Consumer Goods Technology - October 2018 - 7

Tech Trends
InsightsIndustry Insights

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AI is Ready for Prime Time in Consumer Goods

Q

Artificial intelligence has been identified
as "critical" to future success. What are the
primary benefits it's bringing to consumer goods
manufacturers?

REILLY: It's all about shifting time from "causation" to
"ideation." Virtually every leader we talk with in the
Senior Vice
consumer goods world struggles with this. They have
President, Sales
barely enough time to determine what happened in the
and Marketing
last reporting period and not enough time to figure out
AnswerRocket
what to do about it. They need to get creative with retail
partners, brand strategies, media mix - the list goes on. It takes much too
long to understand the changing landscape, which hamstrings efforts to
do what humans do really well: get creative and drive actions to deliver
growth. Fortunately, our industry benefits from the trifecta of AI skills: huge
volumes of data that change over time, with many unknown underlying
factors and complex effects of every decision.

Pete Reilly

" An AI insights feed should relieve a brand
manager from ever having to browse
data directly."

Q

Much of the early testing and implementation of AI tools has
taken place in the marketing function. What have companies
learned so far?
REILLY: Companies that implemented AI early on started with simple scenarios
and automated away the most repetitive tasks, working up toward higher and
higher value functions. The type of deep learning that works really well right
now is what [AI guru] Andrew Ng calls "supervised learning." Think of this as
being like how you learned in school. You get some examples and answers,
and you can then extrapolate from the examples you learned. From enough
example inputs and outputs, neural nets can start to learn what will happen,
given a set of inputs.

Q

In our Tech Trends survey, insights/analytics was identified
as a priority area for implementation. What should be the key
objectives here?
REILLY: To focus on the desired business result, which is often bottom-line
growth. Like a newspaper that signals items worthy of attention, an insights
"feed" should relieve a brand manager from ever having to browse data directly.
Reams of KPI reports don't have to be reviewed when AI is already scouring
all of that information in real time for the important events that need attention.

Machines can voraciously take in the volume of data produced by CG businesses
and point out important events that a business expert should review. Over time, the
machine learns to point out an insight and
what action to recommend for it.

Q

Where else in the enterprise
should companies be placing
an emphasis right now?
REILLY: I'd emphasize the parts of the business that drive revenue: sales, category
management, brand management, etc.
Modeling all of the moving parts of a CG
business involves vast amounts of data
and computing power at a scale that is only
now coming into focus. Today's market
mix models will give way to demand simulators tracking and responding in real time.

Q

Despite the recognition of AI's
potential, a lot of companies
have been slow at implementation.
How do companies move beyond the
current obstacles?
REILLY: Another thing Ng talks about is the
idea that "anything a human can do in one
second, a machine can either do now, or
will soon be able to do." He suggests looking for things that humans can do in one
second as potential targets for automation.
One example he gives is the task of evaluating a security video. A human can evaluate the current scene in security footage in
one second. How many people, where are
they headed? Are they carrying anything?
Analyzing the health of a brand is similar in
many ways: Is share increasing or decreasing? Penetrations? Value? Volume? Which
brand has the highest increase in share?
Companies should look for these opportunities and start experimenting.

AnswerRocket supports some of the largest global brands with AI-powered
analytics. The platform is designed for business leaders seeking immediate
insights to fuel bottom-line growth.



Consumer Goods Technology - October 2018

Table of Contents for the Digital Edition of Consumer Goods Technology - October 2018

Contents
Consumer Goods Technology - October 2018 - Cover1
Consumer Goods Technology - October 2018 - Contents
Consumer Goods Technology - October 2018 - 3
Consumer Goods Technology - October 2018 - 4
Consumer Goods Technology - October 2018 - 5
Consumer Goods Technology - October 2018 - 6
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Consumer Goods Technology - October 2018 - Cover4
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