Using data to iron out hiring problems helps raise efficiencies, says people leader speaking at upcoming National HR Summit Australia
Working with analytics in HR helped Rian Thompson and his team reduce the time involved in recruitment by more than 10 days for one government department, he says.
By using analytics to iron out hiring problems in an area of high recruitment volumes in the education sector, they created tools for managers to measure individual performance and provide better visibility of the process to identify areas that were potentially challenging to fill.
“By unpacking some of the bottlenecks, and working to reassign people in the workflow, the team managed to get a 10-day reduction per requisition, and that was just from providing visibility of the numbers,” says Thompson, who will be presenting at the upcoming National HR Summit Australia in Sydney.
Thompson – who is director of workforce insights and transformation at NSW Health - has been a people leader for over 20 years and is passionate about working with analytics, including in the area of remote working.
“A lot of what I've been doing is about how we get the best out of the systems we have and drive towards optimising outcomes,” he says.
Having been in government for some time, working in education prior to his current role in health, he notes that “remote working was probably not the norm for most government agencies pre-Covid.” The pandemic changed that rapidly, he says.
One aspect of his role during the pandemic was to assess data to address people’s concerns that remote working would reduce productivity. This involved looking at data such as volumes of emails and number of hours people were connected to the network.
“Most of those weren't showing a decline, even when we started to look at some of the qualitative things back from managers around the work that was being produced and the quality. There was really very limited evidence to suggest a decrease, which was a surprise for a few people,” says Thompson, who at the Summit will be on the panel addressing ‘Powerful productivity measures for a remote workforce’.
“My mantra with a lot of the measures and metrics though is that you’ve got to be careful about what it is that you're measuring, and whether that's right for your actual goals. If for an IT support team we measure solely the number of tickets closed, it doesn’t give any indication of how good the IT experience was or whether issues were resolved first time, so it’s important to be careful around structuring the measures in the right way,” he says.
“What you measure matters – it’s what people will work to unless we’re careful to really measure what the business is striving to achieve, we might not end up where we were aiming.”
Where it gets trickier measuring productivity, he says, is where teams are involved in higher order functions like policy development.
“You can measure output for a lot of these teams but whether that's productive or not, and how you compare that between some of these teams, is fraught,” says Thompson.
“If a policy team’s tasked with something particularly complicated, it could take weeks, but if they resolve the matter effectively, it could save other people hours further along the track. So, for teams like, that some of those output measures aren’t necessarily sensible.”
In instances like this, he says, it’s important for managers to be clear about exactly what is needed from those teams and then work out how to measure some of those aspects.
“It might be that you need a team to be collaborative and engaged with other teams or stakeholders. So useful things to know might be how to measure that team's relationship with peers, which could be insightful as to how productive they are.”
Despite analytics being a passion, Thompson emphasises that data alone doesn’t work universally.
“You can't take data in 100% isolation,” he says. “Data is a very powerful tool, but you’ve got to utilise it in the right context for the right purpose and incorporate that with what your people are saying.
“Oftentimes, it's the union of metrics and the people-side that works best. If you blend those together, that’s where you see what's actually going on.”
This is particularly the case in a remote workplace setting, he says.
“I’ve been managing people for a long time now and when I’ve had really good performers suddenly not doing so well, data helps identify that, but you often sense that a lot sooner in person.
“I view the data outcomes as traffic lights, warning signs, but if you're not listening to people, and you're not there to hear what they're saying, you're probably missing quite a lot of information.”
Use of data to analyse engagement and burnout is very topical, says Thompson.
“Burnout is harder to measure because it’s a little bit more intrinsic about a person and you’ve got to be conscious of how you're framing the question, as well as all of the psychological safety elements that are hidden within that.
“To measure engagement, surveys need to be a bit more frequent than annual and need to be a lot lighter in touch than some of the big surveys. Otherwise, you don't get the timeliness of the information you need or the level of insight in order to use it to make an effective difference.”
