Data Trends in Human Resources

Posted in: Technical Track
The dynamics of work have fundamentally changed in the past three years. Data has been a large driver of this change, providing better information to candidates about organizations they are considering joining and enabling employers to better understand what makes for successful team members and how to enable that success. Today’s focus is on how data can provide employers richer details to improve employee productivity, relationships and career opportunities.
The center of this change is our human resources (HR) organizations, benefits teams, talent acquisition and learning & development organizations. They collectively set the standards for how we gather data about employees and performance, use that data to plan initiatives and benchmark themselves against outside organizations. The collective role of these teams has access to data never before available to improve the training available to their organizations, identify high performers and manage workforce churn through targeted interventions to protect the most impactful employees. Some of the advanced areas of applying data to HR include:
  • Candidate Targeting – As organizations work to attract talent in an increasingly competitive job market, the ability to target candidates’ profiles becomes highly differentiating. Organizations that have the ability to pull in social media data, combine it with recruiting priorities and assess candidates’ community impacts have an advantage at filling the funnel with proven team members with matching experience to open roles.
  • Benefits Analysis – Many organizations look to evaluate how effectively employees are using available benefits and the competitiveness of benefits packages against the job market. HR data can tell a strong story about both, helping HR teams understand what changes to make year over year to maximize their competitive abilities to attract talent. This data further enables HR and benefits teams to target their internal training and campaigns to ensure employees are maximizing the benefits available to them through awareness and reminders to take advantage of specific benefits.
  • Learning & Development Curriculum Planning – Many organizations look to create L&D recommendations for employees with the common focus being on courses defined by role. Moving beyond, many organizations are looking to analyze how staff take training, looking at when and the scores from specific tests of knowledge to optimize future curriculum based on organizational needs.
  • Churn Prediction – Employee churn can be a large cost for an organization, hard costs associated with recruiting and training and the soft cost imposed by rework and work slow downs. Organizations are looking for new ways to understand employee engagement, identify those at high risk of churn and enable managers to engage in appropriate ways to understand the employee’s needs, communicate career paths and work to provide opportunities the employee many not have been aware of.
  • Moving beyond 9-box – Traditional approaches, including the 9-box, measure an employee’s impact and potential. But these are a point in time evaluation by a single manager with input from working peers. The ability to move beyond and continually measure the impact of individuals and teams brings new visibility to managers to intervene to address performance issues, promote those with the highest potential and restructure teams to meet changing business needs.
Effectively using data for these use cases is dependent upon strong governance, a set of integrated systems and organizational alignment on proper use of data. When beginning the journey for effective data analysis teams, analytics teams focused on HR functional needs should begin with:
  • Governance across HR Information Systems – HR data brings a unique set of requirements for analysis, appropriate use and internal sharing amongst teams. Your HR data journey should begin with organizational agreement on how to leverage data, how to identify employees for analysis and intervention, and what data must be collected to ensure uniformity in analysis and reporting.
  • Systems Integration – Once you have established what data is collected for employees, and how that data is modeled and appropriately used, you can focus on developing integration roadmaps for the systems supporting different aspects of HR needs. This includes employee management, payroll, benefits administration, learning & development and employee engagement & collaboration tools. Unified integration with free flow of data between these systems is critical to ensuring a positive experience by employees throughout their journey from candidate to employee and important for the HR analytics team to provide uniform reporting across different systems & employee touch-points.
  • Embedded Analytics Capabilities – Each function within an organization should have their own capacity and skills for doing data analysis, ensuring they can prioritize data needs in alignment with organizational objectives. Shared analytics teams can lead to bottlenecks and mis-matched priority. As you embark on your HR data journey, building a focused team that knows the data, is aligned on priorities and has access to all necessary systems increases the value of the output and chance of success for big initiatives.
Your HR data journey begins with a cohesive data strategy defining how and where data will be used, the outcomes the organizations desire and the acceptable use of data for analysis and intervention. This data strategy serves as the roadmap for how to implement the necessary data governance to ensure data is protected, how to begin the process of integrating data from disparate systems and how to structure the right organizational model to drive effective outcomes.
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About the Author

VP Analytics
Joey Jablonski is VP of Analytics at Pythian, he leads strategic engagements assisting customers in developing their data strategy, defining and executing on data governance programs and building analytical models to power the modern data-driven organization. Prior to Pythian, Joey was VP of Product at Manifold, where he brought a product mind-set is part of all engagements—allowing for delivery of value quickly in any project, and building over time to drive adoption of new data-centric capabilities in an organization. Joey led engagements across industries including high tech, pharmaceuticals and for the federal government. Before Manifold, Joey held executive leadership positions at Northwestern Mutual, iHeartMedia and Cloud Technology Partners. He brings 20+ years of experience in software engineering, high performance computing, cyber security, data governance and data engineering.

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