Exit HR Practitioners, Enter Talent Analytics Algorithms
Guest Blog: Ian O’Keefe
“Choose a job you love and you will never have to work a day in your life”. Confucius was the first Chief Human Resources Officer. He had it right from the beginning. His words have captured our imaginations over the years, but still, to this day, fulfilling career choices and genuine engagement among workers remains as elusive as ever.
Corporate mission statements – attempting to link company pursuits to who we are and shareholder interests to how we feel about our work – often fail to inspire. According to a recent Gallup survey, 87% of employees worldwide, nearly 1.2 billion people, are either “not engaged” or “actively disengaged” at work. Workplace disengagement breeds negativity, thwarts innovation, hinders growth, and generates economic losses upwards of $500 billion annually in the U.S. alone.
The stakes are high and important questions remain unanswered. What are the sources of individual fulfillment and the drivers of productivity for each of us in the workplace? How do they change over time? How can work choices and career paths become more meaningful? The discipline of Talent Analytics – accelerated by the proliferation of BI technologies and the explosion of structured and unstructured human capital data – can bring us closer to the answers. Let’s get more specific.
Based on advanced statistical analysis of employee biographics, demographics, psychometrics, sociometrics, work history, performance trends, career goals, documented strengths and learning objectives, Talent Analytics algorithms will soon lead to highly customized and individualized:
- Performance improvement recommendations based on real-time analysis of unstructured crowd-sourced feedback via Natural Language Processing and Cognitive Computing (think Yelp)
- Career development plans that automatically evolve with links to open-source learning content, MOOCs, corporate social media follower suggestions, and internal job alerts (think Netflix)
- Skill-building “time investment” opportunities that are gamified and pushed to your mobile device via alerts for short-term projects sponsored by other departments (think Kickstarter)
- Mentor-mentee assignments created from pairing algorithms, deployed through system-generated calendar invites, and improved with Machine Learning feedback loops (think Match.com)
- Leadership pipelines and critical positions that are slated with evolving successor lists based on attrition probabilities of incumbents and predicted gaps in team performance (think Moneyball)
The list goes on. In the future, we will begin to see Big Data methods driving Little Data solutions with clear and measurable benefits to the organization, workforce, and individuals.
Hyper-personalization (something that Marketing Analytics data scientists have been doing for years), will reshape the talent solutions of tomorrow to be tailored to individuals like never before. Being truly data-driven, the talent solutions of the future will evaluate reams of information generated by enterprise-wide programs and processes and then dynamically create customized talent “product offerings”. Workers will choose to opt in to a symbiotic data exchange with the enterprise, because traditionally static HR activities (e.g., annual performance reviews, paper-based career development plans, off-the-shelf training, informal mentorship approaches, calendar-driven succession planning exercises, etc.) will morph into integrated and fluid talent systems designed to drive personal enablement and innovation. Workers will begin to experience deep personal connections to the ways the organization can seamlessly help them be more successful. Choosing to give more data will mean regularly getting more personalized insights. This will redefine concepts like Reciprocity, Trust, and Generosity and elevate them to the forefront of cultural transformations and organizational values frameworks. Agile technology integration, beta-product experimentation, and change leadership will be crucial success factors to bring this to life.
While complex organizations and evolving people practices create an abundance of workforce data, generating the insights to improve business outcomes and drive innovation is a tall order. Talent Analytics clearly needs to rise to the challenge. But how? By identifying broad organization-wide performance gaps aligned to overarching business objectives? By isolating unique development needs aligned to specific goals? Yes, on both accounts. Talent Analytics insights are most powerful when they can be applied broadly across the enterprise with seamless execution for all, as well as deeply within specific talent segments with targeted excellence for a chosen few.
The most innovative applications of Talent Analytics – based on principles of data-driven dynamic interactions – are only beginning to emerge. When this happens, the possibilities for Human Resources as a value creator and Talent Analytics as an innovation engine will become game-changing. Corporations, universities, member-based consortia, technology platform providers, and third-party consultants all stand to benefit from a growing ecosystem of partnerships and alliances aimed at advancing the Talent Analytics discipline.
So, the question to ask isn’t if your HR function will be disrupted. It will. Rather, ask whether your HR practitioners and Executive Leadership Teams are ready to embrace Talent Analytics to reshape the future of work and reinvigorate the engagement of workers. Possibly your own work and engagement. What would Confucius say?
Throughout fifteen years of management consulting and Fortune 100 leadership roles, I have been fortunate to observe how the intersection of people, process, and technology creates almost unlimited opportunities, as well as challenges, for organizational and individual success. Exploring this intersection has been a driving force throughout my career. Currently, as the Head of Talent Analytics for Sears Holdings Corporation, I lead a team that generates operational reporting, program effectiveness models, and advanced analytic studies impacting over 220,000 employees and billions of dollars in annual labor spend. Our team advises on a variety of business issues and the skillsets we employ are equally diverse. Economics, Statistics, Psychology, Computer Science, and Management Consulting form the core of our expertise. Our end goal is to discover new accelerators of workforce Engagement, Collaboration, and Productivity that will help transform Sears Holdings into the world’s largest integrated retailer.