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Optimizing business with
new efficiencies
Machine learning can be used to create greater
efficiency through sophisticated demand planning
and forecasting models. While this is true in almost
every industry, retail provides some specific evidence.
AI-based forecasting is reducing lost sales due to
product unavailability by up to 65 percent and
resulting in two million fewer product returns per
year.⁴ Using an AWS-based predictive ordering
solution, Domino's Pizza Enterprises Limited is
delivering on an initiative to have pizza ready for
pickup within three minutes of ordering or safely
delivered within 10.
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Smarter, faster decision-making
Informed by data and analytics sources that grow
smarter through machine learning, businesses
and their workforces can make more informed,
faster decisions that allow them to act on
opportunities sooner and get better results.
T-Mobile customer service agents use AI to
quickly access the information most salient
to customer needs. By providing agents with
contextual information in real time, T-Mobile
helps guarantee that each customer's issues are
quickly and accurately resolved.
Why machine learning?
Before digging into the steps of the machine learning journey, let's explore why businesses should go on that
journey in the first place. After all, even with the guidance in this eBook, completing the steps outlined here will
require continued investment and unwavering dedication. Businesses will need to regularly remind themselves what
they're fighting for—keeping their eyes on the precise business benefits that can be unlocked by fully leveraging
machine learning technology.
Businesses already realize the impact of:
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intelligence%20can%20deliver%20real%20value%20to%20companies/mgi-artificial-intelligence-discussion-paper.ashx
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