When Flight Centre experienced a downturn in performance and profitability globally, it looked for new and innovative ways to answer the important question: what drives success? That’s where talent analytics comes in.

One reason that Flight Centre and Hudson landed on a talent analytics project was to undertake a bit of myth busting.

“There were many different perspectives across the business about what was actually critical to performance in one of Flight Centre’s critical roles,” says Dr Crissa Sumner, Hudson’s director for talent management across New South Wales and Australian Capital Territory. “There were particular differences in opinions across different global regions, and of course everyone thinks that their perspective is right.”

To get at the heart of good talent analytics measures, Viren Thakrar, research, development and innovation manager, Hudson Asia Pacific, says Hudson relied on its proprietary performance driver model that looks at three key factors: ‘know how’, ‘can do’ and ‘want to’.

‘Know how’ includes biographical data such as knowledge, technical skills, work history,  tenure at the company and work practices. ‘Can do’ assesses personality attributes and cognitive ability. And ‘want to’ is what drives people and motivates them to do good work.

Drawing insights from data

Flight Centre’s area leaders were chosen for a high performance modelling study. This group sits in a middle-management position, and is seen to be a critical ‘connecting’ role for Flight Centre.

“Employees in this tier have the tough job of balancing strategic objectives that come from upper management with the practicalities of day-to-day business operations,” Thakrar says.

In total, 180 area leaders across the globe were assessed. Their answers to surveys, psychometric assessments and cognitive ability tests were used to create a series of performance benchmarks to differentiate Flight Centre’s top performers from the lowest.

Besides obvious signs of success such as high profit or retention, Dr Sumner says that some interesting patterns emerged. For example, according to the talent analytics, the attributes that make someone successful in a grass-roots consultant level don’t always correlate to factors that make great area leaders. This can be problematic because Flight Centre primarily promotes its area leaders from within.

“This project influenced changes in both recruitment and development practices,” says Dr Sumner. “HR and hiring managers knew exactly what to focus on during the recruitment process, and leadership development programs were tweaked to focus more strongly on the things that we know actually predict high performance.”

“It was interesting from a development perspective as well because the talent analytics can provide practical advice on what current employees can do to improve – it provides a corrective perspective,” says Thakrar.

In terms of outcomes, the evidence is there. Kylie Paatsch, national leader of Flight Centre’s Leadership Academy, says that in the first year of using this new talent analytics program, 30 per cent of area leaders were more productive in terms of sales turnover and profit margins, and retention increased by 20 per cent. 

“One of the benefits of Hudson’s talent analytics was that it gave us better information about high performing area leaders, and how to recruit and develop them,” says Paatsch. “That kind of insight is gold. It gives us a competitive advantage.”

As for being nominated for the AHRI Award for Talent Management, Dr Sumner says it reinforces the importance of projects like this.

“It supports our view that this is the future of talent management,” she says. “It’s about getting clarity about your people. You can get real answers to questions, and it’s exciting to be at the forefront of that.”

Top tips for implementing talent analytics

Ready to get started on a talent analytics project of your own? Here are Dr Sumner’s and Thakrar’s words of wisdom.

1. Do your own myth busting: “Have good questions you’re looking to test to give your analyses focus,” Thakrar says. “And do something that has business importance, especially if it’s your first one.”
2. Question the quality of your data: A healthy dose of scepticism is required to wade through vanity metrics. “If you simply look at overall sales results, for example, that can be misleading because you can have areas that have an easier market than others,” says Dr Sumner.
3. Don’t wait until your data is perfect: That will never happen, say Thakrar. “Know the limitations before you get started, but don’t let that stop you.”