Supply Chain 2030

Next-Generation Supply
Chain Management
May 2018
For the Supply Chain Leader Who Wants to Rise Above

Supply Chain Insights LLC Copyright © 2018, p. 2
I Am A Social Scientist

I Write for the Supply Chain Leader

Today’s Reality

Third Industrial Revolution Productivity Impact
Stopped in 2004

Risk Drivers

What I Believed

Only 12% Of Companies Are Driving Improvement and
Performance Better Than Their Peer Group at the Intersection
of Operating Margin and Inventory Turns.

Customer Service
The Supply Chain Is a Complex System with
Increasing Complexity.

• Improvement
• Performance better than Peer Group
• Resiliency
• Balance
• Strategy to Action
What Defines Supply Chain Excellence?

2006
2016
6.6
6.8
7.0
7.2
7.4
7.6
7.8
8.0
0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15
InventoryTurns
Operating Margin
Food
Best
Scenario
Food
0.11, 7.38
Average (Operating Margin, Inventory Turns)
Source: Supply Chain Insights LLC, Corporate Annual Reports 2006-2016 from YCharts
Shifts in the Food Manufacturing Market
Operating Margin vs. Inventory Turns (2006 - 2016)

Normal
Distribution
SKU/L
SalesVolume
Anything But Normal
The “Long Tail” is Growing

Why? Commodity Pressures

Gaps in Alignment

Functional Management of Costs: Manage Costs
Like a Decathlete

Efficient Is Usually Not Effective

What Makes a Difference?

Driving a Digital
Transformation

What Is Next-Generational Thinking?

Current Supply Chain Process Thinking
Rows and Columns:
Transactional Data
Fixed Hierarchies with
Structured Data
One-to-One Enterprise Linear Flows
Descriptive and Predictive Analytics

Digital Supply Chain:
Transforming the Atoms
and Electrons of the
Supply Chain through the
Confluence of
Technologies
What Does Digital Transformation Mean for
You? There Is No One Definition

Data Needs to Move Securely Through Value
Networks In…
Clouds Streams Pools

Need for New Forms of Analytics

Evolution of Insights

Autonomous
Supply Chain
Cognitive Computing
Machine Learning
Text Mining and
Pattern Recognition
Predictive and
Prescriptive
Analytics
Building the Autonomous Supply Chain

Evolution of Cognitive Computing

• Data Mapping. The average company has 5 to 7 Enterprise Resource Planning Solutions (ERP). While the solutions are sourced from the
same provider, each has a different data definition. It is difficult to map data from one to the other. The use of cognitive learning with a rules-
based ontology enables the mapping of data with different context.
• Automation of Master Data Management and the Replacement of Data Standards. Today master data is hard-coded. The data
definitions are manually determined and mapped. They are inflexible. As the business changes, the data becomes obsolete. With cognitive
learning we redefine master data. It is adaptive.
• Redefinition of Rules. In the first generation of planning technologies the rules were single “ifs” to single “thens.” Rule sets –like ATP, VMI,
Transportation Routing, Allocation and Assortment logic– are simple rule sets.
• Rethinking Planning. Today companies try to get very precise on imprecise data. Rows and columns define forecasting. Companies lose
visibility on the patterns and demand flows. Cognitive learning solutions provide systems of insights that can combine profile pattern
recognition along with learning on unstructured data. Examples include the number of google searches on an illness or symptoms, which is a
predictor of the spread of an illness and subsequent prescription sales. Social sentiment on twitter and Facebook combined with point-of-sale
data drives insights to understand regional sales in days. Today it takes weeks.
• Planning Master Data. Most companies install supply chain planning solutions, stabilize the implementation, and then forget about them.
The data parameters of lead times, cycle times, and rates quickly become outdated. In most cases this data is a variable not a constant. For
example, moving rail through Chicago in the winter is not the same as the summer. Unloading a container in Long Beach varies by the
season; yet, the planning systems have a fixed value.
• Rethinking Decision Support. Building Systems of Insights Cognitive computing, layered on existing decision support tools—revenue
management, trade promotion management, demand planning, production planning, transportation planning and supply network planning–
drives deeper insights.
• Listening Posts. Today’s analytics drive answers on the questions we know, but we cannot track the important data that answers the
questions which we do not know. Examples are many. Why are consumers raising concerns on quality? What do patterns tell us?
• Quality. Many production environments–coolers, dryers and distillation columns–are complex with many variables. Once the variables
exceed 5 to 7 it is hard to model outcomes without collinearity. Cognitive learning enables new forms of insights to better control quality.
• Customer-Centric Supply Chains. Cognitive learning is ideal to map customer policies to fulfillment. The dynamic nature of inventory to
order matching is difficult. This is an area of great opportunity.
• Network of Networks. The connection of data between trading partners is a use case that excites me. In this podcast episode, I explain
some of the planned tests. For more on this important initiative join our webinar on January 11, 2017. We will be testing the potential to
replace EDI messaging through the combination of Apache Spark, Blockchain and cognitive learning. In short, today’s business networks
lack agility and are too costly. We believe that cognitive learning improves data mapping and gives insights to data relationships and
inferences which are not obvious.
Cognitive Use Cases

Sentiment: The Need to Listen

An Example

Redefining
Time

1.5M sku locations
~ 95% slow or intermittent
Seasonal demand (at the item level) is identified down to a specific
location.
Simplified for clarity In reality, looks more like this
•365 days
•150+ local climates
•Avg 3,000 items / location (165M)
•15 year lifecycle changing amplitude
Lennox International

•Replace
•Compressor
•Engines
• Dealer gets service event
• We get parts sales
• Customer has non-event
• Customer - Dealer & Brand loyalty
Your compressor shows that it will fail
within the next 30 days. What day would
be good for us to come replace it?
Redefining Service

Internet of Things

Rich user interface in full HD
Evocative sound track with
burring grinder and tinkling
of spoons
Memorable flavours and
fragrances
Cutting edge reliable /
ultra efficient computer
processing hardware
Stunning curved design by
Italian automotive designers
Irresistible aromas of Costa’s
coffee shops
Innovative coffee-making
system providers
Redefining Replenishment

Transforming Inbound Logistics
Mobile Device Apps
AIS Vessel Location
Sensors

Improved On-Time
Delivery

State of Hands Free

What is Visibility?

The adoption of distributed and open technology
by the ecosystem of technology providers and
business users to drive inter-operability in value
networks to improve business outcomes.
What Is the Network of Networks?

What Does Not Work

Confluence of Technologies

Blockchain is an incorruptible, and immutable, digital ledger of economic
transactions that can be programmed to record anything of value.
While blockchain is secure, the software on blockchain may not be.
There are many variants of blockchain. Public and Private understand
the differences.
What Is Blockchain?

Community Registry. Today network registration is onboarding to every network as an individual or as a company. It lacks the system of
reference of division/company or company/industry. What if we could have a community registry where we have a single sign-on
which could be accessed by all value networks? (Analogous to network DNS.) This numbering schema would be carried in blockchain
messaging, enabling writing information once, and safe/secure communication across the network.
Replacement of EDI. Today EDI is the workhorse of the supply chain. Messages are transmitted and opened safely and securely.
However, it is batch, and there is latency as the message is opened. In addition, the passage and receipt of EDI requires sophisticated IT
groups. As a result, it is costlier. (This is not always a reality for small companies in emerging economies.) Could blockchain replace EDI?
This is a stretch objective, but I think it’s possible.
Lineage. Track and Trace. Track and trace across multiple parties is cumbersome and lacks reliability. Blockchain offers the ability to
embed the origin and transfer points in the chain to encode lot codes, origin points and destinations. This could help in food track and trace,
the management of gray market goods to eliminate counterfeit items, and the assurance of origin for tracking social responsibility goals for
fair labor, Congo metals, etc. This will enable compliance and could streamline recalls.
Safe and Secure Supply Chains. As goods pass through the supply chain, multiple parties handle the goods. Blockchain technologies
enable a chain of custody. In the process, the requirements of each product for handling are communicated on receipt. Why is this an
issue? We discard 1/3 of perishable items. What if the use of blockchain, along with temperature sensing, could redefine code dates real-
time based on handling for perishable items like fruits/vegetables and chicken? And, in extreme cases of temperature or handling abuse
indicate disposal? (This is extremely important in pharmaceutical cold chains.) Or, what if the conditions for handling could be read on
receipt to enable safe put-away for flammables?
Improving Social Responsibility Goals. Tracking carbon and point of origin for compliance is difficult. One thing is clear: audits do not
work. As we tackle issues like fair labor, clean water, Congo metals, and carbon consumption, blockchain can track the code of custody
and help us to better understand and measure energy consumption, carbon emissions and other social responsibility goal tracking
Supply Chain Finance. The origin of blockchain is safe and secure payment. Could we disintermediate banks as we know them? Each
time a supply chain transaction passes through a bank, there are charges. Could we drive a massive restructuring of world banking to
reduce bank charges for credit cards, wire transfers, and EFT/ACH payments?
Document Sharing. I think the world has too many lawyers. In supply chain, we spend hours upon hours negotiating terms and conditions
of contracts. After completion, the filed contracts are never used again. We do not connect the contracts to supply chain execution. So,
what if contracts could accompany a PO, and as conditions change, rules change the cost based on delivery conditions? Or delivery
conditions, based on availability (dynamic dock scheduling) and weather?
Use Cases

Blockchain is Disruptive

Future View

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

Shifts in Planning Architecture

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

Today’s Challenges

Where Are You Willing to Invest?
Early Adopter Late Adopter
Cognitive, Machine Learning,
Blockchain, Internet of Things,
Wearables, Drones, Autonomous
Vehicles
Cloud, Concurrent Planning,
Descriptive Analytics, Production
Planning, Inventory Management,
Transportation Planning
2 Options:
Little
Choice in
Between

• Remove the handcuffs. Eliminate the expectation of well-
defined ROIs.
• Develop a stage-gate process for process innovation.
• Embrace small scrappy teams.
• Partner with technology innovators.
• Manage the hype cycles.
Have the Talk with Your CFO

Wrap-up
• Embrace New Technologies at
the Right Time.
• Focus on Capabilities. Build
with the Goal in Mind.
• Manage the Supply Chain as a
Complex System.

Time to Take a Different Path?

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

Supply Chain 2030

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