How Artificial Intelligence is Applied to Drive Trade Effectiveness

UNLEASH YOUR EXCELLENCE © VISUALFABRIQ 2018
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L E T ’ S G E T S T A R T E D
Applied AI to Drive
Trade Effectiveness

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Introduction
APPLIED AI TO DRIVE TRADE EFFECTIVENESS
Carst co-founded visualfabriq in 2013
together with Jaco, after 15 years of working
in consultancy for CPG organizations. He
designed and rolled out many Revenue
Management and Predictive Analytics
solutions for companies such as Unilever,
Heineken, Tiger Brands, Canon,
FrieslandCampina and Heinz.
Carst is also a mentor at Europe’s first AI
startup accelerator, the Rockstart AI
Programme
Carst Vaartjes
Co-Founder &
Chief Product Strategy
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As consumers we are all already daily users of AI, telling us…
When to Act
How to Act
The Likely Result
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So, why is your business
not using AI yet for Trade
Promotion Planning?
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By 2030 your
work will have
been radically
transformed by AI
With many CPG
functions affected
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It’s 2018.
Most capabilities
are already
here.
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But the CPG industry is still way behind in adoption of AI
And perhaps lacks some imagination
Source:
McKinsey Global Institute AI adoption and use survey; McKinsey Global Institute analysis
(1) Based on the midpoint of the range selected by the survey respondent. (2) Results are weighted by firm
size
32302826242220181614121086420
0
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3
4
5
6
7
8
13
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10
11
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FutureAIdemandtrajectory1
Averageestimated%changeinAIspending,
next3years,weightedbyfirmssize2
Current AI adoption
Percent of firms adopting one or more AI technology at scale or in a core part of their business, weighted by firm size2
FALLING BEHIND
LEADING SECTORS
Travel and Tourism
Professional Service
Education
Construction
Consumer Package Goods
Retail Energy and Resources
Financial Service
Health Care
Media and Entertainment
Automotive
and Assembly
High-tech and Telecommunications
Transportation and Logistics
Fig. 30. High-tech and Financial Service Firms Lead Demand for AI
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The conversation is stuck on efficiency
656K USD
364K USD
Revenue per Employee
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Feeling threatened by AI while simultaneously thinking it’s far off
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Avoid the “unique product means unique processes” trap
Unique
Products
Standard
Processes
Standard
Data
fit perfectly with
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We believe that anyone working in CPG Sales or
Operations will soon have AI Assistants augmenting their
day to day work and performing, routine operational tasks
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You can translate that ambition into tangible goals for 2018
Embedded in an automated, total IBP at commercial level of detail
80% promotions automated
90% baselines automated
So that, users can focus on what really matters
Prescriptive AIPre Event
OptimizationPost Event Optimization
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Full financial forecast in a single day
80-90%+ automated for promotions
and baselines
Both Shopper and Ex-Factory views
Applying AI to your
TPx and Revenue
Planning can give
you the following:
And put more ambition in your commercial processes
Significantly more reliable
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This means mastering all key Demand Sensing area issues with
Shopper and Ex-factory Demand, Revenue Planning & TPx
Demand Forecast Promotion
Financial Forecast
• Inventory Management
• MRP
• Purchasing Scheduling
• Production Scheduling
• Order Allocation
• Logistics Execution
baseline
incrementals
&
promoted
open orders
signaling
sell in
data
sell out
data
demand promotional
spend
Demand
Sensing
Supply
Sensing
All are on detailed
commercial account /
product level
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First arrange that basic data is in place (where available)
Data Platform
Predictive Analytics
Authorization & Security
Insights
Product Master Data
(SAP Native; excel; flat files)
Customer Master Data
Display BOM
Budgets/LEs
(excel; flat files)
Ex-Factory/Sell-In
(excel; flat files)
Pricing Data
Demand Forecast
(excel; flat files)
Nielsen
(CreCha; FFS)
IRI
(Tape II)
(e)POS
(flat files)
Campaign Data
(excel; flat files)
Consumer Data
(excel; flat files)
Folder Data
(excel; flat files)
GfK
(flat files)
Brand Rating
(excel; flat files)
Pricing Scans
(excel; flat files)
Weather
(excel; flat files)
Internal Data External Data
NB: A lack of external data does not make AI impossible, only less accurate
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It’s not a single prediction and not a single model
S&OP
Baseline
Lift & In
Market
Cannibalization
Phasing
& Dip
Forward Buy
& Ex-Factory
Brand &
Chain
Switching
Distribution,
Events &
Weather
Pricing
Elasticity
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You need a standardized approach
Having standardized data sets and standardized JupyterLab notebook templates
Investigate
Data
Feature
Selection
Compare
Performance
Filter Data
Create
Model(s) Apply
1
2
3
4
5
6
The visualfabriq 6 steps proven and structured AI approach
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An approach that can be used by any data scientist
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It will not work without the data & AI embedded in the system
And with continuous attention to data quality and models
Plan Negotiate Execute Evaluate
Predictive Analytics
Insights
Authorization & Security
Visualfabriq end-to-end TPM – TPO – TPE process
Internal Data Product Life Cycle External Data
MODELS DATA
PREDICTIVE MODELING
A predictive
model directly
applied in your
business
04
Use leading AI
models03
No manual data
preparation
No manual
cleansing
Save 90% of the
work
02
Integrate any
data source
Any volume
of data
01
BENEFITS
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Help users to use AI in their processes
ZERO BELIEF BLIND BELIEF
Trust the Machine?
Tailor Made &
Rare Products & Promotions
There is a clear necessity to guide users on likely prediction reliability
When is the user planning one of the 10% manual promotions?
The Reliable Majority
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The key is being able to plan automatically from the bottom up
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Handling both In-Market and EF predictions on SKU level
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This also includes predicting the demand impact of pricing and weighted distribution

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And move to AI based promotion planning
Negotiate with
the Retailer
Pick the best Volume,
Revenue, Margin or
Penetration Strategy
Select the Product Mix
Select the Period
Select the Customer
Enter Zero Touch Planning
for Promotions
The system looks at different scenarios for you and
suggest the best options
It will tell you how reliable the prediction will be
All operational steps are fully automated and guided
by AI, leaving only the negotiation and approval
cycles for the users
THIS IS ALL AVAILABLE NOW IN
2018
Always up-to-date, person-independent and reliable
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Zero Touch Planning
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Using new, AI powered ways of working
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User interactions will be more
and more voice based
Users will be able plan and review predicted
results directly together with clients

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Models can be compared to human estimations and other models
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An example of in-market promotion effect estimations
Human Planning AI Planning

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AI models are consistently twice as accurate as human
estimations*
Lift
Demand Baseline
Phasing
FWB
Week Level Promotion Product Level
In-MarketEx-Factory
30% -> 10-15% 50% -> 20-30%
20% -> 10-15%20% -> 10-15%
*All figures are expressed in forecast error; human and prediction accuracies are based on averages of various
categories and clients in over 10 markets
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Realize that AI is not a goal but a journey
All data available as
insights for users
and as input for
modeling
AI models leading to
reliable and
accurate predictions
Creating
consistency
regardless of
individuals
And the ability to
optimize any choice
in the process
But one that will deliver results along every step of the way
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Disclaimer
The information contained in this presentation is intended solely for personal reference. Such information is subject to change without notice,
and although we made all reasonable efforts to ensure the correctness of this presentation, its accuracy is not guaranteed and it may not
contain all material information concerning Visualfabriq (the “Company”). The Company makes no representation regarding, and assumes
no responsibility or liability for, the accuracy or completeness of, or any errors or omissions in, any information contained herein.
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