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The Fascinating Ways
Artificial Intelligence
And Machine Learning
PepsiCo Uses
To Deliver Success
© 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
Title
Text
IntroductionIntroduction
One business who realized that using artificial intelligence (AI) and machine
learning is a business need, no longer a competitive advantage is PepsiCo. The
food-and-beverage company behind brands such as Pepsi, Gatorade, Tropicana,
Lipton, Frito-Lay, and Quaker sells products in more than 200 countries and
brought in $64.7 billion in annual revenue last year. From robots to machine
learning, PepsiCo uses AI and machine learning throughout the organization in
many ways.
The Fascinating Ways PepsiCo Uses
Artificial Intelligence And Machine Learning
To Deliver Success
© 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
Snack Delivery Robot
There’s a six-wheeled mobile vending machine robot tooling around the University
of the Pacific chockful of PepsiCo snacks and beverages from Hello Goodness—a
healthier line-up that includes SunChips, Baked Lay’s and bubly sparkling water.
Named Snackbot, these self-driving robots are a partnership between Robby
Technologies and PepsiCo. Students can order their snacks from the Snackbot app,
and then the robot will deliver it to more than 50 spots across the campus without
charging a delivery fee. The bots have a range of 20 miles on a single battery
charge, and they can even navigate at night, in rain or up curbs thanks to onboard
headlights and all-wheel drive capabilities.
Snackbot represents the solution to the needs of strapped-for-time college
students and their preferences identified through PepsiCo’s research. There are
three to five Snackbots on campus to keep up with demand.
© 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
Manufacturing with Machine Learning
The Frito-Lay (a subsidiary of PepsiCo) manufacturing plant is benefiting from
machine learning. One project uses lasers to hit chips and then listen to the sounds
coming off the chip to determine texture. Algorithms process the sound and
determine the chip texture to automate the quality check for Frito-Lay’s chip
processing systems.
From this beginning, Shameer Mirza, senior research and development engineer at
PepsiCo, realized several more applications of machine learning could impact
process control within the factory. Next, Mirza developed a machine learning model
that could be used with a vision system to be able to predict the weight of potatoes
being processed. This led to considerable savings for the company because it no
longer had to spend $300,000 per line (they had 35 in the U.S. alone) for weighing
elements. Mirza's systems used only a camera and the machine learning model and
are essentially just additional data points collected with no additional cost.
© 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
Manufacturing with Machine Learning
Another project still in development would assess the "percent peel" of a potato
after it had gone through the peeling process. By understanding this data, it can
help the Frito-Lay team to optimize the potato peeling system. This project alone is
estimated to save the company more than $1 million a year just in the United
States.
PepsiCo is launching a global training course on advanced machine learning and
computer vision for its internal research and development associates this year to
broaden its team's abilities to use these technologies to continue finding insights
that will drive efficiencies in its manufacturing facilities.
© 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
Vera Streamlines the Hiring Process
PepsiCo used Robot Vera for the first time to phone and interview candidates for
open positions in sales, as drivers and to fill factory vacancies in Russia when HR
professionals needed to fill 250 jobs in two months. Vera was developed by Russian
startup Stafory and is capable of interviewing 1,500 candidates in nine hours, a job
that would take humans nine weeks.
Advanced speech recognition software and tools from Amazon, Google, Microsoft
and Russian technology company Yandex allow Vera to make calls and screen
candidates for open positions such as fork-lift operators, factory workers, and sales
staff. Its software can scan CVs to determine if a potential candidate has the right
experience for the position, can respond to yes and no answers, ask follow-up
questions and send out follow-up correspondence.
© 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
Vera Streamlines the Hiring Process
It can also forward transcripts of a call to a human HR specialist for further review.
So far, the reception from the majority of candidates when dealing with the robot
has been positive. There was a bit more hesitation from human HR professionals. It
turns out one of the biggest hurdles is "reprogramming humans" to feel
comfortable with the technology.
© 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
PepsiCo’s In-House Technology Platform Ada
Ada provides “augmented intelligence” that relies on human’s insight in
combination with algorithms. The company expects this philosophy will lead to
rapid learning. Ada can pull together data from a variety of sources to allow
PepsiCo to better leverage the massive amounts of data it collects. Ultimately, Ada
will be involved in all aspects of operations including innovation, design, research
and price decisions.
Other areas that PepsiCo will put data to use is in product development and sales
and marketing. The company has used social prediction tools that aggregate
publicly available consumer conversations in combination with its own data to
identify new products to bring to market. This represents a transition for the
company to create insights from the data it has and focus it on actionable activities.
As more and more data get layered, PepsiCo is able to identify trends and
marketing placements.
© 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
Pep Worx: Big Data and Analytics Platform
The cloud-based data and analytics platform PepsiCo uses called Pep Worx helps
the company advise retail stores on the best items to stock, where to place them
and what promotions to use. When the company wanted to launch Quaker
Overnight Oats, it was able to identify 24 million households from a dataset of 110
million US households that it felt would be appropriate to market the product to.
Then, PepsiCo identified the shopping venues that these households would be
more apt to use and created promotions to appeal to that audience. This use of
data and focusing on a very specific market helped drive 80 percent of the
product’s sales growth in the first 12 months after launch.
© 2017 Bernard Marr , Bernard Marr & Co. All rights reserved
© 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a
strategic business & technology advisor to governments and companies. He helps
organisations improve their business performance, use data more intelligently, and
understand the implications of new technologies such as artificial intelligence, big data,
blockchains, and the Internet of Things.
LinkedIn has ranked Bernard as one of the world’s top 5 business influencers. He is a frequent
contributor to the World Economic Forum and writes a regular column for Forbes. Every day
Bernard actively engages his 1.5 million social media followers and shares content that
reaches millions of readers.
Visit The
Website
© 2017 Bernard Marr , Bernard Marr & Co. All rights reserved
© 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a
strategic business & technology advisor to governments and companies. He helps
organisations improve their business performance, use data more intelligently, and
understand the implications of new technologies such as artificial intelligence, big data,
blockchains, and the Internet of Things.
LinkedIn has ranked Bernard as one of the world’s top 5 business influencers. He is a frequent
contributor to the World Economic Forum and writes a regular column for Forbes. Every day
Bernard actively engages his 1.5 million social media followers and shares content that
reaches millions of readers.
Visit The
Website
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© 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
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The Fascinating Ways PepsiCo Uses Artificial Intelligence And Machine Learning To Deliver Success

  • 1. The Fascinating Ways Artificial Intelligence And Machine Learning PepsiCo Uses To Deliver Success
  • 2. © 2018 Bernard Marr, Bernard Marr & Co. All rights reserved Title Text IntroductionIntroduction One business who realized that using artificial intelligence (AI) and machine learning is a business need, no longer a competitive advantage is PepsiCo. The food-and-beverage company behind brands such as Pepsi, Gatorade, Tropicana, Lipton, Frito-Lay, and Quaker sells products in more than 200 countries and brought in $64.7 billion in annual revenue last year. From robots to machine learning, PepsiCo uses AI and machine learning throughout the organization in many ways. The Fascinating Ways PepsiCo Uses Artificial Intelligence And Machine Learning To Deliver Success
  • 3. © 2018 Bernard Marr, Bernard Marr & Co. All rights reserved Snack Delivery Robot There’s a six-wheeled mobile vending machine robot tooling around the University of the Pacific chockful of PepsiCo snacks and beverages from Hello Goodness—a healthier line-up that includes SunChips, Baked Lay’s and bubly sparkling water. Named Snackbot, these self-driving robots are a partnership between Robby Technologies and PepsiCo. Students can order their snacks from the Snackbot app, and then the robot will deliver it to more than 50 spots across the campus without charging a delivery fee. The bots have a range of 20 miles on a single battery charge, and they can even navigate at night, in rain or up curbs thanks to onboard headlights and all-wheel drive capabilities. Snackbot represents the solution to the needs of strapped-for-time college students and their preferences identified through PepsiCo’s research. There are three to five Snackbots on campus to keep up with demand.
  • 4. © 2018 Bernard Marr, Bernard Marr & Co. All rights reserved Manufacturing with Machine Learning The Frito-Lay (a subsidiary of PepsiCo) manufacturing plant is benefiting from machine learning. One project uses lasers to hit chips and then listen to the sounds coming off the chip to determine texture. Algorithms process the sound and determine the chip texture to automate the quality check for Frito-Lay’s chip processing systems. From this beginning, Shameer Mirza, senior research and development engineer at PepsiCo, realized several more applications of machine learning could impact process control within the factory. Next, Mirza developed a machine learning model that could be used with a vision system to be able to predict the weight of potatoes being processed. This led to considerable savings for the company because it no longer had to spend $300,000 per line (they had 35 in the U.S. alone) for weighing elements. Mirza's systems used only a camera and the machine learning model and are essentially just additional data points collected with no additional cost.
  • 5. © 2018 Bernard Marr, Bernard Marr & Co. All rights reserved Manufacturing with Machine Learning Another project still in development would assess the "percent peel" of a potato after it had gone through the peeling process. By understanding this data, it can help the Frito-Lay team to optimize the potato peeling system. This project alone is estimated to save the company more than $1 million a year just in the United States. PepsiCo is launching a global training course on advanced machine learning and computer vision for its internal research and development associates this year to broaden its team's abilities to use these technologies to continue finding insights that will drive efficiencies in its manufacturing facilities.
  • 6. © 2018 Bernard Marr, Bernard Marr & Co. All rights reserved Vera Streamlines the Hiring Process PepsiCo used Robot Vera for the first time to phone and interview candidates for open positions in sales, as drivers and to fill factory vacancies in Russia when HR professionals needed to fill 250 jobs in two months. Vera was developed by Russian startup Stafory and is capable of interviewing 1,500 candidates in nine hours, a job that would take humans nine weeks. Advanced speech recognition software and tools from Amazon, Google, Microsoft and Russian technology company Yandex allow Vera to make calls and screen candidates for open positions such as fork-lift operators, factory workers, and sales staff. Its software can scan CVs to determine if a potential candidate has the right experience for the position, can respond to yes and no answers, ask follow-up questions and send out follow-up correspondence.
  • 7. © 2018 Bernard Marr, Bernard Marr & Co. All rights reserved Vera Streamlines the Hiring Process It can also forward transcripts of a call to a human HR specialist for further review. So far, the reception from the majority of candidates when dealing with the robot has been positive. There was a bit more hesitation from human HR professionals. It turns out one of the biggest hurdles is "reprogramming humans" to feel comfortable with the technology.
  • 8. © 2018 Bernard Marr, Bernard Marr & Co. All rights reserved PepsiCo’s In-House Technology Platform Ada Ada provides “augmented intelligence” that relies on human’s insight in combination with algorithms. The company expects this philosophy will lead to rapid learning. Ada can pull together data from a variety of sources to allow PepsiCo to better leverage the massive amounts of data it collects. Ultimately, Ada will be involved in all aspects of operations including innovation, design, research and price decisions. Other areas that PepsiCo will put data to use is in product development and sales and marketing. The company has used social prediction tools that aggregate publicly available consumer conversations in combination with its own data to identify new products to bring to market. This represents a transition for the company to create insights from the data it has and focus it on actionable activities. As more and more data get layered, PepsiCo is able to identify trends and marketing placements.
  • 9. © 2018 Bernard Marr, Bernard Marr & Co. All rights reserved Pep Worx: Big Data and Analytics Platform The cloud-based data and analytics platform PepsiCo uses called Pep Worx helps the company advise retail stores on the best items to stock, where to place them and what promotions to use. When the company wanted to launch Quaker Overnight Oats, it was able to identify 24 million households from a dataset of 110 million US households that it felt would be appropriate to market the product to. Then, PepsiCo identified the shopping venues that these households would be more apt to use and created promotions to appeal to that audience. This use of data and focusing on a very specific market helped drive 80 percent of the product’s sales growth in the first 12 months after launch.
  • 10. © 2017 Bernard Marr , Bernard Marr & Co. All rights reserved © 2018 Bernard Marr, Bernard Marr & Co. All rights reserved Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a strategic business & technology advisor to governments and companies. He helps organisations improve their business performance, use data more intelligently, and understand the implications of new technologies such as artificial intelligence, big data, blockchains, and the Internet of Things. LinkedIn has ranked Bernard as one of the world’s top 5 business influencers. He is a frequent contributor to the World Economic Forum and writes a regular column for Forbes. Every day Bernard actively engages his 1.5 million social media followers and shares content that reaches millions of readers. Visit The Website © 2017 Bernard Marr , Bernard Marr & Co. All rights reserved © 2018 Bernard Marr, Bernard Marr & Co. All rights reserved Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a strategic business & technology advisor to governments and companies. He helps organisations improve their business performance, use data more intelligently, and understand the implications of new technologies such as artificial intelligence, big data, blockchains, and the Internet of Things. LinkedIn has ranked Bernard as one of the world’s top 5 business influencers. He is a frequent contributor to the World Economic Forum and writes a regular column for Forbes. Every day Bernard actively engages his 1.5 million social media followers and shares content that reaches millions of readers. Visit The Website
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