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Driving value in talent processes using analytics

Imagine abandoning traditional resumes and campus interviews in favor of online games, videos, and algorithms to identify and land fresh recruits.
Driving value in talent processes using analytics
Carla Arellano

Brings a background in finance and organization in helping companies strengthen and transform their culture and talent management and create value using people analytics

Neel Gandhi

Advises leading organizations on how to strengthen their talent-management capabilities and build an HR function that operates as a true strategic partner and value driver for the business

Imagine abandoning traditional resumes and campus interviews in favor of online games, videos, and algorithms to identify and land fresh recruits to your company. Welcome to the budding new world of talent acquisition—a radical change that embeds advanced people analytics into HR processes.

Consumer-products giant Unilever, for one, already has made hundreds of global entry-level job and internship hires using such advanced analytics and artificial intelligence tools. Candidates now need only click on a Unilever ad on Facebook or a targeted career-advice site and use their LinkedIn profile to fill out an application.

If an algorithm that sifts applications sends theirs along, they play a set of online games that assess their skills. If they clear that hurdle, they submit video interviews through a website or app. The lucky finalists then get in front of a hiring manager.

Unilever and other employers are finding that the real value in advanced people analytics is the ability to make the process a sustainable, repeatable process. And in our view, it’s at the heart of four core shifts required to achieve HR 3.0—the vision for maximizing HR functions to deliver greater value.

Embedding analytics applies insights from advanced data analysis to HR decisions. In many cases, this process automates the decision itself based on the analytical insight. Unilever is a prime example of this implantation to select which resumes pass through initial screens.

In fact, McKinsey’s People Analytics team has demonstrated repeatedly to clients that an algorithm can more effectively screen resumes than a human being. How? By producing better talent decisions, as measured by the success of recruits in their new roles and by removing unconscious bias from the hiring process.

Employers should replicate this principle across as many HR processes as possible. Take succession planning, which can and should be disrupted by data analytics. Choosing three-to-five potential successors for important leadership roles proves to be a key part of best practices for organizational development and talent management. But many organizations do it inconsistently. While managers and HR business partners sometimes confer about potential successors and, on occasion, refer back to those discussions when a role emerges, such early planning is often later ignored.

Analyzing the past experiences of successful employees, their key capabilities, or the learning opportunities associated with success in a given role can yield several potential successors automatically. Plus, the data can be updated frequently with little effort. Also, successor candidates can be connected systematically to the learning opportunities that will better qualify them for a role—again, without human judgment.

Automation has been a buzzword for years. And HR departments have deployed automation technologies effectively in processes that don’t require judgment or real human insight. Embedding analytics is the next step in that journey.

Today, automating insight-generating processes to produce better talent decisions rates as a core step HR can take to build a concrete connection between talent and business value.

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