INDEX
Page numbers followed by f and t refer to figures and tables, respectively.
Abstract digital skills, 235
Accuracy, at T-Moblie, 262–263
Action, in DSN transformation, 247–248
Additive manufacturing (AM), 38, 39f
digital enabling technologies for, 132–134
in intelligent spare parts management, 182
Advanced manufacturing, 166f
Agility:
in DSNs, 25
AGVs (automatic guided vehicles), 194–195
AI (see Artificial intelligence (AI))
Airline service providers, 7–8
Algorithms, for machine learning (see Machine learning algorithms)
AM (see Additive manufacturing (AM))
Amazon:
aggregation of buyers by, 6
entrepreneurial mindset at, 255–257
as example for other companies, 261
technology and employment at, 229
technology-related discrimination at, 225
use of drones by, 41
workforce at, 228
Amazon Go, 256
AMRs (autonomous mobile robots), 194–196
Analytics (See also Data analytics)
in digital stack, 32
as enabling technology, 39
AR (see Augmented reality (AR))
Artificial intelligence (AI), 72–78, 82–87
applications of, 83–84
in autonomous mobile robots, 195
for autonomous vehicles, 197
benefits of, 86
challenges for, 85
in dynamic fulfillment, 202–203
as enabling technology, 36, 37f
historical perspective on, 73f
levels of, 79f
and machine learning, 72–75, 74f
and machine learning algorithms, 75–78
machine learning vs., 73f
predictions about, 82–83
and rapid technological development, 70f
and social inequality, 225–226
in synchronized planning, 110–111
technological basis for, 71f
terminology in, 74f
used by Amazon, 256
Asset digitization, 252
Asset maintenance strategy, 178, 179f
Asset management:
intelligent, 178–183
Assets:
digital, 91–92
digitization of, 252
ATLAS web portal, 260–261
Auditability, with blockchain, 98
Augmented reality (AR), 39–40, 40f
in cargo loading, 200
in digital product development, 130
in picking operations, 199–200
wearable technology as, 199
Automated demand sensing, 148
Automated workflow, 117
Automatic guided vehicles (AGVs), 194–195
Automation:
with artificial intelligence, machine learning, and robotics, 70–71
factory, 171
in intelligent supply, 147–148, 153–157
in procurement activities, 146, 156–157
selecting tasks for, 79
in smart manufacturing, 162
at T-Mobile, 262
as wave of industrial change, 11
Automotive industry, 226
Autonomous delivery, in China, 263–264
Autonomous mobile robots (AMRs), 194–196
Autonomous stations, 198
Autonomous vehicles, 196–199 (See also Automatic guided vehicles (AGVs); Unmanned aerial vehicles (UAVs))
Autonomy, in contract management, 149
Bayliss, John, 259
Beginning-of-life (BOL) applications, 132
Big data, 53–60
infrastructure for, 64–67, 64f
Bitcoin, 99
Blockchain, 89–104
capabilities of, 95–98
challenges for, 103
components of, 91–93
as data connecting tissue, 43f
as enabling technology, 42, 42f
in intelligent supply, 148
network designs for, 94–95
role of, in DSN, 98–101
smart contracts, 101–103
used by Walmart Canada, 259–260
BOL (beginning-of-life) applications, 132
Braun, Dustin, 261
Brookings Institution, 228
Brynjolfsson, E., 229–230
Bullwhip effect, 159
Business case, 251
Business models, 52–53
Business strategy, 239–242
CAD (computer-aided design), 130
CAM (computer-aided manufacturing), 130
Capabilities:
of blockchain, 95–98
of connected customers, 215–222, 216f
of digital development, 128, 129f
in digital stack, 30
of intelligent supply, 146–152, 153f
of smart manufacturing, 170–171
of synchronized planning, 109–111
CAPP (computer-aided process planning), 130
Cardenas, A. A., 174
Cargo loading:
augmented reality in, 200
virtual reality in, 200f
Category management strategy, 150
China:
data-related policies and laws in, 62, 62t
workforce changes in, 232
Chipotle Mexican Grill, 96
Classification, in machine learning, 76
Cloud computing:
and digital twins, 181–182
as infrastructure, 66
in intelligent asset maintenance, 183
in product tracking, 220
Cloud manufacturing, 168
Clustering, in machine learning, 76
Cobots, 41
Cognitive automation, 43, 44f, 71t
Cognitive decision support layer, 117
Collaboration:
as digital discipline, 28–29
necessary for supply chains, 98–99
Collaborative autonomous mobile robots (AMRs), 194–196
Collaborative demand sensing, 112, 113f
Collaborative networks, 6–7
Collaborative supply planning, 112, 113f, 114
Commercialization activities, 128
Communication skills, of workforce, 234
Communication technologies, 130
Competition, in DSN transformation, 252–253
Complex problem-solving capabilities, 234
Compliance, in intelligent supply, 148–149
Computer-aided design (CAD), 130
Computer-aided manufacturing (CAM), 130
Computer-aided process planning (CAPP), 130
Concept, in digital development, 126, 126f
Concurrent planning, 110
Connected customers, 205–223
in age of personalization, 205–209, 206f
capabilities of, 215–222, 216f
and customer processes in traditional SCM, 208f, 209–214
in DSNs, 209f
experience of, 129f
at Nike Inc., 268–269
technologies for, 214–215
Connected field service, 221–222
Connected service network, 220–222
Connectivity:
for autonomous mobile robots, 195–196
in digital stack, 30–31
and Internet of Things, 173
as principle of smart manufacturing, 168
Consensus validation, 92–93
Consumer Products Group, 257–258
Contract management, 149–150
Co-Pilot smart headsets, 269–270
Cost:
and degree of automation, 81–82, 82f
and efficiency, 96–97
Council of Supply Chain Management Professionals (CSCMP), 2
CPPS (see Cyber-physical production systems (CPPS))
CPS (see Cyber-physical systems (CPS))
Creativity, as workforce skill, 233
Critical suppliers, 143f
Cryptographic security, 92
CSCMP (Council of Supply Chain Management Professionals), 2
Culture, and DSN transformation, 246–247
Customer expectations, 4
Customer experience:
at Amazon, 256
delightful, 216
design for, 129f
in DSN transformation, 250
tracking and monitoring of, 218–220
Customer issue management, 211, 217
Customer processes, 208f, 209–214
Customers:
as center of design process, 213
impact of digital transformation on, 7–8
reaching more, 6
in traditional order fulfillment, 185
in traditional SCM, 17–19
Customization, 138–139 (See also Personalization)
Cyber-physical production systems (CPPS), 164
and digital twins, 177f
DSNs as, 50–51
in Industry 4.0, 164
in smart manufacturing, 174, 177
Cyber-physical systems (CPS), 160
DSNs as, 50–51
in Industry 4.0, 160
in smart manufacturing, 174, 176f
Cybersecurity, 60–62
and digital stack, 31
in DSN transformation, 253
Daimler AG, 270
Daimler Trucks Asia (DTA), 270–272
Data, 49–67
accessibility and acquisition of, 50–52
and artificial intelligence, machine learning, and robotics, 85
big data, 53–60
big data and data analytics infrastructure, 64–67
and cybersecurity, 60–62
in DSN transformation, 242, 251
governance of, 60–62
impact and value of, 50–53, 51t
impact of digital transformation on, 9
and interoperability, 63
preprocessing of, 77–78
quality of, 59
real-time response to, 117
required for intelligent supply, 154
security of, 61
shared by customers, 212–213
sources of, 50–52
utilization of, 169–170
Data analytics:
at Daimler Trucks Asia, 271
in dynamic fulfillment, 202–203
infrastructure for, 64–67
and smart manufacturing, 170
for suppliers, 152
and supply chain planning, 119
for unstructured data, 57
Data lakes, 48
Data lifecycle, 59–60
Data Silo, 261
DCOR (design chain operations reference model), 126
Decision making:
in digital stack, 32
in DSNs, 26
Degree of automation, 72, 80–82, 82t
Delightful customer experience, 216–217
Delivery:
in digital development, 126f, 127
last mile, 196–199
Demand sensing:
automated, 148
Design:
for customer experience, 129f
in digital development, 126–127, 126f
for manufacturing innovation, 129f
Design chain operations reference model (DCOR), 126
Design thinking, 250
Digital assets, 91–92
Digital barrier, in adopting technology, 167–168
Digital core:
Control Tower in, 32–34
in DSN transformation, 250
enabled through digital stack, 29–32
at Georgia-Pacific, 257–258
Digital Core project, 257–258
Digital development, 125–140
collaborative tools and digital design teams, 128, 130
examples of, 138–139
process for, 126–128
and servitization, 135–138
for smart-connected products, 131–134
and traditional product development, 126
Digital disciplines, 28–29, 29f
Digital enabling technologies, 132–134
Digital literacy, 233
Digital procurement, 144–146
Digital products, 135
Digital reality types, 39–40, 40f
Digital replicas, 110–111, 117, 119
Digital robotization, 12, 15–16
Digital services, 135
Digital stack, 29–32, 30f, 31f
Digital supply network strategy, 239–242
Digital supply networks (DSNs), 23–48
approach to transformation of, 243f
artificial intelligence and machine learning in, 84
benefits and consideration of, 44–48, 45f
blockchain in, 89–91, 98–101, 100f
capabilities of, 21f
and collapse of linear supply chain, 23–24
connected customers in, 209f
digital transformation to, 19–21
and dynamic fulfillment, 187–188
impact of, 47f
intelligent supply in, 155f
representation of, 20f
technologies enabling, 35–44
and technology, 242–245
Digital technologies:
effect of, on workforce, 225–230, 227f
in electronic automation, 11
Digital transformation, 1–22
to DSNs, 19–21
impact of, 7–9
importance of, 2–7
of manufacturing industry, 164
preparing workforce for, 230, 232
of procurement activities, 145f
and traditional supply chain management, 16–19
waves of industrial and economic change, 9–16, 10f
and cyber-physical production systems, 177f
in cyber-physical systems, 174
predictive modeling and maintenance by, 180–182
in smart manufacturing, 162
at Unilever, 264–266
and virtualization, 169
Digitization:
of assets, 252
in digital robotization wave, 15–16
social impact of, 226
Dimensions, of smart-connected products, 131–132
Disintermediation, with blockchain, 98
Dispatchers, 269–270
Disruption:
caused by technologies, 225–226
from digital technologies, 1
new PSS business models as, 137–138
Disruptive innovation, 99
Distributed computing, 92
Distribution centers, 194
Distribution requirements plan (DRP), 108
Drones, 41
DSN transformation playbook, 239–254
business strategy and DSN strategy, 239–242
DSN approach and technology, 242–245
factors impacting DSN transformation journey, 249–253, 249f
recommended steps for, 245–249, 246f
DSNs (see Digital supply networks (DSNs))
DTA (Daimler Trucks Asia), 270–272
Dynamic fulfillment, 185–204, 187f
and DSN, 187–188
impact of digital transformation on, 8–9
supply chain and traditional fulfillment, 185–187
technologies for, 191–203
Dynamic visibility, 170
E. coli outbreaks, tracing, 96
Edge computing, 65
EDI (electronic data interchange), 2, 63
Education:
provided during DSN transformation, 246–247
for workforce, 230, 232, 236–238
Efficiency:
and asset maintenance strategy, 179f
and cost, 96–97
improved, in digital transformation, 4–5
in sourcing practices, 144
ELD (electronic logging devices) requirements, 269
Electronic automation:
information and communication technologies in, 15
as wave of industrial change, 11
Electronic data interchange (EDI), 2, 63
Electronic logging devices (ELD) requirements, 269
Electronic Product Code Information Services (EPCIS), 63
Employees, in DSN transformation, 251 (See also Workforce)
End-of-life (EOL) applications, 130
End-to-end planning model, 112–114, 113f
End-to-end transparency, 45f, 46
in synchronized planning, 120
at T-Moblie, 262–263
“Enterprise brain,” 117
Enterprise resource planning (ERP):
in digital transformation, 2, 14–15
in fulfillment, 186
and procurement, 142
Entrepreneurial mindset, 233–234, 237, 255–257
Environment, in DSN transformation, 253
EOL (end-of-life) applications, 130
EPCIS (Electronic Product Code Information Services), 63
Equity, in contract management, 150
ERP (see Enterprise resource planning (ERP))
European Union (EU):
data-related policies and laws in, 62, 62t
skills gap in, 230
Evolution, in DSN transformation, 249, 253
External data, in intelligent supply, 154
Factory automation, 171
Feedback, from customers, 210
Field service network, 220–221
First industrial revolution, 164, 165f
Fleck, Jeff, 258
Fleet management:
autonomous mobile robots in, 196
at Maven Machines Inc., 269–270
Flexibility, 97–98
Flows, in traditional SCM, 17f
Fog computing, 65
Footwear industry, 138–139
“Formal Relational Contracts,” 149–150
Foundational technology, 99
“Fourth industrial revolution,” 164, 165f
Frydlinger, D., 149
Gartner Supply Chain Masters category, 265
Geller, Avishai, 269
General artificial intelligence (AI), 72–73
“Genesis blocks,” 93
Georgia-Pacific, 257–258
Germany:
data-related policies and laws in, 62
smart manufacturing in, 164
technology and employment in, 228–229
Healthcare, 225
Heuristic planning engines, 121
Holistic decision making, 45f, 46
Honesty, in contract management, 149–150
Hybrid clouds, 66–67
IBM, 102–103
IBP (integrated business planning), 106, 107f
Identification (in DSN transformation), 247–248
Immersive technology, 40f
Immutability , with blockchain, 98
Industrial Internet (II)/IIot platforms, 66, 173–174, 175f
Industrial Internet of Things (IIoT), 169, 173–174, 174f, 177
Industrial product service systems, 135–138
Industrial product service systems (IPSS), 136
Industry 1.0, 164
Industry 2.0, 164
Industry 3.0, 164
Industry 4.0, 160–168
Information:
flow of, in traditional SCM, 16–17
sharing, with customers, 207, 209
Information and communication technologies:
in DSNs, 19
in supply chain management evolution, 15
Information technology (IT):
in smart manufacturing, 160, 161f
in third industrial revolution, 164
Innovation:
at Amazon, 255–257
disruptive, 99
in intelligent supply, 156
manufacturing, 129f
in supply networks, 151
Insights:
in digital stack, 32
in monitoring of customer experience, 218–219
Integrated business planning (IBP), 106, 107f
Integrated sensor systems, 134
Integration, in DSN transformation, 248
Integrity, in contract management, 150
Intelligence, levels of, 131–132
Intelligent asset management, 178–183
Intelligent contract management, 149–150
Intelligent manufacturing, 164 (See also Smart manufacturing)
Intelligent optimization, 45f, 46
Intelligent product tracking, 219–220
Intelligent spare parts management, 182–183
Intelligent supply, 141–157
automation in, 153–157
capabilities of, 146–152, 153f
and digital procurement, 144–146
in DSNs, 155f
impact of digital transformation on, 8
and traditional procurement concepts, 141–144
Interconnected ecosystem signaling, 188–189
Internal synchronization, 112, 113f
International Data Spaces Association, 61
International Federation of Robotics, 232
International trade, 96–97
Internet of Things (IoT), 39, 40f, 173, 174f
and Daimler Trucks Asia, 271
dynamic fulfillment, 201–202
and Maven Machines Inc., 269
used by Walmart Canada, 259–260
Intranet infrastructure, 65–66
IPSS( industrial product service systems), 136
ISO 10303, 63
IT (see Information technology (IT))
Jet engine production, 139
Koch Industries, 257
Land O’Lakes, Inc., 260–261
Large multinational enterprises (MNEs), 166–167, 167t
Last mile delivery, 196–199
LaValle, Erik, 262–263
Laws, related to data, 61–62, 62t
Leadership, in DSN transformation, 246–247, 250–251
Learning mindset, 237
Leverage suppliers, 143f
Liability, with AI, ML, and robotics, 85
Line fill rate, 210
Linearity, of traditional SCM, 18–19
Local computing, 65–66
Logistics, 13
Loyalty:
in contract management, 149–150
of customers, 217–218
Machine learning (ML), 72–78, 82–87
algorithms for (see Machine learning algorithms)
application process for, 77f, 78
applications of, 83–84
and artificial intelligence, 72–75, 74f
artificial intelligence vs., 73f
benefits of, 86
challenges for, 85
as enabling technology, 36
levels of, 79f
predictions about, 82–83
Machine learning algorithms, 75–78
in intelligent spare parts management, 182
in intelligent supply, 145
Machine teams, 48
Made in China 2025, 232
Manufacturing innovation, 129f
Manufacturing resource planning (MRP II), 14
Manufacturing systems, 165f
Master data, in intelligent supply, 154
Master production schedule (MPS), 108
Material requirements planning (MRP I), 14
Maven Machines Inc, 269–270
McAfee, A., 229–230
Mechanization, 10–11
Metcalfe’s law, 70
Meyer, G. G., 131
Middle-of-life (MOL) applications, 130
Minimum viable product (MVP), 248
MIT Sloan Management Review, 237
ML (see Machine learning (ML))
MNEs (large multinational enterprises), 166–167, 167t
Model-based manufacturing, 129f
Model-based product definition, 129f
MOL (middle-of-life) applications, 130
Monitoring, of customer experience, 218–220
Moore’s law, 70
MPS (master production schedule), 108
MRP I (material requirements planning), 14
MRP II (manufacturing resource planning), 14
MTConnect, 63
Multichannel management, 211
Multi-matrix organization, 115, 116f
MVP (minimum viable product), 248
Network collaboration platforms, 154
Network designs, for blockchain, 94–95
Networks, in DSN transformation, 253
New product and services development (NPSD), 126–128, 127f
New product development (NPD), 126–128
Nike Inc., 268–269
Nonownership business models, 53, 137–138
Nonrelational databases, 58
NPD (new product development), 126–128
NPSD (new product and services development), 126–128, 127f
OECD (Organization for Economic Cooperation and Development), 12
OEE (see Overall equipment effectiveness (OEE))
Omni-channel competency, 190
On time in full (OTIF) metric, 152
Open Application Group Integration Specification (OAGIS), 63
Operating processes, 4–5
Operational technology (OT), 160, 161f
Operations:
driven by data, 52
optimum, 171
picking, 199–200
smart delivery, 191
smart distribution, 190
Optimization:
as digital discipline, 29
Optimization planning engines, 121
Optimum operations, 171
Order fill rate, 210
Organization for Economic Cooperation and Development (OECD), 12
Organizations:
adaption of, in digital transformation, 47–48
DSN transformation in, 246–247
impact of DSN on, 47f
plans for workforce changes, 232
synchronized planning in, 119–122
viewing suppliers as strategic partners, 146
OT (operational technology), 160, 161f
OTIF (on time in full) metric, 152
Overall equipment effectiveness (OEE):
and asset maintenance strategy, 179f
in intelligent asset management, 178
Owen, Loudon, 259
Ownership, of data, 60–61
P2P (procure to pay), 141
P2P (peer-to-peer) architecture, 92
PaaS (Products as a Service), 217–218
Packing, as complex skill, 234
Partners:
in DSN transformation, 253
Peer-to-peer (P2P) architecture, 92
Permissioned blockchains, 94–95
Permissionless blockchains, 94–95
Personalization:
and connected customers, 205–209, 206f, 213
of customer experience, 216–217
with digital product development, 138–139
at Nike Inc., 268
Physical automation:
artificial intelligence and machine learning in, 84
examples of, 71t
Physical-to-digital-to-physical loop, 34–35, 34f
Pick optimization, 196
Picking:
and packing, 234
technology-enabled, 199–201
Planning:
computer-aided process, 130
concurrent, 110
in DSNs, 21
end-to-end planning model, 112–114
enterprise resource (see Enterprise resource planning [ERP])
integrated business, 106, 107f
manufacturing resource, 14
material requirements, 14
of robotics applications, 80–81
sales and operations (see Sales and operations planning [S&OP])
sequential, 110
supply (see Supply planning)
supply chain, 119
synchronized (see Synchronized planning)
in traditional SCM, 18
Platforms:
created by Maven Machines Inc., 270
developed by WinField United, 261
DSN transformation supported by, 244
Industrial Internet (II)/IIot, 66, 173–174, 175f
network collaboration, 154
PLM (product lifecycle management) systems, 130
Policies, related to data, 61–62, 62t
POs (purchasing orders), 148
Predictive capabilities, 188
Predictive maintenance strategies, 179–180
Predictive modeling, 180–182
Predictive strategic sourcing, 156
Preprocessing stage, machine learning in, 77–78
Prescriptive maintenance strategies, 179–180
Preventive maintenance strategies, 178–179
Private blockchains, 94
Proactive sensing, 270–272, 271f
Problem-solving capabilities, 234
Processes:
creating paperless, with blockchain, 96–97
for digital development, 126–128
impact of digital transformation on, 8–9
in traditional SCM, 17f
Procure to pay (P2P), 141
Procurement activities (See also Intelligent supply)
in digital age, 144–146
digital transformation of, 145f
traditional, 142–143
Product development, 17 (See also Digital development)
Product lifecycle management (PLM) systems, 130
Product service systems (PSS), 136–138
Product tracking, 219–220
Products, as solution, 217–218
Products as a Service (PaaS), 217–218
Provenance, 95–96
Public blockchains, 94
Purchasing orders (POs), 148
Rada, J., 137
Rapid design optimization, 129f
RDBMS (relational database management system), 58
Reactive maintenance strategies, 178–179
Real-time collaboration, 129f
Real-time digital replicas, 110–111
Real-time product intelligence, 129f
Real-time response, to data, 117
Reciprocity, in contract management, 149
Record keeping, with Blockchain, 42
Regression, in machine learning, 76
Regulations, in DSN transformation, 252
Reinforcement machine learning (ML), 75
Relational database management system (RDBMS), 58
Remaining useful life (RUL), 178
Republic of Korea, 232
Resource optimization, 26, 46 (See also Intelligent optimization)
Response, as digital discipline, 29
Retail, 206–207
Retail strategy, 263–264
Retraining programs, 238
Revenue, 5–6
RFID tags, 192
Risk management, 252
and automation, 78–82
benefits of, 86
challenges for, 85
in dynamic fulfillment, 193t
as enabling technology, 40–41, 41f
joining with workforce, 228
lack of social intelligence skills in, 235
in last mile delivery, 198–199
levels of, 79f
predictions about, 82–83
and workforce, 226
Robotics process automation (RPA) capabilities, 36, 156
RUL (remaining useful life), 178
S2P (source to pay), 141
S2S (source to settle), 141
Sales and operations planning (S&OP), 107f
at Georgia-Pacific, 257
and synchronized planning, 106–108
in traditional SCM, 17
Scale, in DSN transformation, 249
Scandinavia, 62
Schwab, 12
Science, DSN guided by, 244
SCM (see Supply chain management (SCM))
SCOR (supply chain operations reference model), 15, 126
Second industrial revolution, 164, 165f
Security (See also Cybersecurity)
and blockchains, 103
in digital stack, 31
Selection, in DSN transformation, 248
Self-driving trucking capabilities, 71–72
Self-service network, 220–221
Semi-structured data, 57f, 58t
Sense, as digital discipline, 28
Sensors:
in autonomous mobile robots, 195
at Daimler Trucks Asia, 270–272
in dynamic fulfillment, 188
integrated sensor systems, 134
in physical-to-digital-to-physical loop, 35
in smart manufacturing environments, 179–180
in warehouse automation systems, 201
Sequential planning, 110
Servitization, 135–138
Shipping industry:
improving efficiency of, 96–97
new processes necessary for, 269–270
transparency with, 258–260
Skills development, 251
SKU portfolios, 109
Small- and medium-sized enterprises (SMEs), 166–167, 167t
Smart contracts:
in intelligent supply, 150
used by Walmart Canada, 259–260
Smart delivery operations, 191
Smart devices, 4
Smart distribution operations, 190
Smart factory, 163f (See also Smart manufacturing)
Smart manufacturing, 159–183
and advanced manufacturing, 166f
capabilities of, 170–171
core principles of, 168–170
defining, 165
impact of digital transformation on, 8
and Industry 4.0, 160–168
and intelligent asset management, 178–183
technologies for, 171–178, 172f
Smart network design, 191
Smart sourcing execution, 146–149
Smart-connected products:
challenges and barriers for, 131–132, 133t
digital development for, 131–134
jet engines as, 139
Smartsense IoT platform, 270
SMEs (small- and medium-sized enterprises), 166–167, 167t
Social impact, of DSN transformation, 253
Social inequality, 225–226
Social intelligence skills, 235
Social media, 55
Socio-emotional skills, 235
S&OP (see Sales and operations planning (S&OP))
Source to pay (S2P), 141
Source to settle (S2S), 141
Spare parts management, 182–183
Specific artificial intelligence (AI), 72–73
Spend cube, 145
SQL (Structured Query Language), 58
Stakeholders’ expectations, 6–7
Storage:
of data types, 58
local, 65–66
Strategic data, 154
Strategic skill sets, 232–235
Strategic suppliers, 143f
Structured data, 57–59, 57f, 58t
Structured Query Language (SQL), 58
Supervised machine learning (ML), 75–76, 76f
Supplier network collaboration, 151–152
Suppliers:
analytics for, 152
identification and onboardng of new, 148
proactive management of, 157
viewing as strategic partners, 144
Supply chain management (SCM), 16–18
artificial intelligence and machine learning in, 84
challenges of, 18–19
collaboration necessary for, 98–99
collapse of linear, 23–24
customer processes in, 208f, 209–214
defined, 2
and digital transformation, 16–19
processes and flows in, 17f
recent evolution in, 13–16, 13f
smartification of, 19–21
and traditional fulfillment, 185–187
Supply chain model, linear, 24f
Supply chain operations reference model (SCOR), 15, 126
Supply chain optimization, 15
Supply chain planning, 119
Supply chains:
collaboration necessary for, 98–99
unplanned outages in, 115
Supply network design, 111–112
Supply network traceability, 189–190
Supply planning, 108
functional requirements in, 121
Synchronized planning, 105–123, 118f
benefits of, 114–115
capabilities of, 109–111
enablement of, 115–119
end-to-end planning model for, 112–114
need for, 109
organizational considerations for, 119–122
supply network design for, 111–112
and traditional sales and operations planning, 106–108
Tactical suppliers, 143f
Talent:
adaption of, in digital transformation, 47
impact of DSN on, 47f
Technological displacement, 226–227
Technologies:
and artificial intelligence, 70f, 71f
for connected customers, 214–215
for connected field service, 221
in digital transformation, 47
digital transformation of traditional SCM with, 3
disruption caused by, 225–226
disruption from, 1
in DSN transformation, 242–245, 245f, 252
for dynamic fulfillment, 191–203
impact of digital transformation on, 9
impact of DSN on, 47f
information and communication, 15, 19
rapid development of, 70
for smart manufacturing, 171–178, 172f
for smartification of traditional SCM, 19
for synchronized planning, 121–122
testing of, 248
Technology-enabled picking, 199–201
Third industrial revolution, 164, 165f
3D design system, 269
3D printing (additive manufacturing), 38, 39f
in blockchains, 90–91
at Nike Inc., 269
360 degrees technology, 40f
Tiers, in digital transformation, 47–48
Time horizon, of traditional SCM, 106, 108
T-Mobile, 261–263
Total cost of ownership, 146
Toyota Production System, 20
Traceability, 95–96
Tracking, of customer experience, 218–220
Traditional fulfillment, 185–187
Traditional procurement concepts, 141–144
Traditional product development, 126
Traditional supply chain management (see Supply chain management (SCM))
Training:
in DSN transformation, 251
provided during DSN transformation, 246–247
Transaction data, in intelligent supply, 154
Transformative applications, 99–100
Transparency:
in DSNs, 25
in dynamic fulfillment, 189–190
in smart manufacturing, 169
at T-Moblie, 262–263
at Walmart Canada, 258–260
Transportation, 193–194
Trust, in blockchains, 94–95
UAVs (unmanned aerial vehicles), 41, 192–194, 193t
Uncertainty, in traditional SCM, 17–18
Unilever, 264–266
Unit fill rate, 209–210
United Kingdom, 229
United States:
data-related policies and laws in, 62, 62t
skills gap in, 230
technology and employment in, 228–229
Unmanned aerial vehicles (UAVs), 41, 192–194, 193t
Unstructured data, 57–59, 57f, 58t
Unsupervised machine learning (ML), 75–76, 76f
Use cases, 255–272
Amazon, 255–257
Caterpillar, 266–268
Daimler Trucks Asia, 270–272
Georgia-Pacific, 257–258
Land O’Lakes, Inc., 260–261
Maven Machines Inc., 269–270
Nike Inc., 268–269
for synchronized planning, 121–122
T-Mobile, 261–263
Unilever, 264–266
Walmart Canada, 258–260
Valinhos, Brazil, 265
Value:
and big data, 56
considering, in DSN approach, 242
created, in DSN transformation, 247
Value chain, 114
Value-added relationships, with customers, 7
Vandermerwe, S., 137
Variability, 56
Variety, 55
Velocity, 55
Veracity, 55–56
Virtual reality (VR), 39–40, 40f
in cargo loading, 200f
in digital product development, 130
wearable technology as, 199
Virtualization, 169
Visibility:
in dynamic fulfillment, 189–190
improving, with blockchain, 97–98
at T-Moblie, 262–263
Vision picking, 199–201
Visualization:
and big data, 56–57
in smart manufacturing, 169
Volume, 55
VR (see Virtual reality (VR))
Walmart, 95
Walmart Canada, 258–260
Walmart China, 264
Warehouse automation systems, 201
Waves of industrial and economic change, 9–16, 10f
Wearable technology, 199–201
WinField United, 260–261
Wong, C. Y., 131
Workflow, automated, 117
Workforce, 225–238
changes in, due to automation, 83
changes in, for synchronized planning, 120, 120t
effects of digital technology on, 225–230, 227f
future directions for, 236–238
strategic skill sets for, 232–235
World Manufacturing Forum report (2019), 83