, visualization, and understanding of practical machine learning – competencies that are required now by all HR leaders.

Showing the ROI of people processes

Isabel Naidoo, Global Head of People Strategy & Analytics at FIS, described how strategic talent function was build in the company, based on data. Naidoo offered an inside look at how informed decisions are made at FIS regarding the combination of people, skills, and solutions that will enable everybody in the company to thrive in the future of work. She explained how key aspects of the function were digitalized. Among her examples, I like most the one about attrition and leadership. The People Analytics function managed to prove, based on data, that People are half as likely to leave their manager if the manager has been through leadership training. It is a great example of how People Analytics enables us to show the ROI of people processes.

Another innovative use case of People Analytics was presented by Caitlin Bigsby, Director of Product Marketing at Visier. Bigsby discussed the optimization of the hourly workforce, which may influence their health and happiness. Even little changes make a big difference when the bottom line depends on hourly workers’ productivity. Bigsby showed how payroll, timekeeping, and performance data are crucial to ensure that the little changes are the right changes. However, for me, the most interesting use case in her presentation was in regards to safety. Bigsby described how analytics enables us to examine incidents by employee characteristics, identify who is at most risk, correlate training with safety, and make sure to have the right impact.

More great examples for business impact via People Analytics were presented in a session by Kiran Pasham, President, Chief Architect, and Co-Founder of SplashBI. Pasham discussed the ways successful HR Departments leverage massive amounts of people’s data to fulfill business goals and present the data to management in an effective way. His interactive session included examples of how predictive analytics forecast the ROI of HR initiatives and prescribe a cost-effective course of action. Some of Pasham’s tips for a successful People Analytics implementation, to which I totally agree, were to align with the goals of business leaders, deliver actionable analytics to the right people, measure outcomes of interventions, and provide them with terms familiar to business leaders.

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Littal Shemer Haim

Littal Shemer Haim brings Data Science into HR activities, to guide organizations to base decision-making about people on data. Her vast experience in applied research, keen usage of statistical modeling, constant exposure to new technologies, and genuine interest in people’s lives, all led her to focus nowadays on HR Data Strategy, People Analytics, and Organizational Research.

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