
30 ISE Magazine | www.iise.org/ISEmagazine
How the intelligent enterprise will drive innovation
isn’t too relevant at the enterprise level (though it could ac-
tually be important for automation in the human resources
department), but recognizing nuance is critical to under-
standing complex adaptive systems in general. For example,
understanding the subtle shades of human behavior is es-
sential for identifying the potential underlying causes of
market shifts that are rooted in the collective decisions of
its human participants.
Where machines are weak, humans often excel. Our
brains are hard-wired to instantly recognize familiar faces
in a crowd and detect emotions from slight shifts in tone
or facial movements. Our ability to appreciate nuance con-
tributes to our ability for creative expression that machines
simply lack.
Likewise, where machines excel, humans are weak.
We’re terrible at multiplying 10-digit numbers and re-
membering details with precision. Humans also become
bored easily with repetitive tasks. So if our goal is to drive
across Kansas on a flat, straight road
on a sunny day, AI is going to do a
much better job than a human. But
if the task is driving on a snowy day
in Boston, you’re much better off if a
human takes the wheel.
The intelligent enterprise is de-
signed to take advantage of the com-
plementary nature and the symbiosis
of man and machine. From biology,
we know different species of living things have founds ways
of living in harmony with one another. Commensalism is
the term used to describe what happens when one side gets
most or all the benefit in a symbiotic relationship but the
other side doesn’t mind being used. Orchid flowers, for ex-
ample, often attach to trees to access the sunlight they need
to survive. They aren’t parasites since the tree is not harmed
by the flower’s presence but the tree does not derive any
particular benefit.
A better arrangement is known as mutualism, which de-
scribes species that form a partnership allowing both sides
to benefit. In the wild, for example, zebra herds are often
spotted teaming up with ostriches. This peculiar collabora-
tion between bird and mammal starts to make sense if one
evaluates the relative strengths and weaknesses of each. The
ostrich has mediocre senses of hearing and smell, but supe-
rior eyesight. Zebras are the opposite, with terrible vision
and great senses of hearing and smell. By grouping togeth-
er, they draw upon a superior sensory defense that greatly
enhances their joint chances of survival against predators.
Optimizing humans to deal with AI
For man and machine to work in similar harmony, human
employees will have to make the most of their strengths.
That means workers in the intelligent enterprise should
come from a different background, upbringing and edu-
cation to maximize diversity of thought. Each new hire
would be expected to bring new perspectives and insights
to the table to avoid one of the most common pitfalls of
large organizations: groupthink. As we saw, having mul-
tiple perspectives is a key aspect of success when using the
OODA Loop, and drawing upon diversity through hiring
decisions can deliver those unique perspectives.
But it takes more than cognitive diversity to build an ef-
fective team. The workers of the intelligent enterprise would
need to draw from a common foundation of training that’s
rigorous enough to allow the workers to extract maximum
value from AI assistance. This would mean taking individu-
als who could be from opposite extremes on the educational
spectrum – say a liberal arts graduate who studied history in-
stead of math and an electrical engineer – and sending them
through a common set of programs like Certified Analytics
Professional and Project Manage-
ment Professional.
While this is obviously a tougher
path for the historian to take, it en-
sures the unique perspective that this
calling has to offer can be effectively
communicated to other team mem-
bers. It creates a common language
that every other employee can un-
derstand. You keep the benefits of
cognitive diversity without losing the scientific rigor.
Organized in this fashion, humans can work well with
one another and with machines, as the workforce is primed
to bring new perspectives to every situation. The human op-
erators can then make the most of their creativity when us-
ing these tools at every level of the organization. All of these
factors combine to make the intelligent enterprise a unique
entity that’s more than the sum of its parts. By honing the
adaptability and understanding of the relationship between
man and machine, the intelligent enterprise of the future
will drive innovation beyond anything we’ve seen before.
Joseph Byrum is chief data scientist at Principal. He was previously
senior R&D and strategic marketing executive in life sciences-global
product development, innovation and delivery at Syngenta. In that
role, he was chief architect of initiatives that won Syngenta the
2016 ANA Genius Award in Marketing Analytics and 2015
Franz Edelman prize for contributions in operations research and
the management sciences. His bachelor’s degree in crop and soil
science and his master’s degree in genetics are from Michigan State
University. He earned a master’s degree in business administra-
tion from the University of Michigan Stephen M. Ross School of
Business. His Ph.D. in quantitative genetics is from Iowa State
University. He is an IISE member.
The intelligent enterprise is
designed to take advantage
of the complementary nature
and the symbiosis of man
and machine.