The right data insight is key for decision making

This resource was also featured as a Briefing Industry Interview in the November 2015 issue of Briefing magazine. To read the issue in full, download Briefing magazine.  


As organisations expand quickly, it’s all too easy for talent’s potential to fade rather than flourish.

The wheels of bigger business can unceremoniously – if possibly inadvertently – squash qualities and confidence alike. So companies need to build a compelling case for employee engagement around the bigger strategic picture. But the largest professional workforces are also in constant flux – joining, moving projects, progressing and training – and management may struggle to keep track of their biggest assets.

“All the transactions over an employee lifecycle offer an extremely rich data set for decision-making,” says Karen Minicozzi, vice-president of human capital management product strategy EMEA at Workday. “You can analyse what sort of a worker someone is, and how that changes over time, alongside the skills they gain. This sort of information adds value.”

In the past, she says, enterprise resource planning systems have tended to focus on single, siloed talent management tasks – transfers or pay rises, for example. But that hinders the collaboration needed for a dispersed, international or otherwise complex organisation to come up both with the best possible individual decisions and a pipeline of high-potential HR activity for the longer term.

She continues: “It really wasn’t unknown for someone to walk a piece of paper around offices to get necessary signatures – before HR would key in all the new details. That’s inefficient − and it’s failing to leverage what HR can bring. These systems didn’t have the workflow capability to enable collaboration on a process.”

Human capital management (HCM), by contrast, she says, can offer hundreds of more efficiently automated business processes – but processes that can easily be modified by different parts of the network to reflect local priorities, regulations or new demands.

“There are processes that are standard across the globe – but there are also local requirements and differences depending on job role. Hiring a lawyer, for example, triggers a different set of reviews and approvals to hiring administrative support.”

Rise of the machine

The real trick, however, is to make complex, tailored and multi-party processes a simpler experience – particularly when the workforce and HR alike are much more mobile and juggling multiple priorities.

Minicozzi explains: “Now, a manager can initiate the transaction for a transfer simply because they’re the person closest to follow up at the time. They may not know all the minutiae of the change – but a process can be set up to route others with knowledge of key details in at a later date.” Everyone’s participating, but you aren’t waiting for each person to play their part.

At the same time, people aren’t bothered with details that they don’t really need. “You aren’t confronted with a screen full of fields that aren’t relevant,” explains Minicozzi. “Only information needed for a task is displayed, which leads to quicker completion.”

In addition to faster transactions, a more mobile system of managing change means choices can be based on the most up-to-date organisational picture possible.

“You make better decisions when you’ve accurate data to hand as you’re making them,” she says. “For example, a firm can search the workforce remotely for people with the right skills or case experience for a project or pitch. You can quickly narrow a search down until you reach the near-as-perfect fit – with visibility of everyone’s official availability and likely last-minute bandwidth.”

More data also makes for better international oversight. “It’s useful, for example, first to tie variations in pay and progression to a common job profile, and only then to account for factors such as local currency or cost structures. It’s important for a global business to probe further if it’s paying significantly larger sums for similar work in different countries − or to explore where a diversity imbalance appears to need the most urgent action.”

But the most critical information could be that which stops you making the same mistakes again – losing talent you haven’t even fully appreciated. HR systems can use “machine learning”, says Minicozzi, to capture trends that may be costing the business dear in retention.

“Once you have someone securely on board you really want to keep them there − which means you need to understand what would motivate them to leave. Machine learning uses data to surface a set of people most at risk of moving on.”

You might make more sensible resourcing decisions in the knowledge a high-value loss is on the cards. But ultimately the intention is prevention rather than cure. Not only can HR predict the people who’ll leave – and leave behind a dangerous business gap. They can recommend actions to prevent the departure.

From faster turnaround times on the move, to greater insight into talent’s strengths and weaknesses, HCM is about building a talent base that’s both fit for purpose now and fully onboard for the future.

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