VIEWPOINT

2024

L AY E R I N G U P
THE TRANSPORTT E C H N O L O GY P O R T F O L I O
An operating model perspective
AUTHORSThe mobility sector is undergoing rapid

Ashish Sharma

technological changes; organizations must adapt

Joseph Salem

their technology operating models to keep pace.
In this Viewpoint, we propose a differentiated,

Andrei Timoshenko

multilayer operating model for planning, operating,Francesco Cotrone

and governing technology systems, based on their

Gaya Hacianeposition on the technology maturity S-curve.
Adopting this approach will help companies find theright balance between agility and efficiency for eachtechnology system in their portfolio.

ARTHUR D. LITTLE

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NE W OPP OR TUNITIES& CHALLENGES

For example, the sensors embedded in advanced

A confluence of technological breakthroughs has

infrastructure, vehicles, and passengers. Integrating

disrupted the transport and mobility value chain.

this data from different OT systems will unlock new

Travelers are accessing mobility services in new

insights and synergies, for both optimizing existing

ways, new classes of vehicles are emerging,

operations and for planning new development.

and transport networks and traffic flows are
increasingly monitored and optimized in realtime. This sector has often found itself at theforefront of progress, but most of its advances
have always been more relevant to moving
atoms than to moving bits. The latest challenge
facing mobility players is the current technology
revolution’s emphasis on capturing, integrating,and leveraging large flows of data.

operational technology (OT) systems are gathering
expanding amounts of data on transport

In addition, several key disruptive technologies
presently transforming other industries are
driving the need for IT/OT integration within
the mobility sector (see Figure 1). These include
big data analytics, blockchain and distributed
ledger technology (DLT), artificial intelligence(AI)/machine learning (ML), and digital twins/metaverse. For example, the widespread use of
sensors and Internet of Things devices generates

This challenge is pressing for public transport

an abundance of data that can be leveraged tooperators for two key reasons. First, as

optimize transport operations, reduce costs,

government bodies overseeing critical public

and improve safety. Moreover, DLT can enhance

infrastructure, the guiding mantra must remain

payment authentication, which helps refine the“move slowly and make sure that nothing breaks,”transparency, security, and efficiency of transport

which is diametrically opposite to the stance

operations.

often adopted by digital-native innovators:“move fast and break things.” Second, becausesuch entities usually oversee all key aspects oftransportation within a certain geographical area,
it is necessary to align and integrate previously
differentiated and siloed units, each responsiblefor its own mode of transport.

Finally, mobility involves asset-intensive
operations, and digital twins — especially thosepowered by AI and ML — play a crucial role infacilitating sustainable asset management fromthe outset. Digital twin technologies offer advanced
abilities for planning and designing networks while
integrating essential modeling tools to simulate theure 1. Technological disruption in mobility sector behavior of urban transportation infrastructure. This
Figure 1. Technological disruption in mobility sector

enables informed decision-making and optimizes
operations. In addition, digital twins can contributeto a more effective asset management approachby utilizing real-time data feeds to monitor

Hyperscale edge
computing
Decentralized
identity
Unified,governmentverified profileOpen
payment
Blockchain

Digital licenses

Urban airmobility

EVs

Smart
spacesMetaverse(GenAI)

Predictive
maintenance
Multimodal
UI
Digital
twins

Range
6-8 years

Hyperautomationin security

6G

3-6 years

Tokenization

1-3 years

AutonomousvehiclesEdge computer
visionMaaS & transportation
super apps
AI network
monitoring

V2V comm

Autonomous drones& service robots

Current (0-1 year)

Mass
Low
Mediumasset conditions. This allows for identification ofpotential issues and implementation of predictive
maintenance schedules, which ultimately optimizes
operations. Consequently, downtime is minimized,
and reliability is enhanced, leading to improved
performance and cost savings for transportation
systems.

High

VR road design& planning

MaaS = mobility as a service; EVs = electric vehicles; V2V = vehicle to vehicle; VR = virtual reality; UI = user interface
Source: Arthur D. Little

mobility as a service; EVs – electric vehicles; V2V = vehicle to vehicle; VR = virtual reality; UI = user interface
LAYERING UP THE TRANSPORT TECHNOLOGY PORTFOLIO
Arthur D. Little

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ARTHUR D. LITTLE

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OPER ATING MODEL
ARCHE T YPESMANY PUBLIC TRANSPORTO P E R AT O R S H AV E
BEGUN TO CENTR ALIZE
A L L T E C H N O L O GY
O P E R AT I O N S
UNDER A SINGLEO R G A N I Z AT I O N A L U N I T

Most leading transport operators have adopted an
operating model structured by mode of transport,
which reflects the traditional way of managing
transportation. As such, most OT systems havebeen developed to manage transport operations
for specific modes of transport and are operated
by dedicated specialists, independently from OT
systems for other transport modes. There has

Seeing both the need and opportunity tolong been a tendency to consider IT separately

integrate their technology operations, manyfrom OT, with IT mostly seen as a support function

public transport operators have begun to

implementing standardized, corporate-wide

centralize all technology operations under aservices.

single organizational unit. When successfullyWith software continuing to eat the world, there

implemented, this modification has the additional

is now a rapid convergence of IT and OT, driven

advantage of improving efficiency, an important

by SDx (software-defined everything) and XaaS

goal for all companies, but particularly for publicly(everything as a service) — see Figure 2. This

funded entities. For example, Transport for

ongoing merger, both between IT and OT, and OT

London, the local government body responsible

systems for multiple modes of transport, presents

for most of the transport network in the UK city,a major challenge to transport operators in terms

realized significant OPEX efficiencies (estimatedof both organization and culture. Successfully

at an approximate annual reduction of 50%)

navigating this challenge will be critical to

thanks to the full centralization of both IT and OT

unlocking additional innovation opportunities

operations into a single organizational unit.

for transport operators. For example, the ability
to analyze integrated data flows is central tosmart city technologies, such as dynamic traffic
operations, smart parking, and the deployment
of autonomous and multimodal public transport
services.

Figure 2. Convergence between IT and OT
Figure 2. Convergence between IT and OT

OT
IT/OT
convergence

IT

OT Type 1
OT Type 2…
OT Type n•

Critical infrastructure requiredfor data processing•

Systems serve as repositories
for corporate information,
making data available tobusiness apps & users•

Two distinct networks merge& share data that eachcollects/distributes•

Network of devices/software
used in industrial, manufacturing& process control systems•

Two teams that worked
independently pool
resources & expertise•

Supports specialized gear tocapture/relay data & enableindustrial equipment to perform
specific tasks

Source: Arthur D. Little

LAYERING UP THE TRANSPORT TECHNOLOGY PORTFOLIO

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VIEWPOINTALIGNING OPER ATINGMODEL S TO P OR TFOLIO
MATURIT Y

It is important to note that no single technology
operating model archetype should be viewed as
the best practice target state for technology
organizations (see Figure 3). Instead, eacharchetype has a distinct set of advantages andLarge technology functions commonly oversee

disadvantages for different technologies in an

sizeable portfolios of products and systems,

organization’s portfolio and any trade-off may

comprised of technologies of varying degrees

shift for any given technology as it matures andof maturity. Moreover, given the broader trend indevelops. For example, significant benefits can betechnological development, the maturity of any

gained through full IT and OT centralization, but

single technology will evolve from promising but

two important drawbacks must be considered. First,

uncertain innovation to effective competitive

successful centralization can be a daunting task;

advantage and eventually to a commonlyleaders of operational units may be wary of giving

available solution and ultimate obsolescence.

up control over their critical OT systems and could,

This evolution has been well studied and istherefore, often show resistance to the proposedcommonly known as the “technology maturity

changes. Second, a higher level of centralization

S-curve” (see Figure 4).

typically decreases an organization’s flexibility,

Thus, technologies at different stages of maturity

overall agility, and ability to innovate. Centralized

have different requirements for being mostorganizations are a good fit for managing matureeffectively leveraged. In other words, different

technologies toward the end of their lifecycle

technology operating model archetypes canbut are too regimented to succeed in identifying,

be a better fit for technology portfolios withincubating, and scaling innovative technologies.

a preponderance of technologies at a certain

With significant technological disruption

development phase. The following details

expected to continue affecting the transport andhighlight the three phases of the technology

mobility sector over the medium term, responding

maturity S-curve:

to the convergence of IT and OT by centralizing
the technology function would deliver efficiency
at the expense of agility and could lead to less-than-optimaloperating
results for transport
operators.
Figure 3. Technology
model
archetypes
Figure 3. Technology operating model archetypes
FULLY DECENTRALIZEDEXTERNAL IT SPIN-OFF

IT CoEHYBRID OTFULLY CENTRALIZED

CEO

CEO

CEO

Holding

Regulator
CEO

CEO
Governanc
e

OpCo
1

OpCo
2

OpCo
3

BU 1

BU 2

BU 3

IT
OT

IT
OT

IT
OT

OT

OT

OT

Rationale• Enables IT/OT convergence• Efficiently drives innovation
within each BU• Ensures innovation scaling

ExampleFully IT/OT agile model, withIT+OT infused into BUs

Networks of independent-butcoordinating operators for
multimodal & MaaS

Separate IT
serviceprovider

BU 1

BU 2

BU 3

OT

OT

OT

IT

GovernanceGovernance

BU 1 BU 2 BU 3

OT

OT

OT

IT

IT

BU 1

BU 2

BU 3
OT

OT

Separate IT legal entity
providing support to BUs alongwith internal OT teams

IT center of excellence (CoE)providing support to BUs alongwith internal OT teams

Central IT & OT teams:
central OT focuses on
multimodal; oversees BUs’ OTs

Fully centralized
IT & OT teams• Creates tech-focused org
without legacy constraints• Enables independence frompublic sector restrictions &focuses on services
monetization• Unlocks economies ofscale for IT governance& operations• Allow BUs to retain
flexibility for OT• Unlocks economies of scale• Encourages multimodal
technology innovation• Allows BUs to retain
flexibility• Unlocks economies of scale• Encourages multimodal
technology innovation• Simplifies collaboration• Consolidates accountability• DigitalX• Confidential (MENA)• Confidential (MENA)• NSW Government• Land Transport Authority• Hong Kong Transport Dept.

• Transport for London

Level of centralization

Source: Arthur D. Little, expert interviews

Source: Arthur D. Little, expert interviews
LAYERING UP THE TRANSPORT TECHNOLOGY PORTFOLIO

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Figure 4. Technology maturity S-curve
Figure 4. Technology maturity S-curve
Integrate successful experiments
into production systems

Phase 2
Scaling•

Growth•Phase 3Maturity••

Differentiation forcompetitive advantage
Balance agility& efficency

Phase 1
Exploration••

Industry-standard solutions
Maximum efficiency

Phase 4
Reinventing the Future•

Sandboxed experiments
Maximum agility

Use current-generation mature systems
as strong foundation for next-gen
experimentation

TimeStandardize systems/processes& centralize operations

Sunset obsolete systems &rationalize application landscape

Source: Arthur D. Little- Phase 1: Exploration — experimenting
Source: Arthur D. Little

with new and innovative technologies.

- Phase 2: Scaling — technologies that haveachieved product-market fit are readyThis stage requires high flexibility and agility

for rapid growth, or scaling. This stage

and maximum proximity to the business andrequires finding the right balance between

customer. Success during this phase is mostagility and efficiency. The need to develop

often achieved by making multiple small bets

significant new features remains, but thewith a high rate of failure. Governance is adtechnology’s overall direction is becoming

hoc, processes are difficult to define formally,clear, and considerable investment is requiredand efficiency is not a key factor for success.

to deliver broad market adoption. GovernanceTechnologies at this stage help identify

and cost-control increase in importance,

potential new areas of competitive advantage

and stringent, frequently tracked KPIs

and are predominantly delivered at the proof-

must be imposed to verify growth of user

of-concept (PoC) or minimum viable productadoption and ensure the new system fully(MVP) level. Success is measured against OKRs

and effectively integrates with the existing(objectives and key results) set individuallytechnology landscape. Technologies at thisfor each project, typically looking at user

stage help strengthen current competitive

adoption or revenue-generation metrics.

advantage. Responsibilities for them must

Financing models are more flexible and may

be shared between the business/productinclude funding drawn from a preapproved

team and the centralized technology

innovation fund or pool or from externalfunction; the interface between these twoinnovation partners.

becomes critical. According to our experience,
effective coordination between business

T E C H N O L O G I E S AT
D I F F E R E N T S TA G E SO F M AT U R I T Y
H AV E D I F F E R E N T
REQUIREMENTS

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and technology is ensured, through theintroduction of dedicated business technology
evangelist teams. These teams should havea fairly deep understanding of both thebusiness and the technological aspects ofthe product or system in question and use
their understanding to guide its development.

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ARTHUR D. LITTLE

VIEWPOINT- Phase 3: Maturity — once firmly- Fully decentralized (IT and OT in BUs). No

established, technologies serve as

process exists for centralized innovation

the foundation and backbone for the

tracking or sharing lessons during exploration.

functioning of the entire organization,

Scaling can easily be achieved within one BU,

including business-critical operations. The

but coordination across multiple BUs is harder

focus at this stage is stability and efficiency,

during the scaling stage.

- External spinoff. Similar to the above,

often best achieved via the adoption of bestpractices and industry standards. Processes

there is no process for OT or IT to track

are clear, easily defined, and optimized

centralized innovations or share innovation— and must be stringently followed (seelessons learned. The “BU versus centralized”

Figure 5). OPEX may be significant, but theand “internal versus external” splits create

risk of unplanned obsolescence or productcoordination hurdles, making joint scaling

failure is low. Strict, quantitative KPIs are

difficult. At the maturity stage, IT and OT live

aimed at ensuring efficiency and continuous

apart from each other; it is very complex tosystematic improvement. Technologies atmanage data integration and operational

this stage are best overseen exclusively by
the centralized technology function to ensure
strong integration and avoid unnecessaryinterfaces.

- IT center of excellence (CoE). Innovation
in OT is dynamic as it is centered aroundcustomization, complexity, or duplication

BUs, but IT works centrally at a very differentof features. In turn, business units (BUs) must

speed. This makes it difficult to prototype

adapt their processes to the technological

technologies requiring both IT and OT

solution rather than having the technology

components. It is also likely to be challenging

tailored to their needs.

to scale IT and OT scale at the same pace,As stated earlier, no single approach or

especially when integrations are required.

technology operating model is an ideal fit for

Thanks to quick and agile delivery cycles,

all three of the identified technology maturity

OT is managed closely to the BUs, but thestages, as each model presents different

lack of centralization makes efficiency anddrawbacks for each stage. The operating model

standardization difficult.

archetypes and their limitations are as follows:

Figure 5. Characteristics of technology maturity phases

Figure 5. Characteristics of technology maturity phases
EXPLORATIONSCALING

MATURITY

Light touch

Value-risk balance

StrictAgility

Product-market fit

Efficiency

Required investment
Risk/uncertainty level
Degree of standardization
Governance approach
Key success factor

Low

Medium

High

Source: Arthur D. Little

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ARTHUR D. LITTLE

VIEWPOINTNO SINGLE APPROACH OR
T E C H N O L O G Y O P E R AT I N GMODEL IS AN IDEAL FIT
FOR ALL THREE OF THE
IDENTIFIED TECHNOLO GY
M AT U R I T Y S TA G E S

A MULTISPEED APPROACH
We propose extending the concept of atechnology S-curve to the design of technology
operating models. This aims to lessen the intrinsic
tension between efficiency and agility that often
creates an issue for organizations with large andcomplex technology functions. The proposedsolution involves clustering technologies within- Hybrid OT. During exploration, OT at the BU

level can be experimented with, but IT works
centrally at a very different speed, making it
difficult to create prototypes with IT and OT
components.

- Fully centralized. At the exploration stage,
individual BUs would not be able to identify
and drive long-term and company-wide
innovations, but a centralized unit would.
When scaling for only one BU, it is likely toresult in unnecessary overhead. The process
may be too removed from the business tocapture and quickly respond to product/
solution fit challenges during this phase.

an organization’s portfolio by their maturity level
and introducing separate approaches for theplanning, operations, and governance of eachcluster.
Using the technology maturity S-curve as its
foundation, the proposed operating model would,
in effect, create three distinct and specialized
operating and governance regimes within an
organization. Each regime will supervise a subsetof the organization’s technology portfolio, and alltechnologies in the portfolio will move between
regimes as they mature, as if on a conveyor belt.
First, all promising technologies make their way
into the technology funnel and are trialed andincubated under the organization’s decentralized

The archetypes are easily observable wheninnovation regime. Second, any innovations thatcomparing the operating models of technology

demonstrate initial success and reach their OKRs

companies that focus primarily on delivering

will graduate into the organization’s integration,technologies at a particular stage. For example,

scaling, and development regime. Finally, wheninnovative start-ups will be more decentralized

technologies reach their peak scale and ceaseand focused on agility, whereas well-establishedto demonstrate rapid growth, they transfer

players with mature services and technologies

to the centralized operational efficiency andwill be more centralized and focused onstandardization regime for eventual outsourcing

efficiency and integration. Furthermore, as theor retirement.

technologies themselves mature, this frequently
poses significant transformation challenges forthe organization. Initially, successful start-ups
may fail at the scaling stage due to an inability
to formalize their process and discipline theirorganization, while the most successful playersof the previous technological cycle may become
too centralized and move too slowly to identify
and capitalize on the next generation of
innovations in their field.

LAYERING UP THE TRANSPORT TECHNOLOGY PORTFOLIO

As we argue below, such a hybrid, maturitycentric technology operating model will helporganizations benefit from a type of dynamic
stability, which will be capable of simultaneously
delivering decentralized agility with standardized
efficiency of technology operations. In effect, theproposed approach provides certain operationaland governance aspects of the optimal technology
operating archetypes, identified above, for each of
the three technology maturity stages:

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1. Exploration stage. BUs are granted complete

regime and (2) creating an independent andautonomy in IT and OT decisions, which iscross-functional team. This team should consist

supported by dedicated teams tasked withof representatives from both the BUs and the key

identifying emerging technologies andcentralized functions (e.g., technology, strategy,

conducting early-stage experiments, preferably

finance) charged with evaluating and enforcing

using Agile or DevOps methodologies.

the transition points. Below, we suggest rules

2. Scaling stage. A hybrid model facilitates thesmooth expansion of projects across multiple
BUs through a blend of decentralized andcentralized IT/OT responsibilities. This modelfor transitioning between each governanceand operations regime:- Innovative technologies are handed overfor scaling. Conditions for transition typicallyrelies on synergistic cooperation between

include proof of a good product-market fit,

BU-specific teams and a centralized

as indicated by fulfilled OKRs, and the needtechnology and innovation team. Adopting

to start integrating the PoC or MVP with theAgile principles is crucial for this collaboration

broader technology landscape. In addition,

to ensure that the specialized BU teams,

a time limit is recommended for products

which will oversee product delivery, workin the experimentation stage; a product oreffectively with the central technology team,technology that fails to reach its OKRs within

which will integrate these products into thea specified time frame (typically one to twoorganization’s broader technology portfolio.

years) should be considered unsuccessful

3. Maturity stage. Decision-making iscentralized, focusing on continuous
improvement, service and tool standardization,and maximizing operational efficiency. The

and wound down to free up resources foralternative innovation opportunities.

- Growing technologies reach maturity.

Conditions for transition typically include

responsibility for operating and enhancing

technological growth slowing to the same ratemature technologies and products lies solely

as that of the overall organization, the broadwith the centralized technology operations

adoption of similar technologies by industry

team, which employs traditional waterfall

peers, and the emergence of industry standards

methodologies for implementation.

and best practices. This transition can present

The main challenge for the proposed approach
revolves around the efficient handover oftechnology systems from one maturity stage
to the next. This challenge has two components:(1) identifying the current maturity stage fora given technology and (2) facilitating thetransition of the technology or product between

challenges, as it requires business owners
to relinquish responsibilities for importantsystems and frequently entails refactoring or
rationalizing existing applications in favor ofbest-practice solutions.

- Mature technologies are retired. Conditions
for transition typically include a decline indifferent teams (considering any expertiseuse and the emergence of more powerfulor capabilities uniquely specific to the team).

alternatives at the start of their scaling

Thus, for the dynamic model to be successful,phase. This transition can be consideredorganizations must pay attention to the“reinventing the future” and the fourth phasetransition of systems between each of the threeof the technology lifecycle. Timely retirement

stages and consequently between each relevantof obsolete technologies is an important

governance and operations regime.

process that reduces technology debt,

The success of the transition process depends on
two factors: (1) establishing clear rules or gates togovern the transition between each governance

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decreases security risk, and ensures that thehealth of the overall technology landscapeis not undermined by the need to continue
supporting systems of minimal value.

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Case study — Leading multi-division organization in the transportation industry in MENA
A leading transportation organization in theCare was taken to ensure that the principles

MENA (Middle East/North Africa) region took its

and processes for the transition and handovertechnology-pioneering goals to the next level ofof systems between maturity clusters werematurity by using the principles in this Viewpoint

clear, efficient, and well defined. Ultimately,

to transform its technology organization. The

the transformation rested on three key pillars:

technology function across the organization was
facing dual challenges: simultaneously being
viewed as excessively rigid and process-oriented
while also being unable to deliver a unified
and integrated technology landscape for theorganization. Additionally, there were issues withscaling innovative projects, and the technology
acquisition cycle was seen as ineffective andslow. While the existing technology governanceapproach worked well during the company’s
earlier years, it was no longer optimal for
meeting either the rapid pace of technology
innovation or the need for deep integration of
the client’s systems and data. Instead, a vicious
circle emerged. To rationalize and integrate theheterogeneous and siloed technology landscape,the central technology function enforced evermore requirements on the operational BUs;
the BUs, in turn, bypassed exceptions andworkarounds to effectively deliver the rapid paceof innovative projects the organization’s senior

1. For systems during the growth or scalingstage, a dedicated technology evangelistrole was created to ensure close alignmentand coordination between the business andtechnology units. This role combined productmanagement and business technologist
responsibilities and ensured that criticaltechnology systems met architecture andintegration requirements without sacrificing
business needs.
2. A central innovation team in the technology
division was created and given a mandate
to coordinate and assist the decentralized
innovation teams in each BU. The central
innovation team worked to ensure that
innovation projects were not duplicatedbetween BUs and spearheaded multimodal,
longer-term R&D initiatives.
3. A transformation roadmap was launched torationalize and transition the client’s mostly

leadership expected from them.

on-premises corporate technology systems

We recommended a technology operating model

to cloud-native platforms with a particulartransformation initiative. The client’s current
and future technology systems were clusteredaccording to their place on the maturity S-curve,
and separate acquisitions, governance, andoperations frameworks and processes were
designed for each cluster.

LAYERING UP THE TRANSPORT TECHNOLOGY PORTFOLIO

focus on creating a single, unified data fabricto provide easy and application programming
interface (API)–based data sharing between
the organization’s current and futuretechnology systems, as well as to implement
open data access to external parties.

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CONCLUSIONSUC CES SFUL TECHNOLO GY& I N N O VAT I O N M A N A G E M E N T

T E C H N O L O G Y A N D I N N O VAT I O N S H O U L D B E
M A N AG ED T HR O U G H A DY N A MI C A PPR OAC H

We propose managing technology and innovation througha dynamic approach that leverages separate operationaland governance regimes for technology systems at different
maturity levels. The proposed approach requires a high levelof organizational maturity to be executed effectively andaims to:1

Deliver the right balance between agility and efficiency.

2

Align business and technology interests.

While we have developed and tested this novel approachwith organizations in the transport and mobility sector,
other industries with complex technology portfolios canpotentially benefit from the same model, including energy/
utilities (e.g., implementing smart grids), industry/mining(e.g., enabling Industry 4.0), and healthcare (e.g., utilizing
smart health technologies and 4P [predictive, personalized,
preventive, and participatory] medicine).

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LAYERING UP THE TRANSPORT TECHNOLOGY PORTFOLIOARTHUR D. LITTLE

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