HR should leverage tech to recruit top talent, cut cost
Data Analytics
Can Help Cos Raise Performance & Profit
Imagine a scenario where the human resources (HR)
enters an employee’s basic details into a system and finds out his expected
tenure, performance, ideal learning curve, development needs and learning mix
at the click of a button! While this is a slightly futuristic scenario, it
certainly is not far-fetched. Organisations today no longer make gut-feel
decisions, but those based on data analytics. Companies that have got their
data architecture accurate can predict the time to fill for different roles and
address gaps in their recruitment processes.
Much of this journey has been possible due to the
increasing availability of talent-related data. While supply chain, marketing
and finance functions have already embraced data in decisionmaking, HR is still
lagging — relying more on HR-metric forecasts. Though this has improved
internal HR efficiencies, it still does not present clear benefits to the
business. HR needs to align with business needs and prepare for improving an
organisation’s performance.
The big (data) HR challenge:
With
data, HR functions in India face challenges on three fronts. The first is lack
of understanding on what data needs to be captured, which talent challenges are
hampering business achievement, and what insights will help businesses address
those challenges? The second is not understanding how to set about capturing
data. Should we capture this data through a technology intervention or should
this be done through surveys that link back to the technology? The third is not
knowing how to report data for quick and easy decision-making.
Best-in-class organisations focus on the most
critical talent-related problems facing different parts of the business to
determine what data to capture. For example, to predict employee attrition,
some organisations are studying technology triggers (such as visiting the “exit
process” page or applying for mass leaves) and their impact on employee
attrition. They are also using organisation network analysis (ONA) to capture
continuous data to determine the strength of internal networks by analysing
email metadata and internal social interactions, supplemented by pulse surveys.
This information acts as input in predicting employee attrition and
performance, employee potential, learning needs and even improving workplace
layouts. Advanced visualisation tools with an underlying analytics engine now
help HR teams generate customised dashboards with insights relevant for
different businesses.
Embarking on the talent
analytics journey:
A leading life insurer in India was faced with over 60%
annual frontline sales (FLS) attrition, resulting in a bad hire cost of more
than $10,000 per employee. The organisation used analytics to inform the
different phases in solving this challenge. This involved building a predictive
model for frontline sales hiring by evaluating data of past and current
employees. The firm was able to identify cohorts of candidates with different
probabilities of attrition. This further helped the organisation evaluate
reasons why those with high probabilities of attrition left, which resulted in
redesigning the entire hiring architecture, infusing more technology and a
mindset shift.
Time to shift gears:
There is
no denying the fact that the future is going to be more datadriven, and
possibly machine-driven. At the end of the day, while data analytics will throw
up valuable insights and predictions, it will be the role of HR professionals
to contextualise and implement them given organisational realities and
practical challenges. For that, organisations will have to build a diverse HR
team — data scientists, seasoned HR professionals and people with experience in
business roles — to drive organisation priorities.
The onus is on HR to leverage data, technology,
machines and the power of its collective intellectual capital to unlock the
strong business value trapped in its operating model.
By Anurag Malik
The writer is partner — people & organisation,
advisory services, EY.
TAS 4APR18
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