Data-driven service innovation strategy for Scania - Data fuelling Scania's future business - TU Delft ...
←
→
Page content transcription
If your browser does not render page correctly, please read the page content below
Data-driven service innovation strategy for Scania Data fuelling Scania's future business Master thesis Shudan Chi
Master thesis
Delft Univiersity of Technology
Faculty of Industrial Design Engineering
MSc Strategic Product Design
Author
Shudan Chi
chishudan@gmail.com
Supervisory team
Chair
Dr. ir. L.W.L. Simonse
Design Organization Strategy
Industrial Design Engineering
Delft Univiersity of Technology Data-driven service
Mentor
Dr. E.Y. Kim
innovation strategy for Scania
Design Organization Strategy
Industrial Design Engineering
Data fuelling Scania's future business
Delft Univiersity of Technology
Sarah Hantosi Albertsson
Development Engineer
Connected Intelligence, R&D
Scania AB
Robert Landau
Business Model Designer
Connected Service
Scania AB
Master thesis
May 2020
Shudan Chi
Acknowledgements Executive Summary
Dear reader, Scania is one of the world-leading manufacturers of trucks and buses for heavy transport,
combined with an extensive product-related service offering. This thesis proposes a data-
With this thesis I finalize my Master Strategic Product Design at the faculty of Industrial driven service innovation strategy to leverage the potential of data and data intelligence for
Design Engineering from Delft University of Technology. I have been honoured to work on Scania's future business in the truck segment.
a thesis for Scania and have experienced a different life in Sweden for the past five months.
Before you start reading my graduation project, I would like to thank some people who The freight transport industry is significantly disrupted by trends such as digitalization,
helped me and supported me during my graduation project. automation, connectivity and electrification. These trends will restructure the value network of
the freight transport industry by creating new ways of doing business. Enabled by connectivity
First of all, I would like to thank my Scania supervisor team. Sarah, thank you for supervising and data intelligence, vehicle data can be aggregated and processed to provide data insights
me, inspiring me, supporting me, trusting me, giving me tips to push through when I was that benefit the logistics chain. It unlocks new opportunities for Scania to deliver new digital
stuck and confidence when I doubted myself. Robert, thank you for sharing lots of valuable services driven by data, extending beyond their traditional business model. Therefore, to fully
insights and feedback and helping me to reach out to stakeholders. Johan, thank you for exploit the possibilities of the value pools created by data, the thesis aims to create an
initiating this great project and supporting me throughout the project. Without you three, innovation strategy to define Scania's new market positions and customers and create a
the goal of this project would not have been realized. coordinated roadmap for Scania's future data-driven services.
Secondly, I would like to thank Lianne and Euiyoung, my supervisory team from TU Delft. You This strategy has been developed by analyzing the internal environment, the value network
have helped me a lot by providing me with rich insights and feedback and valued the effort of the freight transport industry, the logistics chain, market trends and technologies. Insights
that has been made while developing this work. from research have been synthesized to envision the future scenarios of the value network and
define Scania's strategic direction. In the short term, Scania delivers digital logistics services to
Thirdly, For people that participated in my interviews and creative sessions, thank you for your shippers and carriers, enabling them to achieve efficient and sustainable transport operations
time and engagement. Special thanks to Lóri Tavasszy, Professor in Freight and Logistics at collaboratively by data sharing. In the long term, Scania aims to offer Logistics as a service with
TU Delft, for helping me get to know the freight transport industry, sharing valuable insights, autonomous vehicles directly to shippers by partnering with a digital logistics broker. A future
and helping to reach out to more experts in this industry. vision has been created for Scania's service development by 2030: "Scania as a sustainable
transport ecosystem enabler, providing customers collaborative and optimized logistics
Last but not least, I would like to express my sincerest thanks to my parents for their selfless solutions powered by open innovation to drive their business forward."
support and care in the past two years. To my friends, wherever you are, thank you for caring
about me, encouraging me, giving ear to my experience in Sweden from time to time, and To reach the future vision, four main service systems were designed incrementally and related
letting me know that I was not alone, especially during the corona times. to other technologies:
1. Connecting & Sharing: Enable visible and controllable transport operation for both carriers
and shippers through seamless data orchestration and sharing.
Enjoy reading! 2. Optimizing transport operations: Delivering sustainable and efficient logistics and transport
management services to customers via data-driven decision making and integration of digital
Shudan Chi logistics brokerage platforms.
3. EV transition Acceleration: Accelerating the transition to electrified vehicles by providing
customers effortless transport experience with smart routing and power charging services.
4. Logistics as a Service with autonomous vehicles: Transforming towards the transport
ecosystem enabler by providing Logistics as a Service with autonomous vehicles.
The strategy is presented in the format of a roadmap with all the elements such as trends,
user values, service systems, technologies and business. By following this path and delivering
these data-driven services to the market, Scania can create multi-dimensional business
models and shift from a truck OEM (original equipment manufacturer) to a service provider
with production.
1. Project Introduction 10
1.1 Project context 10
1.2 Problem definition 11
Reading Guide 1.3 Project deliverables
1.4 Project approach
12
12
2. Literature research 14
Abbreviations
Table of contents
2.1 Smart, connected products 16
2,2 Data intelligence 16
OEM Original equipment manufacturer
2.3 Data, analytics and value creation 19
LSP Logistics service provider
3PL 3rd party logistics provider 3. Company research 24
API Application program interface 3.1 Introduction to Scania 26
ICE Intelligent control environment 3.2 Scania’s strategy and developments 29
TMS Transport management system 3.3 Scania data-driven services 32
FMS Fleet management system
4. Context research 38
WMS Warehouse management system
4.1 Value network analysis & Main actors 40
ERP Enterprise resource planning
4.2 Logistics chain analysis 45
EV Electric vehicle 4.3 Actor’s needs 50
IoT Internet of Things 4.4 Data sharing implementation 54
TCO Total cost of ownership
FTL Full truckload 5. Trend research 56
LTL Less than full truckload 5.1 Market 58
DC Distribution hubs 5.2 Technology 60
5.3 Consumer behaviour 63
RFID Radio-frequency identification
5.4 Policy 63
BOL Bill of lading
5.5 Summary of trend research 65
ICT Information and communications technology
EDI Electronic data interchange 6. Future visioning 68
E-CMR Electronic consignment note 6.1 Future scenarios of the value network 70
ETA Estimated time of arrival 6.2 Value mapping 72
6.3 Future vision 76
INCOTERMS International Commercial Terms
7. Roadmapping 80
Text box 7.1 Roadmap horizons 82
7.2 Time pacing strategy 110
7.3 Strategic roadmap 112
Discussion or chapter conclusion 7.4 Tactical roadmap 112
Text in this red box represents a discussion or summary 7.5 Evaluation 118
with the main conclusions from that chapter.
8. Discussion 120
8.1 Conclusion 122
8.2 Recommendations 124
8.3 Personal reflection 127
References 128
Project
Introduction
This chapter gives an introduction to the thesis context, defined problems
with research questions, project assignment and design approach.
01
Chapter overview
1.1 Project context
1.2 Problem definition
1.3 Project deliverables
1.4 Project approach
10 11
1.1 PROJECT CONTEXT Service development & Connected intelligence
This thesis project was initiated by Connected Service department and Connected
Road freight transport is the backbone innovate their business.
Intelligence department in Scania R&D. The Conneted Service team focuses on developing
of Europe's economy, growth, and
service strategy and delivering new data-driven services to customers. The Conneted
competitiveness. The freight transport The technology of the Internet of Things
Intelligence department aims at building technology infrastructure and connectivity
i n d u s t r y i n E u r o p e i s fa c i n g s e v e ra l (IoT) enables vehicles to generate enormous
solutions enabled for data analytics and helping other R&D departments and the service
fundamental challenges today. The industry real-time sensor data and create a direct
development team to make new services and products possible.
needs to adapt to major changes in d a t a exc h a n g e w i t h n e a r by d ev i ce s ,
customers' behavior, global megatrends, vehicles, infrastructures, and cloud through
One of the primary purposes of this thesis is to bridge service development and data
technological changes, and new mobility different networks ( Coppola & Morisio,
intelligence technology by creating tangible materials. It is because delivering scalable
concepts. 2016). Enabled by big data analytics, a
analytics requires inputs from the service development team, and they need to understand
large amount of data can be aggregated
how customer demands will change in a more disruptive environment and what data
The worldwide freight volume is expected and processed to provide data-driven
insights based on vehicle data is valuable for customers. Without service and business
to grow by 4%, mainly driven by economic insights and drive smart actions (Coppola
innovation driven by user values and a clear definition of the relationship between data and
growth and global trade (Mckinsey, 2016). & Morisio, 2016). With the integration of
user values, it would be difficult for the data scientists to deliver the data knowledge and to
Customers have more buying power than digitalization, these vehicle data and data
have an agreement on the direction of Scania's future data-driven services.
ever before, and they increasingly want insights are very likely to contribute to the
products and services on their own terms: logistics chain significantly. Therefore, it
delivered at the location and time they brings new opportunities to develop data-
request (Deloitte, 2016). Companies expect driven services by truck manufacturers who
their supply chain to be smart, customer- have access to the vehicle data, extending
centric, transparent and efficient to reduce beyond their traditional business models.
the operational costs and provide better
1.2 PROBLEM DEFINITION
purchasing experiences to their customers. This thesis is an assignment for Scania:
Besides, governments, industries, and one of the world-leading manufacturers
companies are under pressure to reduce of trucks and buses for heavy transport,
carbon emissions and waste and to adopt combined with an extensive product- Although the market environment and Secondly, Scania's new position in industry
more sustainable and green transport related service offerings. The thesis focuses technological breakthroughs seem to open change is missing. How can Scania be
solutions. on the truck segment. Leveraging data from up space for Scania to unlock new business co m p e t i t i ve w i t h t h e i r n ew s e r v i ce s
vehicles, Scania has developed data-driven opportunities and data-driven services, it is by leveraging their ow n data assets?
To fulfill the increasing demand for freight services that help customers to manage still not clear for Scania in three aspects: Digital players have also recognized the
transport capacity and respond to these their fleets and increase the uptime of potential for digitalization and connectivity
trends, main actors in the freight transport vehicles. Firstly, there is no clear view on who will technologies and are already active in this
industry like vehicle manufacturers (e.g., be their future customers in the freight market today, offering a variety of digital
Scania, Volvo) and logistics providers are To fully exploit the possibilities of the value transport industry. The traditional industry solutions. Therefore, Scania sees a need for
dedicated to developing new technologies pools created by data and favorable market borders will likely blur by coorporations and a coordinated roadmap enabling them
s u c h a s a u t o m a t i o n , e l e c t r i f i ca t i o n , environment, Scania has to think how data digitalization. Market actors in this industry to explore how data will fuel their future
connectivity, and digitalization. These new as a key enabler can lead to future business have the potential to approach potential business. The roadmap needs to map out
technologies will restructure the value opportunities with digital services and what users in the value network to deliver values how they build their digital capabilities for
network of the freight transport industry by the future value proposition will be in this via digital services (Riasanow, 2017). Should new services, acquire external resources,
creating new ways of doing business in the disruptive transport ecosystem. Scania still focus on their current customer and cooperate with partners in the value
future (Roland Berger, 2012). The interaction segment or explore the new one in the network.
of these developments will open up space transport ecosystem? What new data-
in the industry for new actors and new driven services can Scania create? What is Thirdly, how data as a key resource can
business models, but also create new its business model that brings the revenues support Scania's new digital services is also
opportunities for established actors to to Scania as well as values to its customers? not clear. Valuable data insights and smart
“The world’s most valuable resource
is no longer oil, but data.”
— The Economist, 2017
12 13
decisions can be offered to customers • What favourable position could Scania Phase 1: Discover vision were defined. The future vision was
enabled by data analytics. Therefore, a clear take in the freight transport industry to In the diverging 'discover' phase, Scania's validated with employees.
view on what data sources are available and create competitive advantage? internal and external environment
what data analytics can be applied should were researched. The insights of smart, Phase 3: Develop
be discovered in the thesis. • What new data-driven services could connected product, data intelligence and In the diverging 'develop' phase, the
Scania offer to create values for the value creation with data were discovered user values were defined in more detail
Therefore, the research questions were customer? by literature research. Scania's business, and ideas for new service solutions were
defined below: vision, strategy, developments, and current generated. The chosen ideas were shaped
• How data as a key resource can service offerings were analyzed by internal into concepts and the business models
• Who are Scania's future customers in support Scania’s new services? interviews. Context research was conducted were designed per horizon. The ideas were
the freight transport industry? to analyze the road transport industry linked to each other and were plotted
based on the value network analysis on four horizons of the roadmap with a
approach (Biem and Caswell, 2008), timeline that is based on Scania's current
followed by logistics journey analysis and developments and technology strategies.
1.3 PROJECT DELIVERABLES problem areas. After analyzing the current
industry environment, expert interviews and
Ideas were also linked to the technologies
of data intelligence and validated with
I n t h i s t h e s i s , a d a t a - d r i v e n s e r v i ce business model for new service solutions desk research was done to discover trends Scania employees.
innovation strategy is created for Scania, that Scania can get benefits as well as its influencing the future of the road transport
where Scania delivers values to its future customers. 4) Technology implementations industry and Scania. Phase 4: Deliver
customers and obtains a competitive with a focus on data collection and data In the final converging 'deliver' phase, all
position in the road transport industry, with analytics that are mapped out to support Phase 2: Define the service solutions were mapped out
data-driven service offerings. the new service solutions in several horizons. In the converging 'discover' phase, in the roadmap and all the elements.
5) Internal and external collaborations that insights gathered were synthesized and Two roadmaps were created: A strategic
This thesis consists of the following: are planned based on current and needed analyzed. Two value mapping sessions roadmap for the stakeholders with main
1) A compelling and clear statement of capabilities and resources. were conducted with Scania employees to user values, new services in visualization
future vision that Scania can capture, define the user values and future direction. and future vision, and a tactical roadmap
follow and reach. 2) Incremental data- In the end, the innovation strategy is Combining the insights from individual for internal usage with all the elements. The
driven service solutions that Scania offers summarized in a visualized strategic and brainstorming, Scania's future direction, final roadmaps were validated with Scania
to its customers to meet their needs in tactical roadmap. future customers, and a clear future employees in different departments.
several horizons. 3) A value proposition and
1.4 PROJECT APPROACH
The approach is based on a strategic design designerly approach with user-centered
process. Strategic design refers to the use and future-oriented research, co-creation
of design principles and practices to guide with problem owners within the company,
strategy development and implementation future visioning, diverging and converging
towards innovative outcomes that process, and several rounds of iteration.
benefit people and organizations alike
(Calabretta et al., 2016). A combination of The project can roughly be divided into
the traditional Double Diamond design four phases: discover, define, develop, and
process (Design Council, 2015) and the deliver based on the Double Diamond
Design Roadmapping process (Simonse, design process (Figure 1).
2018) were used in this thesis. It is a
Figure 1: Project design process
Literature
Research
This chapter draws a literature study starting from the understanding of
smart, connected products and its main capabilities of generating added
values by implementing data analytics. The study moves towards more
specifically how data and data analytics can create values for business from
an ecosystem perspective. This will provide insights on creating Scania' s
02
future vision on its new data-driven service development.
Chapter overview
2.1 Smart, connected products
2,2 Data intelligence
2.3 Data, analytics and value creation
16 17
2.1 SMART, CONNECTED PRODUCT Connected vehicle
The technology of the Internet of things (IoT) Physical components consists of the
is revolutionizing products to become smart product’s mechanical and electrical parts.
and connected. The physical products
equipped with smart and connectivity Smart components consists of the sensors,
components enable gather insights about microprocessors, data storage, acuators
the product use status, performance and and software that can be an embedded
environment and communicate with the operation system with user interface.
Internet and other smart objects (Turber et
al. 2014). This smart, connected products Connectivity components consists of
are transforming traditional industries, the ports, antennae, and protocols and
especially the manufacture industr y, communication networks that allows
into a new era companies are forced to information to be exchanged between the
rethink what values of developing smart, product and its user, systems and service
connected products they can create and cloud.
capture (Porter & Heppelmann, 2015).
Based on these essential embedded
Figure 2: Connected vehicle operational data
To fully grasp how smart, connected components and a technology
products can positively influence the infrastructure that contains a platform
Connected vehicle is one type of smart, A SIM card and modem in the device enable
company's future business, its technology for data storage and analytics, more
connected product, which also comprises communication on the cellular network and
and capabilities should be understood. capabilities of smart, connected products
physical, smart and connectivity elements. frequent data transmission to a cloud server
According to Porter and Heppelmann can be discovered.
The complete set of operational data consists at a predefined interval (V2N). The cloud
(2014), smart, connected products
of certain different operational variables server is a central data hub that combines and
have three core components: physical
belonging to different electronic control units processes data for value-added services and
components, smart components, and
in the vehicle. They are sorted to different applications (Figure 3).
connectivity components.
buses throughout the vehicle. The information
over the vehicle status can be collected by In addtion, the smart and connectivity
2.2 DATA INTELLIGENCE a small telematics device installed in the
vehicle through plugging into the CAN bus
components enable other different types of
vehicular communication systems (Coppola &
port. This telematics device receives, stores Morisio, 2016).
While reading sensor data from smart, four building blocks – Data, information,
and transmits different types of information
co n n e c t e d p r o d u c t s o r a g g r e g a t i n g knowledge and wisdom (Figure 4). Each
re l a t i n g t o t h e ve h i c l e's p e r fo r m a n c e, Vehicle-to-infrastructure system (V2I) allows
other data sources in the data lake, the building block up the pyramid builds upon
condition, and usage. Apart from the tractor vehicles to collect information about traffic
technology of data analytics can be applied the previous one, adding new values on it.
data, a connected truck as a unit also can flow, cameras, charging stations, etc. Vehicle-
to generate deep insights and even make
collect data from trailers, drivers, and cargo to-vehicle system (V2V) enables vehicles to
intelligent decisions to serve customers' On the bottom of the pyramid is the layer of
through smart components embedded. Figure transmit information with nearby vehicles.
needs. It also brings great opportunities for data: a collection of raw and unstructured
2 gives an example of vehicle operational data
companies to create new value offerings data such as vehicle position data, sensor
assets.
enabled by data analytics. data that only explain the fact in each
point. If the data is without any context, it Connected vehicle Cellular Network Cloud server Applications
2.2.1 DIKW pyramid can mean little.
DIKW pyramid (Rowley, 2007) is a simple Information is the next layer of the DIKW
way to explain the capabilities of data Pyramid. Useful information can be derived
analytics in hierarchies. It consists of from data that has been given meaning by Telematics
device
Figure 3: Vehicle-to-Network communication system (V2N)
18 19
defining relational connections. It is a set
of data that has been cleaned, aggregated
Therefore, the more the data is enriched
with meaning and context, the more 2.3 DATA, ANALYTICS AND VALUE
and processed in a way that makes it
easier to measure, visualize and analyze for
knowledge and insights can be gotten out
of it.
CREATION
a specific purpose. The analysis is usually The previous discussion is more about the understanding of the requirements and
carried out to find the answer to Who,
2.2.2 Stage model of data capabilities of smart, connected products and data analytics from a technology
What, When and Where questions. For perspective. More research is presented below to discover how data and data analytics can
example, we can derive a vehicle's actual analytics create values for business.
route on a day by analyzing the positions Figure 5 is another wide-used stage
of it from point A to point B sent out by in- m o d e l f o r ex p l a i n i n g d a t a a n a l y t i c s
vehicle GPS. use cases (Steentrup et al., 2014). It can 2.3.1 Servitization
be characterized by four types of data
Servitization is one of the main drivers servitization and technical realization. It also
analytics: descriptive, diagnostic, predictive
to push the manufacturing industry to relates to how manufacturing companies
and prescriptive (Figure XX). Each stage
change the traditional way to deliver reposition themselves on the market and
presents how sophisticated the data
values and focus on innovative value- what their business models can be.
analytics capability could be, which has
added service developments with their
the same characterization of the DIKW
current product offerings to satisfy unmet The evolution from product to solution
pyramid. It also implies the level of human
customer’s needs (Baines et al., 2009). provider is to offer further products and
input in decision and action activities. It
The smart, connected products create services for the core manufactured product
means that the more machine input it
massive new opportunities to open up that customers need.
has, the less human input it needs. To the
service innovation as its generated data
final prescriptive stage, it aims at decision
can foster smart, digital services. It is a way Value-added ser vices driven by data
support or even automated decision
to shift the business goal of manufacturers insights are more closely linked to the
making to derive actions based on the data
from one-time product selling to gaining usage and performance of the product.
without requiring any human input.
continuous profit from customers by value- Meanwhile, these value-added services are
Figure 4: DIKW Pyramid (Rowley, 2007)
added digital service solutions, which will likely to be linked to the connected, smart
enhance the company’s core competencies products from other companies, which
The third layer is to move from information
in the future. In the end the boundary of pose a threat to a company with no such
to knowledge to achieve the goal. Many
the manufacturing industry and service service.
pieces of the information connected to
industry will be burled.
other data sources can have more meaning
The next stage is to deliver the core
and value and help to understand how to
leverage information to meet customers’ Evolution of the market offerings manufactured product as a ser vice ,
of manufacturers enabling manufacturers to offer their
needs. For example, more precise time of
products and services as a unified solution.
arrival could be delivered by integrating Figure 6 (Rabe et al., 2018) presents possible
weather, real-time or historical traffic directions for the market offering of a
The final stage refers to everything as
information with the best route selected. manufacturing company, which is highly
a service (XaaS). Through the technical
And the goal is to achieve accurate time of dependent on the levels of digitalization,
system, many product functions and value-
arrival. Figure 5: Stage model for characterizing data analytics use
cases (Steentrup et al., 2014)
The fourth layer is wisdom, which means
to apply knowledge in action. In other
words, the machine or the application can
proactively give the suggestions of the next
decision or automatically make decisions
by itself.
Figure 6: Evolution of the market offerings of manufacturing companies (Rabe et al., 2018)20 21
added services are digitized and transferred For the manufacturing industry, many
2.3.2 Creating values with data analytics
to service clouds and offered on their own ser vices are based on data analytics
or external digital platforms. Customers application in order to derive data-driven on an ecosystem level
can purchase these services and use them insights and integrate intelligence into Traditionally, the main value creation of data in a service ecosystem when applying data
whenever they want. the services. According to Engel and Ebel analytics is focused on a direct relationship and analytics, namely Data-as-a-Service
(2019), data-driven service innovation refers model between current customer and (DaaS) and Analytics-as-a-Service (AssS).
Therefore, the potential of such digital to using data as a key resource for value analytics ser vice provider based on a DaaS regards a data service that aggregates
ser vice offerings leads manufacturing creation towards customers. In addition closed system (Chen et al., 2011). This type and provides access to more data sources
companies to expand their service-oriented to selling data, companies can adopt the of traditional analytics ecosystem usually through cloud infrastructure. The benefit of
business along the servitization path (figure data exploitation strategy to become a operates in a siloed and inefficient model processing and aggregating in the cloud is
7). data re-user through data analytics and (Chen et al., 2011). End users or other relative to offer low cost and scalable infrastructure
deliver value-added services to their current partners need to work with multiple service for big data analytics ( Chen et al., 2011).
and potential customers, while creating a providers to acquire and integrate data Open APIs can be one format to deliver
multi-dimensional business model (Zhu & sources and apply analytics technologies to DaaS. Beyond DaaS, AssS offers a rich set
Madnick, 2009). address their business needs, which is often of analytics components on demand and
costly and hard to implement. There is little infrastructure that are easy to integrate with
sharing of related operation data, tools, and other business applications or processes.
services for a broader customer base in the Th e s e t w o n e w co n ce p t s e n a b l e a n
ecosystem. ecosystem transformation from a closed,
proprietary, and business-directed model
Chen et al. (2011) proposed two concepts into a more open, collaborative, value co-
FIgure 7: Servitization path (Schuh et al., 2004)
Figure 8: New Industry Boundaries and Systems of Systems22 23
creation ecosystem that benefits multiple
stakeholders: customers, industries, partners
and Heppelmann, 2015). This will enable
new forms of collaboration on a data and
Chapter conslusion
and end-users (Chen et al., 2011; Porter and analytics level.
This chapter gives insights into smart, connected products, data intelligence, and how data
Heppelmann, 2015). By entering into this
intelligence creates values for the business. Main smart components (sensors) embedded
open service ecosystem, companies are According to Porter and Heppelmann
in the connected vehicle and three types of communication technology (V2N, V2V, V2I) are
likely to unlock new business models by (2015), the industr y boundar y will be
studied to understand its capabilities. By aggregating and processing data from connected
applying analytics as a value creator and expanded by shifting from a single product
vehicles, data analytics can be applied to derive data insights.
key differentiator. For example, companies system to systems of systems that connect
can aggregate data from one type of an array of product and service systems
Connected products and data intelligence bring business opportunities for companies to
customers and create additional value for and external information to improve the
transform from a manufacturer to a service provider with production by delivering values
other business partners or end-users by overall operation on an industr y level.
and focus on innovative value-added service developments with their product offerings to
deriving insights from the collected data Within these dynamic ally networked
satisfy unmet customer's needs. To discover more values from data intelligence, companies
and analytics. systems, there will be multiple players
should consider themselves in a broader ecosystem where data insights can benefit more
participating in the systems of systems,
potential users and businesses.
Meanwhile, the applications of smart, and companies are intentionally seeking
co n n e c te d p r o d u c t s , p hy s i ca l a n d to broaden and reshape their business as
virtual value creation activities are often well as their industry. Figure 8 presents an Three main insights can be taken away from this chapter on developing
combined. Information, resources and example of how a single product from a new data-driven services for Scania:
smart objects are linked to each other, and tractor company can evolve and expand its
customers and other business partners capabilities in a broader ecosystem. 1) Instead of focusing on selling data assets or providing customers with basic data insights
actively interact in the value network (Porter on their product performance, Scania could deliver new digital services with aggregated
data and data insights by data analytics to meet customers’ unmet needs, while enhancing
the company’s core competencies.
2) The smart, connected product and capabilities of data intelligence can derive a multi-
dimensional business model for Scania with different value offerings and enable a new
position in the market.
3) Focusing on a single product system or a closed, proprietary system can hardly leverage
the potential of data analytics. This is because only limited data sources (e.g., vehicle data)
can be accessed and higher capabilities of data analytics are hard to achieve only by Scania
itself. Scania needs to position itself into a broad, open, value co-creation ecosystem to
unlock new business opportunities with data analytics.Company
Research
To create a successful service innovation strategy for Scania, Scania's
vision and strategy, business, current data-driven services and on going
developments should be researched and analyzed.
03
Chapter overview
3.1 Introduction to Scania
3.2 Scania’s strategy and developments
3.3 Scania connected service26 27
2.3 INTRODUCTION TO SCANIA Product sales Services
Scania was founded in 1891 in Sweden and over a million Scania vehicles are in active
use in more than 100 countries. Scania is a world-leading provider of transport solutions,
Truck Repair and maintenance Data-driven services Finance & Insurance
including trucks and buses for heavy transport applications combined with an extensive
product-related service offering. Scania is also a leading manufacturer of industrial and
marine engines (Scania, 2018).
Global dealers 1,700 Workshops
3.1.1 Scania’s business
FLeet
management Tachography Driver services Scania zone Trailer & Assets
system control
Offering heavy trucks and vehicle-related value-added services that maximize vehicle
services to transport companies is Scania's uptime including flexible maintenance, Figure 10: An overview of Scania’s service offerings in the truck segment
core business and consists of 61% and 19% fleet management system, finance and
of Scania's global net sales (Figure 9). Scania insurance, application-based driver training
offers tailor-made transport solutions for 36 and coaching that can be adapted to Scania's value creation
different industries including construction, specific industries. Figure 10 presents an S ca n i a ' s v a l u e c r e a t i o n i s b a s e d o n by vehicle data. The service offerings such
retail, mining, manufacturing, courier and overview of Scania's offerings in the truck p r ov i d i n g c u s to m e r s w i t h p r o f i t a b l e as financing, insurance and maintenance
postal, long-haulage, urban applications, segment. The flexible maintenance service and sustainable transport solutions that contracts enable Scania to be closed to the
etc. Scania has strong connections with enables vehicle servicing based on real- move their businesses ahead. This means customers and their business operation,
over 1,000 global dealers in major markets, time operational data and actual usage, that Scania's business model is about creating a long-term relationship and
offering sales services including trucks, used with maintenance only when needed. understanding and improving the revenue bringing Scania continuous profits. Figure 11
trucks, Scania parts. Scania's dealerships provide maintenance and cost aspects of transport companies' presents Scania's and customers' business
services that link to over 1,700 workshops industries by offering tailor solutions model components.
Scania's services in the truck around the world, presenting one of the including vehicles and services supported
segement primary profit sources for Scania apart
from selling trucks. Scania will own more
Utilizing the data from over 400,000
workshops globally to be close to the
connected vehicles, Scania has developed
customers and drivers. + Customer revenue— Customer cost*
European long-haulage
Uptime Tyres
Customer
Flexibility Drivers
Customer* operating
Load capacity Fuel income
Vehicle
Repair and maintenance
Administration
Customer: transport company
Vehicles
€ Services
+ Scania revenue — Scania cost
Vehicles and engines Production of vehicles,
Scania Repair and maintenance engines and services Scania
Research and development operating
Financing and insurance
income
Used vehicles Selling and administration
Financing
Figure 9: Scania product portfolio and global net sales Figure 11: Scania and customers' business model components
(Illustration based on Scania, 2018) (Illustration based on Scania annual report, 2018)28 29
3.1.2 Scania’s Parnership
Scania is also part of TRATON GROUP. The main collaborations focus on synergies In the future, the adoption of electrification Th e r e fo r e , t h e s e m a r ke t t r e n d s a n d
Under this umbrella the brands Scania, in the components of hardware and requires the electrified powertrain, and it technology developments are pushing
MAN and Volkswagen, RIO work closely i n f ra s t r u c t u r e o f b a c k - e n d s y s t e m s , will abandon the traditional engine that has Scania to selectively abandon some past
together with the aim to turn TRATON which also applies to the development been the core capabilities of truck OEMs offerings and transform the company
GROUP and its brands into a Global of new technologies such as electric and for decades. Besides, there would be no strategy towards a bigger picture to find a
Champion of the truck and transport autonomous vehicles. The competition cabin needed for autonomous vehicles, and competitive position in the transport and
services industry by utilizing the strong between Scania and other brands within vehicles will become a mainly software- logistics ecosystem instead of only being
network of strategic partners to access all TRATON GROUP should be fair on the defined sensor platform. All development an OEM.
major profit pools (Scania, 2018). market, whether it is truck sales or digital will be based on simulations and data from
service business. the connected product.
3.1.3 Scania’s vision " We used to belong to the heavy
commercial vehicles industry. Now we belong to
the ecosystem of transport."
Scania's vision is to drive the shift towards a sustainable transport
— Scania CEO
system, creating a world of mobility that is better for business,
society and the environment.
Leader in sustainable transport
3.2 SCANIA'S STRATEGY AND
Global
Urbanisation
Sustainability
Ecosystem Industry
DEVELOPMENTS
trends Transport & Logistics trends
Digitalisation To achieve the company vision of being a transport system solution provider, Scania has
invested heavily in developing new technologies such as automation, electrification and
connectivity to provide customers with sustainable and efficient fleets and also try to
integrate these new technologies into new business models. The insights gathered below is
Excellence in core based on internal interviews. See Table 1 for the intervew list.
Selectively abandon the past
Create the future
The automation will be first deployed in Scania has set the objective to be fossil-
the confined area for specific industries free in 2050 and focuses efforts on
such as mining and forestry, followed by electrification technologies for both
hub-to-hub autonomous driving on public batter y and infrastructure to reduce
Company vision explanation roads with supporting infrastructure. Scania environmental impact. It will enable digital
has been developing the Intelligent control integrations with external partners and
One of the reasons why Scania set up e l e c t r i f i ca t i o n a n d a u to m a t i o n , n ew
environment (ICE), which means that the stakeholders such as charging ser vice
this company vision is that transport is an business models and new market entrants
customer's transport can be followed and platforms, charging infrastructure providers,
industry where the digital revolution is will disrupt the traditional freight transport
monitored in real-time from the back-end etc.
moving fast. Connectivity, digitalization, industry in the next few years.
office.30 31
The technologies of connectivity and IoT
can enable data-driven insights to optimize
Sennder
Internal Interview — Transport System Lead
v e h i c l e p e r f o r m a n ce a n d m i n i m i z e An internal interview was set up with the Lead of transport system in Scania R&D
customer total cost of ownership (TCO) department. The goal is to see his vision on Scania's future position in the transport
and also to increase the efficiency of the and logistics industry and Scania's strengths and weaknesses of developing digital and
transport system and optimize the logistics connected services.
flow. This means that Scania may not only Scania also invested in a startup, Sennder,
be an OEM focusing on its traditional a digital, contract-based road freight Insights on future services:
b u s i n e s s m o d e l , b u t s h i f t towa r d s a matching platform for small carriers and The development of new digital and connected services by leveraging existing data that
transport system provider with multiple big shippers. Sennder mainly focuses on Scania has collected can be two directions:
business models in parallel enabled by Full Truck Loads (FTL) shipments, which One is still developing the services around the vehicle performance and usage that Scania is
technology push and market pull. means that one truck drives exclusively for making profits now. Future services might also work around vehicles with electrification or
one shipper. See figure 13 for Sennder's automation.
Th e r e a r e s o m e S ca n i a ' s s u b s i d i a r y business focus. According to the internal
companies and invested companies going
Another way is to integrate or develop new logistics services enabled by vehicle data and
interview, one of the reasons Sennder find the roles of Scania and carriers in the logistics system.
on to drive this shift. focuses on FTL is that FTL is relatively easy
to set up and gain higher profits compared
LOTS GROUP to Less Full Truck Loads (LTL). Meanwhile, Market leader of vehicle manufacture
the EU road freight market is vast, with an A considerable amount of vehicles running on roads globally
overall size of 350bn euros with significant Strong competence in developing new technologies (ACE)
structural inefficiencies and top 5 logistics Strong connection with customers
service providers (LSPs) only hold less than Strengths Possibility to collect considerable vehicle data
5% market share. The platform, such as Knowledge of modular thinking (possible to adapt to the logistics system)
Sennder, would be a new industry entrant Lean thinking (possible to develop efficient logistics transport system)
to gain a certain market share. Through
Scania's wholly-owned subsidiary LOTS
close cooperation, Sennder now offers
group, Lean Optimised Transport Systems,
its customers key tools based on Scania's
focuses on mining, agriculture, and forestry A relatively narrow business model
connected service portfolios, such as fleet
transport across the world (Scania, 2018). It Limited transport buyer relation
management software, Fleet App for
is a strategic investment and an example of Limited knowledge about logistics business and its operation
drivers.
how Scania is moving forward to optimize Weaknesses Limited software development competence (e.g., artificial intelligence)
transport flows. LOTS leverages data from
connected trucks, information from fuel
partners, and other key data to optimize
the daily flows of the fleet based on the
principles of Lean (Scania, 2018).
Discussion
All of the strategies and developments pave the way for Scania to achieve the company
vision. However, transforming towards a transport system provider seems to be a big
challenge. This is because Scania only knows the sales market well, but has limited
knowledge about the transport and logistics business and customers' operating systems,
which is hard for Scania to monetize data and develop digital services that are more
logistics-related. Although Scania has the logistics competence of its vehicle supply chain, it
is not business-related. Meanwhile, historically, Scania have had a more focus on hardware
development. Limited software development skills such as artificial intelligence and big
data analytics might be a reason to slow down this transformation.32 33
3.3 SCANIA DATA-DRIVEN
SERVICES
Interviewed Scnania employees Since the goal of this paper is to develop a roadmap for Scania's future data-driven
This table presents an overview of interviews conducted with internal employees services, Scania's current data-driven services should be introduced and analyzed as the
(including informal interviews) during the 'discover' phase of the graduation new data-driven services should be linked to existing service offerings and capabilities.
project. The primary purpose of the interviews was to understand Scania's strategy,
partnerships, products and services, developments, technologies, and data usage.
See more interview insights in Appendix 1. In 2019, Scania reached over 400,000
connected vehicles across the world, and
1. Head of Strategy and product planning, Conneted Service the strategy for 2025 is to reach 95%
Goal: 1) Understand Scania's partnership in TRATON and its purpose. 2) Get Insights connected fleets. By leveraging the vehicle
into collaborations between Scania and RIO. data, Scania has developed a series of FLeet management Tachography Driver services
system
data-driven services for carriers to increase
2. Lead of transport system, Scania R&D their uptime and efficiency of operation.
Goal: 1) Get insights into Scania's future service direction and its limitations both Currently, Scania offers three primar y
from Scania itself and industry environment (data sharing). 2) Scania's strengths and connected services: 1) Fleet Management
weaknesses of developing new digital services. Services, 2) TachographServices and 3) Scania zone Trailer & Assets
control
Driver Services. Scania Zone and Trailer
3. Business model designer, Conneted Service Control are new services that are subjected Figure 12: Scania's main connected services
Goal: 1) Get insights into Scania's connected service strategy 2) Get insights into to Fleet Management Services (Figure 12).
Scania's current data-driven projects.
1. Fleet Management system
4. Strategic business developer, Conneted Service & Sennder The fleet management system is one of the costs by collecting and analyzing the
Goal: 1) Understand Sennder's business, business model and service roadmap to core services offered by Scania. It provides vehicle data. Main functions are explained
the future 2) Get Insights into Sennder's current data-driven services for carriers and customers benefits in increased uptime, below:
shippers. improved safety, and reduced operating
5. Development engineer, Scania R&D
Goal: 1) Get insights into Scania's strategy, organization culture, current research
projects at the data intelligence department and the relations between Scania's
technology roadmap and service roadmap.
6. Product owner, Conneted Service
Goal: 1) Get insights into what data assets in Scania's FMS and rFMS standard APIs.
7. Head of central operations & digitalization, LOTS
Goal: 1) Get insights into LOTS business, the strategy of digitalization, tools and the
applications of data analytics to drive transport performance in operations. 2) Future
strategy on automation
Table 1: Interviewed Scania employees
Figure 13: Fleet management system — Fleet positioning34 35
1) Fleet Positioning gives the customer activities related to service planning well 4) Scania Zone allows drivers to receive
an interactive map where they can see organized and increase the uptime. notifications when the vehicle enters
their vehicles and equipment in real-time geo-fencing areas with traffic restrictions
(Figure 13). It helps carriers to track and 3) Vehicle performance helps customers such as speed limits, emissions and noise
take control of their fleets. The transport to evaluate how their vehicles are being regulations, which prevents drivers from
operator can see who is driving, how long used (Figure 14). Customers can find over overriding the set rules (Figure 15).
they have been driving, when they started 90 parameters of data that display vehicle
driving, where they stopped, how long they performance. Customers can receive the 5) Trailer control & assets control allows
stopped driving and when the driver has environmental report that shows calculated customers to connect equipment such
to take their rest based on the standard EU emission values for their vehicles. The as trailers, commercial vehicles or mini-
law. They can also see the speed at which emission values are based on a vehicle's vans by providing the data of location,
the vehicle is traveling, how much fuel is calculated fuel consumption. performance & goods control. The offerings
left. of performance and goods control are still
Figure 15: Scania zone
4) Driver Evaluation is a service that gives under development. It helps carriers track
2) Service planning is the service where customers an overview of drivers' driving and find the trailers easily and monitor the
fleet managers gain control over the behavior. It also identifies the parameters condition of the goods, which is also one of
maintenance and repair requirements within which there is the greatest potential the requests from shippers.
of the fleet. If the customer has a Scania for improvement. If a driver starts with
Maintenance plan, the planned service grade E and improves their grade to A, 6) Fleet APP helps to link driver and fleet
events are shown in Ser vice Planning. they have the potential to reduce their manager closer in the daily operation. The
Through positioning and vehicle operational fuel consumption with around 15% due to app gives them access to their positioning,
data, Scania actively diagnoses how vehicles improved driver behavior. grades and vehicle information (Figure 16).
perform and plans ahead which vehicles
will need maintenance service, when and
7) API integration
for how long they will need to be in the
Scania also offers API data services for its
workshop to avoid unexpected breakdown.
customers when they have another own-
This offering helps carriers to keep all
built or the third party systems. The API
data can be integrated into the third-party
digital platform with standardized vehicle
1
data formats (rFMS ). Since customers
may have fleets with multiple brands, they
can integrate all vehicle data from several Position Driving profile
systems into one third party FMS. Figure 16: Fleet APP
2. Tachograph services 3. Driver services
Scania's tachograph ser vices provide S ca n i a l eve ra g e s a va r i e t y o f ve h i c l e
customers insights into driver activity operation data to monitor drivers' driving
and vehicle usage, which helps them to behavior and performance periodically,
analyze potential legal responsibility issues and offers the driver coaching sessions if
regarding infringements, delays, required they find negative trends in terms of driving
calibrations, etc. The tachograph records efficiency.
the speed, distance, driving time and
drivers' rest periods.
1. The rFMS API is used to remotely access vehicle FMS data in a standardized way without installing any additional hardware to the
Figure 14: Fleet management system — vehicle performance vehicle by using the existing OEM hardware.36 37
Discussion on Scania current Chapter conclusion
data-driven services Scania is a world-leading provider of transport solutions, including trucks and buses for
heavy transport applications. Scania is a part of TRATON GROUP with MAN, Volkswagen
and RIO, a telematics service platform. The focus of this partnership is on synergies in the
Scania's current connected services mainly focus on fleet management to increase vehicle hardware, back-end infrastructure and new technologies.
uptime, having limited interaction with the operation of logistics and transport. Most control
and monitor packages offered by Scania are to deliver the information of assets' positioning, In the truck segment, Scania has developed value-added services including flexible
performance. maintenance, FMS, finance and insurance, driver training and coaching. Scania's company
vision is to drive the shift towards a sustainable transport system, which is mainly driven by
According to the DIKW pyramid studied in the previous chapter, these offerings are only at changes in the external environment.
the information level. The levels of knowledge and wisdom are rarely achieved by current
offerings. For example, the fleet management system gives customers an overview of all To reach this future vision, Scania has invested heavily in developing new technologies
the vehicles' real-time locations. However, it cannot provide insights into when the truck such as automation, electrification and connectivity and also trying to integrate these new
potentially arrives at the terminal or which route is faster. Geo-fencing services, as another technologies into new business models. Scania's subsidiary companies, LOTS GROUP and
example, are valuable for drivers to efficiently follow the environmental rules, but it also has wholly invested company, Sennder also expand Scania's transport solutions to different
more potential to be integrated into route planning. The Fleet APP focuses mainly on vehicle applications.
performance and linkage between fleet managers and drivers, which contains only part of
drivers' daily operation activities. Scania's main data-driven services have been introduced and analyzed. Most data-driven
services offered mainly focusing on fleet management, having limited interaction with
Meanwhile, some parameters presented on the FMS portal are just vehicle-related transport operations and logistics activities. The value of data and data intelligence from
information stacks that customers might not even check or leverage for their operation. The current offerings has not been fully discovered yet.
value of providing these parameters to customers is relatively low.
The strategy of offering API for customers to integrate data from Scania's connected vehicles
into their own system will benefit third-party telematics providers to leverage data for more
new offerings. To some extent, it limits Scania to develop services that focus on improving
transport and logistics operations.
Most of Scania's service offering focuses highly on the current customer segment - carriers,
without thinking from the perspective of customers' customers which refer to shippers.
To deliver new data-driven services, Scania needs to consider how the data collected from
vehicles and current service offerings will benefit the logistics system and how Scania can
expand its narrow business model.Context
Research
This chapter provides insights into the context of the freight transport
industry. The freight transport industry and its main actors are studied,
followed by logistics chain analysis, which identifies the major problem
areas and relative actors' needs that are data-related.
04
Chapter overview
4.1 Value network analysis & Main actors
4.2 Logistics chain analysis
4.3 Actor’s needs
4.4 Data sharing implementation40 41
4.1 VALUE NETWORK ANALYSIS &
MAIN ACTORS
Due to the freight transport industr y current value offerings of truck OEMs are and improving the cost of ownership. Workshops
becoming more complex and connected, a still based on product sales and after- Most OEMs put much emphasis on high- Most OEMs incorporate
framework of the value network is proposed sales services to their existing customers, quality hardware production and advanced Workshops worldwide as
to analyze the main market actors and their transport companies, having little technologies such as electrification and aftersales are the primary
interactions in the current freight transport interaction with other actors in the freight automation. When it comes to digitalization profit driver and bring
industry (Figure 17). transport industry. transformation, OEMs are experiencing a continuing revenues to OEMs. It also helps
hard time developing new value-added OEMs to keep a tight relationship with their
Value network is a method to visualize The current offerings of telematics services digital services with multiple business customers. Scania incorporates more than
inter-organizational value exchanges and from most OEMs are similar, focusing models within the logistics sector (Deloitte, 1,400 workshops, performing maintenance
dependencies (Biem and Caswell, 2008). on improving the uptime of the vehicles 2017). on complete vehicles, including trailers.
The value network displays cooperation
alliances and relationships, which helps
y services
Deliver
the strategist to analyze the company’s
current position in the industry and identify
strategic moves. The value network analysis
Add
is dif ferent from traditional strategic itio
na
lt
modeling approaches that only focus Add
itio ra
Carriers-2PL
na
lt
ns
on fulfilling the needs of the immediate (Transport as a Service)
po
Sub-contractor
ra
rt d
on driving/f
customer. The value creation and exchange vice
ns
ue
Ad
em
lu
po
icle usag sa
of offerings should be targeted towards
ity
and
rt via
Veh ed
l / Electric
End-users
ge
at
€
a
identifying the value drivers to the end-
bility
e
nc (recipients) Maintenance ser
rie vice
users (Biem and Caswell, 2008). This means expe Driver
Maintenance dem
Fue
€
and
that the interactions with current customers
g
Tra ns p ort pl
D e l i ve r y f u l l
in
as
will be analyzed and downstream market Fleet Manager
ch
pur
actors will also be considered. Energy Fle
Goods +
€ et
s
ma
cle
an
Provider ty
fill
ci na
ni
hi
tri ge
m
c
ng
ve
Ele na
l
m
en
F u el / ru e
Truck OEMs ti o ck
t
tory man
Inven Workshop
a
O p er
ag o
nt
em
Tr u c k O E M s r e f e r
se
e
pe
rv
ra
ice
to original truck
nt
tio
Shipper Transport Planner
s+
na
Coope
manufacturers
ld
Up
(Manufacturer；
ata
tim
such as Scania, Wholesaler;
rati
e se
Ve h
Retailer)
Mercedes-Benz, Volvo, DAF and MAN, that
Fee
ce
on
rvice
vi
clei
s
er
manufacture and offer engines and heavy
db
Warehouse/DC po
rt
s
d
s
ac
L o gis
ns an
trucks for different applications. OEMs
k
e tra e m
De -tim td
or
ti c
usually sell vehicles to truck dealers across € vliv On sp
ery
sm
n
na sceh Tra Vehicles
the world to transport companies. Besides dules
a
ge
me Mark
it, OEMs have expanded their business into nt se
r vices Truck Dealer
et + Feedback
more vehicle-related services including Logistics Service Truck manufacturer
Provider-3PL Logistics Planner
contracted workshop services, FMS services,
driver training, finance, insurance, etc. The (LSP, CEP)
Figure 17: Value network of the freight transport industryYou can also read
