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Supply Chain 4.0 –Digitization of the Supply Chain May 9th, 2018

2McKinsey & Company

What do we mean by digital?

SOURCE: McKinsey, External Expert Interviews

Data,

computational

power, and

connectivity

Analytics

and

intelligence

Human

machine

interaction

Digital-to-

physical

conversion

3McKinsey & Company

Does digital matter to our supply chains?

SOURCE: SC 4.0 Innovation survey – responses from 76 experts from different sectors

OM&D EnablePlan

5 Automation of planning/ machine-

learning

1 Autonomous container

2 Human-free container ships

3 Fully autonomous (driverless) truck

4 Ergonomic exoskeletons

6 Augmented reality assistance for truck

driving and delivery activities

7 Drones for delivery

8 Real-time and mobile S&OP

9 Micro-segmentation

10 Automated profit-optimization in

planning

11 Early warning system for SC risks

and deviations

12 Nearly autonomous truck and truck

convoying systems

13 Cloud logistics platform

14 3D printing for slow movers

15 Joint planning in cloud

16 Predictive shipping

17 Delivery to trunk of car

Adoption rate

1 2 3 4 5

68 9

1011

12

13

14

15

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33 35

36

37

38

39

40

44

45

4647

48 4950

51

52

53

3441

42

43

7

16

18 Closed-loop planning

19 Dynamic end-to-end network

optimization and warehouse design

20 Data mining and automated root-

cause analysis for performance

management

21 Range imaging sensor systems

22 Fully automated ITEM picking/

Robotics

23 Real-time performance transparency

and target adjustment

24 Real-time re-planning

25 Uberization of transport

26 Gesture and motion tracking

27 Wearable user interfaces/

Smart glasses

28 Optimizing shipping by influencing

customer order behavior

29 Analytical evaluation of manual inputs

to demand forecasts

30 No-touch order processing

Vision Technological

pre-requesites developed

Innovation

developed

Pilot use Selective use Broad use

(or failure)

Cycle

stages

1 2 3 4 5 6

We surveyed 76 Supply Chain experts

with a combined prof experience of 1000

years from different industries on

▪ Current state in cycle

▪ Time to broad use/pilot

Failure

31 Predictive maintenance

and augmented reality maintenance

assistance

32 ATP based on real-time constraints

33 Real time point-of consumption

inventory tracking

34 Predicting optimal delivery times

35 Information platforms

37 Smart packaging

36 Smart shelves

39 Location and condition control

38 Online auction of logistic capacity

41 Fully automated CASE picking/

Robotics

42 Use of demand probability

distributions

40 Predictive analytics in demand

planning

43 Advanced Warehouse

Resource Planning &

Scheduling

44 GPS-based map generation &

customer location determination

45 Asset utilization & yard manage-

ment for logistics assets

46 Onboard units for economic

driving

47 Advanced Transport

Management Software (TMS)

and dynamic

routing and load identification

48 AGV-based goods-to-man

solutions

49 Smart public and personal parcel

lockers

51 Vehicle tracking and data mining

50 Automated replenishment

53 Online order monitoring

52 AGV solutions for internal transport

Broad

use

4McKinsey & Company

Some of digital innovations –we are told – could be game changers

SOURCE: SC 4.0 Innovation survey – responses from 76 McKinsey and industry experts,

Average impact potential along low-high and optimization-disruptive axes

▪ AGV-based goods-to-man

solutions

▪ Ergonomic exoskeletons

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100

Disruptive change (vs. optimizing) expected

Percent

High impact expected

Percent

8 tweaks to existing processes

4 niche applications

34 high impact optimization of existing processes (5 highest listed)

7 game-changers

▪ Cloud logistics platform

▪ Joint planning in cloud

▪ Information platforms

▪ Automation of planning/

machine-learning

▪ Nearly autonomous truck and truck

convoying systems

▪ Fully autonomous (driverless) trucks

▪ 3D printing for slow movers

▪ No-touch order processing

▪ Uberization of transport

▪ Online order monitoring

▪ Closed-loop planning

▪ Real-time performance transparency

and target adjustment

▪ AGV solutions for internal

transport

▪ Gesture and motion

tracking

▪ Micro-segmentation

▪ Onboard units for economic driving

▪ Smart public and personal

parcel lockers

▪ Delivery to trunk of car

▪ Predictive shipping

▪ Asset utilization & yard management

for logistics assets

▪ Drones for delivery

▪ Autonomous container

5McKinsey & Company 5

Customer Order Logistics Planning Manufacturing

Overall digital could secure new levels of connectivity, optimisation and automation

Multi-data

source

forecasting

Transparent

“availability to

promise”

Digital Control

Tower

Cross site/cross

supply chain

optimisation1 3 5 7 10

Big data

assured

differentiated

pricing

No touch

replenishment

New logistics

options

Machine learning

for safety stocks2 4 6 8 9

Continuously

optimized network

Margin

optimizing S&OP

6McKinsey & Company

A first glimpse: forecasting

1 Next 30 weeks + next 7 months

SOURCE: McKinsey; Blue Yonder

150,000,000 probability distributions of expected demand calculated every day

130,000articles

3years of history

40prediction horizons1

200+ influencing variables

7McKinsey & Company

A second glimpse: no touch closed loop demand and replenishment management

SOURCE: McKinsey

Only ~0,1% of daily

replenishment

decisions (120.000+)

are touched by a

planner - how could

this look like for you?

Demand

forecasting

Price, promotion,

and channel

optimization

Fully integrated

and automated

Replenish-

ment

Inventory

allocation and

optimization

8McKinsey & Company

And now a deep dive: how can digital help us improve a complex cross-functional process like a supply chain

SOURCE: Cognite

Horizontal data platform

Applications

Data layer

Data sources

Standard access

regardless of assets

9McKinsey & Company

Gathering data is one challenge but so too is creating a context for that data –as we have learned from our partner Cognite

SOURCE: Cognite

Other context: weather, satellite images, maps++

Maintenance logs, ERP data

3D models

Process diagrams

Sensor

values

Sensor

metadata

Equipment hierarchy

Physical Process Digital Twin

3D Digital Twin – from equipment

to entire asset

Real time replica

of sensor values

Models (e.g. predictive

Maintenance)

10McKinsey & Company

We are now going to look at how to manage flows of oil –but the same principles could apply to flows of orders in a supply chain

SOURCE: McKinsey

https://www.youtube.com/watch?v=RPNab0o38nc&t=0s&list=PLpPSwTUsTLWlEE-c4lB_lP742N2NCYccE&index=5

11McKinsey & Company

What to do next? Perhaps run a maturity assessment along the major Supply Chain dimensions to assess the digital opportunity?

41 5 11 1 21 1 5 2 1 1

15 1 33 2 11 4 3 1 4 3

31 2 14 5 11 3 2 1 3 4

41 5 11 1 21 1 4 2 1 1

15 1 33 2 11 4 3 1 4 3

Network

design

SC

segmen-

tation

Sched-

uling

S&OP

Integra-ted

bus. Plan-

ning

Demand

planning

Inventory

mgmt

Master

planning

Ware-

house

operation

Transport

operation

Assess-

ment &

tender of

logisticsOrder

mgmt

Collab-

oration

Perfor-

mance

mgmt

Enablers Mindset &

CapabilitiesSC organization SC IT

SOURCE: McKinsey

Analytics

Data

Software/

hardware

People

Process

ScoreX

SC Strategy Planning Physical flow