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Selling High with Intelligent Planning
Dipu Mukherjee Go-To-Market Director of Innovation & Analytics Frito-Lay North America - A Division of PepsiCo dipu.mukherjee@pepsico.com
Rahul Bhattacharya Principal – Accenture Analytics Accenture rahul.r.bhattacharya@accenture.com
2
Global Beverages
Global Snacks
Global Nutrition
Brands
22 billion-dollar
brands
Performance
More than $65 billion
revenue
Scale
>200 countries
& territories
People
~280,000 employees
PepsiCo is a global food and beverage powerhouse.
Our broad range of more than 3,000 delicious products offers consumers
convenient, nutritious and affordable options in nearly every country around the world.
Who is PepsiCo?
3
Agenda
Context & Burning Issue
Objective & Scope
Key Project Elements , Deliverables
Modeling, Key Insights
Enhancing Account Management
Interactive Dashboards
Final Thoughts
4
Simplify Business Processes
Customer
FRONTLINE MOBILITY
TPM
PLAYBOOK
KAM DESTINATION
ZONE DESTINATION
DSL DESTINATION
FRONTLINE DESTINATION
Enable with Technology
Close the Loop to Integrate All Sales Roles
Integrated Execution Closes the Loop Among All Sales Roles and
Enables Media-to-Shelf Granular Execution to Maximize Growth
Three Key Programs:
Analytics & Insights Infinity Program Destination Programs ∙ ∙
Integrated Execution
5
GTM Analytics Continuum
Descriptive Analytics
Diagnostic
Analytics
Predictive Analytics
Quick Wins
VALUE
• Identify trends • Visualizations
by role
• Value Drivers • Customer DNA
• Correlation • Segmentation
Analysis
• Business rules • Regression
Analysis
TIME
What will
happen?
Why it
happened?
What
happened? Enhance Current
Reporting
1 Visualization Actions/Insights 2 Trends & Correlations 3
HQ HQ, Frontline Managers Account Teams
Role Based Analytics To Achieve Execution Excellence
6
• Key Account Managers spend only 4 hrs/week selling
• Support structure, account management process is inefficient
• Manual, time-intensive static customer sell deck preparation process
• TPO engine provides optimized plan at a customer level
Future State
• Double the selling time spent by Key Account Managers
• Enable analytics driven mobile account management capability
• Dynamic interactive selling tool to aid negotiations with buyer
• Real-time tactical & granular updates to plan
Current State
Solving The Burning Issue
7
Objective
Demonstrate the power of predictive analytics methods to enhance planning and selling capabilities for account teams
Leverage rich customer specific POS data to develop models with high degree of prediction accuracy
Bring capabilities to life through interactive dashboards that empower account teams to execute with enhanced certainty
Generate insights driven promotion planning and evaluate its impact to the account and the customer
8
Scope
109 Stores One
Division
Store Clusters • Premium • Mainstream • Value
Customer
• Salty Snacks Category • 29 Frito-Lay Product Promotion Groups • 52 Competitor Product Promotion Groups
Category
• POS at UPC, Store, Weekly • 121 weeks of data starting wk 17 2012 • Frito-Lay Promotion Calendar (APEX) • List Price, Promoted Cost, COGS, Inventory , Promoted Price
(Finance Team)
Data
Leverage rich POS
and Frito-Lay
financial data to
make targeted trade
promotion decisions
to achieve improved
ROI, growth and
retailer profitability
9
Key Project Elements
Data
Integration
Predictive
Modeling
Planning / Selling
Capability Build
Capability
Enablement
POS data for Salty Snack category
Trade promotion information
Pricing, Cost
Statistical models to predict trade promotion effectiveness
“What-if” simulation of promotional events
Projected performance metrics for Frito-Lay and customer
Interactive planning, selling & metrics dashboards
10
Key Project Deliverables
2. Analytics 1. Diagnostics
4. Dashboards 3. Simulations
• Sales & Share - Growth and Trends • Base Price Derivation, Discounts • Promotions on Ad, Display, Tactic,
Duration
• Promotion Coefficients, Volume Decomposition
• Projected Volume, Units, Sales • Events, Seasonality, Cannibalization
Effects • Promotion Effectiveness, ROI Assessment
• Model outputs used for simulating thousands of scenarios across PPGs, time, promo tactics, price points.
• Simulations used for evaluating the volumetric and financial impact – Lift, Share Gain, ROI
• Planning Dashboards for Scenario Planning
• Frito-Lay Detailed Metrics Dashboard for Deep Dive into KPIs
• Selling Dashboard for Metrics of Interest to Customer
11
Modeling Ilustration
Employed Advanced Multi-Level Bayesian Model Included Effects of Seasonality, Cannibalization, Competitive Activity Utilized Multiple Causal Variables like Feature, Display, Discounts for
Baseline and Incremental Computations
(Illustrative for PPG X)
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Sale
s V
olu
me
(‘1
00
s)
Display Flyer Discount Seasonality dollar_off Sales Volume Predicted Volume
Model Development & Key Parameters Model Accuracy : 91%
Post March Madness
Pre Easter
Pre Independence Day
Independence day
(Illustrative for PPG X)
Actual data for single metropolitan division of a multi-banner supermarket channel (# of weeks = 32)
12
Key Insights: Trade Promotion Volume Driver Performance
Top 6 PPGs account for 79% of the trade promotion spend . PPG 1 accounts for 37% of the total Trade Promotion spend.
Among the 6 PPGs having maximum share of Trade Promotion spend, PPG 3 has the lowest CID at 0.40.
PPG 1 has the highest CID out of 29 PPGs.
PPG Order – Total Unit Sales High Low
Hig
h
Low
P
PG
Ord
er
– To
tal U
nit
Sal
es
Total Sales vs. Incremental Sales
Median Value (50th Percentile): 44
High Incremental Units (‘000s)
Low
PPG Order – Total Promotion Investment High Low
Hig
h
Low
P
PG
Ord
er
– To
tal P
rom
oti
on
In
vest
me
nt
Promo Investment vs. CID
High CID
Low
Median Value (50th Percentile): 0.40
PPG 1 1,100
PPG 2 690
PPG 3 550
PPG 4 512
PPG 5 180
PPG 6 110
PPG 7 320
PPG 8 205
PPG 9 95
PPG 10 50
PPG 11 130
PPG 12 30
PPG 13 2
PPG 14 70
PPG 15 110
PPG 16 1
PPG 17 30
PPG 18 35
PPG 19 30
PPG 20 45
PPG 21 20
PPG 22 40
PPG 23 3
PPG 24 5
PPG 25 4
PPG 26 3
PPG 27 1
PPG 28 1
PPG 29 1
PPG 1 0.60
PPG 2 0.45
PPG 4 0.42
PPG 3 0.39
PPG 7 0.40
PPG 5 0.50
PPG 8 0.30
PPG 10 0.40
PPG 6 0.28
PPG 9 0.39
PPG 11 0.24
PPG 22 0.53
PPG 14 0.40
PPG 21 0.54
PPG 15 0.29
PPG 18 0.40
PPG 20 0.25
PPG 17 0.26
PPG 12 0.22
PPG 24 0.50
PPG 19 0.15
PPG 23 0.50
PPG 25 0.22
PPG 26 0.15
PPG 27 0.10
PPG 29 0.04
PPG 28 0.03
PPG 13 PPG 16
13
Key Insights: Trade Promotion Profitability Performance
Of the top 6 PPGs, PPG 2, PPG 3 & PPG 4 had maximum Incremental Margin from trade.
PPG 1 wipes out almost 18% of the incremental margin earned from promotions of the remaining top 5 PPGs incremental margin.
Among the top 6 PPGs with heavy trade spend PPG 4 provides maximum ROI with PPG 1 at the bottom with negative ROI.
PPG 11 (1.24) PPG 7 (0.85) have the highest ROI among the top 12 PPGs.
High Low
Median Value (50th Percentile): 0.41
ROI
PPG Order – Total Promotion Investment High Low
Hig
h
Low
P
PG
Ord
er
– To
tal P
rom
oti
on
In
vest
me
nt
PPG Order – Total Unit Sales High Low
Hig
h
Low
P
PG
Ord
er
– To
tal U
nit
Sal
es
Median Value (50th Percentile): $18
High Incremental Margin (‘000s) Low
Total Sales vs. Incremental Margin Promo Investment vs. ROI
PPG 1 (-$170)
PPG 2 $328
PPG 3 $234
PPG 4 $250
PPG 5 $23
PPG 6 $103
PPG 7 $166
PPG 8 $35
PPG 9 $25
PPG 10 $39
PPG 11 $105
PPG 12 $20
PPG 13 $1
PPG 14 $30
PPG 15 $15
PPG 16 $5
PPG 17 $15
PPG 18 (-$12)
PPG 19 $26
PPG 20 $24
PPG 21 (-$1)
PPG 22 (-$5)
PPG 23 (-$0.23)
PPG 24 (-$0.45)
PPG 25 $2
PPG 26 $2
PPG 27 $0.95
PPG 28 (-$0.40)
PPG 29 $0.30
PPG 1 (-0.05)
PPG 2 0.32
PPG 4 0.42
PPG 3 0.40
PPG 7 0.38
XPPG 5 0.06
PPG 8 0.19
PPG 10 0.28
PPG 6 0.84
PPG 9 0.28
PPG 11 1.23
PPG 22 (-0.11)
PPG 14 0.46
PPG 21 (-0.05)
PPG 15 0.46
PPG 18 (-0.35)
PPG 20 0.80
PPG 17 0.77
PPG 12 1.15
23oz PPG 18
(-0.01)
PPG 19 2.10
PPG 23 (-0.01)
PPG 25 1.05
PPG 26 1.45
PPG 27 1.35
PPG 29 1.20
PPG 28 -2.15
PPG 13 PPG 16
14
Key Insights: Top 10 Promo Events that Drive Incremental Units
Endcap Display
Perimeter Display
Front Page Ad
Interior Page Ad
Dollar Off Event
Loyalty Event
Event
2/$4
2/$4
2/$4
$1.99 Mega $1.49
10/$10 Pro Bowl
$1.99 Mega $1.49
Promoted Price – $3.00
2/$4
Promoted Price – $2.00
2/$4
Average Incremental Units for specific promotion
combination
18
25
30
32
39
40
42
42
82
85
- 20 40 60 80 100
Incremental Units (‘000s)
PPG 1
PPG 2
PPG 7
PPG 4
PPG 15
PPG 3
PPG 6
PPG 11
PPG 5
PPG 8
15
Key Insights: Top 10 Promo Events that Drive Incremental Margin
Endcap Display
Perimeter Display
Front Page Ad
Interior Page Ad
Dollar Off Event
Loyalty Event
Event
Promoted Price – $3.00
2/$4
Promoted Price – $4.99
Base Price
2/$6
Promoted Price – $1.99
Promoted Price – $2.25
Promoted Price – $1.99
Base Price
2/$5
Average Incremental Margin for specific
promotion combination
$8.49
$13.40
$14.44
$18.74
$19.42
$20.97
$26.79
$27.04
$8100
$31.05
$- $10 $20 $30 $40Incremental Margin (‘000s)
PPG 6
PPG 2
PPG 10
PPG 1
PPG 7
PPG 4
PPG 11
PPG 3
PPG 21
PPG 12
16
Enhancing Account Management
P r e d i c t i v e A n a l y t i c s
E n g i n e +
M e t r i c s G e n e r a t o r
Store Clustering
BU Sales
Price Discounts
Promotion Tactics
Growth Targets
Ticket, Net Sales
CID, Turns, GMROI
Retailer Margin
Sales, Vol. Lift
Share Change
P
l
a
n
n
i
n
g
S
e
l
l
i
n
g
Leveraging the Predictive Analytics Engine to validate opportunities that help Account Teams achieve their internal and external targets
17
Business Advantage
Align Priorities Better selection of promotion event tactics.
Selling story for various locations.
Leverage PPG/Cluster level Insights Volume/Business planning (Improved forecast)
Optimize promotion offering to channel partner.
Better planning & insights at portfolio & category level.
Streamline Communication Effective communication with Customer Team.
Discussion points with account team leadership
Call The Best Scenario For the right product.
In the right cluster.
At the right time.
18
Planning Component – Scenario Comparison
1 2 3
4
5
6
7 8 9
Total $ Sales at List Price (SDV) 1
Total $ Sales at Promoted Cost (SDV – Trade Spend) 2
3 Frito Lay’s Vol share Gain in Salty Snacks Category
Incremental # of bags sold/ Base # of bags sold 4
Incremental Portfolio (FL) Volume/ Base Portfolio (FL)Volume 5
Incremental Portfolio (FL) Revenue/ Base Portfolio (FL) Revenue 6
Retail Price (i.e., Cost to consumers) 7
SDV – Trade Allowance (cost to retailer) 8
(List Price – Promo Cost ) * Total Units 9
Customer Customer
19
Planning Component – Detailed Metrics
1 2 3 4
5
6
7
8 9 10 11 12 13
14
Total $ Sales at List Price (SDV) 1
Incremental # of bags sold/ Base # of bags sold 2
3 Incremental Portfolio (FL) Volume/Base Portfolio (FL) Volume
Incremental Category Volume/Base Category Volume 4
Incremental Margin $ for every $ of promo Investment 6
Cost per Incremental Dollar Sales 7
Decomposition of Total Unit Sales 8, 9
Decomposition of Portfolio (FL) Volume 10, 11
Decomposition of Category Volume 12, 13 Total $ Sales at Promoted Cost (SDV – Trade Spend) 5
Frito Lay’s Vol share Gain in Salty Snacks Category 14
Customer
20
Selling Component – Retailer Metrics
Total Units Sold
Total Dollars Sale by the Retailer
Dollar Profit earned by Retailer
# of times the display/product turn during an event
1 2 3
4
5
6
1
2
3
4
Gross Margin Return on Investment : Amount of Gross Profit dollars that a retailer will make in a year for every dollar invested in inventory
Gross Margin Return on Inventory Investment : Defined as Gross Margin/Average Inventory Cost
5
6
Customer
21
Final Thoughts
22
Introduced an efficient account management process by leveraging predictive analytics
Enhanced negotiation opportunity with buyer through real-time in-market insights
Empowered account teams with information that enable category and customer growth
Embraced digital disruption by creating mobile analytics solution in the cloud
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