People talking

People & Organizations

People Analytics: Are You Asking the Right Questions?

September 29th, 2016

Overview

Talent management is no longer just an HR imperative. Questions such as “are we getting the best talent in the market?” and “are we at risk of losing our best performers?” are increasingly becoming board-level priorities. At a time of global skills shortages and increasing competition, integrating talent strategy with business strategy is essential. With more data available than ever before, management teams are beginning to look to predictive analytics to better understand and plan for one of their most unpredictable assets: their people.

From anticipating consumer demand to matching inventory with demand, forecasting analytics are nothing new. Smartly applying people data, however, is not an easy feat. More importantly, deriving actionable insights from this data can be even more daunting to an organization.

Why? Access. As many multinational organizations know all too well, HR-related data is typically housed in various systems, ranging from sophisticated cloud-based programs to spreadsheets and even slides. Business leaders might have a difficult time getting an accurate headcount, let alone gleaning insights from advanced analytics.

But this is changing. The talent conversation is evolving and gaining more visibility with senior leaders across organizations. And with the emergence of sophisticated systems, progressive organizations are looking to predictive analytics as a way to answer the big talent-related questions that best progress business strategy. However, to get the greatest value from data and analytics, integration across teams is important. From human resources teams to finance teams, there is a need to combine systems and data to really develop the core insights needed to drive strategic business outcomes.


In Depth

“The fact is, you can’t predict the future, particularly when it comes to human beings,” says Eddie Short, Managing Director, People Analytics, Aon Hewitt. “However, historical data can help business leaders better understand trends to help predict even the more unpredictable elements of the world – human behavior.” This, implemented intelligently, can help leaders make better decisions about what they could do, and what they should do.

Accessing, understanding and acting on analytics isn’t a simple task, cautions Usha Mirchandani, Partner, Talent Analytics at Aon Hewitt. “Best-in-class organizations are using analytics to solve business challenges.” She adds, there is a very clear difference between prevalent analytics and high value analytics. She explains, “prevalent analytics consider HR dashboards that review simple metrics like turnover, headcount, talent movement, and diversity representation.” While these metrics provide a pulse rate for your workforce, it is in the high-value analytics that business challenges can be solved by connecting the right people data to the right business data. This type of analytics enables companies to take a cost-based perspective on the workforce, including how to best manage productivity and profitability with staffing models to achieve their growth targets.

But with so much data and so many questions that could be answered – where do organizations begin?

Four people-based areas emerge that could most easily benefit from a blend of prevalent analytics with aspirations to move to the more high-value analytics.

1) Smarter Recruitment

One of the core areas where workforce analytics can make an impact is in anticipating skills gaps and identifying high-potential recruits.

Systems could, for example, extract historical data to predict when certain positions would most likely be vacant. For competition-savvy organizations, systems can also monitor direct and indirect competitor’s advertised openings, possibly identifying new opportunities for industry growth.

Tools and techniques are being applied to recruit top talent. Recruiters and hiring managers are able to better match openings with prospective candidates by leveraging social media data and technologies that allow employers to build sophisticated applicant profiles and actively recruit passive talent – that is, potential employees who aren’t engaged in active job-hunting.

2) Managing Turnover

Turnover is expensive. Although costs can vary throughout the globe, sustained churn can end up being a big drain on a company’s resources.

Predictive analytics can provide much more granular insight into at-risk individuals and teams. “Many organisations are still only doing basic analytics such as attrition and turnover analysis, says Short. “But some are using predictive models to better identify groups or teams and ultimately individuals that are at highest risk of leaving the business.” Whether the best response is to anticipate decisions to quit and thus begin a succession plan for the role, or whether intervention can help address concerns – having the knowledge of who is at risk arms the organization before talent walks out the door.

3) Addressing Generational Needs

With five generations in today’s workforce, analytics can be beneficial in helping plan for the needs of various workers – especially older workers. “We use the term ’Ageonomics‘ to describe how workforce analytics can sync up with healthcare provision to deal with the interaction between aging workers and their workplace, and implement holistic wellbeing solutions,” says Joe Galusha, Group Managing Director of Risk Control and Claims, Aon Risk Solutions. This can help drive higher performance and productivity, and reduce turnover – as well as make for a better working environment for older workers. “Data and the insights they enable can bring significant long-term economic benefits to organizations challenged with addressing shifting worker demographics.”

4) Nurturing Talent

Data can help organizations understand performance in a more holistic sense, and look at other value-indicating metrics, like how well certain employees sustain client engagement, or how well they grow business along other avenues. Identifying high-potentials is one thing, understanding how to best nurture those that bring long-term business value is another. Short explains, “by using more sophisticated assessment, engagement and reward analytics, we can ensure that we truly have the most effective talent in the most critical roles.”

Stephen Hickey, Partner and Head of Talent, Aon Hewitt Pacific, states that organizations should be basing more decisions on known predictors of individual, team and business performance. “Most organizations currently gather huge amounts of data on their people, but do very little analysis of how this data can be turned into insight that can help to take the guesswork out of how to get the best results from their people.” Having a solid understanding of the trends of their lowest and highest performers can help decision-makers derive predictions. Not only can this information indicate how training can be improved, but can also help identify what types of personality traits – – are essential for long-term success.

Many questions are posed and much data either is, or can be made, available. With the amount of data generated across an organization, the trick then lies in asking the right questions of the data amassed.

Asking The Right Questions

Successful business planning is about being able to anticipate and prepare for the future. With HR departments driving talent strategy and the Global Leadership Forecast finding that only 18% of participating HR departments saw themselves as “anticipatory,” the ability to forward-look should become more of a priority. Despite the spread of predictive analytic technology and techniques, their application is still little understood and education is necessary.

“If HR departments focus only on performance data of employees without the broader business context, they will continue to struggle to see the big picture,” says Short. The key to extracting insight is to combine multiple layers of data to find meaningful relationships that help to predict future performance. Hickey explains, “employee engagement data can be combined with leadership feedback to build the profile of leaders that are generating the highest discretionary effort and productivity from their people. Ultimately, these insights will improve the overall quality of future investments in leadership recruitment and development.”

Not only does embracing an “analytics-mindset”, as Mirchandani terms it, help teams understand patterns and trends to answer today’s questions, but the new way of thinking brings with it a more holistic view of talent management. Mirchandani emphasizes the benefits that can be seen by rethinking and de-siloing data within an organizations. “Tangible business outcomes such as sales and revenue growth are board-level priorities. And so is talent. As organizations begin to map their people data to business outcomes, they can begin to predict and build business scenarios to determine, for example, which high-potentials are most likely to develop tomorrow’s game changing product.” She explains that teams responsible for answering these big-picture questions will prioritize, among other things, answering whether an organization is getting the best talent in the market, how investments in corporate and employer brand are impacting recruitment and how skills shortages are impacting an organizations’ external talent availability.

While implementing this type of mindset is not yet ubiquitous, one thing is clear – analytics are only as good as two things: the access to quality data and the specific insights that they can provide. And perhaps the greatest challenge of all – identifying the questions that move the business forward and mapping the right data to be able to answer those questions.


Talking Points

“People analytics – the fast-growing practice which companies use to analyze large amounts of data to quantify employee performance – has the potential to revolutionize the workplace and vastly improve how all of us are rewarded for our efforts.” – Harvard Business Review

“The heart of science is measurement. We’re seeing a revolution in measurement, and it will revolutionize organizational economics and personnel economics.” – Erik Brynjolfsson, Director of the Center for Digital Business at the Sloan School of Management, M.I.T.

“Predictive analytics are only as good as two things: the quality and volume of the data you can access, and the quality of the business insight you can provide.” – Eddie Short, Managing Director, People Analytics, Aon Hewitt


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