1. 32 issue 14.3 hRmasia.com 33issue 14.3 hRmasia.com
Feature Feature
Performance Management
“Big data” and “analytics” are terms repeatedly bandied
around by firms looking to increase productivity levels
and raise bottom lines.
They describe the endless amount of data companies
collect in the hope of analysing and translating into
meaningful and attainable targets, which will in turn
boost company revenue.
However, these lofty ideas can often become Catch-22
scenarios; companies are constantly looking for new
ways to utilise tools to increase their profit margins but
are unsure over how to put such plans into practice.
The 2014 Strategic Directions: Utility Automation and
Integration report by Black and Veatch, a global
engineering, consulting, construction and operations
firm, paints a telling picture regarding the application
of analytics.
It says utilities are keen on data analytics but a
staggering 32% out of 235 respondents claimed they do
not know how to utilise such technologies.
Further proof that companies are struggling to dissect
the complexities of analytics is epitomised from a new
report by professional services firms KPMG. In August
last year, it surveyed 144 chief financial officers and
chief information officers at major businesses
generating more than $1 billion yearly.
Some 96% of its respondents admitted “they could do
more with big data and make better use of analytics” in
their organisations, while 56% claimed that the
advantages that could be gained from the untapped data
could be “significant”.
Using analytics for HR functions
Some of the biggest sources of big data are HR
departments, and analytics can also be used as a
barometer to monitor the success of individually-crafted
strategies, says Timothy Long, Director of Workforce
Information, Micron Technology.
“Talent Analytics is used to inform HR organisations
on precisely how programmes should evolve to be more
effective” says Long.
He says that for many organisations, although
manpower spending is the largest single category of
their annual expenditure, firms are unable to understand
the real return on their investments.
“Talent Analytics is the means to measure the value of
these HR programmes,” he says.
Jaclyn Lee, Senior Director of HR, Singapore
University of Technology and Design, says analytics are
“a very critical part of the HR function”.
“Many departments are caught in the day-to-day
operations and processes of HR and forget that having a
good talent analytics framework in the organisation, and
especially in the HR department, can make their
function a lot more strategic and measurable,” she says.
Big data and analytics have become the
big buzzwords for business. However, many
companies are still in the dark over how to
effectively utilise analytical tools to boost
company performance
By Sham Majid
Analysing
analytics

2. 35issue 14.3 hRmasia.com34 issue 14.3 hRmasia.com
Feature
Performance Management
Long stresses that it is insufficient for HR
organisations to “simply understand and source the
workforce needs of the firm”. In order to remain
relevant and firmly aligned with the business, HR
departments must develop strategies to maximise
workforce productivity by enhancing people
programmes and practices.
”Many HR organisations set direction by reviewing
‘best-practice’ benchmarks, or other popular trends in
the industry. Only from analytics can a firm understand
the true effect of HR programmes to the bottom line and
use this information to continuously improve the
productivity of the firm,” says Long.
Utilising metrics for HR
Metrics is another crucial element that HR
organisations can tap, particularly in talent development
and management, says Yan Renyi, Head of Learning and
Organisational Development, Integrated Health
Information Systems.
“Metrics” refer to a wide range of tools companies use
to measure and assess if their targets, goals and
objectives are being met.
Yan believes that HR can benefit from “objective,
evidence-based analysis to support human decisions”.
“Talent development at times is undertaken as a
reactive measure to plug capability gaps that leaders see
in people. Learning investment decisions entail
significant time and resources, and metrics help support
that decision-making process –identifying the
capabilities required in people and the type of
investment required, for example,” he says.
Lee says HR can partner with top management to
identify key HR metrics to measure and analyse through
the available data.
“This can help to make a great deal of strategic
difference to the way HR adds value as a strategic
partner to the business,” she says.
Yan adds that metrics can then initiate the decision by
identifying and mapping the skills gaps in the workforce
against emerging trends from the industry or business,
before then feeding that information into the learning
management system so as to provide critical learning
and development needs for people.
However, a one-size fit approach won’t work for every
organisation or market. Instead, Yan says talent analytics
can help develop country-specific learning roadmaps for
key talents.
“Identifying capability needs in people provides a
starting point of reference towards formulating an
enterprise-wide learning roadmap,” says Yan.
Using simple analaysis tools such as correlation can
help to ensure the right learning intervention is
provided to the individual, and that such investments
are optimised for the organisation, he adds.
Yan says correlations can identify if a technical
capability area is critical to develop so as to support the
firm’s business growth in that segment. Organisations
can then add accordingly by training the individual.
“Leveraging on analytics gives substance to support
human decisions and can pay off when resources are
optimised to generate a healthy return on investment on
development,” Yan adds.
Quality, not quantity of data
Contrary to the popular notion that business are
required to make perfect sense of endless data, Long
says quality is far more important than quantity.
“HR data is particularly challenging to work with
because most of it is assessed and entered by people, and
therefore it is wrought with error and biases. It’s
important for HR analytics teams to first implement the
infrastructural technologies and processes to ensure
data collection is as accurate and calibrated as much as
possible before attempting to amass more data,” he says.
That being said, Long adds that small databases are
often too minute to produce any statistically noteworthy
data and can often produce incorrect conclusions that
may be based purely on a coincidental sampling error.
He adds that retaining full snapshots or monthly HR
data over a number of years usually provides the scope
for insightful and succinct analytics implementation.
Long says the first step firms should undertake is to
identify the strategic reason that justifies the investment
69%
of business
leaders believe
that data
analytics
is either
crucial or very
important to
their business
Source:
KPMG’s “Going
Beyond the
Data” Survey
in analytics, and use this understanding to structure a
persuasive business case.
“A mature analytics implementation takes time – it’s
important to link to a strategic business opportunity and
find ways to prove value from analytics early and often,”
he says.
Lee believes that firms must first identify “the core
business strategies and drivers that are needed to impact
organisational goals” before they decide to take the
plunge into analytics.
“Once the goals are clearly defined and we are clear on
the key metrics that are needed to drive the business, we
start to look at the necessary talent analytics that are
needed to help in decision making and planning for
programmes,” she says.
Using analytics effectively
Long says that business intelligence and applied data
science are acknowledged as the next strategic
differentiator for firms.
“Because firms spend so much directly on the
workforce, leaders are often willing to invest modestly in
analytics to help optimise their workforce investments,”
he says.
For companies working on a limited budget, Long also
cautions that analytics should be targeted towards the
most pressing imperative.
He says firms must ensure analytical investment is
directed towards supporting the most important business
opportunities. “Successful analytics projects are also
virtuous – success in one project gives confidence to
leaders to invest more in future projects,” he adds.
Lee suggests that firms should “start small”.
“Go for small wins and low lying fruit. We don’t need
complicated systems if we target for areas that really
need massive improvement, and use simple metrics to
track.”
+65 6423 4631
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CONGRESS
SERIES
HR ANALYTICS
CO N G R ESS
9 April 2014 | Hilton Orchard Singapore
Featuring:
Jaclyn Lee
Senior Director -
Human Resources
SINGAPORE UNIVERSITY
OF TECHNOLOGY AND
DESIGN
Interactive Workshop
HR Measurement: Analysing the HR Value Chain
and Applying the Balanced Scorecard in Human
Capital Management
BY POPULAR DEMAND!
Cheng Fong Tuan
Head - Group Talent and
Performance Management
MAYBANK
Joy Roman
Head - Talent Solutions
3M ASIA PACIFIC
Shweta Mishra
Lead - Human Resources
DELL
Timothy Long
Director - Workforce
Information
MICRON TECHNOLOGY
Renyi Yan
Head - Learning and
Organisational Development
INTEGRATED HEALTH
INFORMATION SYSTEMS
(IHIS)
The endless potential of big data and analytics is an appealing concept for many
companies. The KPMG’s “Going Beyond the Data” report found that 69% of business
leaders believe that data analytics is “either crucial or very important to their
business”. Over half (56%) claimed their firms had transformed their strategies to
“meet the challenges” of big data.
The chief reason for the reticence of analytics is clearly epitomised from more
than 40% of the chief financial officers and chief information officers surveyed
who said that their toughest challenge in utiliising big data was integrating data
technology into their existing systems and business models.
A staggering 85% of businesses are also encountering huge problems in
“implementing the correct solutions to accurately analyse and interpret their
existing data”.
Some 75% of respondents confessed to having troubles formulating decisions
regarding data analysis, while they also added that the biggest obstacle to
constructing a data and analytics strategy was knowing what specific data to
amass.
Nevertheless, there are signs that firms are increasingly beginning to invest
more resources in analytics, as more than a third (38%) of large firms have
hired analysts and data scientists specifically for that task. A further 28% of
respondents claimed their organisation had engaged with external consultants or
suppliers to incorporate data and analytics into their operations.
KPMG survey reveals
analytics appeal
While most firms seem to be keen on embracing the utilisation of big data and
analytics, it appears that a majority of businesses in the UK are unconvinced by the
arguments in favour of this approach.
Research from data storage and analytics firm EMC revealed that while 75% of
professionals in this space felt that their organisational decisions could be enhanced
by effectively utilising data, only 37% concurred that their senior departments had
faith in big data analysis to make impactful business decisions.
Only 21% of respondents to EMC’s survey had accomplished a competitive
advantage due to big data analytics insights, while only 44% felt that markets that
flourish will be the same ones utilising such analytics.
UK businesses nonplussed
over analytics