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Improving Supply
Chain
Effectiveness
March 2, 2020
I Am A Social Scientist
I Write for the Supply Chain Leader
About Lora Cecere
Founder of Supply Chain Insights
“LinkedIn Influencer”
Guest blogger for Forbes
Author: Bricks Matter (2012), Supply Chain Metrics That Matter (2014), and Shaman’s Journal (2014-19)
Partner at Altimeter Group (leader in open research)
8 years 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/Blue Yonder)
15 Years Leading teams in Manufacturing and Distribution for Clorox,
Kraft/General Foods, Nestle/Dreyers Grand Ice Cream and Procter & Gamble.
Contact Information:
• Email: lora.cecere@supplychaininsights.com
• Blog: www.supplychainshaman.com (18,000 pageviews/month)
• Forbes: www.forbes.com/sites/loracecere
• Twitter: twitter.com/lcecere (9,600 followers)
• LinkedIn: www.linkedin.com/in/loracecere (318,000 followers)
• LinkedIn Influencer: www.linkedin.com/today/author/446631
Technology In Transition
Traditional supply chain thinking is:
Functional
Linear
Transactional
Inside-out
Moving forward, the thinking becomes:
Cross-functional
Non-linear
Focus on sense, learn and act
Outside-in
What Is An Effective Supply Chain?
Outcome:
Performance
Improvement
Resilience
Goal:
Efficient
Responsive
Agile
Fit for Function
Email from a Financial Analyst
I think one of the huge problems is that US-centric food companies (Kellogg, General
Mills, Smucker’s, Conagra etc.) are working on a “if all you have is a hammer, all you
see is nails” problem – they have been making boxed, canned and otherwise shelf-
stable packaged food for well over a century but now consumers and retailers are
looking for fresh foods and they don’t know how to adapt. Certainly, Campbell’s foray
into its c-Fresh business ended in tears.
We have the rise of new channels, particularly eCommerce. And again, companies
aren’t sure how to configure themselves to play profitably in there.
Meanwhile, retailers are getting far more sophisticated in their analytical capabilities,
which is reducing the importance of the category captain role for the largest CPG
brands in each category.
Everything is getting faster – new products are introduced and eliminated more
quickly, better analytics are enabling better real-time feedback on what should go
where on a shelf and at what price at a much more granular level – may be down to
individual stores. Yet, companies are blind to these insights.
Supply Chains Are Stuck
What I Believed….
…companies spent
1.7% of revenue on
information
technology
investments and
drove improvement.
I Was Wrong….
[CELLRANGE]
[CELLRANGE]
4.2
4.7
0.07 0.08 0.09 0.10 0.11 0.12
InventoryTurns
Operating Margin
Apparel Retail
Best
Scenario
Apparel Retail
0.10, 4.51
Average (Operating Margin, Inventory Turns)
Source: Supply Chain Insights LLC, Corporate Annual Reports 2010-2018 from YCharts
Apparel Retail
Operating Margin vs. Inventory Turns (2010 - 2018)
[CELLRANGE]
[CELLRANGE]
11.0
12.0
13.0
14.0
0.02 0.03 0.04 0.05
InventoryTurns
Operating Margin
Food Retail
Best
Scenario
Food Retail
0.04, 12.76
Average (Operating Margin, Inventory Turns)
Source: Supply Chain Insights LLC, Corporate Annual Reports 2010-2018 from YCharts
Grocery Retailing
Operating Margin vs. Inventory Turns (2010 - 2018)
Supply Chain Insights Global Summit 2019 Twitter: #Supplychain2030
[CELLRANGE]
[CELLRANGE]
1.4
1.5
1.6
1.7
1.8
1.9
2.0
2.1
2.2
2.3
2.4
2.5
2.6
2.7
2.8
2.9
3.0
0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11
InventoryTurns
Operating Margin
Personal Products
Best
Scenario
Personal Products
0.07, 2.13
Average (Operating Margin, Inventory Turns)
Source: Supply Chain Insights LLC, Corporate Annual Reports 2010-2018 from YCharts
Personal Products
Operating Margin vs. Inventory Turns (2010 - 2018)
[CELLRANGE]
[CELLRANGE]
4.5
5.0
5.5
6.0
0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11
InventoryTurns
Operating Margin
Chemical
Best
Scenario
Chemical
0.07, 5.20
Average (Operating Margin, Inventory Turns)
Source: Supply Chain Insights LLC, Corporate Annual Reports 2010-2018 from YCharts
Chemical
Operating Margin vs. Inventory Turns (2010 - 2018)
[CELLRANGE]
2018
[CELLRANGE]
2018
4.0
5.0
6.0
7.0
8.0
0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.20 0.21 0.22
InventoryTurns
Operating Margin
Procter & Gamble Co. Kimberly-Clark Corp.
PG
0.20, 6.05
Average (Operating Margin, Inventory Turns)
Source: Supply Chain Insights LLC, Corporate Annual Reports 2006-2018 from YCharts
KMB
0.14, 6.13
Kimberly Clark and P&G
Operating Margin vs. Inventory Turns(2006 – 2018)
Best Scenario
[CELLRANGE]
2018[CELLRANGE]
2018
4.0
5.0
6.0
7.0
8.0
0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.20 0.21 0.22 0.23 0.24 0.25 0.26
InventoryTurns
Operating Margin
Nestle SA Unilever PLC
UL
0.15, 6.46
Average (Operating Margin, Inventory Turns)
Source: Supply Chain Insights LLC, Corporate Annual Reports 2006-2018 from YCharts
NSRGY
0.15, 5.17
Example: Nestle & Unilever
Operating Margin vs. Inventory Turns (2006 – 2018)
Best Scenario
Focus on A Balanced Scorecard Focused to
Drive Value
Functional Metrics Shift to Focus on Reliability
Plan Sell Deliver Make Source
Forecast improvement
(FVA)
Minimization of slow and
obsolete inventory
Inventory mix quality
Promotion timing
adherence
Forecast bias
On time shipments
Orders shipped full
Hands-free orders
First pass yield
Schedule adherence
On time materials to
plants
Schedule adherence
Supplier quality
Define a Balanced
Scorecard
Align Functional Metrics
to Reliability Redefine S&OP
Supply Chains Are Stuck
Are Supply Chains Effective?
____________________________________________________________________
Source: Supply Chain Insights LLC, Sales & Operations Study ((Mar-May, 2019))
Base: HAVE A S&OP PROCESS -- Total (n=107)
Q29. For each of the following pair of words, please pick the one that best describes your company’s supply chain today.
 Higher than other answer at 90% or higher level of confidence
Aligned
Risk-taking
Agile
Proactive
Controlled
Working well
Outside-in
40%
39%
37%
37%
37%
33%
28%
27%
29%
23%
33%
25%
45%
31%
Independent silos
Cautious
Fixed
Reactive
Uncontrollable
Room for improvement
Inside-out
Supply Chain Descriptors*
WORS
E
BETTER
Strengths
Challenges
Organizational Silos Are Not Aligned
US Productivity Stopped in 2004
Inventory Levels Higher Now Than 2007
Normal
Distribution
SKU/L
SalesVolume
Anything But Normal
Complexity: The “Long Tail” Is Growing
The Long Tail of the Supply Chain Increases Complexity Reducing
Margin, Increasing Inventory Turns and Reducing Asset Utilization.
Supply Chains Are Stuck
Why?
• Belief in Best Practices
• Focus on Shiny Objects
• Focus on Functional Excellence
• One Size Fits All
• Inside-Out
Why?
The Reasons We Are Stuck How Do We Unstick the
Supply Chain
The How
Belief in Best Practices Recognize These as
Historic Practices.
Learn to Unlearn to Rethink
Outcomes.
Focus on Shiny Objects Test but Verify. Fail Forward.
Functional Metrics Drive Balance Sheet
Excellence.
Focus on Cross-functional
Alignment and Focus the
Functions on Reliability.
One Size Fits All Multiple Supply Chains. Build Capabilities based on
Rhythms and Cycles.
Inside-out Outside-in. Build Value Networks.
A Case Study
• One out of two orders shorted. Deductions for
issues on case fill rate expected to be
9M$/year in 2020.
• Order shortages not measured. Five ERP
systems. Email and Excel environment.
• Took 6 months to begin the process.
Order Short Data
5%
45%
5%
41%
4%
Packaging Plant Underperformance Scheduling Quality Issue Demand
View Before
Sprint
Demand Analysis
Managing Multiple Supply Chains
Supply
Chain
United States Canada
COV 0-<.5 .5-1.25 >1.25 0-<.5 .5-1.25 >1.25
Make to
stock
83.6% of volume
83.5% of items
5.1% of volume
11% of the
items
83.3% of
volume
59.8% of items
14.7% of volume
27% of items
New
product
launch
10.8% of
volume
4.8% of
items
1.8 % of volume
12.8% of items
Make to
order
.5% of volume
.7% of items
.1% of
volume
.2% of items
Tactics Sell Deliver Make Source
Make-to-Stock
Item/location
forecasting
Demand Sensing
Allocation
VMI
Safety stock
buffers
Full truck load
shipments
Cycle stock
planning using
rhythm wheel
logic
JIT/Reliable supply
Potential for
contract
manufacturing
Phase-in Phase
Out
Attribute-based
forecasting
Use of customer
data
Air/small
shipments
Attribute-based
planning
Agile
manufacturing
work centers
Platform
rationalization
Postponement
local sourcing
Make-to-Order ATP Air from factory
Shorten cycles
Agile
manufacturing
work centers
Platform
rationalization
Postponement
DDMRP
Managing Multiple Supply Chains
Digital Supply Chain:
Transforming the Atoms
and Electrons of the Supply
Chain through the
Confluence of new
Capabilities/Technologies.
Digitization: Making signals
and processes digital.
What Does Digital Transformation Mean for You?
There Is No One Definition
Data Needs to Move Securely Through Value Networks
Clouds Streams Pools
Analytics Adoption
Data Types
The Need to Listen
Evolution of Cognitive Computing
Progressing in the World of Analytics
Known/Known Unknown/Unknown
Visualization Flexible/Easy to Use by
Business Leaders
Discovery/Learning
Questions The Questions You Know to
Ask
The Answers You Need, but
the Questions You Don’t
Know to Ask
Data Known Unknown
Answers the Questions You Do Not Know to Ask
Data
Inputs
Engines Plan
Outputs
Align Engines with Outcomes
Planning Master Data
Evolution of Insights
Impact of Localized Assortment
Looking Forward
In the future, companies will not compete
company against company, but value chain to
value chain.
Today’s focus is on organizational efficiency is
making value networks fragile and less resilient.
What Is A Network?
Current State
Maturity
Vendor Master
Case study
Task:
• Research ALEIs for 24,245 suppliers in 81 countries
Results:
• ALEIs could be verified for 17,111 suppliers (71%) in 33 countries
• 7,134 (29%) of the suppliers will need to be asked for more information to verify their
legal status
• Of the 17,111 verified suppliers 7,060 (41%) were duplicate records
ALEIs researched 24,245 100%
ALEIs verified 17,111 71%
Further information required from vendor to validate legal entity 7,134 29%
Verified ALEIs 17,111 100%
Verified Legal Entities 10,051 59%
Duplicate records linked to master Legal Entity records 7,060 41%
Can Blockchain Help?
Is Blockchain the Answer?
Write once and use company and contact information many times.Community Directory
• Reduce onboarding through once source of data.
Blockchain redefines visibility and track and trace.Traceability
• Confluence of Blockchain and Spark/Internet of Things Redefine Lineage.
Bitcoin and Blockchain disintermediate traditional banking.Supply Chain Finance
• Emergence of the supply chain digital wallet.
• An alternative to EDI.
Cognitive computing eliminates the need for master data management
and standards.Interoperability
• Data is mined through patterns and translated for context through cognitive computing. Shift from
standards to process canonicals.
What Could Change?
Integration Data portability and
synchronization
Linear flows Network bidirectional flows
Functional focus Need for plan, source, make
and delivery to work together
Master data Need for authoritative
identifiers
Insights?
What Can We Learn?
1. Leadership matters. There is no significant difference in
technologies deployed.
2. Outperforming supply chains are fit for purpose. They
change with shifts in business strategy.
3. 67% of supply chains drive performance in single metrics
throwing the supply chain out of balance and reducing value.
4. Companies focusing on innovation outperform. There is a
clear mission and understanding of the customer.
5. Question the status quo. Only 3% of companies outperform
their peer groups.
6. We cannot save our way to value.
ENGAGE WITH US!
Visit Us Online
www.supplychaininsights.com
www.supplychainshaman.com
www.linkedin.com/company/supply-chain-insights
www.slideshare.com/loracecere
Follow Us on Twitter
@scinsightsllc
@lcecere
Attend a Live Event
www.supplychaininsightsglobalsummit.com
www.supplychaininsights.com/the-shamans-circle
What To Learn More?

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Presentation by Lora Cecere at the Foundation of Strategic Sourcing

  • 2. I Am A Social Scientist
  • 3. I Write for the Supply Chain Leader
  • 4. About Lora Cecere Founder of Supply Chain Insights “LinkedIn Influencer” Guest blogger for Forbes Author: Bricks Matter (2012), Supply Chain Metrics That Matter (2014), and Shaman’s Journal (2014-19) Partner at Altimeter Group (leader in open research) 8 years 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/Blue Yonder) 15 Years Leading teams in Manufacturing and Distribution for Clorox, Kraft/General Foods, Nestle/Dreyers Grand Ice Cream and Procter & Gamble. Contact Information: • Email: lora.cecere@supplychaininsights.com • Blog: www.supplychainshaman.com (18,000 pageviews/month) • Forbes: www.forbes.com/sites/loracecere • Twitter: twitter.com/lcecere (9,600 followers) • LinkedIn: www.linkedin.com/in/loracecere (318,000 followers) • LinkedIn Influencer: www.linkedin.com/today/author/446631
  • 5. Technology In Transition Traditional supply chain thinking is: Functional Linear Transactional Inside-out Moving forward, the thinking becomes: Cross-functional Non-linear Focus on sense, learn and act Outside-in
  • 6. What Is An Effective Supply Chain? Outcome: Performance Improvement Resilience Goal: Efficient Responsive Agile Fit for Function
  • 7. Email from a Financial Analyst I think one of the huge problems is that US-centric food companies (Kellogg, General Mills, Smucker’s, Conagra etc.) are working on a “if all you have is a hammer, all you see is nails” problem – they have been making boxed, canned and otherwise shelf- stable packaged food for well over a century but now consumers and retailers are looking for fresh foods and they don’t know how to adapt. Certainly, Campbell’s foray into its c-Fresh business ended in tears. We have the rise of new channels, particularly eCommerce. And again, companies aren’t sure how to configure themselves to play profitably in there. Meanwhile, retailers are getting far more sophisticated in their analytical capabilities, which is reducing the importance of the category captain role for the largest CPG brands in each category. Everything is getting faster – new products are introduced and eliminated more quickly, better analytics are enabling better real-time feedback on what should go where on a shelf and at what price at a much more granular level – may be down to individual stores. Yet, companies are blind to these insights.
  • 9. What I Believed…. …companies spent 1.7% of revenue on information technology investments and drove improvement.
  • 11.
  • 12.
  • 13. [CELLRANGE] [CELLRANGE] 4.2 4.7 0.07 0.08 0.09 0.10 0.11 0.12 InventoryTurns Operating Margin Apparel Retail Best Scenario Apparel Retail 0.10, 4.51 Average (Operating Margin, Inventory Turns) Source: Supply Chain Insights LLC, Corporate Annual Reports 2010-2018 from YCharts Apparel Retail Operating Margin vs. Inventory Turns (2010 - 2018)
  • 14.
  • 15. [CELLRANGE] [CELLRANGE] 11.0 12.0 13.0 14.0 0.02 0.03 0.04 0.05 InventoryTurns Operating Margin Food Retail Best Scenario Food Retail 0.04, 12.76 Average (Operating Margin, Inventory Turns) Source: Supply Chain Insights LLC, Corporate Annual Reports 2010-2018 from YCharts Grocery Retailing Operating Margin vs. Inventory Turns (2010 - 2018) Supply Chain Insights Global Summit 2019 Twitter: #Supplychain2030
  • 16.
  • 17. [CELLRANGE] [CELLRANGE] 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 3.0 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 InventoryTurns Operating Margin Personal Products Best Scenario Personal Products 0.07, 2.13 Average (Operating Margin, Inventory Turns) Source: Supply Chain Insights LLC, Corporate Annual Reports 2010-2018 from YCharts Personal Products Operating Margin vs. Inventory Turns (2010 - 2018)
  • 18. [CELLRANGE] [CELLRANGE] 4.5 5.0 5.5 6.0 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 InventoryTurns Operating Margin Chemical Best Scenario Chemical 0.07, 5.20 Average (Operating Margin, Inventory Turns) Source: Supply Chain Insights LLC, Corporate Annual Reports 2010-2018 from YCharts Chemical Operating Margin vs. Inventory Turns (2010 - 2018)
  • 19.
  • 20. [CELLRANGE] 2018 [CELLRANGE] 2018 4.0 5.0 6.0 7.0 8.0 0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.20 0.21 0.22 InventoryTurns Operating Margin Procter & Gamble Co. Kimberly-Clark Corp. PG 0.20, 6.05 Average (Operating Margin, Inventory Turns) Source: Supply Chain Insights LLC, Corporate Annual Reports 2006-2018 from YCharts KMB 0.14, 6.13 Kimberly Clark and P&G Operating Margin vs. Inventory Turns(2006 – 2018) Best Scenario
  • 21. [CELLRANGE] 2018[CELLRANGE] 2018 4.0 5.0 6.0 7.0 8.0 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.20 0.21 0.22 0.23 0.24 0.25 0.26 InventoryTurns Operating Margin Nestle SA Unilever PLC UL 0.15, 6.46 Average (Operating Margin, Inventory Turns) Source: Supply Chain Insights LLC, Corporate Annual Reports 2006-2018 from YCharts NSRGY 0.15, 5.17 Example: Nestle & Unilever Operating Margin vs. Inventory Turns (2006 – 2018) Best Scenario
  • 22. Focus on A Balanced Scorecard Focused to Drive Value
  • 23. Functional Metrics Shift to Focus on Reliability Plan Sell Deliver Make Source Forecast improvement (FVA) Minimization of slow and obsolete inventory Inventory mix quality Promotion timing adherence Forecast bias On time shipments Orders shipped full Hands-free orders First pass yield Schedule adherence On time materials to plants Schedule adherence Supplier quality Define a Balanced Scorecard Align Functional Metrics to Reliability Redefine S&OP
  • 25. Are Supply Chains Effective? ____________________________________________________________________ Source: Supply Chain Insights LLC, Sales & Operations Study ((Mar-May, 2019)) Base: HAVE A S&OP PROCESS -- Total (n=107) Q29. For each of the following pair of words, please pick the one that best describes your company’s supply chain today.  Higher than other answer at 90% or higher level of confidence Aligned Risk-taking Agile Proactive Controlled Working well Outside-in 40% 39% 37% 37% 37% 33% 28% 27% 29% 23% 33% 25% 45% 31% Independent silos Cautious Fixed Reactive Uncontrollable Room for improvement Inside-out Supply Chain Descriptors* WORS E BETTER Strengths Challenges
  • 28. Inventory Levels Higher Now Than 2007
  • 29. Normal Distribution SKU/L SalesVolume Anything But Normal Complexity: The “Long Tail” Is Growing The Long Tail of the Supply Chain Increases Complexity Reducing Margin, Increasing Inventory Turns and Reducing Asset Utilization.
  • 31. Why? • Belief in Best Practices • Focus on Shiny Objects • Focus on Functional Excellence • One Size Fits All • Inside-Out
  • 32. Why? The Reasons We Are Stuck How Do We Unstick the Supply Chain The How Belief in Best Practices Recognize These as Historic Practices. Learn to Unlearn to Rethink Outcomes. Focus on Shiny Objects Test but Verify. Fail Forward. Functional Metrics Drive Balance Sheet Excellence. Focus on Cross-functional Alignment and Focus the Functions on Reliability. One Size Fits All Multiple Supply Chains. Build Capabilities based on Rhythms and Cycles. Inside-out Outside-in. Build Value Networks.
  • 33. A Case Study • One out of two orders shorted. Deductions for issues on case fill rate expected to be 9M$/year in 2020. • Order shortages not measured. Five ERP systems. Email and Excel environment. • Took 6 months to begin the process.
  • 34. Order Short Data 5% 45% 5% 41% 4% Packaging Plant Underperformance Scheduling Quality Issue Demand
  • 37. Managing Multiple Supply Chains Supply Chain United States Canada COV 0-<.5 .5-1.25 >1.25 0-<.5 .5-1.25 >1.25 Make to stock 83.6% of volume 83.5% of items 5.1% of volume 11% of the items 83.3% of volume 59.8% of items 14.7% of volume 27% of items New product launch 10.8% of volume 4.8% of items 1.8 % of volume 12.8% of items Make to order .5% of volume .7% of items .1% of volume .2% of items
  • 38. Tactics Sell Deliver Make Source Make-to-Stock Item/location forecasting Demand Sensing Allocation VMI Safety stock buffers Full truck load shipments Cycle stock planning using rhythm wheel logic JIT/Reliable supply Potential for contract manufacturing Phase-in Phase Out Attribute-based forecasting Use of customer data Air/small shipments Attribute-based planning Agile manufacturing work centers Platform rationalization Postponement local sourcing Make-to-Order ATP Air from factory Shorten cycles Agile manufacturing work centers Platform rationalization Postponement DDMRP Managing Multiple Supply Chains
  • 39.
  • 40. Digital Supply Chain: Transforming the Atoms and Electrons of the Supply Chain through the Confluence of new Capabilities/Technologies. Digitization: Making signals and processes digital. What Does Digital Transformation Mean for You? There Is No One Definition
  • 41. Data Needs to Move Securely Through Value Networks Clouds Streams Pools
  • 44. The Need to Listen
  • 46. Progressing in the World of Analytics Known/Known Unknown/Unknown Visualization Flexible/Easy to Use by Business Leaders Discovery/Learning Questions The Questions You Know to Ask The Answers You Need, but the Questions You Don’t Know to Ask Data Known Unknown
  • 47. Answers the Questions You Do Not Know to Ask
  • 48. Data Inputs Engines Plan Outputs Align Engines with Outcomes Planning Master Data
  • 50. Impact of Localized Assortment
  • 51.
  • 52. Looking Forward In the future, companies will not compete company against company, but value chain to value chain. Today’s focus is on organizational efficiency is making value networks fragile and less resilient.
  • 53. What Is A Network?
  • 56. Vendor Master Case study Task: • Research ALEIs for 24,245 suppliers in 81 countries Results: • ALEIs could be verified for 17,111 suppliers (71%) in 33 countries • 7,134 (29%) of the suppliers will need to be asked for more information to verify their legal status • Of the 17,111 verified suppliers 7,060 (41%) were duplicate records ALEIs researched 24,245 100% ALEIs verified 17,111 71% Further information required from vendor to validate legal entity 7,134 29% Verified ALEIs 17,111 100% Verified Legal Entities 10,051 59% Duplicate records linked to master Legal Entity records 7,060 41%
  • 57.
  • 59. Is Blockchain the Answer?
  • 60. Write once and use company and contact information many times.Community Directory • Reduce onboarding through once source of data. Blockchain redefines visibility and track and trace.Traceability • Confluence of Blockchain and Spark/Internet of Things Redefine Lineage. Bitcoin and Blockchain disintermediate traditional banking.Supply Chain Finance • Emergence of the supply chain digital wallet. • An alternative to EDI. Cognitive computing eliminates the need for master data management and standards.Interoperability • Data is mined through patterns and translated for context through cognitive computing. Shift from standards to process canonicals. What Could Change?
  • 61. Integration Data portability and synchronization Linear flows Network bidirectional flows Functional focus Need for plan, source, make and delivery to work together Master data Need for authoritative identifiers Insights?
  • 62.
  • 63. What Can We Learn? 1. Leadership matters. There is no significant difference in technologies deployed. 2. Outperforming supply chains are fit for purpose. They change with shifts in business strategy. 3. 67% of supply chains drive performance in single metrics throwing the supply chain out of balance and reducing value. 4. Companies focusing on innovation outperform. There is a clear mission and understanding of the customer. 5. Question the status quo. Only 3% of companies outperform their peer groups. 6. We cannot save our way to value.
  • 64. ENGAGE WITH US! Visit Us Online www.supplychaininsights.com www.supplychainshaman.com www.linkedin.com/company/supply-chain-insights www.slideshare.com/loracecere Follow Us on Twitter @scinsightsllc @lcecere Attend a Live Event www.supplychaininsightsglobalsummit.com www.supplychaininsights.com/the-shamans-circle
  • 65. What To Learn More?

Hinweis der Redaktion

  1. Why the long tail is getting bigger