The presentation discusses the future of supply chain management. It argues that current supply chain processes are flawed in that they are designed for machines but use humans, assume more information always leads to better decisions, rely on batch processing, and feature isolated data exchange between partners. The presentation proposes designing processes that recognize human cognitive limitations, focus on information-centric rather than human-centric processes, enable real-time response, and facilitate integrated planning across partners through virtual marketplaces. Adopting these approaches could significantly improve metrics like profitability, utilization, sales and customer ratings.

1. BJORN MADSEN
The Future of Supply Chain
All statements are the personal view of the presenter and should not be associated with any organisation or individual mentioned. SCL Event has not been asked for permission, nor will accept liability in any connection with the
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2. The Future of Supply Chain
Source: http://coolvibe.com/2010/paris-year-3000/

3. We Can Predict
The Future of Supply Chain
By Inventing It
Source: http://coolvibe.com/2010/paris-year-3000/

4. MAIN PROBLEM:
To make the MOST PRODUCTIVE INTERVENTION, we need to
TRANSFORM INFORMATION
into
DECISIONS
but we keep designing our processes with 4 fundamentals flaws
that inhibit our ability to deliver results.
Source: http://coolvibe.com/2010/paris-year-3000/

5. We design business processes We assume more information
for perfect machines, but use gives better decisions but dazzle
humans that fail at 400ppm decision-makers who
do not have time to attend to it
TRANSFORM INFORMATION
into
DECISIONS
We leave other decision-makers We spend trillions of $ on systems
waiting for the information we & system integration but send
need by queuing information to be spreadsheets with email to get
processed in large batches data to justify decisions

6. PROBLEM 1:
Design: Human
Problem: Limited Management
Attention Time

8. PROBLEM 1:
PAST PRESENT FUTURE
Simple & Tacit Problems Complicated Problems Complex Explicit Problems
Human Superior Human ≡ Computer Computer Superior

9. PROBLEM 2:
Design: Human Centric Processes
& Distributed Information
Problem: Poor Utilisation of Data

10. “No single person, in any
transport office has an overview
of the demand, beyond our own
region.”
“Management DazzleBoards give
us no better coordination. They
rather, distract us.”
A
B

11. “Office A would like to
make better decisions;
And so would Office B.”
“So we give them the
same tools to exploit“,
A
“...and cheat them by
pulling their data to show
the joint case of
AB
collaboration...” B

12. A
AB
B

13. profit profit
100%
100%
A
Internal
market
B

14. profit profit
100%
100%
profit
100%
A
Internal
market
B

15. For the UK Based Operator, the
experiment resulted in an
increase in vehicle
utilisation from
43% to 64%.
“The study makes it clear that
policy depends on facts.
Making policy and hoping that it
becomes fact, is the wrong way
around.”

16. PROBLEM 2:
PAST PRESENT FUTURE
Limited Information Abundant Information Noisy Information
Human Centric Processes ? Information Centric Processes
CONSUMER = PRODUCER

17. PROBLEM 3:
Design: Batch-Processing
Problem: Delay;
Not Real-time

20. Data production rate
( Longest Queue Time + Run-Time ) * Chain Length = Total Delay
Queue length
Growing Queue
Computer Run-time
= larger problem:
Time
= longer runtime
Assignment
problem
Time
Data volume
= queue length

22. “Play-back” using the business’ own data
FRAMEWORK
We know today’s results
We know X % of how today works Very complex noise pattern (humans involved)
...But we don’t know how big X actually is... We know today’s processes
We mapped every process because we
built their existing decision support tools
Professional Judgment of
“when good is good enough”
We imitate today’s processes
...by using our scheduler and adding real-world constraints
This defines our Base Case
We replicate today’s results
Decision Making Trend line Stochastic Cheating*
Model Forecasting Forecasting
Base Case A B C 1
Real-time 2 Remove constraints that
inhibit responsiveness
Real-time + 3
Flexible Bus.
Processes * We load future data to
= 9+1 cases get the result of having a
Improve decision making method perfect forecast

23. Profit Potential
– And how to achieve it
Ideal forecast
100% 88% 82% 81% (un-realistic)
Upper Limit 90%
for practice
Probabilistic
81% 76% 66% forecast
Trendline
76% 61% 56%
adjustment
Real-time Current
Perfect scheduling Real-time
Scheduling Scheduling
(un-realistic) Scheduling
Flex. Process Practice

24. Profit Service Lost Revenue Cost
Case
(of max) Level (of max Profit) (of min for all demands)
Theoretical Ideal (un-realistic) 100% 100% 0% 100%
A. Real-time scheduling w. flex. process
1. Ideal forecast 88% 90% 10% 102%
A. Real-time scheduling w. flex. process
2. Probability oscillating forecast 81% 86% 16% 105% Achievable!
A. Real-time scheduling w. flex. process
3. Trend forecast 76% 86% 20% 105%
B. Real-time scheduling
1. Ideal forecast 82% 83% 17% 96%
B. Real-time scheduling
2. Probability oscillating forecast 76% 79% 22% 96%
B. Real-time scheduling
3. Trend forecast 61% 71% 35% 96%
C. Regular scheduling
1. Ideal forecast 81% 82% 17% 96%
C. Regular scheduling
2. Probability oscillating forecast 66% 69% 31% 95%
C. Regular scheduling
56% 66% 40% 95% Current
3. Trend forecast
Practice!

25. PROBLEM 3:
PAST PRESENT FUTURE
Waiting for information Waiting for answers Real-time Response
Larger Batches + Never Ending
Batch Processing
Exponential Runtime Stream of Updates

26. PROBLEM 4:
Google image search: robot vs human
Design: Process Dependency
Problem: Data Exchange
is Not Integration

27. Schedules
X B A C A B
Y C B A
time X Y

28. Schedules
X B A C A B
Y C B A
time X Y
Change of order: Produce more “C”

29. Schedules
X B A C A B
Y C B A
time X Y
Change of order: Produce more “C”
X/Y orders Scheduling
Company

30. Schedules
X B A C A B
Y C B A
time X Y
Change of order: Produce more “C”
X/Y orders Scheduling
Company
Collective Optimization under Conditions of Pure Competition.
91% of market driven disruptions are gone.
Customer Experience: “...The Industry has improved its responsiveness...”

31. PROBLEM 4:
PAST PRESENT FUTURE
Isolated Actions Partner Alliances Virtual Marketplace in Industry
Tier Based Competition Tier Based Collaboration Market-wide collaboration
Google image search: robot vs human
Google image search: networks

32. Google image search: robot vs human
40 seconds recap

33. The Future of the Supply Chain... Impact...
...See’s management attention as a scarce resource! Human performance limited to
Humans for tacit & simple problems, 78% - 82% of true potential in
Computers for explicit & complex problems. your systems. Google image search: robot vs human
...Shift’s towards Information Centric Processes
with of the shelf software. Human Centric Processes From 43% To 63% Utilisation.
are evidently poorly coordinated
...Needs information processing in a batch of one +25%point profit,
everywhere. Delay of information is simply too +20%point service,
expensive. +24%point sales.
...eliminates silo-planning through market wide +8% sales at no additional cost.
system integration. Joint operational planning can From 3.1 to 4.4 of 5 in customer
literally change the market over night. rating

34. Google image search: robot vs human
But that’s not all...

35. LESSON
LEARNED:
Pre-requisites:
1. Profound understanding of the situation.
2. Can conceive an experiment that
increases productivity immediately.
Google image search: robot vs human
3. Authorised & self-powered.

36. Research, Development & Deployment
of a supply chain
is a supply chain!
Staff it!
Invent it!
Manage it!
Thank You!

37. The Future of the Supply Chain... ...Impact...
...See’s management attention as a scarce resource! Human performance limited to 78%
Humans for tacit & simple problems, - 82% of true potential in your
Computers for explicit & complex problems. systems.
...Shift’s towards Information Centric Processes
Executive Resume
with of the shelf software. Human Centric Processes are From 43% To 63% Utilisation.
evidently poorly coordinated
+25%point profit,
...Needs information processing in a batch of one
+20%point service,
everywhere. Delay of information is simply too expensive.
+24%point sales.
...eliminates silo-planning through system integration. Joint +8% sales at no additional cost.
operational planning can benefit the local industry in From 3.1 to 4.4 of 5 in customer
competition on a global market. rating