Future of Supply Chain Technologies

Supply Chain Insights LLC Copyright © 2015, p. 1
Future of Supply Chain
Technologies
November 2015

Disclaimer: I am a Skeptic

A Social Scientist

A Curmudgeon

A Fortune-teller of Sorts….

I Write for the Supply Chain Leader

Supply Chain 2020

We are five years away from:
 Designing and implementing outside-in processes.
 Supply chains that learn while we sleep.
 Building the network of networks.
 Redefinition of master data management.
 Defining the digital supply chain.
My Predictions

The Supply Chain of the Future
World
Population
Source: “The World at Six Billion” United Nations, 2004; The World UN Population Assessment 2006; “Unsustainable World,” 04/15/08, BBC
North America
2007 2020
339M 342M
Europe
2007 2020
731M 722M
Asia
2007 2020
4.0B 4.6B
L America
2007 2020
572M 660M
Africa
2007 2020
965M 1.3B
Oceania
2007 2020
34M 40M
MARCO TRENDS

Growing Demand Volatility

Why? The Long Tail of the Supply Chain:
Growing Complexity

Evolution of Digital Processes

Confluence of Technologies

Current State

9 out of 10 Supply Chains are Stuck

Progress: All Industries
Industry Snapshots (2006-2013)
Industry
Year –over-
Year Revenue
Growth
Operating
Margin
Inventory
Turns
Cash-to-
Cash Cycle
Revenue per
Employee
(K$)
SG&A
Ratio
Retail Apparel Industry
18%
39%
0.39
27%
05
05%
68
26%
325
18%
27%
05%
Apparel Manufacturing Industry
14%
82%
0.12
32%
05
68%
150
08%
400
355%
27%
63%
Mass Retail Industry
09%
50%
0.06
20%
06
06%
03
148%
350
48%
23%
6%
Beverage Industry
09%
61%
0.19
16%
02
04%
53
46%
512
NC
24%
16%
Pharmaceutical Industry
08%
47%
0.23
29%
03
16%
155
47%
572
32%
27%
08%
Chemical Industry
08%
45%
0.10
10%
06
04%
87
23%
557
23%
14%
27%
Medical Device Industry
06%
38%
0.14
32%
02
13%
206
16%
351
12%
34%
04%
Grocery Retail Industry
06%
31%
0.03
37%
17
01%
10
50%
405
54%
14%
06%
Consumer Packaged Goods
05%
25%
0.14
73%
08
482%
72
17%
333
14%
26%
09%
Food Industry
05%
55%
0.10
19%
07
17%
40
04%
534
55%
20%
18%
Source: Supply Chain Insights LLC, Corporate Annual Reports 2006-2013
Industry Average comprised of public companies (combined food & beverage industry: NAICS 3112% where % is any number from 0-9, 311320, 311520, 311821,
311941 & 312111), (chemical: NAICS 325188 & 325998), (consumer packaged goods: NAICS 3256% where % is any number from 0-9), (medical device
industry: NAICS 339112), (pharmaceutical industry: NAICS 325412) reporting in One Source with 20123annual sales greater than $1billion
NC=no change

Descriptors Used by Leaders

Fallacy: Functional Excellence

Functional Organizational

Corporate Social Responsibility

Risk: Top Disruptions

Shifts in Ocean Cargo

Where are We on Supply
Chain Excellence?

What We Expected

The Supply Chain Effective Frontier

Dow Chemical Company: Treading Water

Toyota and Honda

General Mills More Resilient
5.0
7.0
9.0
11.0
13.0
15.0
0.06 0.08 0.10 0.12 0.14 0.16 0.18 0.20
Operating Margin
General Mills Kellogg
K
0.14, 12.68
2014
2006
2014
2006
GIS
0.17, 11.00
Average (Operating Margin, Inventory Turns)
InventoryTurns
Best Scenario

2006
4.0
5.0
6.0
7.0
8.0
9.0
10.0
-0.10 0.00 0.10 0.20 0.30 0.40 0.50 0.60
Operating Margin
Eli Lilly and Company Novo Nordisk
2014 NVO
0.31, 6.48
2014
2006
Best Scenario
LLY
0.24, 8.30
Average (Operating Margin, Inventory Turns)
InventoryTurns
Novo Nordisk Making Progress

• Continuity of leadership
• Supply chain talent development
• Focus on a multi-year supply chain strategy
• Clear governance to guide cross-functional
decision-making
• Strength in horizontal processes
• Excellence in supply chain planning, network
design and inventory management
What Drives Top Performance?

Future of Supply Chain
Technology

Current State of Technologies

Deployment Options

Focus

Best of Breed versus ERP Planning

S&OP: Technology Matters

Value Proposition: Insights on Effective S&OP

Effective S&OP: Improved Alignment

Analytic Evolution

Data Types

Analytics Maturity

Current Focus

Opportunity
at the Intersection
of the Social and Interest Graph(s)

Simple Example of Test and Learn

Current Focus

• Newell Rubbermaid
Listening: Newell Rubbermaid
#Future15SB @bwdumars

#Future15SB @bwdumars
Newell Rubbermaid

Listening: Lenovo

0
0
0
0
0
0
0
Canada
-Customer A calls about a blue screen on a Yoga
-Customer B posts on Facebook about his X220’s AC/DC adapter issues
Large Enterprise Client experiences 5 keyboard malfunctions in their latest
shipment. Complaints received through account executive
[Critical Situation]
Brazil
-Customer F submits a service from on
esupport.lenovo.com regarding
their W530 hard drive
Morocco
-Customers G & H comment on their
X220’s electrical issues on Twitter.com
-Customer I called about Yoga screen
issues
Australia
-Customer J write a review on
NewEgg.com about AC/DC adapter
issues on X220
-Customer K had an eChat with Lenovo
about Yoga screen issues
China
-Customer L wrote on Weibo about
Yoga screen issues
-Customer M calls about a Tablet 8
battery issues
Voice of Customer Comes in Many Forms
USA
-Customers C & D write X220 product
reviews on amazon.com and mention
issues with AC/DC adapters
-Customer E posts on
forums.lenovo.com that they are
experiencing blue screens on their Yoga

0
0
0
0
0
0
0
Lenovo
- 6 recorded issues about X220’s
AC/DC adapter
- 5 recorded issues about
keyboard issues on X1 Carbon
- 5 recoded issues about Yoga
screen
- 1 recorded issue about W530
hard-drive
- 1 recorded issue about Tablet 8
battery
One Voice – A Single View of Perceptual Quality

Supply Chains Don’t Play by the Rules
51
But,
what if
they
could?

Test and Learn Cross-Channel

3D Printing

Evolution of 3D Printing of Human
Organs

Ultimate Ear

Internet of Things

Automation of Replenishment

2:00am Emergency
Drug Call

11:02

11:1811:22

11:1811:26

SHM PowerPoint Template Guidelines 03.15.10
Intelleflex Confidential
•Opportunity
• 1/3 of shipped produce wasted: $34B in annual
global waste from perishable foods
• 50% is due to temperature variations from the farm
to retail shelf
• Reducing temperature related shrink by half is
approx. $9B opportunity.
1% reduction in Shrink
Increase in profit of
$1,173,555
6% reduction in Shrink
Increase in profit of
$7,378,830
Opportunity With One Commodity: Strawberries

Building Export Pallets
Having different remaining shelf life mixed on pallets, causes problems later. Sending short shelf life berries on
longer delivery cycles turns Good Berries into BAD Berries for the retailer and others. More yellow & red pallets in
Philadelphia & Southern California ~ More shrink at the retailer ~ Lower customer satisfaction
15+ 14+
13+
11+
15+ 15+ 15+
10+
<10
12+
12+
<10
12+
15+
14+
12+
11+
14+
13+
12+
12+
10+
<10
<10
15+
15+
15+
15+
15+
15+
15+
15+
15+
15+15+
Currently berries come in from growers, pass QC, and are put on export pallets on a First In Basis (traceability control)
WHICH RESULTS IN MIXED SHELF LIFE ON MULTIPLE PALLETS….
ALL GOOD BERRIES, BUT - they have different remaining shelf life when received from growers
If we can group berries by shelf life, we avoid problems on multiple pallets – and send pallets to the right destination…

Network of Networks

• Role based. Get data to people who need to make the decisions when
they need it.
• The So What? When it comes to network partners. Answer the
question of "Do we know what you know? When we need to know?"
• The What. Within the Enterprise. "When did you know it? When should
you know it? Who should know it?"
• The Timing? Visibility with the right cadence. "How does the visibility of
data tie to decisions within the organization? What is the right cadence
and granularity?"
• Clarity. Get the language right. The belief is that sometimes we try to "get
too fancy and lose the basics." The group discussion focus was that
sometimes we get into a tool driven discussion versus the basic blocking
and tackling. For example, a packaging company discussed demand
data. When people say demand data, they automatically think of sharing
forecasts. However, for the supplier, the best source of demand data was
not the forecast, or the MRP run. Instead, it was the downstream partners
production schedules.
There is No One Definition of Visibility

Supply Chain Visibility

Vision: Network of Networks

Wrap-up

Traditional Digital
Project definition Large projects with
known outcomes
Small projects that evolve
Funding Licensed deployments Cloud deployments
Type of data Structured transactional
data
Unstructured and
structured data
Data characteristics Data with low velocity Data with high velocity
Leadership Led by IT Led by the business
Process focus Inside-out Outside-in
Capabilities Better response Test and learn
Technologies Large, established
vendors
Small and evolving
technology sources
Shifts

• Supply Chain for 2020 is about Growth.
• The Digital Supply Chain is a great opportunity to
drive Growth. However, do not push digital for the
sake of digital. Instead, define a business
problem, and attack it in a new way.
• Embrace the Confluence of Technologies.
• Learn from the Past to Unlearn and Then Drive
New Outcomes.
Summary

See You Next Year on
September 8 & 9, 2016

Founder: Lora Cecere
• Founder of Supply Chain Insights
• “LinkedIn Influencer”
• Guest blogger for Forbes
• Author of 4 books: Bricks Matter (2012), Shaman’s Journal (2014)
and Supply Chain Metrics That Matter (December 2014), Shaman’s Journal (2014)
• 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 (10,000 pageviews/month)
• Forbes: http://www.forbes.com/search/?q=lora+cecere
• Twitter: lcecere (6500 followers)
• LinkedIn: linkedin.com/pub/lora-cecere/0/196/573 (50,000 followers)

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