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.
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Planning for Complexity and the Predictability of Demand | 2014 IBF Supply Chain Planning Conference
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
1
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
5
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.
7
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
8
Supply Chain Planner
by JDA Software
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
13
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
14
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?”
15
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%
17
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
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.
19
20. How am I doing?
Forecastability-Based Intelligence
Forecast Accuracy
Forecast Accuracy
Conventional
DPIC Forecastability Index™
Forecastability yields a very different conclusion!
20
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.”
21
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
22
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)
23