This document discusses DSV's IT strategy and whether Kafka can help deliver its goals. DSV is a global freight forwarding and logistics company with over 75,000 employees. Its IT strategy focuses on (1) integrating current operations, (2) being ready for acquisitions by quickly integrating new companies, and (3) digital innovation. Kafka could help with integration challenges during acquisitions by enabling real-time data sharing between systems. It could also power new digital products by providing a live data feed. However, Kafka requires significant work to implement properly as a platform and may not be a complete solution on its own. Non-functional requirements, data modeling, and building out capabilities would be challenges to address.

1. 1 | October 2022, Stockholm, Andreas R. Hyllested
Does Kafka deliver what is
needed?

2. 2 | October 2022, Stockholm, Andreas R. Hyllested
The Architect
Andreas Rishede Hyllested
Senior Enterprise Architect
andreas.rishede.hyllested@dsv.com
17 years in
* Development
* Business Consulting
* Architecture
Today
* Architecting the Enterprise

3. 3 | October 2022, Stockholm, Andreas R. Hyllested
What is DSV doing?

4. 4 | October 2022, Stockholm, Andreas R. Hyllested
Running the supply chain
To consignee
From shipper
Freight forwarding services
Shipment booking — Pick-up — Warehouse — Documentation
& customs clearance — Cargo consolidation — Purchase order
management — Cross-dock terminal — Insurance Transport
Subcontracted
Logistics and distribution
Warehousing — Picking/packing — Cross-dock terminal —
Deconsolidation — Labelling, configuration, testing — Distribution
Documentation & customs clearance — E-commerce fulfilment — Carbon
emission reports — Supply Chain innovation — 4PL

5. 5 | October 2022, Stockholm, Andreas R. Hyllested
Global footprint
More than 75,000
employees in over 90
countries
3rd largest
freight forwarder globally
+1,500 offices &
logistics facilities
DKK 182 billion
in annual revenue
Gross profit split on main activities
Air & Sea Road Solutions
63% 19% 18%

6. 6 | October 2022, Stockholm, Andreas R. Hyllested
Customers across all industrues
Healthcare
Retail & Fashion
Technology
Industrial
Renewable Energy
Specialised Air & Sea
verticals
Chemicals
Oil and Gas
Fairs and Events
Project Logistics
Aerospace
Automotive

7. 7 | October 2022, Stockholm, Andreas R. Hyllested
IT Strategy

8. 8 | October 2022, Stockholm, Andreas R. Hyllested
DSV IT Strategy
01
Current operations
02
Acquisition ready
03
Digital innovation
Focus areas

9. 9 | October 2022, Stockholm, Andreas R. Hyllested
01 Current
operations

10. 10 | October 2022, Stockholm, Andreas R. Hyllested
Current operations: Integrations
* This is where we earn the money
* A few thousand apps
* ESB message-based integration
* Centralized teams with knowledge of how to integrate
* Strong governance and control
* Is this where we throw in Kafka?
* Not all at once
=> But maybe if we get data out?
SOR
SOR
SOR

11. 11 | October 2022, Stockholm, Andreas R. Hyllested
02 Acquisition Ready

12. 12 | October 2022, Stockholm, Andreas R. Hyllested
78%
11%
11%
1997
Breakdown of EBIT by division
Air & Sea
Road
Solutions
Breakdown of EBIT by geography
EMEA
Americas
APAC
DSV acquired Samson
Transport
2,694 DKKm
Revenue
98 DKKm
EBIT
1976
10 independent
hauliers established
DSV
2000
DSV acquired
DFDS Dan
Transport Group
19,478 DKKm
Revenue
854 DKKm
EBIT
67,747 DKKm
Revenue
2016
3,475 DKKm
EBIT
DSV acquired
UTi Worldwide
2008
37,435 DKKm
Revenue
1,936 DKKm
EBIT
DSV acquired
ABX LOGISTICS
DSV acquired
Frans Maas
2006
31,972 DKKm
Revenue
1,504 DKKm
EBIT
From local haulier to global player
A global network created through organic growth and M&A
115,932 DKKm
Revenue
In 2019, DSV
acquired
Panalpina
2020
9,520 DKKm
EBIT
2021
182,306 DKKm
Revenue
In August 2021,
DSV acquired
Agility GIL
16,223 DKKm
EBIT
38%
59%
3%
100%

13. 13 | October 2022, Stockholm, Andreas R. Hyllested
Mergers must be swift
Large integrations limit our ability to take market share
* Overlapping customers
* Less internal focus on sale
* Integration seen as a risk from customer perspective
* Data quality
* Discontinued low margin business
02
Acquisition ready

14. 14 | October 2022, Stockholm, Andreas R. Hyllested
Kafka in M&A
SOR
SOR
SOR
SOR
SOR
SOR
?
* In the past solved with ESB
technology - Biztalk
* We need to build a blueprint for
deploying Kafka clusters for M&A
activity
* Feed live data back and forth
* Sever the connection earlier and
focus on business integration

15. 15 | October 2022, Stockholm, Andreas R. Hyllested
03 Digital Innovation

16. 16 | October 2022, Stockholm, Andreas R. Hyllested
Technology Radar
Tracking
Testing
Adopting
Self-driving
vehicles
5G
network
Micro
mobility
Drones
Alternative
fuels
Exo
skeletons Conversational artificial
intelligence
Digital twins
Machine
learning
Visibility platform/
live tracking
Hybrid computing
platform
Automated
storage
system

17. 17 | October 2022, Stockholm, Andreas R. Hyllested
Artificial Intelligence for Customs Declarations
* AI helps with live
consolidation of
paperwork – in this
case Customs
Declaration
* Powered by on real-
time data from back-
office sources and
3rd party
integrations with
customers and
authorities

18. 18 | October 2022, Stockholm, Andreas R. Hyllested
Digital Twin
Automatic scanning for weight and size
* Live feed of data between IT
and OT systems – yields:
* Improved quality in handling
* Reduced average processing
time per pallet

19. 19 | October 2022, Stockholm, Andreas R. Hyllested
Internet of Things (IoT)
Live cargo tracking
* IOT sources and backend system
sources are combined
* Improved visibility and
transparency for customers and
employees

20. 20 | October 2022, Stockholm, Andreas R. Hyllested
Kafka for innovation
* Live data enables creative
solutions
* Improves process quality over all
* Allows for the transparency that
users have come to expect
Digital Product
Digital Product
Digital Product
SOR
SOR
SOR
03
Digital innovation

21. 21 | October 2022, Stockholm, Andreas R. Hyllested
Time for
solutions

22. 22 | October 2022, Stockholm, Andreas R. Hyllested
Ok, So Kafka is useful
But:
1. NFR?
2. How to organize data going in/out?
3. What to build?
SOR
SOR
SOR

23. 23 | October 2022, Stockholm, Andreas R. Hyllested
Platform NFRs
NFR:
* 4-5 Nines uptime
* Geo-redundant
* Zero RPO failover
* Ability to add
clusters (meshing)
SOR
SOR
SOR

24. 24 | October 2022, Stockholm, Andreas R. Hyllested
Design, ownership, change
SOR
SOR
SOR
Ownership
Domain Design
Governance Change mngt

25. 25 | October 2022, Stockholm, Andreas R. Hyllested
Is this a mesh?
SOR
SOR
SOR
Piethein Strengholt
Data Mesh: Topologies and domain granularity
https://towardsdatascience.com/data-mesh-topologies-and-domain-granularity-65290a4ebb90

26. 26 | October 2022, Stockholm, Andreas R. Hyllested
Platform capabilities
SOR
SOR
SOR
Protocol
Syntax
Mapping
Modelling
Windowing
Eventing
Routing

27. 27 | October 2022, Stockholm, Andreas R. Hyllested
Building a platform
SOR
SOR
SOR
Pipelines
Config repo
... and hard work!
A catalogue

28. 28 | October 2022, Stockholm, Andreas R. Hyllested
In conclusion

29. 29 | October 2022, Stockholm, Andreas R. Hyllested
Does Kafka deliver?
Shorter answer:
1. Yes – but not alone
2. Super performant of
course
3. But you still need
in-house teams to
tie it all together
Longer answer:
1. We are beginning to see the
Geo aspects covered – but we
are not fully there
2. The Kafka eco-system feels a
little scattered – and there
are too many decisions to
make
3. Big organizations still tend
to want their own one-stop-
shop – Integrations is not
just Kafka
4. Task of modelling to
abstract away the underlying
complexity is often
underestimated

30. QUE
STI
ONS
?
LinkedIn
Andreas Rishede Hyllested
Senior Enterprise Architect
andreas.rishede.hyllested@dsv.com