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Why 60 Percent of Machine Learning
Projects Are Never Implemented
We’re all familiar with the concept to be considered from the very 2.Lead from the top down. As an
of the Industrial Revolution, but beginning. If you don’t think about executive, you must understand
change has never stopped. We’re how to operationalize machine- that change comes from the top.
now well into the Fourth Industrial intelligence at the start of a project, Without active leadership on
Revolution and it’s transforming you won’t be able to transform your part, it’s highly unlikely that
the way businesses function and your business or realize ROI. As projects will move in the most
grow. an executive and a leader, a big productive direction. You need
part of your role is managing the to be responsible for aligning
Indeed, companies that fail to change that must, by necessity, the entire organization with
transform into data- and model- take place if your organization is to your vision and guiding projects
driven organizations are doomed embrace data science applications. toward operationalization and
to failure. This is especially true Change management is the vital the realization of ROI. It’s all
of incumbents that risk being left step in operationalizing data- about your people, the culture
in the dust by disruptive upstarts, science projects and transforming you cultivate, and the processes
companies comfortable with a your organization into a data- and that will help your organization to
data- and model-driven approach model-driven enterprise. best respond quickly to this game-
from their inception. changing technology.
Four Ways to Solve Change
As a brief primer, the First Management Problems 3.Allow enough time to adopt
Industrial Revolution was about changes. Adopting new initiatives
steam and railroads, the Second Change management can be takes time. Many organizations
about electricity, and the Third daunting. Fortunately, the issues fail to allow enough time to
brought about by the Internet. The I see are consistent, as are the undertake such major changes
Fourth Industrial Revolution is solutions. In this section, I’ll successfully. To implement a
based on artificial intelligence (AI). give you a brief summary of the data science project effectively,
The transformation it brings will most common steps organizations the typical enterprise must start
be bigger than that any previous need to take to solve their change working with their IT team and
revolution has brought about. management problems:
There are three fundamental pillars 1.Business and
of AI adoption: data, technology, technical teams must
and people/ culture/ process. In work together. These
my experience working with many areas of a company
of the largest organizations in the are usually home to
world, I see a consistent pattern: very different types of
they are willing to invest in cutting people, with different
edge projects with the power to talents, priorities,
revolutionize their organization, and background.
but they struggle to operationalize For successfully
these projects. Approximately 40 implementing and
percent reach implementation, operationalizing data
while 60 percent stall or flame out. science, leaders need
to build and nurture an
Why is this? It’s because environment where these
business leaders do not pay two distinct types of
attention to crucial change- people can work together
management processes that need seamlessly.
22 December 2019
