Data Driven Decision Making Frequently Fixes Biases
For most industries, making money is a
question of discovering what hasn’t yet been exploited by other
companies. Spotting and exploiting these sorts of inefficiencies allows
firms to gain first-mover advantages.
The folks who run call centers at Xerox Services turned to big data to reassess how they pick job candidates for interviews.
The initial proposed solution based on the data left some managers
downright shocked. In some cases, the system Data Analytics Software was actually sending in
people with no relevant prior experience. It also singled out
individuals who were on four or more social networks to not be sent in.
As the program moved forward, though, attrition rates for new hires
dropped 20%.
How did this happen? Data driven decision
making often moves companies past human biases. Human hiring managers
frequently look for signals that feel relevant but aren’t. The machines
cut out all the noise of human interaction, focusing on results rather
than imputing biases.
The Data Analytics Arms Race
In some industries, building out data
analytics capabilities is well on its way to being an arms race between
companies. The NBA has been revolutionized by analytics, with the league
utilizing technologies derived from missile-tracking Data Analytics Tools systems to keep
tabs on every footstep and dribble made in each game. A league that was
once dominated by the slam dunk rapidly switched to 3-pt shooting, and
the Golden State Warriors are widely considered the first champion built on hard data. Other teams have since been racing to catch up.
On
Wall Street, companies that use programmatic trading and algorithms are
considered dinosaurs stuck in the 1980s. Private equity has long Data Analysis since
moved beyond learning from the past and is now focused on predictive
data analytics. One high-frequency trading firm posted a profit in 1237
out of 1238 trading days. It’s easy to see why “data scientist” is the hottest job trend in finance.
Data Driven Marketing
Some sectors have found the concurrent rise of social media and big data
to be the confluence of events they required to get out in front of the
competition. For large corporations, this has allowed them to target
niches that were often unreachable. If you’ve walked through the grocery
store and read the packages, there’s a good chance you’ve seen data driven marketing
in action. Brands like Betty Crocker and General Mills now frequently
emphasize niche selling points such as “non-GMO” and “gluten-free.”
These selling propositions Data Transformation were designed by sifting through social media data
to find what concerns drove consumer decisions. The brands then
adjusted their marketing to have appeal to both the general public and
niche markets, allowing them to maximize their exposure without making
massive investments in advertising. Instead, they changed a few things
on their packages.
Cutting Costs
The
difference between a profitable year and a bad one often boils down to
nothing more than costs. Nearly 50% of Fortune 1000 firms say they’ve started data driven initiatives to cut expenses and seen a return on the investment.
In the fashion world, using big data
to track trends has become a key part of the purchasing process. No one
wants to be sitting on inventory because Real-time analytics they made the wrong buy or
bought at the wrong moment. Timing this out can be challenging, too, as
most retailers depend on global supply chains to bring purchased
inventory from overseas to target markets. By monitoring social media
trends, for example, a fashion retailer can send real-time data
to a buyer in Bangladesh informing them of what styles are trending and
how strongly. That can be distilled to data that enables a buyer on the
other side of the planet to determine everything from purchasing volume to shipping method.
Becoming a Data Driven Operation
It’s
not enough to want your company become a data driven organization. You
need to lay out a plan that gets you there. This includes:
- Fostering a culture that values data
- Putting standards in place
- Hiring professionals with big data skills
- Educating stakeholders about the advantage of driving decisions with data
- Building out the necessary infrastructure, particularly computer servers
- Adjusting hiring practices to incorporate big data skills
- Opening up the discussion to all parties from top to bottom.
The move to a data-centric worldview
also means getting tough about things. Companies often end up using
severance packages to ship out folks who refuse to get on board with the
changes. This requires a hard look at why certain people are employed
and whether they can adjust to the new reality.
Ultimately,
a data driven approach is about Real-time analysis competitiveness. Other companies are
already doing it and succeeding. The sooner your operation becomes one
that values data, the sooner it can attract the right candidates for
jobs and become more competitive.

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