HR technology will always rely on the ‘human’ element to make sense of big data and analytics, yet HR remains wary of automation.
Change your question from ‘how many people did we hire last year?’ to ‘how many employees left the company last year?’
HR must present its conclusions in a meaningful way to overcome resistance.
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HR has long been under pressure to demonstrate vision, creativity and the ability to step up into a strategic role. Big data and HR analytics can facilitate that transition with the following steps:
Understand the data available:
Without data you have no analytics. Understand what data is available to you and focus on the technology that will produce more. Data offers organizations the ability to predict future hiring needs and helps to improve the quality of new hires.
Making the right decision doesn’t mean making a popular decision.
Define the issues your business needs to resolve:
Outline a realistic strategy with key initiatives to provide data-driven answers to the most vital questions asked by business leaders. Surveys suggest that staff absence, retention, and attrition are ranking higher in priority than performance. What are the issues that prevent your organization from achieving its objectives?
Transition to HR technology:
Quality of hire was considered to be the most important metric for global employers according to LinkedIn. Despite these findings, over half of HR functions still rely on manual recruitment processes. Make the transition to HR technology with scalable recruitment software to begin collecting essential data such as time to hire, cost of hire and the most effective source of your qualified candidates.
Move beyond the basics:
Big data requires HR to identify patterns and trends, provide new insights into human behavior and be predictive. This means moving away from basic metrics to predictive analytics, for example:
Change your question from ‘how many people did we hire last year?’ to ‘how many employees left the company last year?’
Identify the skills lost from the business (I.e. were the people who left low-skilled, poor performers or high achievers?)
Identify your ‘at risk’ skilled employees
Prioritize those areas that will boost retention levels in your company such as poor leadership, lack of career development opportunities and poor flexible working support
Allow automated processes to cope with the repetitive, mundane tasks and focus on workforce strategies that align with business objectives.
Take responsibility:
An apparent anomaly exists between the clear value of big data and analytics to HR and its ability to impact the wider business. HR must present its conclusions in a meaningful way to overcome resistance. Making the right decision doesn’t mean making a popular decision. Bring in the skills needed to analyze data effectively but retain overall responsibility within HR’s remit. Be confident, consistent and patient to build trust.
Embrace automation:
HR technology will always rely on the human element to make sense of big data and analytics, yet HR remains wary of automation. Psychiatrists suggest that fear may arise from the creation of businesses that have eliminated the skills that differentiate humans from computers. Allow automated processes to cope with the repetitive, mundane tasks and focus on workforce strategies that align with business objectives.
Shape business strategy:
Big data is making its long-awaited breakthrough into HR. With it comes a growing interest in what analytics means, from the correlation between pay levels and performance to the type of skills available within a business. In order to positively influence strategy HR must rapidly recognize the direction, the company is heading in, utilizing big data and analytics to deliver the capabilities needed to achieve its goals.
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