The new era of talent analytics will be predictive rather than prescriptive, and will be used for national and international benchmarking of HR practices, according to leading HR professionals.
Upon winning HR director of the year at the 2011 Australian HR Awards, Alec Bashinsky, national partner, people and performance at Deloitte, told HRM that he believes HR will only become sustainable by focusing on data and metrics, in the same way that other business divisions look at data-driven insights before making decisions.
“The HR industry has to make better use of people data,” Bashinsky said. “We spend a lot of time as an organisation assessing our metrics but I’m not referring to past tense, I mean looking at future trends. What’s happening in certain workforce areas, how do our people want to work and how can we build organisations to support that?”
His words have been echoed by other observers of the HR function.
“Prescriptive analytics will get you so far,” says Eugene Burke, chief science analytics officer at SHL. “HR need better data that’s going to tell them about what happens tomorrow, not what happened yesterday.”
What’s the hold up?
Until relatively recently, HR professionals have been limited in their ability to provide managers with the granular details they need about possibly their most important assets – their people. It’s meant that HR has lagged behind other key business functions like sales, pricing, supply chain. There are two primary reasons for this lag: lack of technology and lack of capability.
Peter Howes, vice president, SuccessFactors, suggests that the past 15 years have seen the growth and maturity of business intelligence (BI) tools. While these tools have allowed for development in capability, the HR community has been less successful in the implementation of the supporting technology to automate the data loading into BI tools.
“Unlike finance, sales and supply chain, HR had people data in multiple systems in every company, in addition to the core HRIS and payroll systems such as employee surveys/engagement systems, and some or all of talent management suites are in independent systems,” Howes explains.
The key to effective utilisation of HR technology, Howes adds, is to integrate data from multiple systems and to have the capability of routinely updated data from these multiple systems.
The second reason why HR has lagged behind is because HR technology doesn’t succeed without pre-packaged content, as opposed to a tool that allows you to build whatever you want to build.
“There are 10-100x permutations of people data that may be insightful compared to sales, finance and supply chain data,” says Howes. “HR practitioners don’t have the knowledge to interpret what all of the implications and insights of the information might be. HR practitioners do not learn how to interpret HR information in the university programmes; AHRI does not have standards for the interpretation of HR information. This area is very immature in the HR profession.”
The changing nature of metrics
The HR function itself has evolved so rapidly over the past decade that measures of effectiveness have scrambled to keep up. The traditional notion of HR ensuring processes are working – for example that recruitment quotas are being met, that absenteeism is being handled effectively – now needs something extra. “We know where everybody is and what they can do. That’s prescriptive analytics; it tells us where we’ve got to. But increasingly leaders want to know where can we go next,” says Burke.
Technology is finally coming to the table. A business execution suite – as opposed to a traditional talent management suite – provides analytical tools that help bridge the gap between business goals, people management practices, individual performance and business results. It integrates workforce analytics and strategic workforce planning applications. That capability allows companies to analyse talent and HR data, and correlate it with data from other business functions such as finance, enterprise resource planning (ERP), operations and customer relationship management systems (CRM). This is the basis for developing true predictive analytics on a company’s workforce.
If a CEO or a senior executive in an organisation is planning to embark on a change – it could be a procurement of a new IT system implementation or a significant acquisition of a new company – they would create an airtight business case. HR is no different.
Ari Kopoulos, national sales & marketing manager at EmployeeConnect, says that accurate and relevant metrics is the first stage in building a case for procedures and strategies that impact on business results, drive change and build competitive advantage.
“In practical terms, this involves the HR professional strategically leveraging measurement to provide a deeper insight,” he says.
This is echoed by Peter Harte, vice president, Kronos APAC. “If you can’t track it and you can’t measure it, then there’s no real ROI on it. CEOs and CFOs want a ROI on any particular system they implement and they haven’t traditionally understood the value of tracking what happens with people once they enter the workforce,” he says.
“We need clear metrics on people – and HR needs to be able to articulate answers back to the line or other senior leaders,” Burke adds.
Lead indicators now fit into three categories.
Where a group of measures or metrics are combined together to provide a more holistic perspective. The metaphor that Howes uses is to equate a single metric to an X-Ray. It gives a static two dimensional picture. A move towards groups of metrics would act more like an MRI. “A group of metrics which can be more predictive would be combining voluntary labour turnover with career path ratio with recruitment source ration. We would want to know these measures segmented by: grade or level, organisation unit, performance rating, position/company tenure, job family/occupational group etc,” Howes explains.
Integrating qualitative metrics like engagement score with quantitative data like voluntary turnover rates – this is much more predictive than standalone measures like turnover rates.
Index related measures – which Howes believes is the key future trend. Traditional metrics consist of one measure (eg voluntary turnover) divided by another measure (eg average headcount) to give a ration or multiplied by 100 to give percentage. “A bit simplistic,” as Howes states. Outside of the HR world, one can look to an example of an index measure with the Southern Ocean Oscillation Index (El Nino/La Nina). “When we watch the news we see the index as somewhere between 120, [indicating] very high probability of significantly above average rainfall over the next six months – to 80, [indicating] very high probability of significant below average rainfall over the next six months). Very few people know how the index is created – variations in the surface temperature of the Pacific ocean, air surface pressure in Western Pacific. We need to build the equivalent for Index measures like managerial bench strength. ROI of training etc.” Howes also feels HR can generate more predictive analytics by integrating people data with business data. Examples: revenue per salesperson by performance rating or impact of employee engagement on branch profitability.
Effectiveness and efficiency
Does this mean that traditional metrics such as cost to hire and time to hire – which are almost benchmarks for efficiency – will lose traction in this march towards measurements of productivity? Not necessarily, but Howes believes they may need to be tweaked. “While we’ll always have efficiency measures we need effectiveness measures,” he says. “In staffing this is primarily related to the effectiveness of recruitment source. We can define effectiveness by measures such as performance rating in the first year – or first two years – and percentage salary increase in the first year.”
Burke adds that “you might have the most efficient method, the most efficient process, but it’s not actually delivering the talent that you need”.
Talent analytics provides answers to key HR challenges – from the effectiveness of recruitment and employee development strategies through to insights on current on-the-job employee performance and management and leadership potential. Industry and regional comparisons can also reveal how workforces stack up against the competition.
Part of this is looking at the potential of existing employees, but this too is rooted in lag analytics: what an employee’s past experience has been, what qualifications they have, etc. The real question regarding employees who show potential, Burke says, is how the organisation can engage them.
“Work potential is something people looked at and scratched their heads, because we can easily see what qualifications someone has, we can check their work experience to see what they’ve worked on. However, I think organisations have started to wise up to the fact that they’re lag measures as well. They tell you what the person has learnt today but not necessarily what they can do with that or what they can learn in the future.”
Burke believes there is a “talent sweet spot”, whereby if the organisation can engage those with the right potential in the right way, “they’re suddenly in that top right-hand corner [of the performance vs potential matrix] where they want to be. That can all be driven by data.”
Pulling it all together
Kopoulos states there is no doubt that analytics can be used to assist the strategic decision making process within HR: “This process is greatly enhanced with access to information that presents ‘what if’ scenarios, trends and drill-down analysis into root cause. This can only be achieved when data is consolidated, integrated with all the HR modules and communicated in real time with clarity, supporting meaning and usability.”
The ‘what if’ scenario building is particularly apt for remuneration review, to use just one example. Analysis usually means selecting an employee demographic or location and applying the increase. The direct impact of a change in remuneration is immediately apparent, but Kopoulos says it shouldn’t stop there. “Look into the history and analyse relationships between other functions such as performance, training and length of service positive and negative trends and indicators.”
Best practice uses visualisation tools like charts, gauges and maps, bringing high-impact, predictive insights to meet operational, analytical and strategic requirements. Dashboards also work well in this regard.
“It doesn’t matter where the data comes from – obviously it’s got to come from the systems you want to measure – but it really is a business intelligence tool and it takes a combination of all that data and then presents it in a way that you want to see it. You must understand what your KPIs are, take the information from your disparate systems, and then present it so it’s effective and you can make decisions,” Harte explains.
Kopoulos adds that in most organisations the hiring, firing and promotion is the manager’s responsibility. “Presenting them with accurate and easy to assimilate talent analysis embeds a level of quality in their decisions,” he says. “For example, understanding the sources of departure, reasons for departure, and sources of high performers and potentials, provides insights that build cost effective strategies for retention and hiring.”
Using the existing data
Burke urges HR professionals to transform the way they look at and interpret the data they already often have at their fingertips, gathered from the recruitment process, from 360-degree reviews, exit interviews and other sources.
“You’re not extracting the best information from that data. It’s not a ‘use once, throw away’ kind of piece. You can use that data in a more aggregated way to get a much better picture of the people profile. Don’t just transact with it, use it in some way to answer those questions.”
Harte notes that ‘joining the dots’ can be surprisingly straightforward. Historical data remains important to make some performance assumptions, based on people and tasks, or metrics around customer service. This then needs to be projected forward so that each employee understands what they need to do and can be measured against it.
“The technology can now be instantaneous, so you can start looking at things like attendance and absenteeism or productivity. When you start looking at trends, you can then focus on who are your top employees as you go forward, and you realise that perhaps they should be treated differently. It might become a performance issue or a coaching issue.”
What might the future hold for HR analytics? Burke suggests it might tie in both the customisation and diversity of HR offerings – specifically taking a leaf out of retail customer loyalty plans.
“At the moment I would shop in Australia or the UK and I’ve got my customer loyalty card. What the organisation is doing is tracking my transactions and is using that data to get a sense of ‘if Eugene Burke shops locally and there are lots of other Eugene Burkes out there, how can we keep that customer engaged? What kind of products, what kind of services do we need to provide to them?’
“Think of the same thing inside organisations. How do we keep employee Eugene engaged? What do we know about Eugene? How many Eugene’s are there in the organisation? I think that’s fascinating; it’s almost drilling it down to diversity or specific individual employees. So that employee has value in terms of their potential and we can use data to know how to keep someone like Eugene engaged.”
Burke concedes that big data can be “frightening” and “intimidating”. However, in his view, “you don’t have to boil the ocean in one go”.
“It’s more around the kind of capabilities in an organisation. If they’re not along a maturity level, of being a high end user of analytics, it’s finding out where to start first. Some organisations such as the big consultancies may have that capability and they’ve got that data – but if you know three or four things about an individual and you know what keeps that individual engaged then at least you can start building up a picture by an individual, by a group, you can start building the journey in a manageable way.”
And technology will continue to make things easier. Engagement questionnaires are coming out on mobiles phones, via the internet, or self-service kiosks – even smartphone apps. Shift workers can now schedule their own work times with self-service tools. And with the web-based technologies the results can be produced in any format users feel comfortable with.
Yet talent management and HR technology alone do not make HR strategic. In order to gain greater credibility with executives, Howes says HR leaders must be able to deliver fact- and data-based business cases for what they are doing, argue why investing in a specific workforce programme will deliver a certain ROI to the business and – when possible – help CEOs prioritise and allocate budgets and resources across business functions for optimal execution and performance.
“To achieve this outcome, companies must create a Centre of Excellence [CoE] in strategic workforce planning and analytics. We must also build the skills in the HR community to interpret the implications of workforce analytics and use this information to formulate HR strategies and HR interventions,” he concludes.
What is the value of your workforce?
An expense - A cost of doing business
A resource - Categories of people with certain skills and hard to retain. Must be properly deployed. An asset, like equipment or materials
A flexible asset - Individuals who produce and adapt to changing conditions
A competitive advantage - A network of individuals who work together to achieve a desired result
What is workforce management?
• Data collection – Automatically collect accurate data
• Time and attendance – Reduce errors; minimise overpayment
• Absence management – Manage the people who aren’t there
• Forecasting and scheduling – Right person, right place, right time
• Activities – Link your people to the work that they do
• Analytics – Monitor, diagnose and address issues
• HR and payroll – Consolidate your employee-related information
• Hiring – Find, select and hire the right people
Solving 3 critical business issues:
Control Labour Cost
• Reduce overpayments
• Eliminate manual processes
• Reduce over-scheduling
• Provide visibility and control
Minimise Compliance Risk
• Centralised policy administration
• Local policy enforcement
• Detailed audit tracking
Improve Workforce Productivity
• Automate productivity-killing processes
• Match labour to volume
• Understand the impact people have on the business
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