Ian Cook, director of product management for Visier, believes that while analytics might be complicated, the platform presenting them doesn't have to be.

Published: May 31st, 2016

Any business with an HR department possesses an enormous amount of workforce data, and as the sector has matured, so too has the software designed to analyze that data – but it often produces results that seem daunting for anyone who doesn’t have close ties with the IT department, an executive behind one such solution admits.

The problem, says Ian Cook, director of product management for analytics firm Visier Inc., is that however substantial it may be, HR data such as survey, salary, attendance, and performance information is often divided between four or five different systems, making the cross-platform access needed to answer questions such as whether highly engaged employees usually have better performance scores, or whether the highest-paid people are the most engaged, more difficult than it should be.

That’s where Visier’s platform comes in – the program is designed to be as intuitive and user-friendly as possible, he says.

“We see the business of analytics being not about huge technological deployment, but getting the data to the decision maker,” Cook says. “So Visier is a platform built specifically so that HR doesn’t need to have a huge amount of IT resources to get answers from the data.”

Unlike similar platforms, which Cook says deluge the user in folders, Visier invites users to type their questions into a search bar, which underneath the hood produces analytics that can identify whatever factors are most relevant to the answer, across every platform available.

“If you’re looking at changing your compensation budget and want to know if you’re putting the money in the right place… you need insight that says, ‘Pay doesn’t really make a difference. Learning does. Opportunities for promotion,'” Cook says. “That way you have the opportunity to shape your organization so that people really thrive and your business is productive.”

Demonstrating Visier for ITBusiness.ca, Cook types “headcount” into the search bar, producing a question tree of inquiries an HR manager might have such as “How is headcount distributed across the organization?”, “What is the trend for headcount?”, and “How is the distribution of headcount changing?”

Typing in a more detailed question such as “what is the headcount and how is it changing?” brings up a “movement” tree in which users can analyze employee entrances and exits over a certain period and discover that, for example, 45 employees left during a three-month period.

“In a fraction of a second you’re getting insight to help make your decision instead of, ‘well, I’d better go ask somebody,’ and then two days later they come back with a spreadsheet,” Cook says.

He notes that as with all such research, any correlation uncovered by analytics does not equal causation – that no software, however advanced, can account for the inherent unpredictability of people, or the intrinsic value of human interaction.

“You will never replace human judgment when it comes to people, and that’s a good thing,” Cook says, citing one tech giant that developed an algorithm which could recommend employees for promotion – which its managers flatly refused to apply.

“Analytics doesn’t automatically get you an answer,” he says. “It’s good at the predictive – what’s likely to happen to this population, which person is at risk of leaving, or whether a person has a high likelihood of succeeding in the next role.”

It can also help employees and their managers make more informed decisions, he adds.

“Too often we’ll promote people who are like us, or who we see in the office at 8 PM at night, which doesn’t necessarily get us the best people,” Cook says. “So analytics adds data to our decisions, leading to a better outcome.”

Presently, HR managers at more than 60 companies are using Visier on a daily basis, Cook says, resulting in benefits such as the 50 per cent increase in employee retention experienced by one client.

“Instead of ‘let’s try and keep everybody,’ they were able to identify exactly who is leaving, drill into what specifically was causing it… and work out what they needed to change that dynamic,” he says.

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