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TECHNOLOGY
Data miners
Companies are gazing into the future
for injury prevention
By Mari-Len De Guzman
H
uge data that may be wilting away in company servers
could have a bigger purpose
in the organization than just satisfying
compliance requirements. Experts are
saying it may just be the key to the ageold quest for total injury prevention.
Through data analytics (also called,
predictive analytics), some companies
are finding good use for data gathered
over a number of years in bringing injuries and fatalities down — which can
only be good for the bottom line. Anything from safety-related stats (safety
inspections, near-miss reports, losttime injuries) to broader corporate data
(employee demographic, equipment
maintenance reports, performance
bonuses), data experts say all have the
potential to produce great intelligence
for safety applications.
This is what Vancouver-based
mining firm Goldcorp has realized
following a six-month pilot project in
one of its mines in Ontario that put its
vast corporate data to the test using
Deloitte’s data analytics software.
“We looked at five years of data, collected over two million data points, and
we started to see this data is telling us
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2013-COS-AugSept.indd 28
something,” says Paul Farrow, senior
vice-president, people and safety for
Goldcorp.
“In some cases, (it) reinforced what
we already knew but now we actually
have quantitative, statistically significant data to work with; in other cases,
it kind of showed us some areas which
we were not expecting to see.”
profiles, climate measurements, equipment maintenance and geo-spatial data
— and fed them into the analytics program developed by Deloitte. The system
then produced intelligent reporting on
trends related to health and safety. In
a nutshell, the data analytics provides
information that allows Goldcorp to
identify key drivers of safety incidents.
For instance, Farrow says, through
the analytics the company found certain types of employees have a higher
propensity to a workplace injury.
“We found the work propensity for an
individual to have an incident is much
higher if you are single, versus married,”
says Farrow. “Married with children even
further decreases (the propensity).”
Goldcorp’s Porcupine Gold Mines in Timmins, Ont., where the data analytics
pilot project was conducted.
Goldcorp took various data from the
Ontario mine — including safety incidents, production, times, production
bonuses, employee socio-demographic
Other key drivers of incidents
Goldcorp has found have to do with
production and bonuses. The company
found the propensity for safety-related
incidents increases with bonuses.
However, with the most experienced
workers — and therefore the highest bonus earners — Goldcorp sees
the reverse is true, as the propensity
for safety-related incidents actually
decreases with this group of workers.
The data analytics also found, overall, January, March, July and September
are higher-risk months for incidents.
There is an increase in incidents among
aboveground employees between September and March, while underground
crew experience the highest number of
incidents in July and September. On a
weekly basis, higher incidents occur
during Tuesdays and Wednesdays.
Goldcorp also found other key drivers
for incidents, including weather, hours
of daylight and other environmental factors; relationship between aboveground
and underground workers and their
propensity for injury; and the influence
of demographic factors (marital status,
experience) on incident occurrence.
While getting this kind of intelligence from corporate data is valuable
for organizations, what they do with
those analytics is key to really achieving
the safety performance improvements
they desire, according to Dave Stewart,
chief operating officer for Deloitte Analytics based in Toronto.
Organizations that are harnessing
analytics capabilities in an effort to
solve business problems tend to be
more successful than those that don’t
understand how to leverage their
data, Stewart suggests. It’s an innovative way of looking at old problems
to generate new insights in reducing
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13-08-01 11:45 AM
TECHNOLOGY
and mitigating risks to people and
companies.
“Data in its smallest form is just
data,” says Stewart. “Data that’s been
analyzed creates some form of information; information combined with
expertise creates intelligence… and that
may help create predictive forecasts.”
He says Goldcorp understands this.
“At the end of the day, the data is
giving us the direction,” says Stewart.
“Whether some companies believe to
take that direction is really (about) culture, the ability to adapt to change.”
Farrow says the greatest value in
data analytics will be derived on the
frontlines.
“The site supervisors and managers
now have that information, they can see
it on a graph. It’s really driving a behaviour change,” Farrow says.
“We are now getting at the precursors of what is causing these incidents
to happen. The leading indicators can
help to make sure that anything you
put in place — whether it’s additional
training or more visible leadership in
the field — the leading indicators will
have to start telling you how well you
are actually doing that and (if there is) a
correlation with improved safety.”
Incident predictions
Multinational construction firm
Lafarge has been evolving its big data
utilization to improve its safety performance over the last 10 years.
With about 80,000 employees across
the globe, Lafarge has a more focused
approach to data analytics, using two
leading indicators: employee engagement by management team — under
its Visible Felt Leadership initiative —
and job observations.
“Imagine all these observations
going on all over the world, all these
conversations, all these interactions,
all these engagements with managers
and employees, and employees and
employers,” says Chris Roach, director of health and safety with Lafarge
Canada in Calgary.
“We’re trying to capture the details
of those conversations to give us some
solid data of where we should focus
our attention.”
These leading indicators are fed into
a custom software program which produces trending reports that identify
what types of risks exist at every site, the
percentage of safe versus unsafe acts at
various sites, and which sites are more
likely to have a safety-related incident
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WHAT IT TAKES?
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WHERE: CSSE 2013 Conference,
The Fairmont Queen Elizabeth, Montreal
WHEN: Tuesday, September 17, 2:00 p.m.
SPEAKERS:
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Guylaine Lacroix, EH&S leader, GE Aviation
Eric Boulé, Director of Canadian Manufacturing,
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Steve Loftus, Owner/General Manager, Innovative Automation
WHERE: Alberta Health and Safety Conference, Keynote panel
discussion, BMO Centre, Calgary
WHEN: Monday, October 21, 3:15 p.m.
SPEAKERS:
Yves Tremblay, President and CEO, Pronghorn Controls
Monique Britten, Director, HSEQ, Hallmark Tubulars Ltd.
Roxanne McKendry, Manager, EH&S, Carewest
Dan Strand, Health and Safety Manager, Vancouver
International Airport
30
Canadian Occupational Safety
2013-COS-AugSept.indd 30
in the near future, explains Roach.
With the analytics tool, Lafarge is
able to identify the top risks or sites that
need special focus.
“For example, we see five per cent
of unsafe acts are related to working at
heights, then we zoom in on working
at heights, zoom in on fall protection
training, zoom in maybe on re-issuing
our working at heights standard in that
area,” says Roach.
“It allows us to get ahead of those
things before the accident happens.
We’re just observing the unsafe acts and
we’re able to capture them and then act
on them.”
According to its 2011 global sustainability report, Lafarge has dramatically
decreased its global lost-time injury
rates from 8.35 in 2002 to 0.63 in 2011,
thanks in part to the company’s data
analytics initiative.
The same positive improvements
are being achieved by other organizations that have started embracing the
potential of data analytics for injury
and fatality prevention.
Denver-based Cummins Rocky
Mountain (CRM), a distributor of
Cummins and Cummins Power Generation products, started implementing
data analytics in 2009. CRM uses SafetyNet, a safety management system
software from Oakland, Pa.-based Predictive Solutions. Within 12 months,
the company’s recordable incident rate
was reduced by 76 per cent and losttime injuries decreased by 88 per cent.
The company enters data collected
through safety observations and audits
(leading indicators) into the SafetyNet
system. The system then generates a
report that predicts where the next
incident may occur, based on leading indicator data, explains Griffin
Schultz, general manager for Predictive Solutions.
The predictive model behind the
SafetyNet technology was developed
through a collaborative study with
The Language Technologies Institute
at Carnegie Mellon University (CMU)
in Pittsburgh. The study used leading
and lagging indicators from actual
workplace data across 250 work sites.
The result was an accuracy rate of
between 80 and 97 per cent in predicting incidents.
The Language Technologies Institute is the same CMU department that
helped IBM develop the Watson supercomputer that is now helping doctors
diagnose rare diseases.
SafetyNet generates “red flag” reports
which tells a company which of its work
sites have a higher risk of safety incidents, says Schultz.
“As you collect more safety observations — leading indicator data — you
fuel the data analytics and the predictive
models get better and start predicting
where your incidents are going to occur,
and then you can prevent them,” he says.
Tim Smith, safety manager for Cummins Rocky Mountain, talks about the
value of data analytics in reducing the
company’s injury rates.
“It enables us to establish a relationship between leading and lagging
Lafarge’s Western Canada health
and safety director, Chris Roach,
talks to Vancouver manager,
Amir Merat, about worksite safety.
indicators so we can understand
whether we’re looking in the right
operations and aspects of our business
operations to identify opportunities to
get better,” says Smith in a video posted
on Predictive Solutions’ website.
What the future holds
Still in its infancy, data analytics for
injury prevention takes many forms
and goes by different names — predictive analytics, leading indicators — and
the technology that fuels this capability
will need a series of enhancements to
maximize the potential in predicting
and preventing the next injury.
For Deloitte, helping companies
understand and take advantage of their
vast corporate data is key.
“What we are looking at is what other
points of data do these companies have
access to that they have traditionally
not tapped into,” says Stewart. “We’re
trying to understand what we don’t
know… does that data add value when
they combine it with other data sets?”
One thing experts are certain about
is that leading indicators are overtaking
lagging indicators in providing good
intelligence for improved safety and
preventing injuries and fatalities in the
workplace.
In mining, industry observers note
that while the number of lost-time injuries has consistently gone down over
the last decade, the number of fatalities
seem to have plateaued — and safety
advocates continue to look for new and
better approaches to prevention.
“Traditional approaches to date have
not seemed to reduce the percentage
of fatalities,” Stewart says. “So there’s
a drive to take a different approach to
the same challenge and the difference
here will be looking at all of these data
sources and converting them into some
form of intelligence.”
The advantage and value of leading
indicators also becomes more prevalent as companies start to improve their
safety performance.
“I do think (data analytics) is the next
level of health and safety,” says Lafarge’s
Roach. “We’re still on that path of finding better ways to capture the data,
finding more consistent ways to capture
it. You get to a certain level of health
and safety and you start to see your lagging indicators levelling off.
“We’re at that point now where our
incident rate is quite low and we’ve got
to do some innovative things to try to
get it down to world-class.”
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13-07-30 5:02 PM