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How to make sense of talent analytics

How to make sense of talent analytics

By scrutinising employee data, in a similar way to assessing sales and marketing data, management can significantly improve business performance while reducing recruitment and hiring costs. It’s a challenge for organisations to leverage this data.

Savvy management is starting to understand their cost per hire (CPH) as a metric to manage costs in the recruitment process. Not counting the sometimes huge amounts of money spent on advertising to get people to apply for a position, the actual costs associated with screening and processing applicants can be an alarming number.

According to Deloittes, HR is becoming a data-driven function. Organisations are looking for the ability to make better talent decisions such as predicting employee performance as well as enhanced workforce planning and forecasting.

Key to their ongoing strategy is analysing employee data. Deloittes’ Josh Bershin highlights that organisations are loaded with employee, HR, and performance data. For the last 30 years HR has captured demographic information, performance information, educational history, job location, and many other factors about our employees.

The ability to utilise this data to enhance selection, management and alignment of people to business processes and objectives promises significant returns. It can help prevent unhappy hiring decisions based on ‘gut’ feeling.

Managers are constantly perplexed by the question of why some employees are more successful than others and some organisations use software to find solutions. The software is used to pull data from human resources systems to analyse the issue in the context of high-level corporate goals. It identifies what makes some individuals or teams successful and others less effective.

BPO providers are already helping organisations address their big data issues, particularly in relation to CRM and social media data. The same skill sets and methodologies can be applied to HR data but in a different context.

According to Bershin organisations can leverage their data in the following areas:

Employee retention – what creates high levels of engagement and retention?

Sales performance – what factors drive high-performing sales professionals?

Accident claims – what factors and which people are likely to create accidents and submit claims?

Leadership pipeline – who are the most successful leaders and why are some being developed and others are not?

Loss analysis – why are some locations more prone to theft and loss and what causes the variation?

Customer retention – what talent factors drive high levels of customer satisfaction and retention?

Expected leadership and talent gaps – where are our current talent gaps in the organisation and what gaps can we predict in coming years?

Candidate pipeline – what is the quality of our candidate pipeline and how do we better attract and select people who we know will succeed in our organisation?

In a recent article Greta Roberts, CEO, Talent Analytics points out: “HR has long applied analytics to metrics like attrition rates. But these efforts have been backward looking: What have been the past patterns of employee attrition?”

Predictive talent analytics is much more useful, because it looks to the future: What will our attrition rate be this year? Who are the people who will leave the company?  What can we do to reduce that turnover?

The same techniques are being used to identify the most relevant measurement of customer satisfaction.

The ‘ultimate question’ in customer service, according to Bain and Company fellow Fred Reichheld, is whether a customer would recommend a product or service to a friend or colleague.

He researched companies across a range of industries, and published his findings in Harvard Business Review in 2003, and later in his book The Ultimate Question, to demonstrate how an accurate measure of customer satisfaction would lead to better products and services, and boost the bottom line.

This led to the formulation of the net promoter score (NPS). Needless to say the correlation between high performers who are client facing and a high NPS score is obvious.

By analysing the skills and attributes of high performers in the present, talent analytics enables organisations to build a template for future hires. And if you combine this insight with the latest online recruitment tools and RPA (Recruitment Process Automation), then you can develop a very strong competitive advantage in hiring, developing and managing the skills necessary for the success of your business.



National Manager at CML Group
John Cooksey is a registered psychologist and is currently National Manager, CML Group: a national provider of Payroll, Finance and Employment Solutions. He has over 20 years’ experience in provision of leadership to sales, operations, human resources and marketing teams in Australia, South East Asia, the Middle East and South Africa.

John is a Board Member of The Food Distribution Network, a not for profit that helps people to make healthy food choices by providing them with a regular supply of fresh produce. Previously a lecturer in Strategic Management, Human Resource Planning and Sports & Performance Psychology, John is also a Level 2 NCAS Martial Arts instructor.
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