People Analytics: A lynchpin to Future HR Success. How?

Thinking in organizations, a decade ago, was different when it came to HR functions. It was narrow and straight, reducing HR roles to managing payroll, taking snapshots of heads and teams, calculating annual performance rather than building informed decisions leveraging human analytics tools. A recent McKinsey report suggests that Human Analytics has become a profound interest to over 70% of business leaders and without taking any blank stares they agree it is a core driver to the future of HR success. Nevertheless, there is very little argument currently of Human Analytics making its entry as an independent course into the Digital HR programs of top and leading universities in the country.

Building a super people analytics model is a hard step, but we have 3 key ingredients that will help human analytics teams to make an impact and sustain growth.

Data Management

Building a great analytics team means high-quality data standards, engineering and management. Companies to realize this bottomline goal need to hire top-end data engineers who can help in constructing qualitative data. Their role does not end with creating data but owning responsibility for the data created, thinking of new ideas and reducing dependency at the organizational level. For People Analytics to reach its full potential, data engineers become a key resource and differentiator as they enable

• Strategic alignment.
• Lay solid data foundation.
• Build strategic data solutions from start to finish.

Analytics Capabilities

Companies need upending data engineering resources to execute classified people analytics projects. People analytics teams to covet roles in key organizations are in a stiff race to master and acquire data science talent. Organizations not just look for HR analytics talent from a skill perspective but also translation and integration capabilities of the data engineers in order to build a good talent bench. To stay a leader in the people analytics, organizations must step in for hiring-

• Data Science engineers with a broad mindset and inclusive approach.
• Not only generalists but also specialists who are nimble and cross-functional to meet the evolving needs of the industry.
• Data Science Engineering is a distinctive qualification but businesses need People Analytics teams who are capable of converting evidence-based data into actionable insights from analytics and stakeholders leading to business impact.

Operational Capabilities

Business field is evolving and dynamic and to stay above the curve, people analytics teams need to cascade the impact across the team for sustainable impact. How does this happen? Simple, best people analytics teams need to place themselves on par with organizational goals basing their functions on experiments and innovation. So, how do you achieve this?

• Human Resource professionals must go beyond the regular functions of exploring innovative human analytics tools and experiments to build a proof of concept.
• HR teams must optimize human analytics capabilities not necessarily to meet current organizational needs but for purely experimental purposes to support constant innovations and how best data can be converted into creative ideas to help C-suite level with cutting-edge insights.
• People Analytics teams have different approaches but more importantly, HRs should ensure that they all encompass and support the organizational needs and clientele expectations. Doing this will also enhance feedback mechanism and iteration in the company which in turn can help human resource management to focus on top-priority goals and pressing business challenges.

As HRMs deal with bottomline and macro business challenges, organizations must step ahead to creating a culture of trust, ownership and empowerment. These baseline factors can help recruitment teams meet clientele needs, deal with sensitive employee data and extrapolate meaningful and valuable business insights to guide leaders and meet desired business success!

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Created on Mar 15th 2022 02:15. Viewed 134 times.

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