HR’s analytics journey at IBM
by Stephen Kelly, VP and CHRO at IBM Global Business Services
analytics and measurement at
McKinsey & Company. The danger,
he explains, is that some tech vendors
use the label ‘prescriptive analytics’ to
suggest their software does
something it in fact does not.
“If you give it a formal term and
someone’s offering it as a part of a
product then you have to assume
they have something in there
where the software tells you what
to do,” he says.
“But often they’ve just put a
few simple rules in which say ‘if
the result comes in like this, tell
the user to do this’. There’s no
actual number crunching
involved. It raises the question of
whether the word ‘analytics’
should be attached.”
Sally Winston, head of EX solution strategy EMEA at Qualtrics,
agrees that people shouldn’t be under any illusions about the
software’s current capabilities. Qualtrics works by identifying
problem areas within an organisation and then “connecting back
with ideas for action”, she explains. “At the moment we’re not in a
place where robots create the advice.”
In light of these limitations, prescriptive analytics should currently
always augment rather than replace human judgement. “We most
certainly need human intervention to oversee the predictions and
prescriptions produced by advanced analytics techniques,” agrees
Padmashri Suresh, principal data scientist at O. C. Tanner.
“Human subject matter experts who understand both the
problem area and the advanced analytics techniques are required to
ensure the data that these algorithms are using, and the algorithms
used, do not result in any inadvertent bias.”
Ian Cook, VP of people solutions at Visier, explains that whereas
prescriptive analytics has worked unproblematically for years in
recommending when to buy, hold
and sell stocks, for example (so that
“the expertise of an investment
analyst is being reproduced by the
analytics”), recommendations that
relate to people are a whole
different ball game.
“The circumstances when it
comes to people, where there’s one
clear answer, I’ve yet to find,” says
Cook. “There’s a group advocating
that there should always be a
human in the loop with any kind of
AI, so you cannot absolve yourself
of accountability.”
As such, application of truly
prescriptive analytics is perhaps
best confined at present to very
straightforward, operational areas
of HR, he says. Which will typically
consist of the employee themselves being “nudged” to do something.
“So with things like benefits claims or questions about your
experience in the organisation, there are opportunities to say ‘you
haven’t signed up for that yet’ or ‘you should probably do that next’,”
explains Cook.
Net ix for L&D
Which brings us to what many feel could actually be the most
compelling application of prescriptive analytics in HR: Netflix-style
recommendations within L&D.
“Prescription in learning is where we’ve already seen some really
cool applications,” says Cook. He explains that algorithms can create
a tailored dashboard of L&D recommendations based on what an
individual is working on, their career aspirations, and what training
people like them have done.
The same principles could be applied to making connections
across the workforce, says Modi. “You can empower employees to
“I do believe that use of
analytics will increase
exponentially over the next
few years. To me this is the
‘sweet spot’ that will help
businesses make more
informed decisions.
At IBM we’ve
dramatically transformed
our own HR function with
our AI platform, Watson. AI,
or ‘augmented intelligence’
as we prefer to call it, is
about providing deeper
insight by looking at
multiple data sources and
factors that allow
managers/leaders to
make more informed
decisions around critical
actions, processes and
work ows, to solve
pervasive talent issues.
In our case we have
leveraged AI to help better
understand our skills,
prevent employee turnover,
match employees and
external candidates with
career opportunities,
support managers with
better salary investment
guidance, and create a
platform for employees
to learn.
This transformation has
driven more than $300
million in bene ts to IBM
and, just as importantly,
created signi cantly better
candidate, employee and
manager experiences.
Today, eight out of 10 IBM
employees have skills
of the future compared
to just four out of 10 ve
years ago.
We need a new breed of
HR professional – one that
is data-driven, business
savvy, comfortable with
ambiguity, and capable
of thinking and
communicating
strategically and using
insight to inform decisionmaking.
In this way, data
will elevate HR to a
different level in many
leaders’ minds.”
HR Technology Supplement Prescriptive analytics
10 HR October 2019 hrmagazine.co.uk
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