HCM “People Analytics” Undergo A Shift
Driven by the widespread adoption of cloud HR systems, companies are investing heavily in programs to use data for all aspects in workforce planning, talent management, and operational improvement. People has now gone mainstream.
Organizations are redesigning technical analytics groups to build digitally powered enterprise analytics solutions. These new solutions — whether developed internally or embedded in new digital solutions — are enabling organizations to conduct real-time analytics in the “need to do this” in a business process.
– While 71 percent of companies see people analytics as a high priority in their organizations (31 percent rate it very important). The percentage of companies correlating HR data to business outcomes, performing predictive analytics, and deploying enterprise scorecards barely changed from last year.
– Analytics is being applied to a wide range of business challenges: Recruiting remains the No. 1 area of focus, followed by performance measurement, compensation, workforce planning, and retention. We see an explosive growth in the use of organizational network analysis (ONA) and the use of “interaction analytics” (studying employee behavior) to better understand opportunities for business improvement.
– Readiness remains a serious issue: After years of discussing this issue, only eight percent report they have usable data; only nine percent believe they have a good understanding of which talent dimensions drive performance in their organizations; and only 15 percent have broadly deployed HR and talent scorecards for line managers.
NEW TOOLS HELP PERFORMANCE
Stakeholders—board members and CEOs—are driving this change. Senior leaders are impatient with HR teams that can’t deliver actionable information and insights; this means that analytics is shifting from a focus on HR to a focus on the business itself. For example:
– Leading ERP vendors are implementing a set of people analytics dashboards available to the CEO, to help senior leaders understand attrition, hiring metrics, employee cost, and employee engagement by geography, business unit, and manager.
– The chief operating officer at a large chain of hospitals uses analytics to understand patterns of patient outcomes and how management and people issues contribute to results.
– The sales organization at a major consumer products company has partnered with HR to develop a complete model for sales productivity, which helps predict and diagnose problems, pinpoint training solutions, and improve quality of hiring.
For companies that have been investing in this area for years say it is now easier to get these answers than ever before. Predictive analytics tools from many HR technology vendors help in analyzing data regarding recruitment, performance, employee mobility, and other factors. And, executives now have access to a many metrics to help them understand, at a far deeper level, what drives results.
Moving beyond the analysis of employee engagement and retention, analytics and AI have come together, giving companies a much more detailed view of management and operational issues to improve operational performance. For example:
– Data-driven tools help predict patterns of fraud, show real-time correlations between coaching and engagement, and analyze employee patterns for time management driven by email and calendar data.
– AI software now analyzes video interviews and helps assess candidate honesty and personality.
– Tools also analyze hourly labor and immediately identify patterns of overtime and other forms of payroll leakage, enabling improvements of millions of dollars through improved practices in workforce management.
– Off-the-shelf retention models are available from SAP, Oracle, Workday, ADP, Ultimate Software, and others,
making it easier than ever to understand attrition drivers.
The 2017 trend shows these new solutions are business driven, not internally HR focused. They challenge HR departments to move beyond their own internal view of data and leverage people data to view/analyze a broad range of business problems.
DATA DRIVES BUSINESS RESULTS
A traditional HR organization installs an analytics team as a separate group of specialists. But today’s companies are rethinking HR as an “intelligent platform” and embedding analytics into their entire workforce management process and operation. Analytics is now a critical part of high-performance hiring. Companies use interview data, carefully analyzing job posting language, and candidate screening data to reduce unconscious bias in recruiting. New tools examine social and local hiring data help companies identify those “likely to look for new jobs” sooner than approached by competitors.
SHIFTING HRM ROLES
The ability to analyze huge amounts of data should be more of a business-wide function, not limited to HR. There is a growing consensus that the best analytics programs are owned by a dedicated, multidisciplinary group. Some organizations place this in HR, while others build a center of expertise outside HR.
More analytics are shifting from “pull” to “push,” where the analytics team no longer simply builds models and does projects but develops dashboards and tools to help managers and employees see relevant data in real time.
Cloud HR technology helps also. Companies must now worry about data quality at all levels, design privacy and anonymity policies, and carefully implement practices to protect employee data from theft and abuse. And larger, companies have governance teams who ensure all people-related data is coordinated as the company reorganizes, acquires others, and implements new systems.
In the same way spreadsheets were once a tool used only in finance, they are now used throughout business. People Analytics is making a similar leap. Businesses and organizations adopting analytics are bringing it into the core of their operations, using it to inform business strategy. Success in analytics will require a prolonged time commitment and continued investment.
Steps to Create a Successful People Analytics Program:
Invest at a senior level in people analytics: Provide global support, not just technical analysis, and require senior executive support, technical resources from IT, and a strong business-focused leader.
Establish clear leadership: A single team and leader should own the initial stages of an analytics effort, even if that capability eventually becomes decentralized.
Prioritize clean/reliable data across HR and the organization: Working with consistent, timely, and accurate data is foundational to all analytics practices. Ensure that data quality is a part of every analytics discussion. Educate HR’s stakeholders and implement data governance programs to clean and maintain data accuracy and consistency across HR and operational data stores.
Understand that analytics is multi-disciplinary: Amass a multi-disciplinary group from across the organization, not just PhDs and statisticians. Technical analysis is only a small part of the function. Data function, data quality, business knowledge, data visualization, and consulting skills are all critical to success.
Increase analytics fluency throughout the organization: Training for both HR and other business functions is critical to operating at scale. Identify a curriculum or other partner to help with education, implementation of standard tools, and standardization of reports and dashboards.
Develop a long-range roadmap for investment in analytics programs: This investment targets building a new business function for the company, not just a technical team within HR.
Focus on actions, not just findings: The analytics team must translate information into solutions, and stakeholders must take action.
Integrate HR, organizational, and external data: Advanced people analytics programs rely on the sharing of data from HR, operations, and external sources. Organizations must encourage the integration and use of structured and unstructured data from internal and external sources.
PROFILES OF COMPANIES TODAY
Today most companies are in the process of implementing AI and robotics, and 34% are piloting selected areas. Only 10% say they are either fully automated or highly advanced in this area. only 20% say they would reduce the number of jobs. Seventy-seven percent of companies will either retrain people to use technology or redesign jobs to take advantage of human skills. While some elements of the future of work are well understood by business leaders, others are still emerging stage of understanding…but interest in this topic is growing exponentially.
THE FUTURE WORKFORCE PARADIGM
The shift from full-time employees to an augmented workforce (technology and crowds) is one of the more challenging of the human capital trends coming. It confuses the familiar concepts of what a job — implications for careers, what work really means, how the workforce is trained and selected and how the workplace is designed. It stretches conventional concepts of the types of work done by people and by machines, and redefines the human workforce segments.
While the adoption of robotics is happening quickly, companies’ abilities to re-skill and reorganize around automation are lagging. Roughly half of the leaders surveyed rate their company weak at aligning competency frameworks to account for new robotics, cognitive, and AI requirements; deploying employees replaced by these technologies; and re-skilling employees to complement these new tools.
NEW ROLE OF HUMAN SKILLS
Digital age programs will expand our vision of the workforce and we will begin thinking about jobs in the context of tasks that can be automated (or outsourced). Consider the new role of human skills. Refocus on the customer experience, employee experience, and employment value proposition for people.
Organizations that automate plants but do not provide people opportunities for re-skilling and new positions, may see their brand suffer and feel pressure from the social and political environment. Ask these questions:
– What parts of a job can be automated, and what is the human “value add” around these skills?
– How can we re-skill and retrain people to learn technology and tools faster, and how can we design the technology so it takes almost no training to use?
– Where does the work—and each individual task—need to be done? What physical proximity is required to serve customers and to design and develop products and services?
– How can we crowdsource activities—and use contingent, freelance, and other talent— to save time and money, increase quality, and improve operational flexibility and scalability?
– How can we redesign the workplace to be more digital in nature, open, and collaborative, yet provide opportunities for development, growth, and focus time?
– How can we evolve, and perhaps separate, the functions of multiyear (3–5 years) strategic work, workforce, and workplace planning to include more crowd sourcing, greater automation, or the increased use of robotics?
– What is our organizational and work design capability and have we explored the way machines can cross functional boundaries to move people from “jobs” to “work” and from “execution work” to “empathy work?”
The function of people analytics — using digital tools and data to measure, report, and understand employee performance — is shifting. After years of investing in cloud HR platforms and specialist teams, business leaders are not getting the results they want. Gone are the days of finding interesting information and flagging it for managers.
People analytics has become a business function focused on using data to understand every part of a business operation, embedding analytics into real-time apps and the way we work. In the context of mobile maps, it is time to recalculate the course.
Source: 2017 Deloitte Global Human Capital Trends