Supply Chain Insights February 2019 Webinar: Selection of Demand Planning

Improving Demand
March 2019
For the Supply Chain Leader Who Wants to Rise Above

Supply Chain Insights LLC Copyright © 2019, p. 2
Who Is Lora? I Am A Social Scientist

I Write for the Supply Chain Leader

What Is Demand?
Demand Is a River that Flows Through the Supply Chain.

The River at a Client

We Are Hard-Wired for Supply

Current Success Is Like a Flip Of A Coin

Demand Sensing: The reduction of time to sense purchase and channel takeaway. Demand sensing is a
process, automated by technology, that reduces demand latency.
Demand Latency: The latency of demand signal due to demand translation of a customer purchase through
the supply chain to an order for a trading partner. The time is different in each supply chain based on product
sales velocity and the technologies used. For example, in a hospital, it is the translation of usage in a procedure
to hospital order to a distributor and the translation of that usage to an order for a manufacturer. This time lapse
varies by product and by channel. For the purchase of Tide at Walmart to translate to an order at P&G, the time
is 5-7 days. For the translation of a purchase of Aleve at a retail outlet store to Bayer, the manufacturer is 60
days. As the long tail (small orders shipped with low-frequency) of the supply chain grows, demand latency
increases and there is a greater need for demand sensing technologies.
Independent Demand. The purchase of a product by a customer in the channel.
Dependent Demand. The translation of this demand signal from a channel demand signal to a manufacturer or
a distributor through a bill of material or a transportation or manufacturing routing.
Demand Translation. The translation of demand by role within the organization. Each role–customer service,
sales, procurement, manufacturing–have a different need/definition for the demand signal.
Demand Shaping. The use of demand tactics –price, sales incentives, marketing programs, new product
launch, promotions, and assortment– to increase baseline forecasting.
Demand Shifting. The shifting of demand from one period to another (examples include pre-shipments at the
end of the quarter, stuffing the channel to get rid of stock, or shipping early) increases supply chain costs and
distorts the demand signal. Try to minimize demand shifting and maximize the value of demand shaping. Get
clear on the difference.
Learning to Speak the Language of Demand

Forecastability. The mathematical determination of ease of forecasting (the determination of the
probability of demand). Many technologies include this in the base software package.
Forecast Value-Add (FVA): A methodology for continuous improvement of the demand plan where
steps of the process are evaluated and the question is asked, “Did this change improve the forecast
(bias and error) as compared to the naive forecast?” (For more on this topic check out the book, The
Business Forecasting Deal.)
Naive Forecast. The historic forecast using prior month shipments.
Downstream Data: Use of channel data (Point of Sale (POS) and Warehouse Withdrawal) to sense
channel demand.
Demand Synchronization. The demand signal must be connected from node to node in the supply
chain and then synchronized and mapped. The most frequently mapped data elements are product
hierarchies, time/calendars, and locations. In this mapping, the data granularity and frequency must be
harmonized.
Demand Visibility. The translation of demand by role across the organization and across tiers and
nodes of the supply chain.
Demand Consumption. The translation of the demand signal across planning horizons. In early
planning products this was accomplished through rules-based consumption. New and more advanced
technologies are using optimization and cognitive learning techniques to consume the forecast across
planning horizons.
Integration. Close coupling of the data elements to use the data into software. Integration without
synchronization and harmonization does little for the demand signal.
Harmonization. Data harmonization enables data of differing granularity and data structures to be
harmonized into a common database.
Learning to Speak the Language of Demand

Current Level Of Satisfaction Is A Flip Of A Coin

Risk Management Issues Growing

Inventory Levels Burgeoning

Unprecedented Commodity Pressures

Today’s Reality

Market Forces

2007 Recession

Do We Have Best Practices?
Or Historic Beliefs?

Normal
Distribution
SKU/L
SalesVolume
Anything But Normal
Evolution Of The Long Tail

Normal
Distribution
SKU/L
SalesVolume
Anything But Normal
Consistent and Forecastable: 874
items representing 77% of the
volume and 74% net sales. 64% of
the volume is forecastable with a
55% error.
Inconsistent demand: 1723 items
representing 23% of the volume and
26% net sales.
Traditional
Optimization
Techniques
Need for Machine Learning/Pattern
Recognition: Inventory Strategy
Not Forecastable
by Conventional
Means
Client Case Study

Traditional Approaches of ERP/MRP/DRP Amplify
the Bullwhip Effect

Gaps in Alignment

Manage Costs Like a Decathlete

Technology Does Not Always Help: Total Costs

Efficient Is Usually Not Effective

Demand Latency
Forecastability
Customer Service: On-time and Infull
Tactical Plan Feasibility
Schedule Adherence
Loads Tendered. Loads Accepted.Forecast Value Added

Effectiveness of Analytics

The Building of Excel Ghettos
Isolated, Disconnected
Decision-making

Data Accessibility Is An Issue for Business Leaders

• A pattern caused by order frequency, order quantity or batch size.
• A type of demand: trade promotion, new product launch, seasonal
consumption.
• A product build to execute a supply chain strategy.
Life for a supply chain planner is not as easy as it used to be.
What Is a Demand Flow?

Companies Make the Mistake of
Trying to Get Precise on
Imprecise Numbers.
Instead, they need to manage
demand flows.

Data
Inputs
Engines Demand
Plan
Outputs
Engines Need to Align with Outcomes
Planning Master Data

Strategic
Planning
• Goal: Plan by
Design
• Set Push-pull
Decoupling Points
• Define Buffers
Tactical
Planning
• Goal: Tactical Demand Plan/S&OP
Planning
• Level Load for Manufacturing/Build a
Feasible Plan
• Improve Aggregate Buying of Direct
Materials
Demand
Sensing
• Goal: Improve
Replenishment
• Timing Usually
the Same as the
Slush Period
Understanding Planning

Planning Maturity: Large CPG Company
Application Channel Sell Deliver Make Source Suppliers
Strategic
Planning
6-18 months
Partner
Planning
Network Design Strategic
Sourcing
Tactical
Planning
12-52 weeks
Sales and Operations Planning Commodity
Council Buying
Strategies
Requirements
Planning
Joint
Value
Creation
Forecasting Inventory
Configuration
Tactical
Supply
Supplier
Development
Transportation
Planning
Material
Orchestration
Operational
Planning
3-12 weeks
Demand Sensing (MDS
and DS)
Inventory Planning
DRP/Load
Planning
Deployment
Production
Planning
MRP Supplier
Sensing
Internal Visibility Supplier Visibility
Executional
Planning
0-3 Weeks
Customer VMI
Trade Promotion Execution
ATP
Supplier VMI
Transactional
Data
Transactions
Planning Master
Data
Planning Master Data

Shifts in Planning Architecture

Businesses are Complex

• Engines: Modeling/Math
• Scalability
• User Interface
• Collaboration/What-if Analysis
• Partner Requirements
• Culture
• System of Record
• Integration
Selection Criteria for Planning

• Scalability
• User Interface
• Culture
• Integration

Impact of Localized Assortment

The Need to Listen

The River at a Client

Baby Boomers, Vendors, Academics, and Remote
Employees Are Most Satisfied with Their Jobs

Today’s Challenges

Discussion: How Do We Give Planners Some Love?

What Makes a Difference?

Wrap-up
We Must Learn to Unlearn to
Relearn.
Focus on Basics. Avoid the
Pitfalls and Potholes.
Build Executive
Understanding.

What To Learn More?

Demand Share Group
How do we transform demand
management processes?
Monthly Calls
Meetings Three Times a Year
Next Meeting: May 21st-22nd at Land
O’Lakes
Current Members: Corning, Nestle, Mars
and Mondelez

LOCATION: UI LABS
1415 NORTH CHERRY AVENUE
CHICAGO, ILLINOIS 60642
Cost $800/person
This event will have a live video feed. However, there will be no breakout
activity for the participants on the livecast.
Network of Networks: March 6th-7th Meeting

Complimentary Monthly Networking
Monthly networking calls. To sign up contact
Regina.Denman@supplychaininsights.com.

About Lora Cecere
• Founder of Supply Chain Insights
• “LinkedIn Influencer”
• Guest blog for Forbes
• Author of 5 books: Bricks Matter (2012), Shaman’s Journal (2014),
Supply Chain Metrics That Matter (2014), Shaman’s Journal (2015),
Shaman’s Journal (2016), Shaman’s Journal (2017)
• Partner at Altimeter Group (leader in open research)
• 7 years of Management Experience leading Analyst Teams at
Gartner and AMR Research
• 8 years Experience in Marketing and Selling Supply Chain Software
at Descartes Systems Group and Manugistics (now JDA)
• 15 Years Leading teams in Manufacturing and Distribution
operations for Clorox, Kraft/General Foods, Nestle/Dreyers Grand
Ice Cream and Procter & Gamble.
Contact Information:
• Email: lora.cecere@supplychaininsights.com
• Blog: www.supplychainshaman.com (15,000 pageviews/month)
• Forbes: www.forbes.com/sites/loracecere
• Twitter: twitter.com/lcecere (9,100 followers)
• LinkedIn: www.linkedin.com/in/loracecere (262,000 followers)
• LinkedIn Influencer: www.linkedin.com/today/author/446631

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Supply Chain Insights February 2019 Webinar: Selection of Demand Planning

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