Key takeaways from People Analytics World, London 2018 – Part 1
Key takeaways from People Analytics World, London 2018 – Part 1
People Analytics World is a leading European annual conference on HR Analytics, Workforce Planning and Employee Insight, in which I was privileged to attend in April 2018. I traveled to London with huge expectations, to learn more about the contribution of People Analysts, which are now becoming an essential part of HR groups across all industries. The growing importance of data-driven HR was well reflected in the conference’s attendees, both speakers, exhibitors, and delegates. My experience in the event exceeded my expectations. Thanks to the professional sessions, the delighting hospitality, and the great chairing of David Green, I had a wonderful opportunity to explore how HR leaders reinvent their domain, train themselves and their organizations to be prepared for the age of data, and get new tools that enable them to provide insights to maintain a competitive edge.
The conference program was challenging. It was split between three parallel tracks: Strategy, Impact and Disrupt. I had a hard time choosing between lectures since I found all the speakers and topics relevant and most interesting. Fortunately, the conference organizers offered interactive tools that helped me to plan my agenda. In this blog, I share my key takeaways from the conference first day sessions, case studies, and demos, in which I attended. My next blog covers the conference 2nd day. In future posts, I may cover many sessions I missed, with some references that I read to recover my horrible FOMO (fear of missing out).
Demonstrate how staffing creates an organizational capability that contributes to competitive advantage
Alec Levenson, a Senior Research Scientist at USC Marshall Center for Effective Organizations, suggested how to make People Analytics a part of organizational strategy. He started with some bad news: we are struggling with data quality while buying some shiny tools, but it won’t lead us to success, since no one in the organization looks at the bigger picture, and own the end to end analysis. Sometimes people in different departments work at cross purposes with each other, yet think that they are pursuing the company’s best interests. While we talk about ROI (Return of investment), this is a short-term financial return, in comparison with competitive advantage, which is a long-term financial return. What is return in the domain of people? We need to build capabilities that eventually will show an impact on productivity and profitability. Our metrics should be designed in three different levels: job, team, and business unit. However, we should start with the business level and not job performance, as we got used to. According to Levenson, the business performance causal model goes from the bottom up. A failure to align these three different levels will end with partial success in goals achieving. Productivity is not an individual issue. We should demonstrate how staffing creates an organizational capability that contributes to competitive advantage. Levenson invited us all to learn more, in his new book “Strategic Analytics: Advancing strategy execution and organizational effectiveness”.
Learn some practical lessons from super-intelligent elite sports teams
Bernard Marr introduced his brand-new book “Data-Driven HR”, which offers practical guidance to HR professionals in leveraging the value of data available at their fingertips. Like elite sports, organizations have a huge amount of data, structured and unstructured, on the cloud and on devices, which will eventually change work. In sports, real-time analysis is done by AI tools that replace people who previously coded data, e.g., cameras or sensors that are used to record every move of athletes and teams. Analysis based on NLP enables to produce automated sports reports and replace journalists. Braking data silos on the cloud enables to optimize learning and offers a huge amount of intelligence related to sports players. Data analysis is not native to the sports domain, so new partners are needed, along with new considerations of data security. Marr claimed that most HR teams are data-rich but insight-poor. He outlined a path to more intelligent HR teams and discussed practical lessons that HR teams can draw from super-intelligent elite sports teams: Find future roles in using data. Design data strategy, i.e., contribute to key goals with data. Use the right data instead of big data. Build new capabilities related to data. Create trust and transparency so people will be ready to give access to data for the value they’ll get. Consider data security and ethics. Consider data diversity and use a variety of sources, e.g., devices, social networks, sensors, videos, etc. Move from report about the past to real-time and predictive analytics. Move to process automation while focusing on a strategic role. Find the right partners in new places, e.g., crowdsourcing and professional communities.
Transform real-time engagement analytics to personalized management insights
John Murray of Peakon discussed how to combine communication, processes, and technology to build momentum in the organization, creating an environment where employees are engaged, productive and working towards the same goal. He stressed that Engagement is not just HR’s responsibility. However, there are benefits and challenges in moving to a real-time employee experience analytics model. In his demo, he showed how to build a tailored action plan based on analytics at all levels of management. In particular, managers can own their personal performance by dashboards that provide them with an overview of their team’s engagement data. As an admin, HR can control managers’ access to data and functions, and offer different dashboards for junior managers and senior leaders. The dashboards highlight findings and priority issues, thus help managers to respond effectively. Engagement scores are tracked over time, encouraging managers to continue their ownership over data and performance. Employee anonymity is a concern. Therefore, the platform limits manager access to real-time feedback until a sufficient number of employees have responded. The platform also offers managers the ability to communicate with employees directly, while preserving employee anonymity. The product includes many other features, e.g., benchmarking, employee conversations, Text Analytics, and many more to explore.
Shape HR priorities using analysis and innovative experiments
Brydie Lear, Global Head HR People Analytics in ING, and her colleague Eva Oudeman, Lead Data Scientist People Analytics, covered how the Bank has been building a mature analytical team, moving away from one-off analyses and experiments, towards being asked by senior management to support strategic initiatives. Not only delivering high profile projects but even shaping strategic (HR) agenda using the output from innovation experiments. They described ambitions, the journey so far, the core services, key pillars for success, and how advanced analytics support strategic data-driven decision making. Their portfolio of analytics products includes – Hiring algorithm that reduces manual support and selection bias, by automatically matching CV’s to job profiles and predicting high performance; Continuous listening process for frequent feedback, to understand employees’ perception of strengths and key issues; Diversity projects, for in-depth understanding of current and expected diversity situation, providing data-driven approach and dialogue on goal setting and realization; Reward solutions, for accurate financial and non-financial recognition, and forecasting, maximizing the return and effectiveness of incentives; Top talent performance, to identify top performers and potential talents, allowing for focused approach and maximum return; Voluntary attrition analysis, for predicting talent at risk to leave ING, enabling pro-active actions to reduce the risk and costs of replacing these key resources. Future add-ins of this portfolio will include team performance, for an in-depth understanding of key ING specific drivers for high and low performing teams, and hidden networks understanding, to boost business performance.
Think about analytics in the space of competency development and validation
Subhadra Dutta, Head of People Science and Analytics in Twitter, reviewed how the company has been mapping individual competencies and performance stats, and their relation to organizational performance, using employee data and operational KPIs. Competencies are abilities or attribute, described in terms of behavior and key to effective performance. There is a data-based approach for developing and validating manager and individual competencies, and Dutta illustrated how operational outcomes are used to develop and validate these competencies. Dutta emphasized the importance of understanding what keeps employees, what makes them leave, and how the organization can help them to do their best. People join organizations for eliminated time. Therefore, it is essential not only to ensure to offer them great employee experience, but also to measure what really matters in their performance to other things in the business, and validate that. She demonstrated how traditional methodology in psychology research is relevant to current practices in People Analytics.
Align people processes that benefit from advanced analytics and adopt an agile mindset
Pauli Dahlbom, Founder of PeopleGeeks, presented a super interesting demo of advanced analytics deployment and success in Musti Group, a leading pet supply chain in the Nordic countries, which has 260 stores in Finland, Norway, and Sweden. The HR group of Musti applied Machine Learning-based sales forecast models, to optimize workforce planning and to automate of their scheduling process. Their predictive model proved to work more accurately than the previous sales budgets that the business had built, and it has a huge impact: It optimized contract types and contract hours and enabled significant yearly savings. It reduced participation time of hiring managers and improved quality of new hires. The project also enabled to redesigned workforce scheduling and planning activities, to build predictive optimization model to align staffing hours to match expected traffic and to identify top performing teams and individuals and target them to most important shopping periods.
Challenge yourself with the opportunity of strategic position by a strong evidence base
Peter Cheese, CEO of CIPD talked about the opportunities and challenges for HR when embracing analytics. From productivity to cybersecurity, to innovation and agility, diversity and inclusion, the issues facing business are about people, and yet, HR base of data, evidence, and insight are fragmented and inconsistent. HR lack common frameworks and language, focus on this domain not necessarily in the right ways and perhaps don’t have the right capabilities. To put this in simple words, “HR has too much PowerPoint presentation and not enough Excel files”. HR must understand outcomes and insight needed, recognize the opportunity of collecting information about people, and built a momentum using AI to analyze and interpret it. However, HR has also profound challenges in raising ethics and trust from the people. Their stakeholders are not only the investors, but also the people, the environment, and society as a whole.
Look at data and analytics across the organization from a perspective of collaboration
Michael Cox, Head of HR Business Excellence, Technology & Analytics, and Jordan Pettman, Global Head of HR Data, Analytics & Planning, both from Nestlé, presented the company’s journey to strategic data partnerships across the organization. In this globally distributed, complex and ever-changing business, the HR team had not traditionally leveraged and managed their data to drive results out of analytical approaches to problem-solving. These two professionals positioned People Analytics as a business enabler, not an HR division, and offered examples for global People Analytics functions and practices. An important lesson is to use the same terms within finance and HR departments. i.e., use the same numbers for the same reasons. Although these professionals managed to offer global report catalog, they stress that there is no need for perfect data, and there is no single way to do it. Furthermore, since HR practitioners don’t know yet how to get the right People Analytics talents, it is essential to turn to colleagues from other departments and to connect with analysts who like to share their practices on collaboration platforms.
Break out common routines of Employee Engagement analysis and produce actionable insights that worth the executives’ attention
Laurie Bassi warned the audience that it is easy to plough deeper and deeper into employee engagement data, but lose sight of what it means for the actual performance of the business. Employee Engagement measurement has all too often over-promised and under-delivered. Bassi focused on practical ideas to get more value from the investment in Employee Engagement analytics: Optimizing its “real estate”, doing simple but clever analytics beyond one-size-fits-all, focusing senior management on the key findings and making it easy for managers to act. Bassi offered five essential steps for valuable employee engagement surveys: ask the right questions, link survey data to outcomes data, “mass-customize” findings and recommendations, make it easy to understand, and point managers to solutions. A good starting point would be Sales, because these departments usually have good data, and executives really care about them. Survey questions can also be a proxy to business results. Bassi suggested some axioms for People analysts to repeat daily: The importance of the problem you are working on is approximately inversely related to the mathematical sophistication of the techniques needed to solve it. Outliers are your friends. Less is more. And finally, if you like to appear to be the smartest person in the room – get over it!
Set your sights on using your capability to turn HR into a profit center
Patrick Coolen, Head of Strategic Workforce Planning & Advanced Analytics in ABN AMRO shared his experience on set up, governance, methodologies, and outcomes of People Analytics. He covered future challenges: concepts of ‘instant’ analytics and continuous listening. He also offered ideas about opportunities to use People Analytics to generate revenue and direct ROI. An interesting perspective Coolen presented was the idea to start your People Analytics journey at the top of the developmental pyramid, assuming that if you could do that, you could do it all. Another interesting idea he presented was the team dashboard for research portfolio, which enables to link a variety of variables from different research to few outcomes across the business.
About the author:
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.