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)

0

100

200

300

400

500

600

700

800

900

1000

0

50

100

150

200

250

300

350

400

450

05

Feb

20

14

12

Feb

20

14

19

Feb

20

14

26

Feb

20

14

05

Mar

201

4

12

Mar

201

4

19

Mar

201

4

26

Mar

201

4

02

Ap

r20

14

09

Ap

r20

14

16

Ap

r20

14

23

Ap

r20

14

30

Ap

r20

14

07

May

201

4

14

May

201

4

21

May

201

4

28

May

201

4

04

Jun

20

14

11

Jun

20

14

18

Jun

20

14

25

Jun

20

14

02

Jul2

01

4

09

Jul2

01

4

16

Jul2

01

4

23

Jul2

01

4

30

Jul2

01

4

06

Au

g20

14

13

Au

g20

14

20

Au

g20

14

27

Au

g20

14

03

Sep

20

14

10

Sep

20

14

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

Questions

23