Presented by Ben YoKell, Principal of the Demand Planning Intelligence Consortium at Chainalytics and Sridhar Bashyam, Director of Supply Chain Planning at Frito Lay North America, on 25 February 2014 during IBF's Supply Chain Planning Conference in Scottsdale, AZ. Product life cycles are growing shorter, and consumers continue to ask for more choices. For many organizations, the increased number of SKUs and item locations means more complex demand planning. Conventional wisdom says that increased complexity means lower forecast accuracy and larger bias, yet Frito-Lay Inc. has demonstrated otherwise. Taking a closer look at the behavior of demand signals yields a new understanding of demand planning performance expectation and potential. In this session, the presenters will highlight practices they’ve used to build a high-performing demand planning environment, including the use of a data-based analytics service from Chainalytics, which measures portfolio forecastability and quantifies improvement opportunity for specific demand segments. Attendees will learn: - How Frito-Lay’s direct-to-store model affects demand planning - A practical framework for demand segmentation - Why advanced analytics are key to measuring, understanding, and improving demand planning performance To learn more about Chainalytics and how the Demand Planning Intelligence Consortium can help to simplify your complexity, visit http://www.chainalytics.com. To request a PDF of this presentation, simply email DPIC@chainalytics.com.

1. Planning for Complexity &
the Predictability of Demand
Sridhar Bashyam
Director, Supply Chain
Frito-Lay North America
Ben YoKell
Principal, Demand Planning Intelligence Consortium
Chainalytics
Supply Chain Planning & Forecasting Conference
February 23-25, 2014 | Scottsdale, AZ
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2. Agenda
Company Overview
Demand Planning at Frito-Lay North America
Demand Planning Benchmarking
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3. Agenda
Company Overview
Demand Planning at Frito-Lay North America
Demand Planning Benchmarking
3

4. PepsiCo Overview
4

5. Who We Are
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.
Global Beverages
Global Snacks
Global Nutrition
Performance
Brands
Scale
People
more than
22
>200
~300,000
billion-dollar
brands
countries
& territories
employees
$65 billion
revenue
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6. Our History
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7. From Seed to Shelf
Frito-Lay owns the entire supply chain, so there are
significant optimization opportunities.
Move Information Before Inventory
Raw Materials
& Purchased
Finished Goods
Plant
Warehouse
Distribution
Sales OPS
Route Sales
Retail Store
R
Product Flow
Visibility to company wide information, enabling optimization and increasing the
velocity through each function, while reducing the effort and improving productivity.
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8. Our Integrated Supply Chain
Statistically Calculated Safety Stock
Multi-Echelon Inventory
Optimization
by JDA Software
Production Planning & Scheduling
Daily Production Planner
by Frito-Lay
North America
Statistical Forecasting Models
Execute
& Deliver
Base Forecast
New Products
+
Promo Lift
+
Event Lift
Cannibalized Products
Discontinued Products
Replenishment Planning
Transaction Data
SAP
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Supply Chain Planner
by JDA Software

9. Agenda
Company Overview
Demand Planning at Frito-Lay North America
Demand Planning Benchmarking
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10. The Whole Truth
Every week we send
a 100% accurate forecast
through the system…
…Sales just sells
the wrong amount.
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11. Demand Signal Threading in a DSD
System
3+ Weeks Out
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Week Of

12. FLNA Forecasting Facts
Number of Regions
13
Avg. Number of SKUs
~800
Lowest Level Intersections
~8.5 Million
Historical Sales & Promotion Data
3 Years
Forecast Bucket
Weekly
Forecast Horizon
1 Year
Forecast Frequency
Once a Week
Duration of Forecasting Process
~60 Hours
Sales forecasted into the store
R
Plant
12
Distribution
DC
Route Sales
Retail Store

13. Frito Lay DP SAS Solution
Historical Sales & Causal Data
Causal Data

Current Functionality
Promotion enrollments by account
–
–
–
SAS Promo Lift

SAS Holiday Lift
SAS Base Forecast
Statistical Forecast
Planner Adjust using DP UI
Final Forecast
Supply Chain Planning
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Price point
Duration
Days in week
Events: Holidays, quarter close, seasonal
activities

14. Delivering the Final Forecast
is a Collaborative Effort
Product Supply
Sales
 Input of accurate and timely
promo enrollments
 Owns the signal
 Notification of non-price
point driven activity
 Capacity and volume push
 Execution
Region Finance
Sales Ops
 Forecast feedback via
weekly calls with
replenishment planners
 Aligning DP forecast to the
organization’s financial
forecast
Demand Planning
Plants
 Forecast feedback from
plant-based replenishment
planners
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 Hold Key Account Managers
accountable for accurate
and timely promo
enrollments

15. Demand Planning Benchmarking
Benefits of Benchmarking
 Accuracy and bias benchmarking
vs. relevant demand
 Use of demand segmentation and
forecastability concepts
– Region accuracy target setting
– Assessing opportunities for
accuracy improvements
“How am I doing overall?”
“How difficult is my portfolio
to plan to for?”
“How well should I be doing for
my level of portfolio difficulty?”
“How well could I be doing for
my level of portfolio difficulty?”
“Where should I focus
my energy and attention?”
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16. Agenda
Company Overview
Demand Planning at Frito-Lay North America
Demand Planning Benchmarking
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17. Demand Planning Intelligence
Consortium
Conventional
Benchmarks
Demand Planning
Intelligence Consortium
Questionnaire-based
Data and analytics-based
 Participants self-report forecast accuracy
however they measure it, which varies
 Reports are typically annual
 Level of aggregation is very high
 Limited comparative analysis
 Best practices ID’d without accounting
for differences in portfolio forecastability
49%
33%
PERSONAL CARE
13%
HOME CARE
5%
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FOOD & BEVERAGE
PET CARE
VS.
 Standardized transactional data collection and
computational approach by unbiased 3rd party
 Reports are periodic and repeating
 Level of benchmarking is highly granular
 Provides understanding of drivers and causes
 Best practices ID’d accounting for differences
in portfolio forecastability
DPIC Statistics




Industry: Consumer Packaged Goods
Geography: North America and Europe
Members: ~ 40 Businesses
Item-Locations: ~ 500,000

18. Segmented Benchmarking &
Analytics
Nearly 1,250
Forecast Accuracy
and Bias
Benchmarks
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19. How difficult is my environment to
forecast?
Segmentation provides an understanding of each portfolio, which drives
demand planning performance potential as much (or more) as complexity.
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20. How am I doing?
Forecastability-Based Intelligence
Forecast Accuracy
Forecast Accuracy
Conventional
DPIC Forecastability Index™
Forecastability yields a very different conclusion!
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21. How well could I be doing?
Targets can be set with more realism by customizing for the specific
demand portfolio, and should be differentiated: “One Size Does Not Fit All.”
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22. Some Frito-Lay DPIC Findings
 Frito-Lay is a top performer, both overall and in segmented
analytics results
 This is in contrast to assumptions around high complexity
 Top performance results stems from good process, great
execution, and relatively high demand forecastability
Forecastability + Process Design & Execution > Complexity
 Room still exists for improvement; even a top overall
performer has segments of the business with opportunity
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23. What’s Next for Frito-Lay Demand
Planning
 Continue our membership in the consortium
– Work on opportunity areas presented by survey results
 Add new causals to our SAS models
 Leverage point of sale data
 Continue to explore new technologies such as demand
sensing
 Grow our modeling team into a Forecasting Center of
Excellence (COE)
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24. Thank you!
Additional Information?
Email
DPIC@chainalytics.com
Visit
http://bit.ly/DPIC-info
Connect
http://bit.ly/ChainLI
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