Workforce Analytics

by Frontier Software.

Frontier Software’s Eugene Harvey explains how workforce analytics can transform your business.

WHAT IF you had a business tool that could boost profits, increase employee satisfaction, retain and engage staff, improve health and safety, and meet your diversity and inclusion goals? Well, workforce analytics can do all of this and more, says Frontier Software’s, Eugene Harvey. The problem is persuading people to use it.

Late last year HR software provider Frontier Software acquired HRIT, a leading provider of human capital management (HCM) solutions – and with it, HRIT founder Harvey.

According to Harvey, even where companies are investing in workforce analytics software, they either don’t know what to search for, or are not acting on their findings, which is why he’s on a mission to drive home what a significant difference adoption and efficient usage of data analytics can make to a company, not least to its bottom line.

Unlike HR metrics, which simply provide a static measure, workforce analytics goes further, looking at the who and the why. Take, for example, the business risk that is an ageing workforce – especially prevalent in well-established companies or government organisations such as councils.

HR metrics can tell you that you have maybe seven people working beyond retirement age, but to extrapolate anything useful from that in the long term you need the analytic data. “If we project that out, you see the significant risk in the next three to five years, when there will be a big gap in the workforce,” says Harvey, who prefers the term ‘workforce analytics’ because it encapsulates everything. “There’s always been confusion between payroll analytics, HR analytics and workforce analytics. Workforce analytics covers productivity, staffing, everything around people and workforce delivery. It’s also around attraction and retention – it all relates to the bottom line of the company.”

And yet, says Harvey, organisations are not actively using them for any real advantage. Ironically, it’s the all-encompassing nature of the tool that is proving to be a sticking point.

The biggest issue is a lack of clarity around ownership. A lot of valuable workforce analytics cross over into areas like financial management and operational management, but ownership absolutely needs to lie with HR, says Harvey; indeed, it has the potential to revolutionise and transform the function. However, traditionally it has been outside of HR’s comfort zone. “HR have not traditionally been heavily invested in analytics, especially outside of their direct function.”

Workforce analytics should be able to be leveraged by many functional areas of the business, with HR driving it and having oversight. But in order to succeed it has to get buy-in from senior leaders and, importantly, must adapt to meet the benefits and challenges of an increasingly data-led environment. This means having individuals with the right skill sets.

Traditionally, HR has used HR-focused analytics to look at diversity, gender equity and attrition, says Harvey.

“These tend to be simplistic once-a-year events that are triggered by noise – from government or the media. HR tends to be very reactive.”

Correcting bad habits

Business has a lot to gain from inquisitively looking at data and seeing how the patterns are impacting its operations, says Harvey. He cites an example of a paper mill that successfully used analytics to address bad practices around working hours.

“It had a habitual issue with engineers drawing out shifts so they could inflate their income. As a result, the company moved to a salary system based on what the engineers earned the previous year. Suddenly what was taking 60 hours to do was taking 40 hours. There was no incentive to draw the work out, and they could achieve a maintenance job within the time allocated.”

In another case, a company in the services industry was barely breaking even – until it introduced a workforce analytics metric showing the ratio of direct (chargeable) services to indirect (non-chargeable). Instant visualisation of the data – broken down into regions – immediately highlighted the disproportionate amount of indirect labour. Management acted on this and saw an immediate return to profitability.

Shifting the focus

Another case study highlights the health and safety benefits of embracing workforce analytics. A manufacturer in a high-risk industry, prompted by a US study showing how accident rates shot up when staff worked over 57 hours a week, decided to look at its own workforce hours.

“To their horror, they found about 80% of staff were working more than 60 hours a week. They took action and within a month got that figure down by getting managers and shift leaders to take ownership of the hours worked.”

Analytics can even effectively shift an organisation’s hiring focus, which was the case at one business’s contact centre. Among the under-25s, the contact centre’s attrition rate was 80%, and tenure was barely a year. When analysing data for women aged 30–35, the tenure jumped to two years and attrition was just over 50%. These were people on a secondary income and return-to-work mothers for whom the contact centre environment and hours were ideal. So the company changed its recruiting focus to target that demographic, and within 12 months attrition was down to just over 60%.

Harvey says too many companies compare their performance to the industry average, which he regards as “striving for mediocrity”.

“If the attrition rate for contact centres is running at 60% and you say ‘we are doing OK, we’re on a par’, it’s a cop-out. Why not say ‘we can be an employer of choice – we can aim for 20%!’ ”

There are many case studies proving the benefits of investing in, interpreting and acting on workforce analytics, says Harvey.

“Not having analytics in an organisation is like going through your house and taking out all the smoke alarms.”

Even when the smoke alarms are there, there is often a reluctance to act, partly because the action required is difficult, or maybe the data points to a problem with management, who might not want to take ownership of the problem.

However, companies have so much to gain from switching to active rather than reactive mode. “You can say ‘we want to be an employer of choice because we employ the right people and we look after the right people and we see that in our surveys, our retention rates and our sickness rates’.”

Transparency drives action

For Harvey, to encourage take-up of this untapped business tool, the systems need to be interactive and dynamic, allowing easy navigation and exploration of results. Also, crucially, the people who need to be interrogating the data should be actually using it. Too often the job of data analysis gets devolved down to HR analysts, who aren’t analysing as such but simply getting data on request and producing graphs and charts. The data needs to be, transparent and available to those with limited computer literacy – including senior management whose buy-in is crucial to driving change. “Most analytics solutions like the ones we deliver have transparency. So if you are at the top, looking, for example, at overtime worked, you can drill down to the regions, the branch, right down to the team leader to see how a particular team or department is meeting your targets. That then becomes a catalyst for each of those department heads and the people below them to take action and reduce their liability. The transparency exposes them.”

Looking for the smoke

You can build the greatest analytics in the world, says Harvey, but ultimately you need to go looking for the problem.

“That is where the gap is in many companies – the skills to actually interpret and look for the issues.”

If HR is to successfully deploy workforce analytics, it must identify metrics that can drive change. This means looking for measures that are aligned to HR and business improvement strategies; using targets for key measures to improve visibility of performance; making targets meaningful and achievable, and engaging all areas of the business to determine what analytics and measures would support their function.

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