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Future of Supply Chain Technologies

The Future of Supply Chain Technologies

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Presentation given at the Terra Technology event in Orlando on April 4th.

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Page 1: The Future of Supply Chain Technologies

Future of Supply Chain Technologies

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Supply Chain Insights LLC Copyright © 2013, p. 2

Metrics That Matter

Fall 2014 Publication

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Supply Chain Insights

Current State

The Future

Going Forward

Wrap-up

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Growth has Slowed

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The Efficient Supply Chain

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The Long Tail of the Supply Chain: Growing Complexity

Volume

Level of PredictabilityPredictability based on forecast accuracy vs Actual Order Profiles

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Increasing Commodity Volatility

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Current State

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Many Systems

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Large Gaps in Current Technologies

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Gap in What-if Architectures

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Growing use of Cloud and BPO

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Future State of Planning

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Future State of Planning

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Greatest Gaps in Visibility Importance vs. Performance:Inter-enterprise Order Management, 1st Tier Suppliers

and 3rd Party Manufacturing

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Building Visibility Solutions

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Supply Chain Insights

Current State

The Future

Going Forward

Wrap-up

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• 1/3 of the fruits and vegetables of the world did not have to be thrown away due to temperature abuse?

• A heart could be printed at a hospital as part of a transplant procedure?

• Garages could be used for overflow storage?• Analytics could give us the answers to the questions that

we do not know to ask?• Supply chains could learn and respond as we sleep?• Improved sensing would enable continuous test and learn

in vitro in market?

What If?

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Connecting to better serve your customers, your employees and your partners outside in.

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Use of Emoticons

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Ratings and Reviews: Giantnerd.com

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Co-Design products like Nike

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Co-Develop like Quirky

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Customer as the Designer

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The Crowd has Built a Car “Wikispeed”

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Amazon Aspires to $100B in CPG Sales

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Emergence of Digital Path to Purchase

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CUSTOMER PATH ANALYTICS

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KINETIC HEAT MAPS

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Four Moments of Truth

The List:• Digital

Recipe• Digital

Coupons• Online

Rating and Reviews

The Basket:• Shelf-

sensing• QR Codes• In-store

coupons• IP Address

Sensing

The Check-out• Downstream

Data• Loyalty Data

Usage• Sentiment Data• Ratings and

Reviews

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Entrance of Digital Path to Purchase

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Mobile Applications

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The Collaborative Economy

Collaborative Economy Definition: An economic model of shared ownership and

access between people, startups, and corporations.

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Co-Storage of Products with Lockitron

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Co-Production with 3D Printers

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Supply Chain Insights

Current State

The Future

Going Forward

Wrap-up

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Evolution

Align:Market Driven

Building Horizontal Process Connectors

ContinuousTesting

LearningImprovingIn Market

OrchestrateDemand and Supply

ResilientReliable

Adapt: Demand Driven

EfficientSense

Demandand Supply

Shape Demand andSupply based

on Market

Absorb DemandVolatility

Absorb Supply Volatility

Right Product

Right Place

Right Time

Right Cost

Cost

Procure to pay/order to

cash

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An adaptive network that senses and translates market changes (buy and sell-side markets) bi-directionally with near-

real time data latency to align sell, deliver, make and sourcing operations.

What is a Market-driven Value Network?

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Market-Driven Value Networks Characteristics

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Rethinking Analytics

DescriptiveConnect with reality, a single source of

the truth

PredictiveUnderstand the most likely future

scenario, and the business implications

PrescriptiveRecommendation of the best

alternative

CognitiveHighly automated optimization

solutions that get smarter over time

What happened?

What will Happen?

What should we do about it?

Learning Systems

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Thinking Harder about the Problem

EngineInputs Outputs

• Deterministic Optimization• Stochastic Optimization• Simulation• Cognitive Learning Engines

Depth of Analysis

Scope• Single function within the enterprise• Multiple functions within the enterprise• Connection of trading partners on single functions• Connection of trading partners on multiple functions (make, source, and deliver)

• Single signals (single numbers)• Time-phased outputs• Multiple signals with time-phased outputs• Patterns and probabilities

• Single signals (single numbers)• Time-phased inputs• Multiple signals with time-phased inputs• Patterns and probabilities

The Data Model of the Engine

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Supply Chain Insights

Current State

The Future

Going Forward

Wrap-up

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Future is Bright: But, we have to learn from the past, to unlearn to be open to the future.

Summary

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Questions?

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Annual Event September 2014

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Who is Lora?

• Founder of Supply Chain Insights

• 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.

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Where Do You Find Lora?

Contact Information: [email protected]

Blog: 100 Posts/Year www.supplychainshaman.com (10000 pageviews/month)

Forbes: Write 2X/Month http://www.forbes.com/search/?q=lora+cecere

Twitter: lcecere 4800 followers.

LinkedIn: linkedin.com/pub/lora-cecere/0/196/573 (Linkedin Influencer over 6000 followers in the network)